prognostic factors in
TRANSCRIPT
PROGNOSTIC FACTORS IN
MEDICAL COMA
A DISSERTATION SUBMITTED TO THE
NATIONAL POSTGRADUATE MEDICAL
COLLEGE OF NIGERIA IN PART
FULFILLMENT OF THE REQUIREMENT
FOR THE FELLOWSHIP IN PHYSIC.
(FMCP, NEUROLOGY)
CANDIDATE: DR OBIAKO ONYEADUMARAKWE REGINALD
B.Med.Sc, M.B.B.S (UPH, 1987)
AF/009/01/003/437
DEPARTMENT OF MEDICINE
AHMADU BELLO UNIVERSITY TEACHING
HOSPITAL, ZARIA.
NIGERIA.
AUGUST 2005.
ii
DECLARATION
It is hereby declared that this work is original unless otherwise acknowledged.
The work has neither been presented to any other college for fellowship nor submitted
elsewhere for publication.
--------------------------------------------- ------------------------------
Signature of Candidate Date
iii
CERTIFICATION I
The study reported in this dissertation was done by DR OBIAKO,
ONYEADUMARAKWE REGINALD of the Department of Medicine, Ahmadu Bello
University Teaching Hospital, Zaria, Nigeria under my supervision.
I have supervised the writing of the dissertation to my satisfaction.
……………………………………………….. ………..……………………
Professor A. 0. Ogunniyi, Bsc,. FMCP, FWACP. Date
Professor of Medicine and Head, Neurology Unit.
Department of Medicine
University College Hospital, lbadan
Nigeria
iv
CERTIFICATION II
I certify that this study was carried out by DR OBIAKO ONYEADUMARAKWE
REGINALD of the Department of Medicine Ahmadu Bello University Teaching
Hospital, Zaria, Nigeria; under the supervision of Professor A.0. Ogunniyi of the
Department of Medicine, University College Hospital, lbadan.
…………………………………………….. …………………………………..
Head, Department of Medicine Date
Ahmadu Bello University Teaching Hospital
Zaria.
v
DEDICATION
TO
THE ALMIGHTY GOD
For guiding ME to my DESTINY
MY WIFE
For Her Magnificent Devotion and Patience
MY CHILDREN
My daughter, Uchechi and her brothers, Chikwado,
Chiemeka and Chidube, for their endurance at their tender ages.
MY TEACHERS
For seeing through my mindset.
vi
ACKNOWLEDGEMENT
My sincere gratitude goes to Professor Adesola O. Ogunniyi for accepting to
supervise my training in Neurology at Ibadan and showing intense personal interest in my
welfare and intellectual progress.
To Professor Ibrahim Abdu-Aguye, who started the process of intellectual
remodeling in me as my first postgraduate research supervisor. I remain his loyal student.
As a Chief Medical Director, GOD used him as a weapon to approve my training at
Ibadan.
Mama, Dr (Mrs) Juliana Okpapi, my head of dept "chose" this path for me. My
sincere gratitude cannot be adequately expressed in words, but by conduct to meet her
expectations.
Professor Geofrey Onyemelukwe deserves special mention. His overt criticisms
but covert encouragements are powerful tonics for intellectual growth. He is a great
teacher. It will be difficult to forget the contributions of Dr S.S Danbauchi, Dr (Mrs)
Ehusani-Anumah, Dr Alhassan, Dr Keshinro, Dr Bosan, Dr Oyati and others too
numerous to mention., to my postgraduate training.
My colleagues - Dr Mbaave, Dr Kwaifa, Dr Yakasai, Dr Akinyemi, Dr
Owolabi, Dr Fadare, Dr Osalusi, Dr Ajuonumah, Dr Gerald etc. I am grateful for
the information which we shared together. I thank Prof Afolabi Bamgboye and Mr
Nathaniel Afolabi for statistical analysis and Miss Nkechi Onwuka for secretarial work.
Finally, I thank sincerely my wife and children for their patience, endurance and
sacrifice throughout the period of my training. May God continue to guide and protect us
as we contribute our quota to quality health care services. AMEN.
vii
SUMMARY
BACKGROUND
Medical coma in the course of an illness traditionally implies a poor prognosis, but few
data define the factors responsible for this. The identification of these factors will enable
physicians and other health care providers to identify comatose patients most likely to
regain meaningful function with proper therapy, and thus enhance patients' care decisions
and resource allocation, This study was undertaken to determine the factors that affect the
prognosis of medical coma in lbadan, Nigeria.
STUDY DESIGN/METHODS
The level of consciousness and brainstern functions of 200 patients admitted in medical
coma were assessed at admission, 6 hours later, then daily for 7 days, on the 14th day, the
21 day and finally the 28th day, after which the best outcome was recorded. The Glasgow
Coma Scale and brainstern sign score were used to determine the neurologic status while
information from biodata, relevant history of illness, time of presentation to the
University College Hospital, lbadan, time of diagnosis and treatment, results of
investigations and questionnaires were used to identify other prognostic factors.
RESULTS
Medical coma constituted 9.8% of emergency admissions, 3.1% of total admissions and
16.8% of deaths in University College Hospital, lbadan during an 8-month study period.
