haematologial scoring system: an early predictor of...
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HAEMATOLOGIAL SCORING SYSTEM: AN EARLY PREDICTOR OF
NEONATAL SEPSIS AS COMPARED TO BLOOD CULTURE
Dissertation submitted in
Partial fulfilment of the regulations required for the award of
M.D. DEGREE
In
PATHOLOGY – BRANCH III
THE TAMILNADU DR. M.G.R. MEDICAL UNIVERSITY
CHENNAI
APRIL 2017
DECLARATION
I hereby declare that the dissertation entitled “HAEMATOLOGICAL
SCORING SYSTEM: AN EARLY PREDICTOR OF NEONATAL SEPSIS
AS COMPARED TO BLOOD CULTURE” is a bonafide research work done
by me in the Department of Pathology, Coimbatore Medical College during the
period from MAY 2015 TO APRIL 2016 under the guidance and supervision of
Dr.A. Dhanalakshmi, M.D, Associate Professor, Department of Pathology,
Coimbatore Medical College.
This dissertation is submitted to The Tamilnadu Dr.MGR Medical
University, Chennai towards the partial fulfillment of the requirement for the
award of M.D., Degree ( Branch III ) in Pathology. I have not submitted this
dissertation on any previous occasion to any University for the award of any
Degree.
Place: Coimbatore
Date: Dr. M.Poornima
CERTIFICATE
This is to certify that dissertation entitled " HAEMATOLOGICAL
SCORING SYSTEM: AN EARLY PREDICTOR OF NEONATAL SEPSIS
AS COMPARED TO BLOOD CULTURE" is a bonafide work done by
Dr.M.POORNIMA, a postgraduate student in the Department of Pathology,
Coimbatore Medical College, Coimbatore under guidance and supervision of
DR.A. DHANALAKSHMI M.D, Associate Professor , Department of
Pathology, Coimbatore Medical College, Coimbatore in partial fulfillment of
the regulations of the Tamilnadu Dr. M. G. R. Medical University, Chennai
towards the award of M. D. Degree (Branch III) in Pathology.
Guide Head of the Department
Dr.A. Dhanalakshmi M.D, Dr.C.Lalitha,M.D,
Associate professor, Professor,
Department of Pathology, Department of Pathology,
Coimbatore Medical College Coimbatore Medical College,
Coimbatore. Coimbatore.
Dr.A.EDWIN JOE, M.D; B.L,
Dean
Coimbatore Medical College, Coimbatore.
ACKNOWLEDGEMENT
To begin with, I thank the almighty God for bestowing his blessings on me in
successful completion of this dissertation.
I wish to thank our beloved Dean Dr.A.EDWIN JOE,M.D,B.L, Coimbatore
Medical College and Hospital, Coimbatore for permitting me to conduct this
study.
I thank Dr. C.Lalitha. M.D., Professor and Head of the Department, Department
of Pathology, Coimbatore Medical College, Coimbatore forher guidance and
support.
I express my gratitude and sincere thanks to my guide Dr.A. Dhanalakshmi,
M.D, Associate Professor, Department of Pathology, Coimbatore Medical
College, Coimbatore. This dissertation bears her valuable suggestions and
highly professional advice.
I wish to express my gratitude and sincere thanks to Professor Dr. A. Arjunan.
M. D., for his guidance and support.
I owe my gratitude to Dr. Geethanjali M.D., Professor of Pediatrics and
Dr.V.K.Sathyan, Neonatologist, Department of Pediatrics, Coimbatore Medical
College Hospital, for their encouragement and suggestions throughout the
course of my work.
I thank all Associate professors, Assistant Professors and Tutors of the
Department of Pathology, Coimbatore Medical College, Coimbatore for their
opinion and encouragement.
I thank my family, my parents, my husband Dr Sakthivel M.S.Mch.and my son,
S.Iniyan who stood behind me in all my efforts.
I thank all lab technicians working in Department of Pathology, Coimbatore
Medical College, Coimbatore.
DR.M.POORNIMA
CONTENTS
SI.NO. PARTICULARS PAGE NO.
1. INTRODUCTION 1
2. AIMS AND OBJECTIVES 3
3. REVIEW OF LITERATURE 4
4. MATERIALS AND METHODS 56
5. STATISTICAL ANALYSIS 61
6. RESULTS 62
7. DISCUSSION 80
8. CONCLUSION 82
9. BIBLIOGRAPHY
10. ANNEXURES
I. PROFORMA
II. LIST OF ABBREVIATIONS
III. MASTER CHART
IV. CONSENT FORM
LIST OF TABLES
SI.NO TITLE PAGE.NO.
1. HAEMATOLOGICAL SCORING SYSTEM 60
2. CLINICAL GROUP DISTRIBUTION 62
3. AGE AND SEX DISTRIBUTION 63
4. AGE DISTRIBUTION 64
5. DISTRIBUTION OF CLINICAL AND
HAEMATOLOGICAL SEPSIS
67
6. ASSOCIATION OF CLINICAL VARIABLES
WITH HAEMATOLOGICAL SCORING
SYSTEM
68
7. TOTAL WBC COUNT AS PREDICTOR OF
SEPSIS
69
8. PERFORMANCE OF INDIVIDUAL
HAEMATOLOGICAL PARAMETERS
77
LIST OF CHARTS
SI.NO. TITLE PAGE.NO.
1. GENDER DISTRIBUTION 65
2. DISTRIBUTION OF NEONATES ACCORDING
TO HAEMATOLOGICAL SCORE
66
3. TOTAL WBC COUNT AS PREDICTOR OF
SEPSIS
70
4. TOTAL PMN COUNT AS PREDICTOR OF
SEPSIS
71
5. IMMATURE PMN COUNT AS PREDICTOR OF
SEPSIS
72
6. I:T PMN RATIO AS PREDICTOR OF
NEONATAL SEPSIS
73
7. I:M PMN RATIO AS PREDICTOR OF
NEONATAL SEPSIS
74
8. DEGENERATIVE CHANGES AS PREDICTOR
OF NEONATAL SEPSIS
75
9. PLATELET COUNT AS PREDICTOR OF
NEONATAL SEPSIS
76
10. PREVALENCE OF CRP POSITIVITY IN THE
STUDY POPULATION
78
11. DISTRIBUTION OF CRP POSITIVITY
ACCORDING TO THE HAEMATOLOGICAL
SCORING SYSTEM
79
LIST OF COLOR PLATES
COLOUR
PLATE. NO.
TITLE
1. LEISHMAN STAIN- NEUTROPHILIC LEUCOCYTOSIS
2. LEISHMAN STAIN- MATURE AND IMMATURE
FORMS
3. LEISHMAN STAIN- IMMATURE FORMS
4. LEISHMAN STAIN- NEUTROPHIL SHOWING
CYTOPLASMIC VACUOLATIONS
5. LEISHMAN STAIN- TOXIC GRANULES
INTRODUCTION
1
INTRODUCTION
Neonatal sepsis is the commonest and the most important cause for the
morbidity and mortality of neonates in developing countries like India (1, 2).
The
signs and symptoms of sepsis in neonates are subtle and non-specific which
makes it difficult to diagnose clinically. Timely diagnosis of sepsis in neonates
is critical as the illness can progress more rapidly when compared to adults (3).
Mortality rate in developing countries is between 10-70/ 1000 live births.
Fortunately neonatal sepsis is a treatable condition if it is diagnosed early and
treated with appropriate antibiotics. But early diagnosis of sepsis is still a great
challenge. Inability to diagnose the sepsis earlier results in unnecessary and
prolonged exposure to antibiotics. This increases the risk of antibiotic side
effects and also the emergence of drug resistant microorganisms. Neonatal
sepsis can be early or late and most of the cases of early sepsis are within 24
hours (4).
As the immune system of neonates is weak, they are more susceptible to
invasive infections. Premature infants are even more prone to infections than
term neonates (5).
The tests which diagnose sepsis with high positive predictive
value like blood culture, haptoglobin and immunoelectrophoresis are expensive
and time consuming (6).
Though definite diagnosis is made by positive blood
culture the test is time consuming. Measures of cytokines, acute phase proteins,
cell surface antigens and bacterial genomes are used for the early diagnosis of
2
sepsis either alone or in combination. Though these markers are sensitive and
specific they are expensive and are not readily available in resource poor
settings. Hence the ideal diagnostic tests should give quick results and should
have good sensitivity, specificity so that unnecessary antibiotic is avoided (7-11).
In order to diagnose the sepsis earlier certain haematological parameters
are evaluated and each of them assessed to find the most suitable parameters.
AIMS & OBJECTIVES
3
AIMS AND OBJECTIVES
To assess the importance of haematological parameters in the early
diagnosis of neonatal sepsis
To compare the variables with other laboratory parameters.
To assess the most sensitive and specific variables in diagnosing neonatal
sepsis.
REVIEW OF LITERATURE
4
REVIEW OF LITERATURE
NEONATAL SEPSIS:
It is a clinical syndrome which is considered when the neonate (< 28 days
of life) has infective signs and symptoms along with presence or absence of
bacteria in the blood.
It includes many systemic infections affecting the neonate like
meningitis, Pneumonia, Osteomyelitis and infections of the urinary tract.
Neonatal sepsis does not include conjunctivitis and oral thrush.
CLASSIFICATION OF NEONATAL SEPSIS
Neonatal sepsis is classified as early onset and late onset sepsis (12)
EARLY ONSET SEPSIS:
In early onset sepsis neonate has symptoms and signs in the first 3 days of
life. In severe sepsis, neonate may present even at birth. The main source of
infection is maternal genital tract. Neonates usually have pneumonia which is
followed by respiratory distres
There are certain maternal and perinatal risk factors to be considered for
the early diagnosis of neonatal sepsis. (12, 13)
Sepsis screen criteria from AIIMS protocol which is followed in NICU
of Coimbatore Medical College is as follows:
5
1. Prematurity/ low birth weight < 2.5 kg
2. Prolonged labour ( 1st and 2
nd stage of labour together comprise >24hrs)
3. Amniotic fluid which is either foul smelling or meconium stained
4. Membrane rupture for >24 hrs
5. Single unsterile vaginal examination or if sterile, more than three
examinations during labour
6. Perinatal asphyxia – with APGAR score <4 at 1 min
7. If mother had fever within 14 days before delivery
INDICATIONS FOR STARTING ANTIBIOTICS
Presence of any one of the factors in neonates at risk of early onset sepsis
(EOS):
Presence of ≥3 risk factors for EOS
Presence of foul smelling liquor
Presence of ≥2 antenatal risk factors and a positive septic screen
Strong clinical suspicion of sepsis.
LATE ONSET SEPSIS (14, 15)
:
Neonates presents with symptoms and signs after 3 days of life. Here
neonates either have pneumonia, meningitis or full blown sepsis. Neonates
acquire the infection during the stay in the hospital (nosocomial or hospital
acquired) or from community (community acquired)
6
RISK FACTORS FOR HOSPITAL ACQUIRED INFECTION:
1. Birth weight < 2.5 kg
2. Prematurity
3. Assisted ventilation
4. Parenteral fluid administration
5. Usage of stock solutions
6. Any invasive techniques applied during labour
RISK FACTORS OF COMMUNITY ACQUIRED LATE ONSET SEPSIS:
1. Lack of umbilical cord care
2. Lack of hygiene
3. Bottle fed infants
4. Prelacteal feeds
Breast feeding improves resistance to infections.
CLINICAL PRESENTATION:
In early stage of sepsis, neonates usually have non specific signs and
symptoms, even though we should have high suspicion for the early diagnosis
of sepsis.
7
NON SPECIFIC SIGNS AND SYMPTOMS
Hypothermia or hyperthermia ( hypothermia usually seen in low birth
weight babies)
Feeble cry
Poor activity
Refusal to suck
Increased or decreased heart rate
Low or high blood glucose
Low perfusion
Metabolic acidosis
SPECIFIC SIGNS AND SYMPTOMS:
CNS: Irritable baby, bulging anterior fontanelle, seizures, neck stiffness.
If these features are present we should suspect meningitis.
CVS: Low blood pressure, poor perfusion, shock
GIT- vomiting, loose stools,distended abdomen, intolerance to
feeds,paralytic ileus, necrotising entero colitis
HEPATIC- enlarged liver, conjugated hyperbilirubinemia (usually seen
in infections of the urinary tract)
HAEMATOLOGICAL- Bleeding manifestations, purpuric spots,
petechial spots
8
RENAL- acute renal failure
Indications for starting antibiotics in late onset sepsis:
Positive septic screen
Strong clinical suspicion of sepsis
INVESTIGATIONS (16)
Peripheral smear
Blood culture
Lumbar puncture
Serological markers
Urine culture
Radiology
PERIPHERAL SMEAR
MANUAL METHOD
Fresh blood with or without anticoagulant is needed for preparing blood films.
Blood films are prepared in a clean glass slide wiped free of dust using cotton.
Slides size should be 7.5x 2.5 cm. Thickness should be 1 mm. One end is
9
frosted to enable labelling. Spreader slide is prepared first by breaking the one
corner of the slide with the help of a glass cutter so that its width is 1.8cm.A
spreader slide can be used several times after proper washing.