The common causes were hemorrhagic stroke, diabetic and uremic coma and
meningitides. Hypertension, hyperglycemia, obesity, HIV and hepatitis B viral infections
viii
were the predisposing factors identified. Aspiration pneumonia was the commonest co-
morbid illness.
Multivariate analysis showed that the most significant prognostic factors were
delayed presentation, family knowledge of cause of coma, family support, cause of coma,
Glasgow Coma Scale and ability to do relevant investigations.
ix
TABLE OF CONTENTS
Title Page i
Declaration ii
Dedication iii
Certification I iv
Certification II v
Acknowledgement vi vi
Summary vii
Table of Contents ix
List of Abbreviations xi
List of Tables xiii
List of Figures xv
List of Appendices xvii
CHAPTER ONE: INTRODUCTION
1.1 Introduction 1
1.2 Neurobiology of consciousness and pathophysiology of coma 3
1.3 Diagnostic and therapeutic approach to coma 5
1.4 Outcome of coma 6
CHAPTER TWO: LITERATURE REVIEW
2.1 Epidemiology of medical coma 7
2.2 Causes, Risk Factors and Co-morbid illness associated with coma 8
2.3 Coma as an independent Prognosis factor 9
2.4 Coma scoring system 9
2.5 Justification for study 10
2.6 Aims and objectives 21
x
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Study period 12
3.2 Study site 12
3.3 Study population 13
3.4 Study procedure 14
3.5 Statistical Analysis 19
CHAPTER FOUR : RESULTS
4.1 Incidence of medical coma in UCH Ibadan 20
4.2 Socio-demography of data 21
4.3 Distribution of causes of medical coma 23
4.4 Distribution of predisposing factors 29
4.5 Distribution of co-morbid illness (es) complicating medical coma (multiple
response analysis) 33
4.6 Outcome of medical coma 37
4.7 Prediction of the outcome of medical coma using the Glasgow Coma
Scale (GCS) and Brainstem Signs Score (BSS) 56
CHAPTER FIVE: DISCUSSION, CONCLUSIONS AND LIMITATION OF
THE STUDY
5.1 Discussion 62
5.2 Conclusions 69
5.3 Limitation of the study 70
References 71
Appendices 83
xi
LIST OF ABBREVIATIONS
GCS Glasgow Coma Scale
APACHE Acute physiology, Age, and Chronic Health Evaluation
ARAS Ascending reticular activating system
RF Reticular formation
USA United States of America
SUPPORT The Study to Understand Prognoses and Preferences for
Outcomes and Risk of Treatments
EEG Electroencephalogram
DM Diabetes Mellitus
ICP Intracranial Pressure
HIE Hypoxic-ischemic encephalopathy
NCSE Non-convulsive status epilepticus
CNS Central nervous system
DKA Diabetic Ketoacidosis
HONK Hyperosmolar nonketosis
DIC Disseminated intravascular coagulation
ARF/CRF Acute renal failure/chronic renal failure
Ca2+ Calcium
Na+ Sodium
K+ Potassium
CL- Chloride
HC03- Bicarbonate
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GIT Gastrointestinal tract
CSF Cerebrospinal fluid
TB Tuberculosis
UI/UCH University of Ibadan/ University College Hospital
A&E Accident and Emergency
ICU Intensive Care Unit
HIV Human Immunodeficiency Virus
CT Computerised tomogram
SPSS Statistical Package for Social Sciences
BSS Brainstem Signs Scores
HBSAg Hepatitis B surface antigen
HT Hypertension
xiii
LIST OF TABLES
Tables Titles Page
Table 1: UCH Patient Admissions and Deaths during Period of study 20
Table 2: Age and sex distribution of patients 21
Table 3: Frequency of causes of medical coma 25
Table 4: Distribution of predisposing factors according to sex 30
Table 5: Distribution of predisposing factors according to age group 30
Table6 : Distribution of predisposing factors according to socioeconomic status 31
Table 7: Distribution of associated medical condition in medical coma groups 32
Table 8: Co-morbid illnesses associated with stroke. 33
Table 9: Co-morbid illnesses associated with metabolic coma 34
Table 10: Co-morbid illnesses associated with infectious causes of coma 35
Table 11: Shows co-morbid illnesses associated with hypoxic-ischemic coma 36
Table 12: Co-morbid illnesses associated with “other” causes of coma 36
Table 13: Distribution of outcome of individual causes of medical coma 46
Table 14: Multiple response analysis outcome associated with predisposing factors in
medical coma
47
Table 15: Multiple response analysis outcome associated with co-morbid illness in medical
coma
49
Table 16: Outcome due to delay before clinical diagnosis and onset of resuscitation 52
Table 17 Influence of the family support/ knowledge of cause of coma on outcome 54
Table 18 Influence of UCH social welfare support on outcome of coma 55
xiv
Table 19. The predictive value of the GCS 57
Table 20. The predictive value of the brainstem sign score 59
Table 21: Multiple logistic regression 61
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LIST OF FIGURES
FIGURE TITLE PAGE
1 Diagram of brainstem reticular formation 4
2 Distribution of patients according to time to present after coma 22
3 Distribution of predisposing factors according to age group 23
4 Distribution of grouped causes of coma according to sex 27
5 Distribution of grouped causes of coma according age groups 28
6 Distribution of grouped causes of coma according socioeconomic status 29
7 Outcome of coma according to functional levels 37
8 Outcome according to place of onset of coma 38
9 Outcome according to time to present after coma 39
10 Outcome according to mode of referral 40
11 Outcome according to sex of patients 41
12 Outcome according to age groups 42
13 Outcome according to socioeconomic status 43
14 Outcome according to grouped causes of coma 44
15 Outcome according to presence or absence of predisposing factors 48
16 Outcome according to presence or absence of co-morbidity 50
17 Outcome according to hospital admission 51
18 Outcome according to ability to do relevant investigations 53
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LIST OF APPENDICES
APPENDIX TITLE Page
I The predictive value of GCS and Brainstem signs scores (BSS) in medical coma 83
II Summary of Brainstem signs 84
III UI/UCH Institutional Review Committee Ethical Clearance Certificate 87
IV Proforma A,B,C 88
V Questionnaire to patients’ relations 95
VI Consent form 97
VII Specific treatments given to the patients
98
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CHAPTER ONE
INTRODUCTION
1.1 Coma1-3 is a deep sleep-like state in which a patient is totally unaware of self and surroundings, and cannot be aroused even after vigorous
external stimulation. Such a patient has no sleep-wake cycle and may make inappropriate or no motor response to painful stimuli.