A drop of blood is placed at 1cm from one corner of a slide in the midline
and a spreader slide is placed at a 30 degree angle in front of the drop .The slide
is moved backwards so that it touches the drop. The drop spreads quickly along
the contact line. Then the blood is spread along the slide for a length of 3 cm.
This forms the monolayer where the cells are widely spaced so that cell counts
can be made. In the slide this monolayer is formed in the feathered edge created
by the spreader. Blood film made is allowed to air dry. The thickness of the
blood film can be altered by varying the spreader angle or by changing the
spreading speed. For anaemic blood, wider angle is used to obtain the correct
thickness. For polycythemic blood, narrower angle is used. For ideal thickness
there should be some overlap of red blood cells throught the smear’s length.
White blood cells should be present throughout the blood film.
AUTOMATED METHODS
In order to stain several batches of stain we can use automated staining
machines. It can be a separate machine or combined along with automated
blood counter. Spreading of the slide, fixation, staining are all done by the
instrument. Either single blood film or multiple blood film per sample can be
obtained. Staining of the slides can be of two methods. One is flat-bed staining
10
where staining solutions are applied to the horizontally placed slide. Other is
“dip and dunk” method slides are immersed in a staining solution. We can even
spray the stains on to the slides in a centrifuge.
LABELLING BLOOD FILMS
The blood film should be labelled with the pencil on the frosted end.
STAINING BLOOD FILMS
Romanowsky stains are employed universally for staining blood films.
Romanowsky dyes consists of two components 1. Azure B (trimethylthionin) 2.
Eosin Y ( tetrabromofluorescein). (17, 18)
The original Romanowsky dyes
constitutes 1. Polychromemethylene blue 2. Eosin There are several factors for
variation in staining pattern. One among them is the presence of contaminants
in the commercially available dyes. As it gives consistent results simple dyes
are preferable to complex dyes (17,19, 20).
Pure dyes of azure B and eosin Y are
expensive. Hence, the stain containing 80% of the dye is sufficient (21).
In
Romanowsky group, simplest dye is the Jenner and complex dye is the Geimsa.
Routinely employed stain is the Leishman stain. pH recommended is 6.8. In
order to obtain uniform pH, 1ml of water is mixed with 50 ml of Sorensen’s
phosphate buffer.
Some component of cell stain with particular dye while the other
component do not. It depends on the difference in interaction between the dye
11
and the molecular structure (22).
Azure B has affinity to anionic molecules. Eosin
Y has affinity towards cationic molecules. Cell nucleus having nucleic acid and
cytoplasmic proteins have acid group. So they stain with azure B , the basic dye.
Cytoplasmic granules of neutrophils stain weakly by azure B. As
haemoglobin molecule contains basic group, it stains with acidic dye, eosin Y.
Granules in the eosinophils contain alkaline group- spermine derivative that
stain with acidic dye. Granules of basophils contain heparin which is an acid
that stains with basic dye hence it appears blue.(18)
RNA binds slowly and DNA
binds more rapidly. Haemoglobin binds very slowly. Therefore, correct
proportion of azure B and eosin should be used. Proper timing for the staining
of the slides should be ensured.
LEISHMAN’S STAIN :( 23)
0.2 g of leishman powder is weighed and is mixed with 100ml of
methanol in the conical flask. After warming for 15 min allow it to cool.
Filtered solution can be used immediately but the staining quality can be
improved on standing.
LEISHMAN STAIN- PROCEDURE (24)
After making the blood film it is allowed to air dry. The slides are
flooded with Leishman stain for 2 minutes. Twice the volume of buffered water
is added and kept for 5 minutes. Slides are washed in buffer water for 2
12
minutes so that it acquire a pinkish tinge. Back of the slide is washed and is air
dried.
OTHER STAINING METHODS
MAY-GRUNWALD-GIEMSA STAIN –PROCEDURE (23)
After drying the slides should be fixed in methanol for 10 minutes. May-
Grunwald stain is taken in a jar and is diluted with buffer water of equal
volume. Fixed films are kept in this jar for 15 minutes. Then without washing it
is transferred to another jar containing Giemsa stain which is diluted with 9
volumes of buffer water. Ph should be 6.8. Wash the slide in buffer water. Three
or 4 changes given. It should be left undisturbed for 5 minutes so that
differentiation can take place. The colour of the blood film is taken as a good
guide or it should be viewed under low power. We should not allow the slide to
dry at any time. Once the differentiation step is over the slides are allowed to
dry.
Stain related problems
Inadequate staining of neutrophil granules.
Degranulation of basophils.
Increased background staining.
Blue staining of red blood cells.
13
AUTOMATED BLOOD COUNT TECHNIQUES
It can be semiautomated or fully automated. Semi-automated requires
dilution of blood sample that is done by the operator. It also measures only a
few components like Hb and WBC. In contrast fully automated instruments
need appropriate blood sample to be presented to the instrument. This
multichannel instruments measure 10 to 20 components for full blood count and
differential count. It also measures some variables that is not counted using
manual techniques. They have higher precision in cell counting and cell sizing
techniques which is superior to the manual techniques. Accurate test results are
obtained by carefully calibrating the instruments and ensuring correct operation
by quality control practices. Blood having abnormal characteristics produce
aberrant parameters which are flagged by the instrument. So inaccurate counts
produced due to abnormal characteristics of blood vary between instruments. It
is necessary for operators to be aware of the factitious results to which the
instruments are prone. (25)
Blood cell counters have automated facilities for the recognition of the
sample, for adequate mixing of the sample, to take the blood sample
automatically and for detecting clots and inadequately sized samples. Fully
automated instruments are needed to perform blood counts in large number of
samples and to give precise and accurate results rapidly. Most instruments count
14
for a specified time period rather than measuring exact blood volume. Hence it
requires calibration in counting cells in a defined volume of diluted blood. (26)
RED BLOOD CELL COUNT
Red blood cells and other blood cells are counted using light scattering or
aperture impedance technology. As large number of cells is counted rapidly
there will be high level of precision. RBC counts and red cell indices like MCV
and MCH rendered by electronic counts have greater relevance clinically than
obtained manually which was slow and imprecise. (25, 27)
IMPEDANCE COUNTING
Impedance counting is based on the principle that red blood cells are bad
conductors of electricity. Some diluents act as good conductors. This forms the
basis in several counting instruments such as Sysmex, Beckman Coulter, Horiba
Medical, and Abbott.
To perform cell count, first blood is diluted with buffered electrolyte.
Either mercury siphon controls the flow rate of the diluted blood sample or by
displacing the tightly fitted piston. Aperture measures 10 cm in diameter and 7
cm in length. It results in the passage of measured volume of blood sample
through the aperture tube. Direct current is flowed between the two electrodes
one placed in the beaker containing sample or the chamber which surrounds the
aperture tube and the other placed inside the aperture tube. When a blood cell
15
flows through the aperture it displaces some conducting fluid thereby increasing
electrical resistance. This produces potential difference between the two
electrodes. It lasts as long as the red blood cell passes through the aperture. The
height of the pulse reflects the volume of the cells flowing through the aperture.
The pulses are recorded on a oscillograph screen. These pulses are passed on to
a threshold circuit which has an amplitude descriminator. It selects the
minimum pulse height that will be counted. (27)
LIGHT SCATTERING
Electro-optical detectors can be used to count red blood cells and other
blood cells. (27)
Diluted blood sample passes in a single file through the aperture
in front of light source. Cells scatter the light while passing through them.
Photodiode or photomultiplier detects this scattered light by converting into
electrical impulses that are counted. The amount of scattered light is
proportional to surface area and hence the cell volume. Hence the cell volume is
estimated by the height of the electrical impulse.
Current instruments use high intensity coherent laser having superior
optical qualities than the earlier non coherent tungsten lights. Sheathed flow
permits cells to pass in a axial stream with the diameter that is not much more
than a red blood cell. This allows precise focussing of light on the cells. Electro-
optical detectors are employed in Siemens systems for red cell counting and
sizing and also used for white blood cell differential counting. (28)
16
HAEMATOCRIT AND MEAN CELL VOLUME
The flow of cells through the aperture or through the light generates
electrical impulse. The height is proportional to the cell volume. RBC count is
determined by the number of pulses generated. MCV or haematocrit is
determined by the analysis of pulse height. Average pulse height gives the
MCV. Hct is calculated by multiplying MCV and the RBC. Summation of pulse
heights gives Hct and MCv can be obtained by dividing haematocrit by RBC.
Before determining Hct or MCV automated instruments should be calibrated.
Calibration of haematocrit is by manual determination of Hct. Calibration of
MCV is by generating pulse heights by stabilized cells or latex beads. But
unfixed flexible biconcave human red blood cells will not show same
charecteristics as latex particles or any other artificial calibrant in a cell counter.
Impedance system measure apparent volume which is more than the true
volume that is influenced by a shape factor. (26)
Shape factor < 1.1 – young,
flexible red blood cells 1.1 to 1.2 – fixed biconcave red cells 1.5- spheres either
fixed cells or latex spheres. (26, 27)
The Hct and MCV will vary with cell characteristics like shape while
determined using automated cell counter. While passing through the aperture in
impedance counters, the normal disc shaped red blood cell gets elongated and
becomes cigar shaped. This is due to deformation of RBC produced by shear
force. It occurs in normal flexible cells. So, cells with low haemoglobin
17
concentration become more elongated than normal leading to reduction of shape
factor. This causes reduction in pulse height compared to the true size of the cell
underestimating the MCV. In contrast, spherocytes with high Hb concentration
and red cells with abnormal rigid membranes undergo less deformation
resulting in overestimation of MCV. (29)
Isovolumetrically sphered cells are used. Sphered red cells have light
scattering characteristics which are predictable permitting the calculation of
both volume of the cell and intracellular concentration of haemoglobin by using
calibrated Mie map. It describes the refraction and scatter characteristics of
spheres in a monochromatic source of light. (30)
Scattering of light by the
individual cell is measured at 2 angles. High angle scatter at 5 to 15 degree and
low angle scatter at 2 to 3 degree allows calculation of both haemoglobin
concentration and cell volume.(29)
Cellular haemoglobin concentration mean –CHCM is a measure of
cellular haemoglobin. It is different from the MCHC derived from the PCV and
Hb. MCHC and CHCM should be the same if all the measurements are
accurate. This provides internal quality control. When compared to manual
methods automated MCV and H ct are prone to some errors.
AUTOMATED DIFFERENTIAL COUNT
18
Many automated differential counters use flow cytometry that is
incorporated into full blood counter. Automated cell counters also provide
differential counts as three parts, five or seven part. Differential counts are done
on diluted whole blood. Here red cells are rendered transparent or it is lysed.
Three part differential count assigns the cells as 1) large cells / granulocytes 2)
small cells / lymphocytes 3) middle cells / monocytes/ mononuclear cells.
Basophils and eosinophils come under granulocyte category but here they are
counted under monocyte category.(31)
Some three part differential counters
assign the white blood cells as WBC-large cell ratio that is equivalent to
neutrophils, WBC- middle cell ratio that is equivalent to eosinophils , basophils
and monocytes and WBC- small cell ratio that is equivalent to lymphocytes. (32)
Five part differential counters categorise the cells as neutrophils,
basophils, eosinophils, lymphocytes and monocytes. Seven part differential
count also includes large immature cells / immature granulocytes that is
composed of blasts and other immature granulocytes, atypical lymphocytes that
includes small blasts. Certain automated counters that do not count nucleated
red blood cells or immature granulocytes either flag or reject counts from
samples with blasts, promyelocyte, myelocyte, atypical lymphocytes or
nucleated red blood cells.
19
Three part differential counter which are not able to enumerate basophils
or eosinophils as separate categories are capable of flagging a sample with
increased number of these cells. (33)
Both light scattering and impedance systems are able to produce three
part differential from a single channel. Cells are categorised based on the
differing volumes of the various cells after partial lysis and cytoplasmic
shrinkage. Five part and seven part differential counters needs 2 or more
channels. Here cell volume and various other characteristics are analysed by
several modalities. Analysis depends on volume or other physical
characteristics. It also depends on cellular enzyme activity or on the binding of
dyes to granules. In order to study the cell characteristics various technologies
are used that includes absorbance and impedance measurement with high and
low frequency electromagnetic current / radiofrequency current and light
scattering. Before studying the cell characteristics, cells are exposed to lytic
agents or to a cytochemical reaction. Either two parameters are analyzed or cells
are divided into clusters that are matched with the position of the different white
cell clusters of normal blood. Some fixed and variable thresholds divide the
clusters from each other allowing the cells in each cluster to be counted. (34)
AUTOMATED IMMATURE GRANULOCYTE COUNT
Automated cell counters count the immature granulocytes that includes
promyelocytes, metamyelocytes, and myelocytes . They are not counted as
20
separate classes of cells. As larger number of cells is counted automated
analysers reliably detect even smaller number of immature granulocytes than by
manual method. Low counts of immature granulocytes in leucopenic blood
samples or when only small percentage of cells are present it can be missed in
manual 100 cell differential count or by blood film review. Immature
granulocytes are identified by light absorbance and impedance after staining the
cells or by flow cytometry detecting the side scattered light and by fluorescence
staining with a fluorescent dye. The immature granulocytes percentage
measured by Sysmex may predict the infection. (35)
Some systems that don’t count nucleated red blood cells separately, their
differential counts include some of the nucleated red cell in the total WBC
count. Therefore, if there is increased number of nucleated red cells the total
count may not be a true WBC count. Absolute White blood cell count calculated
from the total may be erroneous.
BLOOD CULTURE (16)
Blood culture is considered as the gold standard in the diagnosis of
sepsis. This test should be done in all patients with suspected sepsis before
starting antibiotics.
21
If blood culture reveals growth of a particular organism, we can do sensitivity
testing so that we can start appropriate antibiotics. Blood samples should be
collected under sterile condition.
Blood cultures are observed for minimum 72 hrs before reporting it as
sterile. There are certain advanced techniques like BACTEC AND
BACT/ALERT that can detect the growth of organisms in 12 to 24 hrs.
Moreover, they can detect even bacteria in low concentrations (1-2 colony
forming units/ ml).
Blood culture is used in the detection of infections that spread via the
blood stream. As blood is sterile normally, it can be employed to detect
septicaemia/ bacteremia. When a patient presents with signs and symptoms of
systemic infection, from the blood culture results, we can identify whether the
infection is present or not and also the type of microorganism that causes the
infection. Blood culture is used to identify the infective organism in case of
sepsis, puerperal fever, pelvic inflammatory disease, severe pneumonia,
neonatal epiglottitis and fever of unknown origin. Even if there is no growth in
blood culture infection is not excluded.
METHOD
Strict aseptic technique is followed while collecting blood. This involves
cleaning of the venipuncture site with 70% isopropylalcohol or povidone and
22
are allowed to dry. This reduces the contamination of skin commensal
producing false-positive results. Minimum 10 ml blood is collected and with
new needle blood is injected to 2 or 3 bottles containing specific culture media
for both anaerobic and aerobic organisms. (36)
Then they are sent to the
microbiology department. Here, the culture bottles are incubated at body
temperature. They are monitored for 5 days. If the culture vials reveals no
growth they are removed. If the vial shows growth, then Gram stain is
performed on the blood. This blood is also subcultured onto the agar plate in
order to isolate the causative organism. Susceptibility testing is also done that
takes upto 3 days. Assessment of antibiotic sensitivity is needed so that
appropriate antibiotic can be started. In order to confirm series of 3 blood
cultures are performed. (37)
LUMBAR PUNCTURE (14, 38)
Meningitis constitutes 0.5 – 3% of neonatal sepsis. Meningitis can occur
along with septicaemia without any organ specific symptoms. Hence, lumbar
puncture is warranted in neonates having clinical suspicion of sepsis. In early
onset sepsis, lumbar puncture is performed if there is positive blood culture or if
there is clinical signs and symptoms of sepsis. For late onset sepsis, lumbar
puncture is performed in infants before starting antibiotic therapy.
23
INTERPRETATION
CELL COUNT
The presence of leucocytes in CSF is known as pleocytosis. Normally,
few monocytes can be seen. If granulocytes are seen in CSF it is definitely
abnormal. There will be increased granulocytes in bacterial meningitis.
LEUCOCYTES IN CSF
Leucocytes in CSF are also seen in
Reactions to previous drugs or dyes
Repeated spinal taps
Leukemia
Metastasis
CNS haemorrhage
Recent epilepsy
Peripheral blood can be contaminated with CSF which is a common
complication. If so, leucocytes are seen admixed with red blood cells and their
ratio is same as in peripheral blood. Erythrophagocytosis if present, it implies
that CSF haemorrhage has occurred prior to the lumbar puncture. (39)
Hence
erythrophagocytosis suggests other causes like herpetic encephalitis and
intracranial bleed. In such cases, viral culture and imaging studies have to be
done.
24
MICROBIOLOGY
CSF collected can be subjected to microbiological examination to rule out
meningitis.
Various tests done are Gram staining, microbiological culture, polymerase chain
reaction.
Gram stain is used to identify bacteria in case of bacterial meningitis. (40)
Microbiological culture is considered as the gold standard in detecting bacterial
meningitis. Viruses and fungi are also cultured using respective culture
techniques.
Polymerase chain reaction has been widely used nowadays in the
diagnosis of certain viral meningitis like enterovirus and herpes virus and
Neisseria meningitidis.Though PCR technique is expensive, we can get the
results fast and it is a highly sensitive and specific technique. It can be done
even with small amount of CSF. (41, 42)
MARKERS IN SEPSIS
Numerous serological markers like pro-inflammatory cytokines,
chemokines, acute phase proteins, adhesion molecules and cell surface proteins
are used to diagnose sepsis early.
Interleukin-8
25
Interleukin-6
C- reactive protein
Procalcitonin
Tumour necrosis factor- alpha
Integrin alpha-M
CD64
L- Selectin
Melatonin
INTERLEUKIN 8 IN THE DIAGNOSIS OF LATE ONSET SEPSIS
Interleukin 8 is a C-X-C chemokine produced mainly by macrophages,
epithelial cells, endothelial cells airway smooth muscle cells. (43)
Interleukin 8 is
a main chemotactic factor for neutrophils and other granulocytes. (44)
Interleukin 8 in serum is higher in infants with sepsis when compared to normal
neonates. Among the sepsis cases, interleukin 8 level is lower in survived
infants than in those who succumbed to infection.
INTERLEUKIN-6
IL-6 acts as pro-inflammatory cytokine secreted mainly by T-
lymphocytes and macrophages. It induces the hepatocytes to synthesize the
acute phase reactants.IL-6 rises rapidly following the invasion of bacteria. It is
highly sensitive during the early phases of infection as the cytokines are
26
elevated before CRP. But during the late stages it is not sensitive because of its
short half-life. This may be due to plasma protein binding and inactivation
resulting in normalisation of values although the sepsis persists.
C reactive protein
C – Reactive protein is an acute phase protein produced in liver. (45)
Normal CRP level in serum is 5 to 10 mg/L. It is the first identified pattern
recognition receptor. It binds with its high affinity ligand phosphocholin which
is present in the cell walls of microbes and in many bacterias. It activates the
complement pathway through C1Qcomplex. Interleukin-6 and interleukin -1
helps in the production of CRP by hepatocytes.CRP is higher in pregnancy,
viral infection(10-40 mg/L), bacterial infection(40 – 200 mg/L), severe
infections and burns -200mg/L and above.
CRP crosses the placenta only in minute quantities. Hence elevation of
CRP in neonates indicates endogenous synthesis. De novo synthesis of CRP
starts rapidly within 2 hours of inflammation and attain a peak at two days.
Elevated CRP level is not always indicative of sepsis as the rise may be
physiologic after birth or due to non- infectious causes.
CRP is not reliable in the early stages of sepsis. Determination of single
CRP value is also not sufficient for diagnosis. Therefore, serial measurements
27
of serum CRP helps to monitor the treatment response, to identify the possible
complications and to determine the duration of antibiotic treatment.
If two consecutive CRP levels are less than 10mg/l which is determined
more than 1 day apart it indicates infants are not infected or the infection has
resolved.
Preterm infants have lower CRP baseline levels and their response to
infection is also lower than term infants. Initially determination of CRP should
be combined with other sensitive serological markers like IL-6, IL-8, and
procalcitonin.
Non-infectious causes for elevation of CRP in neonates
Perinatal asphyxia/ shock
Prolonged labour
Fetal distress
Prolonged rupture of membranes
Maternal fever
Meconium aspiration
Application of Surfactant
Pnumothorax
IVH
Tissue injury
28
PROCALCITONIN
Procalcitonin is the precursor of calcitonin, the hormone involved in
calcium homeostasis. Normal procalcitonin level is <0.01 microgram/L that
cannot be detected by routine clinical assays. Procalcitonin level rises following
bacterial infection. In such cases it is released mainly by intestinal cells and
lung cells. When procalcitonin level is greater than 0.5 microgram/L, antibiotic
can be started. If it is less than 0.1 microgram/L there is no need for antibiotics.
(46) Procalcitonin was significantly higher in gram positive sepsis than gram
negative sepsis.
TUMOUR NECROSIS FACTOR ALPHA (TNF-alpha):
TNF-alpha is also known as cachexin or cachectin. This cytokine is produced
by macrophages, CD4 T cells, NK cells, mast cells, eosinophils, neutrophils,
neurons. TNF is an acute phase protein responsible for systemic inflammation.
(47) TNF is released in response to bacterial products, lipopolysaccharide. It acts
along with interleukin 1 and interleukin 6 in sepsis. In the liver, it stimulates the
release of C- reactive protein. Helena Martin et al, found that serum levels of
IL-8, IL-6, and TNF alpha were higher in septic neonates.
INTEGRIN ALPHA M (ITGAM)
ITGAM also known as complement receptor 3 (CR-3) or CD11b or
macrophage-1 antigen. It is the heterodimeric integrin found on the surface of
29
white blood cells, macrophages, natural killer cells, granulocytes. (48)
This
integrin is the mediator of inflammation producing phagocytosis, leukocyte
adhesion, chemotaxis and cellular activation. It binds inactivated component of
complement 3b.
CD64
Cluster of differentiation 64 is an integral membrane glycoprotein
otherwise known as Fc receptor. Neutrophils express CD64 when they are
exposed to G-CSF and interferon gamma. SIRS patients had increased
expression of CD11c, CD64 and EMR2 on neutrophils. (49)
L-Selectin
This is a cell adhesion molecule otherwise called CD62L. It recruits
lymphocytes to the secondary lymphoid organs. (50)
Central T lymphocytes
express L-selectin that will proliferate when they encounter antigen. There are
increased expression of L-selectin in leucocytes during sepsis. L-selectin is a
predictor of mortality due to sepsis. (51)
MELATONIN
Melatonin is an indolamine which is endogenously synthesized by pineal
body. It is an anti-inflammatory agent and also an anti-apoptotic factor. El-
Mashad et al found that endogenous melatonin levels are elevated in late onset
neonatal sepsis and it can be used as a potential serological marker for sepsis
30
when combined along with CRP. As melatonin also has anti-oxidant property, it
scavengesthe free radicals responsible for the pathogenesis of neonatal sepsis
and the related complications. Elosio Gitto et al found that white blood cell
count, absolute neutrophil count and CRP were reduced significantly in
melatonin treated sepsis infants.
URINE CULTURE
Urine cultures are usually not indicated as the yield is very low. But in the
following conditions urine examination has to be done.
Neonates suspected to have fungal infection
Neonates with vesicoureteric reflex
Neonates having urogenital malformation
Neonates having symptoms of urinary tract infection ( crying during
micturition ).
URINE SAMPLE
Urine sample can be obtained by three ways
Clean catch midstream urine sample
Suprapubic aspiration
Catheterising bladder
31
DIAGNOSIS OF URINARY TRACT INFECTION
Urinary tract infection should be diagnosed if there is any one of the following
Centrifuged sample- presence of > 10 white blood cells/ cu.mm in 10ml
of urine
Suprapubic aspiration- presence of any microorganism in urine
Catheterised sample- presence of > 10000 organisms/ ml.
RADIOLOGY
Chest X-Ray is indicated in case of apnea or respiratory distress.
Abdominal X-Ray should be considered when there are signs of
necrotising enterocolitis.
CT should be done in all neonates having meningitis.
Clinical features of sepsis are grouped under a syndrome called Systemic
Inflammatory Response Syndrome.
SIRS- SYSTEMIC INFLAMMATORY RESPONSE SYNDROME (52 – 55)
Systemic inflammatory response syndrome is a systemic inflammatory
condition affecting the various organs mainly due to immune system response
to infection. There will be cytokine storm. It may be due to infectious or non-
infectious cause.
32
PAEDIATRIC SIRS CRITERIA (53)
In children, either the heart rate should be more than 2 SD above normal
for that age in the absence of pain or drug administration or persistently
elevated heart rate for more than half an hour to four hours that is
unexplained.
For infants, the heart rate should be < 10th percentile for that age inthe
absence of drugs like beta-blockers, vagal stimuli or any congenital heart
disease. It also includes persistently depressed heart rate for more than 30
minutes that is unexplained.
Abnormal body temperature that is >38.5 degree C or < 36 degree C that
is recorded either orally, rectally or from Foley catheter.
Respiratory rate should be more than 2 SD above normal for that age or
the mechanical ventilation requirement that is not due to neuromuscular
disease or anaesthetic administration.
Higher or lower leucocyte count for that age that is unrelated to
chemotherapeutic drugs or band forms more than 10% including other
immature forms.
CAUSES (54, 55)
Infectious
Non-infectious
33
When infection leads to systemic inflammatory response syndrome it can be
considered as sepsis.
Non infectious causes
Burns
Trauma
Haemorrhage
Ischaemia
Pancreatitis
As surgical complication
Pulmonary embolism
Complicated aortic aneurysm
Cardiac tamponade
Adrenal insufficiency
Anaphylactic reaction
Drug overdosage
SIRS leads to single or multiorgan failure.
It includes,
Acute kidney injury
Acute lung injury
CNS dysfunction
34
Shock
Multiorgan dysfunction
INITIATION OF SIRS (52, 53)
Any infection, inflammation or trauma activates inflammatory cascade.