Coma must be distinguished from other altered states of consciousness4-9. Usually these patients can be differentiated from comatose patients
during clinical evaluation.. The conditions are: drowsiness, confusion, encephalopathy, locked-in-state, akinetic mutism, abulia, vegetative state,
minimal conscious state and neuropsychiatric states (catatonia and hysteria).
There are two types of coma2: traumatic (surgical) and nontraumatic (medical) coma. Traumatic coma is mainly due to space occupying
lesions in the brain such as tumors, abscesses, hematomas and hemorrhages. Medical coma arises from various conditions such as drug
intoxications, metabolic disorders, endocrinopathies, severe systemic infections, brain infections, seizures, cardiovascular diseases, stroke and
hematological disorders. It is estimated that about 3 – 15% of admissions to the emergency wards of large municipal hospitals are due to diseases
that cause a disorder of consciousness and coma.
Clinical signs present in comatose patients usually reflect both the cause and different levels of brain damage. The clinical signs of most
localizing value are those affecting forebrain and brainstem functions. These are:
(a) Level of consciousness: Of all the components of the GCS, the motor response to a painful stimulus provides the best indication of the
level of brain damage. A humane form of noxious stimulus (e.g. strong pressure on the supraorbital ridge; sternal angle or big toe nail bed) will
elicit a purposeful movement of the limb towards or away from the painful stimulus in early diencephalic (above thalamus) lesion. If coma is due
to a rapidly enlarging hemispheric mass10,11 brain dysfunction occurs in a progressive rostral to caudal manner; so that motor response in late
diencephalic lesion (below thalamus, but above midbrain) is decorticate posturing. Limb asymmetry may reflect a contralateral hemiparesis.
When brainstem impairment occurs between the levels of rostral poles of red nuclei and vestibular nuclei (subthalamus to midpons), decerebrate
posturing occurs. Further compromise to the level of lower pons and upper medulla elicits no motor responses to pain, although spinal movements
of leg flexion may occur. Metabolic coma does not produce the typical rostral-caudal impairment of brain function, but may produce vigorous
spontaneous extensor rigidity especially after acute hypoxia.
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(b) Brainstem reflexes: As a rule, when brainstem functions particularly pupillary light responses, corneal reflexes and eye movements are
intact, coma must necessarily be ascribed to bilateral hemispheric dysfunction12-16. The converse, however, is not always true as a mass in the
hemispheres may be the proximal cause of coma but nevertheless produces brainstem signs. Brainstem signs can be used to localize lesions as
summarized in appendix I.
1.2 NEUROBIOLOGY OF CONSCIOUSNESS AND PATHPHYSIOLOGY OF COMA
A normal level of consciousness (wakefulness) depends upon activation of the cerebral hemispheres by neurons located in the brainstem
ascending reticular activating system (ARAS)17. The ARAS is a physiologic system contained within the rostral portion of the reticular formation
(RF). The RF is a group of neurons located bilaterally throughout the length of the brainstem up to the caudal diencephalons (intralaminar and
reticular nuclei of the thalamus), with extensive connections to all parts of the nervous system. In the medulla and pons, the RF lies in the dorsal
part while in the midbrain, it lies in the tegmentum.
The ARAS receives constant excitatory influence from environmental stimuli through somaesthetic, auditory and visual sensory systems
and project same rostrally to the cerebral cortex primarily through thalamic relay nuclei, accomplished by cholinergic and aminergic
neurotransmitters (noradrenaline and serotonin) which act by suppressing some inhibitory cortical pathways. A reduction in alertness is related to
the impairment of the ARAS-thalamo-cortical pathways.
Current biological and clinical evidence indicates that coma reflects the failure, loss or disruption of these specific neural activating
pathways18,19 through diffuse insult to both cerebral hemispheres and/ or upper brainstem from endogenous20,21 exogenous22-25 toxins, extensive
trauma, widespread vascular damage,26-29 increased intracranial pressure11,12 and hypoxia30,31. Figure 1 below is a diagram of brainstem reticular
formation showing its input and output.