Infectious agent release either exotoxin or endotoxin that induces macrophages,
mast cells, endothelial cells and platelets to release cytokines. Interleukin 1 and
tumor necrosis factor alpha is first released and they cleave NF-KB inhibitor.
Hence NF-KB is activated. It enters the nucleus from cytoplasm and starts the
transcription of several genes involved in inflammation. It initiates the
formation of several pro-inflammatory cytokines. In case of viral infection
interferon gamma is released. NF-KB mainly induces IL-8, IL-6 and interferon
gamma.IL-6 causes the release of C-reactive protein. TNF-alpha is released
more in infection than in trauma. Hence there is high fever in infection than
trauma. The proinflammatory interleukins act on the tissue directly or it causes
activation of complement ascade, coagulation cascade. Complment proteins C3a
and C5a causes’ vasodilation, hence vascular permeability is increased.
Prostaglandins produce endothelial damage resulting in multiorgan failure.
TNF-alpha and IL-1 serves 2 functions. One, it acts on endothelial
surfaces exposing the tissue factor leading to the formation of thrombin.
Thrombin promotes further coagulation it itself a proinflammatory mediator.
Second, they impair fibrinolysis by plasminogen activator inhibitor -1
35
production. In addition, the cytokines inhibit activated protein C and anti-
thrombin. If coagulation cascade is unchecked it results in the formatiom of
microvascular thrombosis and multiorgan dysfunction.
BALANCE BETWEEN INFLAMMATORY AND ANTI-INFLAMMATORY
RESPONSE (55)
In order to tackle the inflammatory response, counter inflammatory
response is activated. Both processes run simultaneously.
Counter inflammatory response involves anti-inflammatory cytokines IL-
10 and IL-4. They inhibit the formation of IL-8, IL-6, IL-1 and TNF- alpha.
They are involved in the production of TNF- alpha and IL-1 receptor
antagonists. Hypothalamo- pituitary –adrenal axis activation leads to the
formation of glucocorticoid. It has immunosuppressive effect thereby inhibits
the release of cytokine.
Patient’s prognosis is determined by the balance between SIRS and
counter response. The antagonistic system is activated mainly to balance the
effect of pro-inflammatory and anti- inflammatory cytokines. So any
derangements results in excess activation of proinflammatory cytokines leading
onto severe systemic inflammatory response syndrome with high risk for multi-
organ dysfunction. 2. Immunosuppression due to excess of anti-inflammatory
cytokines.
36
ORGAN DYSFUNCTION (56)
SIRS can cause multi-organ dysfunction. It mainly affects lungs, kidneys,
liver, heart and CNS.
Mechanisms involved are
o Dilation of blood vessels
o Increased vascular permeability- as starling’s mechanism is
impaired , fluid enters the interstitial space
o Endothelial damage and formation of microvascular thrombosis
leading onto DIC
o Formation of free radicals
o Formation of proteases
o Nitric oxide synthase induction resulting in NO production
RESPIRATORY DYSFUNCTION (56)
It is common in SIRS. Patient either have tachypnoea, hypoxia or
respiratory alkalosis. In severe cases it leads to acute lung injury or ARDS.
There is dysfunction of endothelium of pulmonary capillaries due to
proinflammatory cytokines. As capillary permeability is increased , it results in
accumulation of interstitial fluid and formation of protein rich alveolar edema.
With progression there will be destruction of surfactant, type I pneumocytes and
formation of microatelectasis.
37
CARDIOVASCULAR DYSFUNCTION (56)
Pro-inflammatory cytokines have its effect on heart and the blood vessels.
Nitric oxide is synthesized from L-Arginine found in the endothelium of blood
vessel by inducible nitric oxide synthase enzyme. NO causes hypotension due to
reduction of systemic vascular resistance. Hence cardiac output is increased.
Baroreceptors are stimulated causing tachycardia. Hence stroke volume is
increased. But hypovolemia causes decrease in preload thereby reducing the
cardiac output. Moreover endotoxins and cytokines causes myocardial
depression within 24 hours of SIRS. Constitutive nitric oxide causes myocardial
relaxation thus increasing end diastolic volume. Inducible nitric oxide decreases
the contractility of the myocardium.
RENAL DYSFUNCTION (56)
As there is systemic vasodilation in SIRS renal perfusion is reduced.
There is cytokine induced production of vasoconstrictors like thromboxanes and
leukotrienes that decreases renal blood flow. Renin-angiotensin system is also
activated. Kidney is also damaged by leucocyte mediated injury causing
neutrophil aggregation and formation of reactive oxygen species.
38
GASTROINTESTINAL DYSFUNCTION (56)
Hypoperfusion distrupts the intestinal wall causing barrier dysfunction.
As a result there is translocation of bacteria from the intestinal lumen to the
internal environment.
METABOLIC DYSFUNCTION (56)
Hypoperfusion results in hypoxia of tissues and lactic acidosis. Nitric
oxide blocks cytochrome oxidase and hence affects mitochondrial electron
transport resulting in cellular hypoxia and formation of reactive oxygen species.
HAEMATOLOGICAL DYSFUNCTION (56)
Coagulation pathway is affected in SIRS due to cytokine mediated release
of tissue factor from the endothelium. This results in disseminated intravascular
coagulation leading to formation of microvascular thrombi and also bleeding.
Antithrombin III inhibits not only thrombin but also factors IX, X, XI,XII.
Thrombomodulin is derived from the endothelium which inhibits clotting and
activates fibrinolysis. This thrombin binding protein decreases the action of
thrombin. Thrombin-thrombomodulin complex activates protein C and protein
S which inhibits factor V and factor VIII. In sepsis, thrombomodulin production
and circulating protein S levels are reduced.
39
Expected haematological values for term newborns
At birth, term babies have different red blood cell count, white blood cell
count and haemoglobin levels when compared to adults. They have relative
polycythemia and their red blood cells are macrocytic with marked
polychromasia. Nucleated red blood cells are seen and white blood cell count is
high. After birth, there are significant changes in oxygenation. Erythropoietin
slowly disappears after few days. Hence red blood cell production is markedly
reduced during the 1st week of life. This results in the development of
physiological anemia which is transient during the end of neonatal period. (57)
In
the postnatal period the haemoglobin, RBC count and MCV all gradually
decreases.RBC count reaches its lowest level at 7th week and the haemoglobin
reaches its lowest point only during 9th
week. This delay in the fall of
haemoglobin concentration is due to high MCV that progressively decreases
and adult level is reached by 11 weeks. Mean corpuscular haemoglobin
concentration is relatively low in newborns when compared to adults. MCHC
increases in the first 5 weeks and then it remains constant. As the erythropoietic
activity is persistent during the first few days the reticulocyte count is high after
birth. At the 1st week reticulocyte count drops and remains low. Then it
increases and attains the peak level at 9th
week. As the size of the red blood cell
varies red cell distribution width is elevated. In particular, premature neonates
40
have more number of irregular red blood cells that is schistocytes, keratocytes
and acanthocytes.
In full term infants haemoglobin F is 50 to 80% and haemoglobin A is 20
to 50%. After birth haemoglobin A is predominant. As the oxygen affinity for
Hb A is low than Hb F it delivers oxygen readily to the tissues thus provides
better oxygenation. As erythropoietin level is maintained by tissue partial
pressure of oxygen its level decreases following better oxygenation. After birth
erythropoietin is produced mainly from kidney. (57)
Nucleated red blood cells are
routinely seen in the 1st day of healthy neonates. 0 to 10 nucleated red blood
cells per 100 white blood cells can be present. Normally after birth nucleated
red blood cells are cleared from the peripheral blood. By 3rd
to 4th
day, there will
not be any nucleated red blood cells. But in preterm babies it can be seen upto
one week. (58)
Term neonates have increased white blood cell count with increased
neutrophils at birth. The neutrophils continue to rise in the first 12 hrs then it
attains a peak and further it decreases gradually. Neutrophil count will be lower
around 3rd
day of life and then it increases gradually to attain the stable level by
5th
day. This count is maintained throughout the neonatal period. Certain
perinatal factors alter the dynamics of neutrophils. That includes maternal fever,
maternal hypertension, haemolytic disease of newborn and perivascular
haemorrhage. (59)
Girl babies have higher neutrophils 2000cells/ microlitre than
41
boys. Increased neutrophils at birth is mainly due to mobilization of neutrophils
from bonemarrow because of the stress occurring in the labour period and not
due to increased production of white blood cells in the bonemarrow.(57)
Neutrophils show shift to left . Many metamyelocytes, myelocytes and even
blasts are noted in the peripheral blood. Rarely, micromegakaryocytes may be
seen in the peripheral blood of early neonates. It should not be considered as
blasts. Neutrophil count is increased only transiently at birth. Later,
lymphocytes form the predominant population which remains even in early
childhood. In bone marrow erythroid series show marked hyperplasia and
myeloid series show relative hypoplasia. At the last weeks of pregnancy, there
will be rapid growth of fetus and at that time production of red blood cells are 3
to 5 times more than that of adults. (57)
HAEMATOLOGICAL VALUES IN SMALL FOR GESTATIONAL AGE
TERM NEONATES
If birth weight of the baby is below the tenth percentile it is considered as
small for gestational age. Small for gestational age neonates have different
complete blood count parameters when compared to appropriate for gestational
age neonates. (60)
Ozbek et al found that at day 1 SGA neonates have increased
haemoglobin, packed cell volume, red blood cell count and nRBCs than AGA
babies. SGA neonates have increased erythropoietin levels because of
intrauterine hypoxia. Hence they show higher red blood cell indices and relative
42
polycythemia. Compared to AGA term babies, SGA neonates have decreased
leucocyte count and shift to left in neutrophilic series is more pronounced as
there is more metamyelocytes in the peripheral blood. 34% of SGA neonates
have platelet count < 1.5 lakhs/cu.mm. But only 4% of AGA neonates have
reduced platelet count. Platelet count reaches normal by 7th
postnatal day. (61)
EXPECTED HAEMATOLOGICAL VALUES FOR PRETERM INFANTS
Production of erythropoietin and composition of fetal blood are highly
varied with gestational age. Hence normal haematopoiesis is interrupted in
premature birth of babies. Thus premature babies have very low level of
erythropoietin and reduced red cell mass at birth. Anaemia of prematurity may
be due to rapid growth of the body producing hemodilution, reduced lifespan of
red blood cells, poor body iron stares and initial dependence of liver as the
source of erythropoietin. (62)
Hence the haemoglobin concentration continues to
decrease for a more period of time in premature babies for about 8 to 12 weeks.
Moreover, their RBC count is low with reduced life span. Haemoglobin and
hematocrit values are reduced but they have higher mean corpuscular volume.
When compared with term babies, preterm babies have more nucleated red
blood cells and they remain longer in blood. (63)
43
HAEMATOLOGY LABORATORY ISSUES RELATED TO NEONATAL
BLOOD SAMPLES (64)
There are number of pre analytic variables that affect the quality of
laboratory test. It includes collection of specimen, handling of specimen, size of
the sample and analytic interference. These factors are considered for samples
of any age but it is much more important in neonates and infants.
PREANALYTIC FACTORS AFFECTING HAEMATOLOGY TESTING IN
NEONATES AND YOUNG CHILDREN
Limited blood sample, different sampling sites varies the test results
vigorous crying of the baby or any exertion affects the test results. (65)
LIMITED BLOOD AVAILABILITY
In children the total blood volume is markedly lower when compared to
adults as it depends on the weight and height of the individual. The total blood
volume of preterm and term babies ranges from 80ml/kg to 120ml/kg. So in
preterm babies, 10ml of blood collected for testing represents 10% of the total
volume of blood. (66)
Therefore, blood drawn should not be more than 5% of
total volume of blood per draw. Hence in infants, less amount of blood is
available for testing. Moreover, repeated phlebotomies may produce iatrogenic
anemia. Hence greater scrutiny is needed while collecting blood in preterm
neonates.
44
As vacutainer has constant amount of anticoagulant, very small amount
of blood collected may cause clotting of the sample or produce haemodilution.
To reduce those problems, Microtainer tubes are used. But this tube is so small
and is of nonstandard size. It should be handled manually as automatic
haematology analyzers or robotic systems cannot process these tubes
automatically. Moreover, clotting of blood, insufficient sample and haemolysis
are commonly encountered problems in neonates. (65)
VARIATION OF RESULTS DEPENDING ON BLOOD SAMPLING SITES
In neonates and children, we can collect blood from so many sites by
direct puncture of arteries, umbilical vessels or peripheral vein catheterization,
heel prick. In heel prick, we can get adequate amount of blood and there is no
risk of vascular catheterization. (67)
Automatic devices can be used for collecting
blood. In that case, a standard incision is made on the infant’s heel and
adequate blood is collected for testing. Blood collected from skin puncture has
various proportion of blood from venules, arterioles, intracellular and interstitial
fluids. Blood counts show some variations according to the sampling site and
they are very much pronounced in neonates.
Composition of blood varies among veins, arteries and skin puncture and
they are not considered equivalent. Warming the heel of the infant may improve
the circulation but it does not reduce these differences. (68)
Skin puncture blood
have increased haemoglobin, red blood cell count and packed cell volume.
45
White blood cell count and neutrophils are also increased. Capillary blood
composition can be affected by perfusion status, metabolic state or several other
factors. Microcirculation causes higher capillary haematocrit. (69)
Therefore in a
sick neonate, haematocrit value obtained from capillary blood may be
misleading and underlying anaemia may be missed.
Unlike the other red blood cell indices, venous mean corpuscular volume
is higher than capillary MCV. This is due to capillary blood hemoconcentration
and loss of fluid from red blood cells. Mean corpuscular concentration and red
cell distribution width is same in both venous and capillary blood.
Leukocyte counts and differential counts also varies between arterial,
capillary and venous blood. Arterial blood has lower WBC count than capillary
and venous blood. Hence we may consider the neonate to be neutropenic when
actually the arterial blood has normal WBC count. There are only minor
differences when the arterial and venous samples are collected simultaneously.
Mean corpuscular haemoglobin concentration is slightly more and neutrophil
counts are same.
Platelet counts are same in arterial, venous and heel stick samples. Other
studies reveal low platelet count in capillary samples when compared to venous
samples. (69)
As heel stick causes activation, aggregation and local consumption
of platelets it produces low platelet count. This observation is also supported by
the finding that venous platelets have lower mean platelet volume than capillary
46
platelets. Resting platelets have lower mean platelet volume than activated
platelets. (69)
The difference in the neutrophil counts and haemoglobin values among
arterial and capillary blood are more pronounced in preterm neonates.
Thurlbeck and McIntosh found that capillary blood haemoglobin is higher than
arterial blood with an average difference of 2.5 g/dl. WBC count in capillary
blood is higher than arterial blood with a mean of 1.8 x 10^9/L. (70)
If we are
aware of these differences existing between the samples obtained from different
sites we can avoid the unnecessary intervention.
ANALYTIC FACTORS AFFECTING HAEMATOLOGY TESTING
Blood samples of neonates often encounter analytic interference than adults.
Blood sample may be inadequate resulting in various problems. There may be
excess EDTA or insufficient blood sample producing fibrin precipitates,
aggregates of platelets and leucocytes. This leads to spuriously reduced platelet
and leucocyte counts. As there is insufficient blood sample repeat testing of the
sample cannot be done to confirm the test results thus further complicate the
problem. There is no much information regarding any differences between
automatic analyzers and laser technology in dealing with neonatal blood
samples. (71)
Both instruments have its own advantage but none is considered as
the superior instrument regarding analysis of neonatal blood samples. Neonatal
sample analysis can be done in Beckman Coulter, sysmex or Abbott
47
instruments. An automated differential white blood cell count done on Beckman
Coulter is considered superior to manual differential leucocyte count. Though
automatic analyzers are fast and measure accurately, at times spurious results
can be obtained. In neonates, there is much interference in haematological
analysis.
The neonatal red blood cells are resistant to lysis.
Increased number of nucleated red blood cells
Increased serum bilirubin
Hyperlipidemia
In neonates receiving total parenteral nutrition.
In case of hyperbilirubinemia , hyperlipidemia due to total parenteral
nutrition and high leucocyte count ther will be increased turbidity of the blood
sample. It may result in high haemoglobin levels. Hence MCH, MCHC and
PCV all will be elevated spuriously. (65)
POST ANALYTIC ISSUES: INTERPRETATION OF HAEMATOLOGICAL
RESULTS IN TERM AND PRETERM NEWBORNS
As interpretation of results is the starting point to arrive at differential
diagnosis thourough knowledge of the haematological values of newborns is
necessary for proper diagnosis. Complete blood count is associated with
48
gestational age, weight at birth, crying, sampling site, delivery mode, physical
therapy and several other factors. (65)
REFERANCE INTERVALS FOR NEWBORNS
As neonates and infants haematological values different from adults
separate reference values should be maintained in each laboratory. However
health related reference values are difficult to obtain in neonates and young
infants. Extra blood samples from normal healthy infants cannot be obtained.
As it is a difficult task many laboratories use already published reference values
instead of formulating their own. As reference intervals depends on the method/
technology applied the values obtained with old instrumentation or manual
counts are not employed in current practice. With the current instruments and
haematology analysers the results obtained are more precise and more accurate.
In order to solve the problem manufacturers establish their own reference
values. This, statistical methods have been established to formulate reference
intervals.
Haematological values of children who are hospitalized for some health
problems are used in generating reference intervals. By using this method
Soldin generated reference intervals for newborns which were published in
American association for clinical chemistry press. (72)
Main problem with the
published reference intervals for newborns including the published intervals of
AACC does not include the site of sampling, weight of the newborn, gestational
49
age and race. The reference intervals are based on the assumption that all
neonates and all blood samples are similar. Term neonates have haematological
values different from preterm babies. Hence reference values of term babies
cannot be applied for preterm babies. As gestational age advances haemoglobin
and packed cell volume increases, mean corpuscular volume decreases.
In preterm neonates white blood cell count is 30% to 50% lower as
compared to term neonates. Even though it is known that gestational age alters
the haematological parameters, the exact degree of this effect is not certain due
to the inconsistent and limited published data available for preterm neonates.
Due to this reason applying reference intervals of term neonates to preterm
babies may result in misdiagnosis of anaemia. It may lead to unnecessary
workups and repeating the blood sample may aggravate the anaemia. Moreover,
composition of venous blood, arterial blood and capillary blood differ from one
another. Hence reference intervals generated by using capillary blood will vary
from reference intervals generated by using venous blood.
There are also ethnic and racial differences that are not included in
current reference intervels. White infants have higher haemoglobin, mean
corpuscular volume, and packed cell volume than black infants. (73)
50
PLATELETS IN THE NEONATAL PERIOD
Platelets appear first in the fetus at 5th week after conception and it
increases in number reaching 1.5 lakhs by the end of 1st trimester. It reaches
adult levels by 22 weeks. 22 weeks is considered as the lowest gestational age at
which the fetus is viable. Hence even the most premature neonates have platelet
counts in the range of 1.5 to 4.5 lakhs. Healthy preterm neonates usually have
platelet counts in the range of 1 to 1.5 lakhs when compared to term neonates,
children or adults. Therefore in neonates thrombocytopenia is considered when
platelet count is below 1.5 lakhs. (74)
Incidence of thrombocytopenia in sick
neonates admitted in NICU is higher than in the general neonates. Most of them
are most premature having birth weight < 1 kg. Intracranial haemorrhage is
common in preterm neonates of any age and 25% of neonates with birth weight
less than 1.5 kg have an intraventricular haemorrhage especially during the 1st
week. But the cause of IVH in this age is multifactorial and IVH commonly
seen in preterm neonates having normal platelet counts. As premature neonates
have immature haemostatic system and frequent occurrence of intracranial
haemorrhage producing poor neuro-developmental outcome such
thrombocytopenic infant has to be transfused with higher platelet counts than
adults. But transfusion thresholds are not established and hence there are
extreme variability in practicing platelet transfusion. (75)
51
RESPONSE OF NEONATAL MEGAKARYOCYTES TO
THROMBOCYTOPENIA
Normally, adult bone marrow responds by increasing the size and ploidy
of megakaryocytes first followed by increasing the number of megakaryocytes
inorder to overcome the increased platelet demand. This results in 2 to 8 fold
increase of megakaryocyte mass. Neonates with thrombocytopenia can increase
the platelet number but the size is not increased. Hence neonatal
megakaryocytes have some developmental limitations to increase the size to
response to increased platelet demand. (76)
PLATELET FUNCTION AND PRIMARY HEMOSTASIS IN NEONATES
Platelet transfusions are provided routinely when the platelet count is
below a certain level but the risk of bleeding is determined not only by platelet
count but also by several factors like gestational age, post conceptional age,
platelet function and haemostatic balance. Recent study reveals that among
thrombocytopenic neonates 90% of significant clinical haemorrhages occurs in
< 28 weeks of gestation and during first 14 days of life. (77)
Preterm neonates
are more prone to bleeding but most of the studies are conducted in term
neonates using cord blood.
52
PLATELET FUNCTION IN TERM NEONATES
The developmental differences of platelets are first established by platelet
aggregation studies. It is done in platelet- rich plasma derived from cord blood
of term neonates. Initial studies revealed that cord blood derived neonatal
platelets were less responsive to agonists like epinephrine, ADP, collagen and
thrombin. Flow cytometric studies also reveals that neonatal platelets when
stimulated with agonists reduced expression of platelet surface activation
markers. The reduced response to epinephrine is due to lower alpha 2
adrenergic receptors. (78)
The hyporesponsiveness to collagen is due to impaired
calcium mobilization and to thromboxane is ineffective signalling of the
downstream pathways.
Bleeding times were shorter in full term neonates. PFA- 100 revealed
shorter closure times in full term neonates. All these studies suggested an
increased vessel wall- platelet interaction that causes increase in haematocrit,
MCV, VwF. There is increased VwF polymers in neonatal blood which
counteract the hyporeactivity of platelets. (79)
PLATELET FUNCTION IN PRETERM NEONATES
Thrombocytopenia incidence is highest in preterm neonates especially <
30 weeks .There is also increased risk of bleeding in these neonates.
Flowcytometric and aggregometric studies revealed that platelets were
53
hyporeactive at birth in preterm neonates. In vitro hyporeactivity of platelets
was more pronounced in preterm than full term neonates. These were most
evident on infants with lowest gestational age (< 30 weeks) imparting a
correlation between gestational age and reactivity of platelets.
Two of the studies with cone and platelet analyzer revealed that platelet
adhesion was reduced in preterm neonates as compared to full term and the
adherence was also related to gestational age in the first 2 days of life. Hence
the difference in the adhesion of platelets was not due to low VwF antigen
levels or the ristocetin cofactor activity. They were because of some
developmental differences in platelet function. (80)
Bleeding times done on 1st
day of life were higher in preterm when compared to full term neonates.
Neonates with < 33 weeks exhibit longest bleeding time that is approximately
twice as long as in full term neonates.
Closure time done on 1st day neonatal blood in response to ADP using
PFA-100 was inversely correlated to gestational age. These differences reflect
the lower haematocrit and more pronounced hyporeactivity of platelets in
preterm neonates. Closure times measured in neonatal blood even in the 1st 48
hrs of life using PFA- 100 were longer than cord blood. They remained shorter
or same as adult closure times at all gestational ages suggesting that pretetrm
babies have adequate primary homeostasis. (81)
Flow cytometry and platelet
54
aggregation studies suggested that hyporeactivity of platelets was present 3- 4
days after birth in both full term and preterm neonates.
The gestational age dependent difference in adhesion of platelets found to
persist for 10 weeks. Anemia prolongs the BT in preterm in the 1st week of life.
Preterm neonates with sepsis have reduced platelet adherence than healthy
preterm neonates suggesting a increased bleeding tendency in that population.
Full term neonates born to mothers with gestational diabetes and pregnancy
induced hypertension displayed lower platelet adhesion as compared to healthy
full term infants. (82)
ABSOLUTE NEUTROPHIL COUNT
Total white blood cell count acts as a good predictor of occult bacteremia
and absolute neutrophil count is more sensitive than total WBC count. (83)
BAND COUNTS AND TOXIC CHANGES (84)
Absolute neutrophil count and morphological changes in neutrophils like
toxic granulations, Dohle bodies and vacuolations are more sensitive in
predicting bacterial infections. Neutrophil band counts have greater sensitivity
in infants.
IMMATURE COUNTS
Seebach et al evaluated neutrophil left shift parameters in the diagnosis of
infectious diseases. It was found that band count of 20% or more of total
55
leucocyte count has 79% specificity and 53% sensitivity and it was superior to
I:T ratio.
Leucopenia, neutropenia, elevated I:M and I:T ratio were important
predictors of sepsis during the first 3 days of life and C reactive protein was the
best after 3 days of life. (11)
Identifying the patients with sepsis or very prone to sepsis is the most
important aspect of the management. Properly collected blood culture before
giving the antibiotics is the gold standard to diagnose sepsis. But the organism
takes time to grow in blood culture medium and the final report will be
available only after a minimum period of 48-72hours. Antibiotics are started
when the sepsis is clinically suspected after taking the blood sample for culture
and other blood parameters. Sometimes there may be no growth in the blood
culture but the antibiotics are started on the basis of clinical suspicion which
will cause the community and hospital acquired antibiotic resistance. Moreover,
it increases the cost of the treatment. To avoid this problem, there are other
methods which help to predict the neonate in sepsis and so that antibiotics can
be started appropriately. There are certain studies which assessed the
haematological parameters, which rapidly diagnose the neonates with sepsis.
But only a few studies, from India, compared the clinical parameters with the
haematological parameters in patients with sepsis. Hence this study was
conducted in our institution. (4, 5)
MATERIALS & METHODS
56
MATERIALS AND METHODS
INCLUSION CRITERIA:
Neonates( < 28 days of age ) with clinically suspected infection.
EXCLUSION CRITERIA
Neonates who received antibiotics already.
STUDY DESIGN:
Prospective observational study
SAMPLE SIZE:103
This is a prospective observational study which includes neonates (<28
days of age) who were admitted in neonatal intensive care unit of Coimbatore
medical college hospital. Duration of the study was between July 2015 to July
2016. Sample size of this study was 100. Blood samples were collected before
starting antibiotics. In neonates with suspected infection, 2 ml of peripheral
venous blood was taken under sterile precautions. 1 ml for blood culture and1
ml for peripheral smear. 1ml blood was collected in conventional blood culture
tubes and was sent to the microbiology department for assessing culture
sensitivity. The culture reports were collected after 72 hours.