Figure 1: Brainstem reticular formation
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1.3 DIAGNOSTIC AND THERAPEUTIC APPROACH TO COMA
Coma is a challenging medical emergency with a broad differential diagnosis and complex physical presentation. Evaluation should begin
with a rapid visual assessment for a clear airway, intact respiration, intact pulse, possible shock, hypothermia/hyperthermia, and evidence of acute
xx
life-threatening event32,33. In trauma patients, the neck is immobilized until a cervical spine fracture is excluded by cervical spine x-ray. Oxygen
administration, possible intubation and intravenous fluids are instituted. A nasogastric tube should not be placed in a patient with a possible
anterior basilar skull fracture because the tube might penetrate the brain. Random blood glucose check with a glucometer is mandatory.
After respiratory, circulatory, and metabolic abnormalities are stabilised, a more detailed history is obtained and examination performed.
The history should focus on risks for recent toxic exposure, drug overdose, trauma, seizures, metabolic, endocrine, cerebrovascular disease or
brain infections. A thorough laboratory evaluation should be done including computerized tomography (CT) scan of the head and
electrophysiological studies when indicated. Appropriate antidotes35-37 should be administered.
Once the patient is out of immediate danger with appropriate treatment, although still in coma or vegetative state, the medical team will
concentrate on preventing infections and bedsores, providing balanced nutrition and maintaining the patient’s physical state as much as possible.
Physical therapy must also be used to prevent contractures and orthopaedic deformities.
1.4 OUTCOME OF COMA
Coma rarely lasts more than 2 to 4 weeks38. Some patients may regain a degree of awareness after coma (minimal conscious state)39.
However, five levels of functional outcome have been described40,. These are:
i. Good recovery with no or mild disability in which patients may resume all life activities despite minor neurologic and psychological
deficits.
ii. Recovery with moderate disability in which patients remained disabled but independent of others in so far as daily life activities are
concerned.
iii. Recovery with severe disability in which patient is totally dependent on others for daily support because of mental and/or physical
disability.
iv. Vegetative state in which patients remained unresponsive and speechless for weeks or months after acute brain damage, but later open
xxi
the eyes and have sleep-wake cycles. Patients who remain in a vegetative state after one month have a 3% likelihood of recovery and
survival after 3years.41,42.
v. Death.
CHAPTER TWO
LITERATURE REVIEW
2.1 EPIDEMIOLOGY OF MEDICAL COMA
Admission figures for medical or nontraumatic coma are as disparate as the causes. In Europe and United States of America (USA), Levy
et al40 reported 500 cases in a 4-year period in a multi-centre study. However, workers in Tanzania42 and Zambia43 reported the higher figures of
100 and 170 cases in 7 and 16 months period respectively. This difference may be a reflection of the socioeconomic environment in which these
studies were carried out and the causes of coma in those places. For example, while cerebrovascular and cardiac arrest44 were the main causes of
coma in the European/USA studies, cerebral infections45 and metabolic disorders were most common causes in the Africans,46 although
cerebrovascular disease is now a prominent cause of morbidity and mortality in Africans.29
Medical coma can occur at any age,47 but in studies involving adults, the mean age of occurrence was lower in the Africans (mean age 35
years)48 than in the Caucasians (mean age 60years)49,50, possibly reflecting the causes of coma in these patients. The sex distribution in all the
studies showed a higher male to female ratio at ages below 65years and equal or slight reversal of ratio above the age of 65years.50 This has been
xxii
attributed to the occurrence of more risk fact ors for vascular51,metabolic52 and infectious illness in males or more males coming to hospital53.
Many of the African studies reported a bias toward the lower socioeconomic group in the occurrence of medical coma53. Many studies have
postulated that strong family support was predictive of good outcome in coma and vise-visa54,55.
2.2 CAUSES, RISK FACTORS AND CO-MORBID ILLNESSES ASSOCIATED WITH COMA
The cause of coma, location and extent of neural damage have been found to, individually and collectively, influence the outcome of coma.
Generally diseases causing structural brain injury such as subarachnoid haemorrhage28/ intracerebral haemorrhages29 and the large thrombotic
strokes53 produce the worst prognosis, through rapid haematoma formation, massive brain edema, increased intracranial pressure, brainstem
compression and herniation11,12. Prognosis can be improved by massive intracranial pressure (ICP) reduction with 20% mannitol and a loop
diuretic as well as the control of severe hypertension and other risk factors.
Hypoxic – Ischaemic diseases caused by conditions such as status epilepticus56, cardiac arrest severe tetanus57, carbon monoxide poisoning
and septic shock have guarded prognosis which can be predicted from cortico-somatosensory evoked potentials and EEG features within the first
week of injury58.
Metabolic disorders are varied and when well managed carry a very good prognosis40. They include diabetic coma59-64, hypoglycemia65-71
and uremic72,73 and hepatic coma74.
The common causes of CNS infections are meningitides75-79 and cerebral malaria80-81. These conditions have the best outcome if the
patients present early without much co morbid illnesses
Other conditions such as hypertensive encephalopathy83, drug poisoning and the hematological82 disorders also carried good prognosis40 if
they are well managed.