57
Peripheral smear
A clean glass slide of size 7.5 x 2.5 cm and thickness of 1 mm was taken
and was wiped with cotton to remove any dust. The slide was labelled at one
end. The spreader slide was made by breaking the one corner of the slide with
the help of a glass cutter so that its width is 1.8cm.
A drop of blood was placed at 1cm from one corner of a slide in the
midline and a spreader slide was placed at a 30 degree angle in front of the drop
.Then the slide was moved backwards so that it touches the drop. Then the
blood was spread along the slide for a length of 3 cm. A monolayer was formed
where the cells were widely spaced to enable cell count. In the slide this
monolayer was formed in the feathered edge created by the spreader. Blood film
made was allowed to air dry. The air dried smear was stained with Leishman
stain.
STAINING PROCEDURE
The slide was set in a rack and was flooded with Leishman stain for 2
minutes. And then double the volume of buffer was added and was kept for 20
minutes. After that the slide was washed in tap water and was air dried.
Blood films were examined under oil immersion. Total white blood cell count,
platelet count were analysed with Sysmex auto- analyser and total white blood
58
cell count were corrected for nucleated red blood cells. Differential count and
neutrophilic changes were checked manually.
Haematological parameters like total leucocyte count (TLC), total
polymorphonuclear neutrophil count (PMN), immature polymorphonuclear
neutrophil count(iPMN), immature: Total (I:T) PMN ratio, immature: mature
(I:M) PMN ratio, platelet count, degenerative or toxic changes in neutrophils
were assessed and scored. All these seven parameters were assigned a score of 1
if they were abnormal. Abnormal total leucocyte count, abnormal total
polymorphonuclear neutrophil count, elevated immature PMN count (>600),
elevated immature to total PMN (I:T) ratio (>0.12),elevated immature to mature
PMN (I:M) ratio(>0.3), Platelet count (<150,000/cu.mm) degenerative changes
like toxic granulations, vacuolations, Dohle bodies were recorded. Abnormal
total PMN count was given a score of 2 if there was no mature neutrophils in
order to compensate for the low I: M ratio. The reference values of the
haematological parameters of Manisha Makkar et al were used as the standard
values. (Table-1).
Immature neutrophils include promyelocytes, myelocytes,
metamyelocytes and band forms. Absolute polymorphonuclear neutrophil
count, immature to total PMN (I:T) ratio and immature to mature PMN (I:M)
ratio were calculated from the observed values.
59
Score of ≤ 2: sepsis unlikely
Score 3-4: sepsis possible
Score ≥ 5: sepsis very likely
Minimum score- 0
Maximum score- 8
The scores were compared with clinical parameters and the most predictive
factor was identified.
60
Table-1: Hematological scoring system
PARAMETERS ABNORMALITY SCORE
Total WBC Count < 5000µl 1
≥ 25000 at birth 1
≥ 30000 at 12-24hrs
≥ 21000 day 2 onwards
Total PMN count 1800-5400 0
No mature PMN 2
Increased or decreased
count
1
Immature PMN count 600 0
Increased 1
I:T PMN ratio 0.12 0
Increased 1
I:M PMN ratio ≤ 0.3 0
≥ 0.3 1
Degenerative changes in
PMN
Toxic granules or
cytoplasmic vacuolations
1
Platelet count ≤ 1.5 lakhs/µl 1
WBC- white blood cell count; PMN- polymorphonuclear neutrophils; I:T PMN
ratio- Immature:Total ratio; I:M PMN ratio- Immature : Mature ratio
COLOUR PLATES
COLOUR PLATE 1: Leishman stain, Neutrophilic Leukocytosis, 40X
COLOUR PLATE:2 Leishman stain: Mature neutrophils and Immature forms,40X
COLOUR PLATE 3: Leishman stain, Immature forms, 100X
COLOUR PLATE 4: Neutrophil showing cytoplasmic vacuolations, 100X
COLOUR PLATE: 5 Leishman stain: Toxic granules in neutrophils, 100X
s
STATISTICAL ANALYSIS
61
STATISTICAL ANALYSIS
The data are reported as the mean +/- SD or the median, depending on
their distribution. Frequencies are expressed in percentages. The differences in
quantitative variables between groups were assessed by means of the unpaired t
test. ANOVA was used to assess the quantative variables. Sensitivity and
Specficity test was performed. The chi square test was used assess differences
in categoric variables between groups. A p value of <0.05 using a two-tailed test
was taken as being of significance for all statistical tests. All data were analysed
with a statistical software package. (SPSS, version 16.0 for windows).
RESULTS
62
RESULTS
This cross sectional study included total of 103 neonates. Based on the
clinical scoring system, neonates were classified into groups, namely, sepsis,
probable infection and normal infants (Table-2).
Table 2: Clinical group distribution.
Groups Number of cases (%)
Group-1 (sepsis) 36 (34%)
Group-2 (probable infection) 15 (14%)
Group-3 (normal infants) 53 (52%)
The diagnosis of sepsis was made when the blood culture was positive.
Neonates were classified as having probable infection when there was strong
clinical history or presence of 2 risk factors for infection and when the blood
culture was negative. Neonates were taken as normal when there was no clinical
history or risk factors for infection and negative blood culture.
63
Table 3: Age and Sex distribution
95% CI for
Mean
Mean SD Lower Upper Minimum Maximum p value
Male 3.9 3.1 3.1 4.8 1 13
Female 3.8 4 2.7 5.0 1 19 >0.05
Total 3.9 4 3.2 4.6 1 19
Mean age of male and female patients were 3.9 and 3.8 days respectively
(Table-3).
64
Table-4: Age distribution.
Sepsis – Hematological score
Very likely
[n=35]
Possible
[n=28]
No
Sepsis[n=40]
p value
Age
[Days] n (%) n (%) n (%)
1 14 40% 12 43% 11 28%
2 2 6% 3 11% 4 10% >0.05
3 8 23% 3 11% 8 20%
4 2 6% 3 11% 2 5%
5 1 3% 0 0% 6 15%
>5 8 23% 7 25% 9 23%
Among the study population majority of the neonates were within 24 hours of
birth (Table-4).
65
Figure. 1: Gender distribution
Both male and female patients were almost equally distributed in the study
population (Fig.1).
Male 51%
Female 49%
Gender Distribution[N=103]
66
Figure: 2. Distribution of neonates according to haematological score.
38%, 28% and 34% of cases were in no sepsis, possible sepsis and very likely
sepsis group according to haematological scoring system respectively.
(Figure-2) According to haematological scoring system, 86% of the patients in
very likely sepsis group had positive blood culture. None of the no sepsis
group, according to the haematological scoring system had positive blood
culture. Only 6% of patients in very likely sepsis group had probable infection.
But up to 50% of the patients in clinically probable infection group had blood
culture positive (not shown in the Table-5). Only 5% of patients in very likely
sepsis group had normal clinical score.
Very likely n=35 (34%)
Possible n=29 (28%)
No Sepsis n=40 (38)%
Sepsis-Hematological [N=103]
67
Table.5: Distribution of clinical and haematological sepsis groups
Clinical score
Hematological score
Very likely (%)
(score: > 5)
Possible sepsis
(%) (score: 3-4)
No sepsis (%)
(score:0-2)
Blood culture
+ve(n=36) 31 (86%) 5 (13%) 0 (0%)
Probable infection
(n=15) 1 (6%) 6 (40%) 8 (53%)
Normal (n=53) 3 (5%) 18 (33%) 32 (60%)
Majority of neonates (71%) in the very likely and possible sepsis group
were preterm. Low birth weight neonates were predominantly in very likely and
possible sepsis group, 77% and 71% respectively. Most neonates who require
resuscitation perinatally were in very likely and possible sepsis group, 86% and
57% respectively. Up to 30%of the neonates in very likely sepsis group had
meconium stained amniotic fluid.
68
Table-6: Association of clinical variables with haematological scoring system.
Sepsis – Hematological score
Very likely
[n=35]
Possible
[n=28]
No
Sepsis[n=40] p value
Age n % n % n %
1 - 4 26 74% 21 75% 25 63%
5 - 8 3 9% 3 11% 12 30% >0.05
9 - 12 5 14% 2 7% 3 8%
13 - 16 0 0% 2 7% 0 0%
17 - 20 1 3% 0 0% 0 0%
Gender
Male 25 71% 16 57% 17 43%
Female 10 29% 12 43% 23 58% >0.05
Gestational age
Pre
Term 25 71% 20 71% 11 28% <0.001
Term 10 29% 8 29% 29 73%
Birth weight
<2.5 kg 27 77% 20 71% 12 30% <0.01
>2.5 kg 8 23% 8 29% 28 70%
PROM
Yes 2 6% 1 4% 0 0%
No 33 94% 27 96% 40 100% >0.05
Resuscitation
need
Yes 30 86% 16 57% 30 75%
No 5 14% 12 43% 10 25% <0.05
Meconium stained amniotic
fluid
Yes 10 29% 5 18% 2 5%
No 25 71% 23 82% 38 95% <0.05
Prolonged
labour(>24hrs)
Yes 1 3% 0 0% 0 0%
No 34 97% 28 100% 40 100% >0.05
Prematurity
Yes 9 26% 9 32% 9 23%
No 26 74% 19 68% 31 78% >0.05
Activity
Yes 9 26% 15 54% 16 40%
No 26 74% 13 46% 24 60% >0.05
Culture
Positive 31 89% 5 18% 0 0%
No
Growth 4 11% 23 82% 40 100% <0.001
69
89% of the neonates in very likely sepsis group had blood culture positive
and none of the neonates in no sepsis group had positive blood culture.
Premature rupture of membrane, prolonged labour, prematurity and activity of
the neonate were not the predictors of neonatal sepsis. Gestational age, birth
weight, requirement of resuscitation perinatally and meconium stained amniotic
fluid were significant predictors of neonatal sepsis. Prematurity and perinatal
asphyxia which are sepsis screen parameters for at risk of sepsis are also found
to significantly correlate with haematological scoring system.(Table-6)
Table-7: Total WBC Count as predictor of sepsis
Sepsis - Hematological
WBC (ul) Very
likely Possible
No
Sepsis Total %
<5000 2 1 1 4 4%
5000 -
21000 21 24 39 84 82%
>21000 12 3 0 15 15%
Total 35 28 40 103
70
Figure 3: Total WBC Count as predictor of sepsis
Only 4% of neonates had leucopenia (<5000 cells / µl). Among them 2% of
neonates comes under very likely sepsis group.
15% of neonates had leucocytosis (>21,000 cells /µl)
12% of the neonates in very likely sepsis group and none of the case in No
sepsis group had leucocytosis.
Total WBC Count is considered as significant predictor of sepsis.
Very likely Possible No Sepsis
<5000 6% 4% 3%
5000 - 21000 60% 86% 98%
>21000 34% 11% 0%
0%
20%
40%
60%
80%
100%
120%
Total WBC Count as predictor of sepsis
[N=103][p<0.01]
71
Figure-4: Total PMN count as predictor of sepsis
89% of the neonates in very likely sepsis group had high total PMN count
(>5400) and only 30% of the patients in no sepsis group had high total PMN
count. Only very few neonates had low total PMN count. High total PMN count
was significant predictor of neonatal sepsis (p<0.001). (Figure-3).
Very likely Possible No Sepsis
< 1800 0% 7% 3%
1800 - 5400 11% 36% 68%
>5400 89% 57% 30%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Total PMN count as predictor of sepsis [N=103][p<0.001]
72
Figure-5: Immature PMN count as a predictor of sepsis
All the neonates in the very likely sepsis group and 82% of the neonates in the
possible sepsis group had high immature PMN count (more than 600). 90% of
the neonates in no sepsis group had low immature PMN count (less than 600).
Immature PMN count is significant predictor of the neonatal sepsis (p<0.001)
(Figure-4).
Very likely Possible No Sepsis
<600 0% 18% 90%
>600 100% 82% 10%
0%
20%
40%
60%
80%
100%
120%
Immature PMN count as a predictor of sepsis [N=103][p<0.001]
73
Figure-6: I:T PMN ratio as a predictor of neonatal sepsis.
97% of the patients in very likely sepsis group and 75% of the neonates in
possible sepsis group had higher I:T PMN ratio (ie, >0.12). 98% of the neonates
in no sepsis group had low I:T PMN ratio (<0.12). Higher I:T PMN ratio had
more likely chance of sepsis (p<0.001) (Figure-5).
Very likely Possible No Sepsis
<0.12 3% 25% 98%
>0.12 97% 75% 3%
0%
20%
40%
60%
80%
100%
120%
Association of IT PMN ratio with Sepsis [N=103][p<0.001]
74
Figure-7: I:M PMN ratio as a predictor of neonatal sepsis.
97% of the patients in very likely sepsis group and 46% of the neonates in
possible sepsis group had higher I:M PMN ratio (ie, >0.3). 88% of the neonates
in no sepsis group had low I:M PMN ratio (<0.3). Higher I:M PMN ratio had
more likely chance of sepsis (p<0.001). (Figure-6)
Very likely Possible No Sepsis
<0.3 3% 54% 88%
>0.3 97% 46% 13%
0%
20%
40%
60%
80%
100%
120%
Association of IM PMN ratio with Sepsis [N=103][p<0.001]
75
Figure-8: Degenerative changes as a predictor of sepsis.