Other factors known to affect prognosis of coma are high risk life style63-64,83, low socioeconomic status and comorbid illnesses such as
pneumonia, urinary tract infection and pressure ulcers84.
2.3 COMA AS AN INDEFENDENT PROGNOSTIC FACTOR
Coma, irrespective of cause, has an independent poor prognostic value when compared with other causes of death. In general, coma
xxiii
lasting more than 2-4 weeks is associated with many complications, such as pneumonia, decubitus ulcers, malnutrition, deep venous thrombosis
and contractures84. Median prognoses in terms of chance of living for 2 months after diagnosis compiled by the Study to Understand Prognoses
and Preferences for Outcomes and Risks of Treatment (SUPPORT) and the APACHE III were 11% for coma, 17% for lung cancer and 62% for
congestive heart failure85,86.
2.4 COMA SCORING SYSTEMS
Many clinical methods have been developed for the assessment of medical coma55, but reliable criteria for predicting outcome of coma in
these patients in the USA and European studies have been established using the G.C.S 40,87 and brainstem signs88, The G.C.S is simple and
reproducible and can be used by less skilled hospital staff with little inter-observer variability59. Generally, lower G.C.S and abnormal brainstem
responses at admission and/or in the course of coma are established prognostic indices for poor outcome60,89,90. This means that the ability to
accurately predict the outcome of coma using these methods will enable health care providers to reserve the limited and expensive intensive care
facilities for patients with the greatest chance of recovery, especially in developing countries.
Some of the systems which have been developed for the assessment and/or prediction of outcome for both traumatic and non-traumatic coma are:
the Glasgow Coma Scale (GCS),43,44,50,56,58. Glasgow Outcome Scale,40 Innsbruck Coma Scale91, Brainstem reflexes,38,39,41,42,50,84, Clinical
Sickness Score for the critically ill92 and the Acute Physiology, Age and Chronic Health Evaluation (APACHE)55. Among these scoring systems,
the GCS and brainstem functions have been found to be most reliable and have been widely accepted because they are simple, reproducible and of
value in predicting outcome87 in both traumatic and non-traumatic coma. They have also been shown to be of prognostic value in East and Central
Africa in both head injuries and non-traumatic coma43.
2.5 JUSTIFICATION FOR STUDY
The GCS and brainstem functions or any other system for that matter, have their limitations93 and pitfalls88. Therefore, total dependence
on them for predicting coma outcome and determining which patient to initiate or terminate intensive life support may be erroneous94. The
prediction of outcome should be based on a totality of prognostic factors which may be both medical and sociological. This is because the
outcome of a serious illness concerns not only the patient and his family but also the therapeutic teams and the whole community95 - 97.
xxiv
Coma is one of the most common problems in general medicine and certainly the commonest neurological emergency1. On the scale of
intensity of ill health proposed by the New York economists, death occupies the bottom place, with coma just above it39. It is as legendary as
death. For the patient and family members, it may be worse than death; because of the continuing distress this state causes to those who witness it.
In economic terms, it is certainly “more costly than death” because complete dependence can last for many months and sometimes years90.
Although coma, irrespective of cause, has an independent poor prognostic value when compared with other causes of death,85 the outcome has
remained largely uncertain,44. This is because many comatose patients with initial erroneous prediction of poor outcome have recovered with
appropriate treatment. Uncertainty about the outcome of coma and implicit estimates of prognosis in the absence of well established facts have
hampered approach to patient management and added to the difficulty which doctors’ experience in making decisions about coma patients94-96.
Therefore the identification and possible stratification of prognostic factors in medical coma will facilitate the ability to predict its final outcome.
This may offer physicians, patient’s families and health planners information that may prove useful in patient care decisions55 and resource
allocation96.
2.6 AIMS AND OBJECTIVES
A. General: To determine the factors that affects the prognosis of medical coma in the University College Hospital, Ibadan
B. Specific
i. To determine the influence of socio-demographic factors on outcome of coma
ii. To determine the etiological factors associated with coma in UCH Ibadan
iii. To determine the outcome of coma using the Glasgow Coma Scale and brainstem functions.
xxv
CHAPTER THREE
METHODOLOGY
3.1 STUDY PERIOD: This research was a prospective study of patients who presented to the University College Hospital (UCH) Ibadan in
medical coma from August 2004 to March 2005. It was done with the permission of the UI/UCH Institutional Review Committee. (Appendix II)
3.2 STUDY SITE : UCH Ibadan is the premier teaching hospital in Nigeria which was founded in 1948. Ibadan is said to be the largest town
in West Africa with a population of more than one million people. Most of the patients seen in the hospital were mainly from Ibadan township and
neighbouring towns and villages in the Western part of Nigeria.
The hospital has a well-organised Accident and Emergency (A&E) unit under the supervision of a Consultant General Surgeon, but all the clinical
subspecialties are well represented. Patients admitted there are usually transferred to the wards or intensive care unit (ICU), as the case may be,
within 24 hours.
The ICU has 4-beds, cardiac monitors, mechanical ventilators etc. It is under the supervision of a Consultant Anesthetist. Patients admitted into
the ICU are jointly managed by the primary physicians and the anesthetists.
There are 5 medical wards shared by the seven units of neurology, dermatology gastroenterology nephrology, cardiology, endocrinology and
respiratory medicine. Patients recruited for this study were admitted and managed under the consultants in each of these units, but the author
participated actively in the management of the patients with the consent of the primary physician.
3.3 STUDY POPULATION
3.3.1 Sample size: The sample size of 200 used for the study was determined using the
formula,101 N = z2 Pq where
d2
N = the desired sample size (when population is greater than 10,000)
Z = the standard normal deviate at 95% confidence level (1.96)
P = admission rate of coma in literature1,3
xxvi
d2 = degree of accuracy at 0.05
q = 1.0 – p = (1.0 - 0.15) 0.85
N = 1.96 x 1.96 x 0.15 x 0.85 = 0.489804 = 195.92 approximated to 200.0
0.05 x 0.05 0.0025
to take care of losses or referrals
3.3.2 INCLUSION CRITERIA
i. Consecutive patients, 16 years and above, admitted in medical coma to either the A and E unit, the medical wards or the ICU
ii. The patient’s level of consciousness as determined by the author at initial assessment must be G.C.S score of 8 or below i.e. eye
opening of 2 or less, verbal response of 2 or less and best motor response of 4 or less (see appendix III, proforma C).
3.3.3. EXCLUSION CRITERIA
i. Patients with traumatic coma
ii. Patients with altered states of consciousness with GCS score above 8
iii. Delayed recovery from anesthesia
3.4 STUDY PROCEDURE
3.4.1 Clinical assessment: All the patients who met the inclusion criteria had detailed clinical evaluation (i.e. history, physical and neurological
examinations) on initial presentation, 6 hours later, then daily for 7 days, on the 14th, 21st and 28 days respectively, using the format in appendix
III, proforma A,B,C. The outcome at the end of the 28th day was recorded4,38 as good recovery with no or mild deficit, moderate or severe
deficit, vegetative or death.
The results of laboratory, radiological and electrophysiological investigations were also noted and recorded in proforma D.
3.4.2 Questionnaires to evaluate reasons for outcome
On the 28th, day a questionnaire was administered on one of the patient’s guardian (Appendix IV) for an independent assessment of factors
likely to have affected the outcome of coma. This was done after informed consent was obtained from the respondents (appendix V). The
xxvii
information derived from the questionnaires was corroborated with the observations and records made by the author on the patient.
3.4.3 Summary of clinical information
All the information and observations made on the patient were used to confirm the date of definitive diagnosis, cause of coma, type of
outcome and date of outcome. (Appendix III, proforma E).
3.4.4 Diagnostic criteria The diagnoses were generally based on standard criteria with appropriate modifications where necessary, thus,.
A. Cerebral Infections:
i. Meningitidis: 23,24,
Trial of fever, headache and maningeal irritations.
CSF abnormalities (pleocytosis, high protein level, low glucose level)
Isolation of microorganism from CSF.
ii. Cerebral malaria78
High grade fever and anemia
Positive asexual forms of plasmodium falciparum on blood smear.
B Metabolic disorders:
i. Diabetic coma:
Hyperglycemia, dehydration.
± serum hyperosmolatity and ketonuria
ii. Hypoglycemic coma65-67
History of oral hypoglycemic agents ingestion or insulin injection without eating or alcohol abuse.
Sweating, tachycardia + seizures and
Blood sugar of < 4.0mg/dL (2.2mmol/L)
xxviii
iii. Hepatic coma (grade IV encephalopathy)98:
Jaundice, hepatic fetor.
Deranged prothrombin time and abnormal liver enzyme levels and
Ultrasound proven liver diseases.
iv. Uremic coma72,73.
Facial swelling, oliguria + and hypertension
Pallor, brown nails, bruising, excoriations, retinopathy, pericarditis, pulmonary or peripheral odema etc.
Anemia (normocytic, normochromic); serum urea of 35mmo/L, creatinine of >900umol/L and bicarbonate of < 15mmol/L respectively,
normal, creatinine clearance of <15ml/min/1.73m2
C. Cerebrovascular disease
i. Intracerebral hemorrhage and large infarctive stroke (middle cerebral artery stroke)
Severe headache, vomiting, rapid loss of consciousness, + seizures.
Severe hypertension, focal neurological deficits
CT brain evidence.
ii. Hypertensive encephalopathy83
Fluctuating levels of consciousness, ± convulsion
Severe hypertension, grade IV retinopathy
CT brain evidence of diffuse edema of cerebral hemispheres.
D. Cardiac arrest:
Sudden onset of loss of consciousness; apnoea and cardiogenic shock
ECG evidence
E. Status epilepticus
xxix
Known epileptics.
Prolonged convulsions with non-recovery of consciousness for more than 30 minutes.
EEG showed evidence of epileptic-form activities.
Blood glucose and electrolytes were normal.
F. Sepsis syndrome (sepsis, septic shock, multiple organ failure and severe anemia). The clinical presentations were variable but diagnoses
were based on the presence of temperature > 380C or < 360C, heart rate > 100 beats per minute, respiratory rate > 20 breaths per minutes,
leucocytosis, anaemia, hypotension, oliguria and evidence of multiple organ dysfunction
G. Other causes
i. Primary CNS lymphoma:
HIV seropositive CD4+ count <100 cells/µl.