60% of the patients in very likely sepsis group and 11% of the neonates in
possible sepsis group had degenerative changes in PMN like toxic granules and
vacuolations. 89% of possible sepsis group and all the neonates in no sepsis
group had no toxic changes in PMN. Degenerative changes in the PMN is a
significant predictor of sepsis (p<0.001). (Figure-7)
Very likely Possible No Sepsis
Yes 60% 11% 0%
No 40% 89% 100%
0%
20%
40%
60%
80%
100%
120%
Association of Degenerative changes in PMN ratio with Sepsis
[N=103][p<0.001]
76
Figure-9: Platelet count as a predictor of sepsis
57% of patients in very likely sepsis group had thrombocytopenia and 43% of
the patients in very likely sepsis group had normal platelet count. 70% and 30%
of neonates in the no sepsis group had normal platelet count and
thrombocytopenia respectively. Though this difference numerically appears
significant, statistically it is insignificant (p>0.05), hence platelet count is not a
significant predictor of sepsis (Figure-8).
Very likely Possible No Sepsis
<1.5 lakhs 57% 39% 30%
>1.5 lakhs 43% 61% 70%
0%
10%
20%
30%
40%
50%
60%
70%
80% Association of Platelet count with Sepsis [ N=103][p>0.05]
77
Highest sensitivity is seen with immature PMN count, IT PMN ratio and
IM PMN ratio. Total WBC count has lowest sensitivity but high specificity.
Platelet count and total PMN count have lower sensitivity, specificity, negative
predictive value and positive predictive value. Degenerative changes in PMN
and IT PMN ratio have the highest specificity.
Table-8: Performance of individual haematological parameters
Sensitivity Specificity Positve Predictive value Negative Predictive value
S P S+P S P S+P S P S+P S P S+P
Total WBC (µl) 40.00 14.29 28.57 97.50 97.50 97.50 93.33 80.00 94.74 65.00 61.90 46.43
Total PMN count 88.57 64.29 77.78 67.50 67.50 67.50 70.45 58.06 79.03 87.10 72.97 65.85
Immature PMN
count 100.00 82.14 92.06 90.00 90.00 90.00 89.74 85.19 93.55 100.00 87.80 87.80
IT PMN ratio 97.14 75.00 87.30 97.50 97.50 97.50 97.14 95.45 98.21 97.50 84.78 82.98
IM PMN ratio 97.14 46.43 74.60 87.50 87.50 87.50 87.18 72.22 90.38 97.22 70.00 68.63
Degenerative
changes inPMN 60.00 10.71 38.10 100.00 100.00 100.00 100.00 100.00 100.00 74.07 61.54 50.63
Platelet count 57.14 39.29 49.21 70.00 70.00 70.00 62.50 46.67 46.67 46.67 46.67 46.67
S - Sepsis group; P- Possible sepsis
IT PMN ratio, immature PMN count and degenerative changes have high
positive predictive value. IT PMN has the good sensitivity and excellent
specificity and positive predictive value. Degenerative changes have poor
sensitivity but good specificity and positive predictive value. Immature PMN
and I:T PMN ratio and I:M PMN ratio had better negative predictive value than
other parameters.
78
C-reactive protein:
Among the 103 neonates 40% had CRP positive. (Figure-9)
Figure-10: Prevalence of CRP positivity in the study population.
Positive 40%
Negative 60%
CRP [N=103]
79
Figure -11: Distribution of CRP positivity according to the hematological
scoring system:
77% of neonates in very likely sepsis group had elevated CRP and only 13% of
no sepsis group had elevated CRP. 88% of the neonates in the no sepsis group
had normal CRP and only 23% of sepsis group had normal CRP. This
difference was statistically significant.
Very likely Possible No Sepsis
Positive 77% 32% 13%
Negative 23% 68% 88%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
100%
Association of CRP with Sepsis [ N=103][p<0.001]
DISCUSSION
80
DISCUSSION
Sepsis neonatorum, neonatal septicaemia and Neonatal sepsis are the
terms used to describe systemic response in neonates to infective focus.
Neonatal sepsis causes significant morbidity and mortality. Morbidity can be
immediate or delayed sequelae which is devastating. Neonates are more
susceptible to the infection because of the immature development of the
immune system. Because of the subtle signs of sepsis in neonates, early
diagnosis and prompt starting of antibiotics are of paramount importance. (85)
Blood culture is the gold standard to diagnose the sepsis. But there is a
significant delay in getting the final report and sensitivity of the organisms to
various antibiotics. To overcome this problem there are various clinical and
haematological parameters suggested to predict the neonatal sepsis in advance.
(6)
In our study, sensitivity, specificity, and positive predictive value were
significantly more for degenerative changes in the PMN and IT PMN ratio.
These findings were similar when compared to available literature. (3, 86, 87, 88)
There is greater chance of sepsis noted in patients who have higher
haematological score. With the haematological score of less than 2, the sepsis is
least likely.
In our study, total WBC Count had high specificity and positive
predictive value.
81
In our study total PMN count had high sensitivity and Negative predictive
value and this finding was similar to Akenzua et al and Manisha et al. (89, 4)
In our study total platelet count was not a good predictor of sepsis which
is in contrast to the study by Speer et al. (3)
Elevated I:M PMN ratio had good
sensitivity in identifying sepsis which is similar to the study done by Philip et al
and Basu et al. (87, 88)
Immature PMN count is an excellent predictor of sepsis which correlates
with study done by Gosh et al and Narasima et al. (5, 6)
C- reactive protein is considered as better predictor of neonatal sepsis
which correlates with study done byGanesan P et al.
Hematological scoring system improves the accuracy of diagnosis of
sepsis. So, this can be used as a screening test in diagnosing sepsis. But it is of
paramount importance to standardize the procedure and interpretation of the
results by specific protocol.(86)
There are several methods for the rapid detection of microorganisms in
blood culture like, automated culture system, Fluorometric detection system and
DNA probe assay. But still haematological scoring system can be used as a
reliable parameter in predicting the neonates with sepsis
CONCLUSION
82
CONCLUSION
Hematological scoring system is a quick, simple, reliable and cost
effective tool for the early diagnosis of neonatal sepsis. This also helps
clinicians to predict the neonatal sepsis early and start the appropriate antibiotic
therapy to prevent sepsis related events. This also helps to avoid unnecessary
institution of antibiotics and development of resistance.
Immature: Mature polymorphonuclear neutrophil ratio(I:M ratio),
Immature: total polymorphonuclear neutrophil ratio (I:T ratio), degenerative
changes in neutrophils can be viewed as regular parameter which can predict the
possibility of neonatal sepsis.
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ANNEXURES
PROFORMA
Name
Age
Sex
Ward
Ip.No.
Gestational age
Birth weight
PROM
Maternal fever
Resuscitation need
Meconium stained amniotic fluid
Prolonged labour
Foul smelling liquor
Mode of delivery
Prematurity
Temperature (Hypothermia / Hyperthermia)
Activity
Rashes
Bleeding
Sclerema
LIST OF ABBREVIATIONS
RBC RED BLOOD CELL
WBC WHITE BLOOD CELL
PCV PACKED CELL VOLUME
MCV MEAN CORPUSCULAR VOLUME
MCH MEAN CORPUSCULAR HAEMOGLOBIN
MCHC MEAN CORPUSCULAR HAEMOGLOBIN
CONCENTRATION
CHCM CELLULAR HAEMOGLOBIN CONCENTRATION MEAN
CSF CEREBROSPINAL FLUID
CRP C- REACTIVE PROTEIN
SIRS SYSTEMIC INFLAMMATORY RESPONSE SYNDROME
DIC DISSEMINATED INTRAVASCULAR COAGULATION
NF-Kb NUCLEAR FACTOR KAPPA b
SGA SMALL FOR GESTATIONAL AGE
AGA APPROPRIATE FOR GESTATIONAL AGE
VwF VON WILLEBRAND FACTOR
IVH INTRAVASCULAR HAEMORRHAGE
NameAge
(DOL)Sex
Gestational
age
Birth
weightPROM
Maternal
fever
Resuscitation
needMSAF
Prolonged
labour
(>24hrs)
Foul
smelling
liquor
Prematurity Temperature ActivityBlood
Culture
Total
WBC
count
Total
PMN
count
Immature
PMN
count
I T PMN
ratio
I M
PMN
ratio
Degenerative
changes inPMN
Platelet
countScore sepsis CRP
Devi 10days mch term 2.2kg no no yes yes no no no no poor s.aureus 5700 1425 40 0.05 0.19 nil 82000 3 possible positive
Keerthika 10days fch preterm 1.48kg No No No No No No Yes No Normal no growth 12000 2400 61 0.05 0.2 nil 61000 3 possible negative
Leelavathy 10days mch term 2.8kg No No Yes No No No No No Normal nogrowth 9500 5225 274 0.4 0.8 nil 90000 4 possible negative
Poongodi 12days fch preterm 1.4kg no no yes no no no yes no poor E.coli 16100 8694 120 0.17 2.5 nil 43000 4 possible negative
Ramathal 12days fch preterm 1.8kg No No Yes No No No No No Normal cnstaph 23800 16898 145 0.11 0.26 vacuoles 326000 3 possible negative
Sivaranjani 13days mch term 2.8kg no no no no no no no no normal nogrowth 7000 2450 147 0.17 0.5 vacuoles 99000 4 possible positive
Mythili 19days fch preterm 2.3kg No No Yes yes No No No No Poor klebsiella 12800 10624 1792 0.4 1.4 nil 315000 3 possible negative
Anisha 1day fch term 3kg No No No Yes No No No No Normal nogrowth 7900 3397 126 0.18 0.4 nil 211000 3 possible positive
Rishwana 1day mch preterm 1.9kg No No Yes No No No No No Poor nogrowth 9300 5580 450 0.15 0.6 nil 80000 3 possible negative
Sathya 1day mch preterm 1.3kg no no no yes no no yes no normal klebsiella 9700 6111 914 0.16 0.4 nil 230000 4 possible positive
Sudhapriya 1day fch term 2.7kg No No Yes No No No No No poor nogrowth 15000 7050 181 0.15 0.4 nil 190000 4 possible positive
Shanthi
selvaraj1day mch preterm 1.3kg no no yes no no no yes no poor klebsiella 14600 7446 144 0.15 0.3 nil 270000 3 possible positive
Mallika 1day fch term 2.8kg No No Yes No No No No No poor nogrowth 20000 13400 1550 0.2 0.2 nil 126000 3 possible negative
Rajeshwari 1day mch term 2.8kg No No No No No No No No Poor no growth 22400 16800 261 0.13 0.3 nil 135000 4 possible negative
Pavithra 1day fch term 2.7kg No No Yes No No No No No Poor no growth 29000 23200 855 0.14 0.4 nil 170000 4 possible negative
Nandhini 2day mch term 2.3kg No No No No No No Yes No Poor klebsiella 5043 2622 401 0.2 0.2 nil 284000 3 possible negative
Vijaya 2days mch preterm 1.4kg No No No No No No Yes No Poor no growth 3700 1887 874 0.2 0.2 nil 320000 3 possible negative
Anitha 2days mch preterm 1.5kg No No Yes No No No Yes No Poor cnstaph 7100 3976 776 0.09 0.1 vacuoles 188000 4 possible positive
Rubina 2days mch term 2.7kg No No Yes No No No No No poor nogrowth 8800 4488 241 0.11 0.26 nil 101000 3 possible positive
Rajbanisha 3days fch term 3.1kg no no yes no no no no No Normal nogrowth 8000 2400 1315 0.13 0.35 nil 122000 4 possible negative
Malathi 3days mch term 3kg No No No Yes Yes No No No Poor klebsiella 9400 4888 2447 0.2 0.3 nil 350000 3 possible negative
Paronika 3days mch term 3kg no no yes no No No No No poor klebsiella 10700 5885 3420 0.09 0.1 nil 267000 3 possible negative
Malathi 3days mch term 2.8kg No No Yes yes No No No No Poor klebsiella 23000 17250 510 0.14 0.41 nil 267000 4 possible negative
Maheswari 5days mch preterm 1.4kg no no yes no no no yes no poor nogrowth 7700 3850 938 0.64 1.8 nil 74000 4 possible positive