CT scan showed high density enhancing mass(es) in the cerebral parenchyma.
ii. Gamalline poisoning: This was a 25 year old male who attempted committing suicide by drinking gamaline. This was confirmed
by the relations and identified by the pharmacy department.
iii. Osmotic demyelination syndrome was diagnosed in a 36 year old taxi driver who was a known alcoholic and who fell into coma
after a drinking bout. He had clinical features of bilateral ventral pontine hypodense lesion on CT Scan. He was referred from a
private hospital where he had some intravenous fluids for more than 24 hours before referral. His serum Na+ was at lower limit of
normal. There was no magnetic resonance imaging (MRI) confirmation of diagnosis.
3.4.5 Management
A. Resuscitation: After an initial quick assessment of the patient’s level of consciousness and vital signs, clear airway was ensured by proper
positioning and suction of secretions. Oropharyngeal tube was put in place for patients with spontaneous regular breathing to prevent aspiration
and endotracheal intubation for patients with cardiopulmonary arrest.
Oxygen was administered through tubes connected to the nostrils or to the endotracheal tubes. Blood was taken for blood sugar and other
investigations and intravenous fluid (normal saline or dextrose infusion) given to support the circulation. 50ml of 50% dextrose in double dilutions
xxx
was given in hypoglycemic coma. Appropriate emergency drug treatment was also administered to the patients. Nasogastric tube was passed for
aspiration of gastric contents and left in-situ for feeding and oral drug administration. Urethral catheter was passed for proper monitoring of urine
output.
B. Specific treatment All the patients' were admitted and managed under the admitting unit consultants under a treatment protocol for the
unit. The patients’ laboratory investigations, treatments and nursing care were monitored by the author to decipher whether or not patients had
standard medical and nursing care. The specific treatments given to the patients are explained in appendix VII.
3.5 STATISTICAL ANALYSIS
Data obtained was analysed electronically using the Statistical Package for Social Sciences (SPSS). The double entry method was used to
ensure accuracy. Subsequently, a frequency distribution of all variables was carried out as part of data exploration and clearing efforts. Relevant
tables to the study objectives were constructed and appropriate statistical tests were used to investigate the significance of any relationship
between variables. Means and standard deviation were used to describe continuous variables and proportions were used for discontinuous or
categorised data.
The Student ‘t’ test was used to compare means of two continuous variables while the Pearson Chi-Square test was used to determine
significance of association between proportions or groups. Fisher’s exact test was used in place of Chi-Square test where the number in cells was
less than 5. A p-value of <0.05 was considered significant.
The predictive value of both GCS and brainstem signs score (BSS) was calculated using the 2 by 2 contigency table (see Appendix VI).
The critical BSS below which death can be predicted with some certainty and above which survival can also be well predicted was determined by
using the nonparametric Wilcoxon Rank Sum/Mann – Whitney-U test. All significant variables were subjected to multiple logistic regression
analysis to determine the most significant ones.
xxxi
CHAPTER FOUR
RESULTS
4.1 Incidence of medical coma in UCH Ibadan
Medical coma accounted for 9.8% of emergency admissions, 3.1% of total hospital admissions and 16.8% of total hospital deaths during
the study period. The details of emergency admissions, total hospital admissions and deaths during the study period are shown in Table 1 below.
Table1: UCH Patient Admissions and Deaths during Period of study
Source: Statistics Unit, Medical Records Department, UCH, Ibadan
Month Year Emergency
admissions
Total hospital
admissions
Total hospital
deaths
August
September
October
November
December
January
February
March
2004
2004
2004
2004
2004
2005
2005
2005
359
321
330
250
68
48
325
332
1092
1062
1031
927
217
145
989
1079
177
133
141
123
52
17
119
144
Total 2033 6548 906
% Medical Coma
xxxii
admissions and
deaths to
9.8% 3.1% 16.8%
4.2 SOCIO DEMOGRAPHY OF DATA
4.2.1 Sex and age distribution
Two hundred (200) comatose patients of medical aetiology were consecutively studied. There were 132 males and 64 females, giving a
male: female ratio of 2:1. The mean age of all the patients was 50+18years, the males being slightly but insignificantly younger (49.5+16.1 years)
than the females (50.9+20.9 years). (t=-0.514, P>0.05). The age group 40-59 years formed the largest population of 38.5% closely followed by
those above 60 years old (34%). The <39 years age group were the least affected with 27.5%. This distribution is shown in table 2 below.
Table 2: Age and sex distribution
Age (years) Male(%) Female(%) Total(%) t-test P-value
<20
20-39
1(0.5)
30(15.0)
-
24(12)
1(0.5)
55(27.5)
40 – 59 62(31) 15(7.5) 77(38.5) -0.514 0.608
>60 39(19.5) 29(14.5) 68(34)
Total 132(66) 68(34) 200(100)
Mean 49.5±16.1 50.9±20.9 50±17.8
xxxiii
4.2.2 Time to present to UCH after coma
Of the one hundred and twenty eight (64%) who were brought to UCH in coma, only thirty eight (19%) were brought within 6 hours while
ninety (45%) were brought in after 6 hours (p=0.000). 14.5% of those who presented less than 6 hours were brought in by their relatives, while the
remaining (4.5%) were refrred from private hospitals. On the other hand, of the 45% who were brought in after 6 hours sixty five (32.5%) were
referred from private hospitals, while 12.5% were brought in by relatives (p= 0.000). Thus showing a significant difference in the mode of referral
and time of presentation to UCH (p <0.05). This is shown in figure 2.