Hemalatha 6days mch term 3kg No No No Yes no No No No Normal no growth 11047 3755 7604 0.15 0.17 nil 349000 3 possible negative
Valarmathi 6days fch term 2.6kg No No Yes No No No No No poor nogrowth 10300 5459 7417 0.03 0.21 nil 165000 3 possible positive
Vennila 8days fch term 2.9kg No No Yes No No No No No poor nogrowth 8600 3698 10982 0.19 0.2 nil 203000 3 possible negative
Lalithadevi 3days mch preterm 1.3kg no no yes yes no no yes no poor klebsiella 22000 21560 6362 0.29 0.4 nil 247000 3 possible negative
uma 10days mch preterm 800g no no yes no no no yes no poor klebsiella 4000 6400 67 0.1 0.16 nil 340000 0 unlikely positive
Sajnaa 11days fch preterm 1.5kg No No No yes No No No No Normal klebsiella 15000 10950 72 0.13 0.16 nil 275000 1 unlikely negative
Bajavathi 1day mch preterm 1.4kg No No Yes No No No Yes No Poor klebsiella 20000 2800 255 0.06 0.2 nil 45000 1 unlikely negative
Pandiyammal 1day fch preterm 2.6kg No No No No No No No No Normal nogrowth 8500 3400 200 0.03 0.11 nil 120000 1 unlikely negative
Radhamani 1day mch term 2.9kg No No Yes No No No No No poor nogrowth 7900 3634 305 0.07 0.26 nil 130000 1 unlikely negative
Megala 1day mch term 2.6kg No No Yes No No No No No poor nogrowth 9700 3686 510 0.12 0.3 nil 251000 0 unlikely positive
Kalaiselvi 1day fch preterm 750g No No Yes No No No No No poor klebsiella 6000 3900 172 0.02 0.06 nil 155000 0 unlikely positive
Kanimozhi 1day fch term 3.3kg No No No No No No No No Normal nogrowth 12000 4560 213 0.08 0.26 nil 185000 0 unlikely negative
Sumayabanu 1day fch term 3kg No No Yes No No No No No Normal nogrowth 15600 5148 109 0.03 0.1 nil 240000 0 unlikely negative
Sudhapriya 1day mch term 1.6kg No No Yes Yes No No Yes no Poor no growth 15200 5168 147 0.08 0.34 nil 243000 1 unlikely negative
MASTER CHART
NameAge
(DOL)Sex
Gestational
age
Birth
weightPROM
Maternal
fever
Resuscitation
needMSAF
Prolonged
labour
(>24hrs)
Foul
smelling
liquor
Prematurity Temperature ActivityBlood
Culture
Total
WBC
count
Total
PMN
count
Immature
PMN
count
I T PMN
ratio
I M
PMN
ratio
Degenerative
changes inPMN
Platelet
countScore sepsis CRP
Lakshmi 1day fch preterm 1.5kg No No Yes No No No Yes No Poor klebsiella 7300 5475 258 0.07 0.08 nil 266000 0 unlikely negative
Sangeetha 1day fch preterm 2.3kg No No Yes No No No No No Normal nogrowth 10300 5974 462 0.05 0.14 nil 70000 1 unlikely negative
Rani 1day fch term 3.1kg No No No No No No No No Normal nogrowth 9600 6048 1170 0.06 0.19 nil 195000 0 unlikely negative
Devanayaki 1day fch preterm 2.05kg Yes No Yes No No No No No Normal no growth 9607 6148 446 0.06 0.15 nil 253000 0 unlikely negative
Nithya 1day fch term 2.5kg No No Yes No No No Yes No poor nogrowth 11700 6201 251 0.05 0.17 nil 250000 0 unlikely negative
Charlin gupta 1day fch preterm 2.4kg No No No No No No No No Normal no growth 10800 6264 314 0.04 0.12 nil 112000 1 unlikely negative
Sumathi 1day mch preterm 2.1kg No No Yes No No No No No Poor acinetobacter 9500 7125 136 0.05 0.15 nil 210000 0 unlikely negative
Selvi 1day fch preterm 2.1kg No No Yes No No No No No Normal no growth 13100 7205 273 0.12 0.22 nil 225000 2 unlikely negative
Shanthi selvaraj 1day mch preterm 4.2kg No No Yes No No No No No Normal no growth 13035 8081 605 0.04 0.09 nil 311000 0 unlikely negative
Annakodi 1day mch preterm 1.8kg No No Yes No No No No No Normal klebsiella 14400 10080 918 0.03 0.06 nil 290000 1 unlikely negative
Radhamani 1day fch preterm 1.7kg No No Yes No No No Yes No Poor klebsiella 18000 10440 411 0.03 0.11 nil 225000 0 unlikely negative
Ramya 1day mch term 3kg No No No No No No No No Normal no growth 5700 18200 327 0.03 0.09 nil 93000 1 unlikely positive
Soni 1day fch term 2.8kg No No No Yes No No No no Normal no growth 24716 19772 2628 0.05 0.12 nil 185000 0 unlikely negative
Lalitha 1day mch term 2.5kg no no yes no no no no no poor klebsiella 22000 21120 892 0.1 0.2 nil 80500 1 unlikely negative
Vijayakumari 2days mch preterm 1.4kg No No Yes No No No No No Poor nogrowth 7500 2250 2177 0.11 0.54 nil 291000 1 unlikely negative
Murshitha 2days mch term 3kg No No Yes No No No No No poor nogrowth 12600 4536 609 0.09 0.2 nil 85000 2 unlikely negative
Chitra 2days fch preterm 1.8kg No No No No No No Yes No Normal no growth 11300 7571 1222 0.07 0.17 nil 130000 1 unlikely negative
Kavitha 3days fch preterm 1.4kg No No Yes No No No Yes no Poor no growth 2700 810 2151 0.05 0.18 nil 180000 0 unlikely negative
Logeswari 3days fch preterm 1.3kg No No Yes No No No Yes No Normal no growth 3185 1019 682 0.05 0.33 nil 333000 0 unlikely negative
Raihana parveen3days fch preterm 1.4kg No No Yes No No No Yes no Poor no growth 5600 1960 496 0.03 0.08 nil 333000 0 unlikely negative
Revathy 3days fch preterm 2.6kg No No No No No No No No Normal nogrowth 8600 3440 1316 0.05 0.42 nil 317000 1 unlikely negative
Aruna 3days fch term 3kg No No Yes No No No No No Normal nogrowth 10300 4532 640 0.06 0.17 nil 160000 0 unlikely negative
Asiya 3days fch term 2.6kg No No No No No No No No Normal no growth 8300 5146 1669 0.02 0.09 nil 126000 1 unlikely negative
Priyanka 3days fch term 2.9kg No No Yes No No No No No poor nogrowth 12200 5734 282 0.05 0.09 nil 69000 2 unlikely negative
Kanaga 3days fch preterm 2.2 kg No No Yes No No No Yes No Normal no growth 11000 6270 2681 0.05 0.08 nil 200000 1 unlikely negative
Manevda 3days fch preterm 2kg No No Yes No No No No No Normal klebsiella 17500 14000 757 0.05 0.14 nil 130000 2 unlikely negative
Bagadeswari 3days fch preterm 1.8kg No No Yes No No No No No Poor s.aureus 25300 17204 782 0.05 0.35 nil 152000 1 unlikely negative
Lalitha 3days mch term 2.5kg no no yes no no no no no poor klebsiella 22000 21120 427 0.04 0.09 nil 190000 0 unlikely negative
Manju 4days mch term 2.7kg No No No Yes No No No No Normal no growth 11700 6201 831 0.03 0.09 nil 165000 0 unlikely negative
Latha 5days mch term 3.1kg No No Yes No No No No No Normal nogrowth 14500 5800 6300 0.07 0.11 nil 168000 2 unlikely negative
Keerthiha 10days fch preterm 1.38kg No No No No No No Yes No Normal no growth 12100 2420 256 0.3 0.61 nil 50000 5 very likely positive
Therasa 10days mch term 2.5kg no no yes no no no no no poor nogrowth 6100 4636 717 0.1 1.6 nil 17000 5 very likely negative
Gunasundari 14days fch preterm 850g no no yes no no no yes no poor klebsiella 12100 4840 1258 0.3 1.2 nil 30000 6 very likely positive
Boomika 1day fch term 2.7kg No No Yes No No No No No poor nogrowth 9000 3150 231 0.2 0.6 vacuoles 115000 5 very likely negative
Sunaiya banu 1day fch term 1.4kg No No No No No No Yes No Normal no growth 14518 3339 510 0.4 1.7 nil 102000 5 very likely negative
Indirani 1day fch preterm 2kg Yes No Yes yes No No No No Poor strepto 10800 7246 2086 0.3 0.6 nil 132000 5 very likely positive
Dhivya 1day mch term 2.6kg No No Yes yes No No No No Poor klebsiella 15000 9000 18572 0.4 1.7 nil 120000 5 very likely negative
Nashrin esath 1day fch preterm 2.15kg No No No No No No Yes No Normal no growth 23100 10395 1020 0.3 0.5 vacuoles 204000 5 very likely negative
Amutha 1day mch preterm 1.4kg No No Yes No No No No No Poor pseud aeur 17000 13260 154 0.19 0.4 granules 289000 5 very likely positive
Badriya 1day mch term 3.6kg no no yes yes no no no no Normal pseud aeur 26600 24472 972 0.3 2 granules 79000 6 very likely negative
NameAge
(DOL)Sex
Gestational
age
Birth
weightPROM
Maternal
fever
Resuscitation
needMSAF
Prolonged
labour
(>24hrs)
Foul
smelling
liquor
Prematurity Temperature ActivityBlood
Culture
Total
WBC
count
Total
PMN
count
Immature
PMN
count
I T PMN
ratio
I M
PMN
ratio
Degenerative
changes inPMN
Platelet
countScore sepsis CRP
Sasikala 2day fch preterm 2.3kg No No Yes No No No No No Normal nogrowth 6000 3000 290 0.3 0.9 vacuoles 203000 5 very likely negative
Geetha 2days mch preterm 2.3kg No No Yes No No No No No Poor nogrowth 9300 4185 725 0.3 5.5 nil 95000 5 very likely negative
Savithri 3days fch preterm 2.2kg No No Yes yes No No No No Poor nogrowth 9500 5700 678 0.5 1.7 nil 112000 5 very likely negative
Anbumala 3days fch term 2.9kg No No Yes No No No No No poor nogrowth 10500 6090 2882 0.4 0.6 nil 140000 5 very likely positive
Damayanthi 3days fch preterm 2.3kg No No Yes No No No No No Poor klebsiella 15000 11250 1116 0.2 0.4 nil 173000 5 very likely negative
Priya 4days mch term 2.8kg No No Yes No No No No No poor nogrowth 12000 4800 1825 0.5 2.6 nil 75000 5 very likely positive
Sharmila 4days mch preterm 1.7kg No No Yes No No No No No Poor nogrowth 7500 5100 3600 0.4 2 granules 83000 6 very likely negative
Gayathri 4days mch term 2.5kg Yes No Yes No No No No No Normal no growth 10200 5100 2016 0.3 0.6 vacuoles 130000 6 very likely positive
Jothi 4days mch preterm 1.5kg No No Yes yes No No No No Poor E.coli 11500 6440 3758 0.2 0.6 nil 118000 5 very likely negative
Bhuvaneswari 4days fch term 2.7kg No No Yes No No No No No poor nogrowth 11700 6786 5630 0.4 1.2 nil 115000 5 very likely negative
Ammu 4days fch preterm 1.2kg no no yes no no no yes no poor s.aureus 22000 14740 5803 0.45 1.2 granules 170000 6 very likely positive
Anandhi 5days mch term 3.3kg No No Yes No No No No No Normal nogrowth 8100 2835 3375 0.3 1.6 nil 123000 5 very likely negative
Nadhiya 5days mch term 2.8kg No No Yes No No No No No poor nogrowth 7600 2888 5701 0.3 0.5 vacuoles 300000 5 very likely positive
Kokila 5days mch term 2.9kg No No No No No No No No Normal nogrowth 9300 6045 4535 0.49 1.18 granules 100000 7 very likely negative
Sumathi 5days mch preterm 1.4kg no no yes no no no yes no poor nogrowth 12900 8514 3390 0.49 1.18 granules 111000 7 very likely positive
Karpagam 5days mch term 3kg no no yes no No No No No poor klebsiella 24000 20400 8395 0.2 0.5 vacuoles 165000 6 very likely negative
Nasreen 6days mch term 2.7kg No No Yes No No No No No poor nogrowth 8900 3560 2520 0.16 0.2 granules 346000 5 very likely negative
Sumathi 6days mch preterm 2.2kg no no yes no no no no no poor no growth 5200 4056 8085 0.42 1.3 vacuoles 160000 6 very likely positive
Thingalmozhi 6days mch preterm 2.3kg No No No No No No No No Normal nogrowth 10600 5830 9464 0.4 1.7 vacuoles 266000 6 very likely positive
Badri 7days mch preterm 1.8kg No No Yes No No No No No Poor nogrowth 8800 5720 3954 0.47 1.29 granules 96000 7 very likely positive
Thenmathy 7days fch preterm 1.5kg No No Yes No No No Yes No Poor no growth 14000 8540 9792 0.5 4 granules 330000 6 very likely negative
Sivakarthika 8days fch term 3.3kg No No No No No No No No Poor no growth 12600 6678 10982 0.4 2.2 vacuoles 175000 6 very likely positive
Saratha 8days mch preterm 2.4kg No No No No No No No No Normal klebsiella 19000 14630 3665 0.25 0.39 granules 191000 6 very likely positive
Nilofar 8days mch term 3.2kg no no yes no no no no no poor cnstaph 26700 23229 8120 0.28 0.5 granules 283000 6 very likely positive
Priya 9days mch preterm 1.3kg No No Yes No No No No No Poor cnstaph 24000 15840 6736 0.35 0.7 vacuoles 245000 6 very likely positive
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