4.3 DISTRIBUTION OF CAUSES OF MEDICAL COMA
4.3.1 Distribution of medical coma groups
Fig 2: Distribution of patients according to mode and time of presentation after coma
14.5
4.5
12.5
32.5
0
5
10
15
20
25
30
35
Relatives Private hospital Time to present P<0.05
Percentage Before 6hrs After 6hrs
xxxiv
The various grouped causes of medical coma and their distribution are shown in figure 3. The commonest cause was metabolic (35.5%),
followed by cerebrovascular or stroke (33%), infections (22%), hypoxic-ischemic (5%) and others (4.5%).
4.3.2 Frequency of causes of medical coma
Hemorrhagic stroke was the cause in 26% of the patients, followed by diabetic (DM) coma (12.5%), uremic coma and meningitides with 12%
each, infarctive stroke (7%), sepsis syndrome and hepatic coma (6% each) and hypoglycemia (5%).
Fig 3: Distribution of causes of coma in groups
35%
33%
22%
5% 5%
Metabolic Cerebrovascular Infection Hypoxic Others
xxxv
Table 3 below shows the details of causes including others less than 4%.
Table 3: Frequency of causes of medical coma
CAUSES TOTAL PERCENTAGE
1. bHemorrhagic stroke 52 26
2. a1DM coma 25 12.5
3. aUremic coma 24 12
xxxvi
4. cMeningitides 24 12
5. bInfarctive stroke 14 7
6. cSepsis syndrome 12 6
7. aHepatic coma 12 6
8. aHypoglycemia 10 5
9. cPara meningitides 6 3
10. dCardiac arrest 5 2.5
11. eCNS lymphoma 5 2.5
12 dHypovolemic shock 3 1.5
13. cCerebral malaria 2 1
14. dStatus epilepticus 2 1
15. eHypertensive encephalopathy 1 0.5
16. eGamalline poisoning 1 0.5
17. eOsmotic demyelination syndrome 1 0.5
18. eUnknown 1 0.5
a = metabolic a1 = DKA = 4
b = stroke HONK = 21
c = infections
d = hypoxic-ischemic
e = others
4.3.3 Distribution of causes of coma according to sex (See fig 4)
(i) Metabolic Coma: The male: female ratio in this group in descending order were diabetic (5.5%:70%), uremic (7.5%:4.5%), hepatic
(4.5%:1.5%) and hypoglycemic (3.5%:1.5%) coma, showing an overall male: female ratio of 21%:14.5%
(ii) Cerebrovascular: The male: female ratio of causes of coma in this group were hemorrhagic (21.5%:4.5%) and large infarctive (3.5%:3.5%)
xxxvii
strokes, showing an overall male: female ratio of 25%:8%
(iii)Infections showed an overall male predominance with a male to female ratio of 13%:9%, made up of meningitides (8%:4%), sepsis syndrome
(3%:3%), parameningitides/ brain abscess (1.5%:1.5%) and cerebral malaria (0.5%:0.5%).
(iv) Hypoxic-ischemic coma: The overall male to female ratio in this group was (2.5%:2.5%). Cardiac arrest (1.5%:1.0%) was the highest cause,
followed by hypovolemic shock (0.5%:1.0%) and lastly status epilepticus (0.5%:0.5%)
(v) Unknown cause: Was 0.5% (male)
(vi) Others: This group was made up of CNS lymphoma (2.5%), hypertensive encephalopathy (0.5%), osmotic demyelination syndrome (0.5%),
gamalline poisoning (0.5%). There was no female in this group.
4.3.4 Distribution of causes of coma according to age groups (see fig. 5).
Fig 4:Distribution of grouped causes according to sex
21
25
13
2.5
4.5
19.5
8 9
2.5
0 0
5
10
15
20
25
30
Metabolic Cerebrovascular Infection Hypoxic Others Causes P>0.005
Percentage
male female
xxxviii
In metabolic coma, the ≥60yrs (elderly) had a slight dominance of 12.5% over the middle aged(40-49yrs) and the youth (<39yrs) with
11.5% each respectively. In coma due to strokes, the % distribution for the age groups (arranged in descending order of ≥60yrs, 40-59yrs, <39yrs)
were 17.0, 12.5 and 3.5 respectively. Individual causes were distributed as follows: hemorrhagic stroke(11.5, 11 and 3.5); infarctive stroke (5.5,
1.5 and 0).
In coma due to infections, the % distribution is descending order of age groups (as above) were 3, 10.5 and 8.5 respectively with the
middle age group forming the majority. The infections were distributed as follows: meningitides (0,5.5,6.5), sepsis syndrome (3.0, 2.5,0.5); para-
meningitides (0, 0,1) and cerebral malaria(0,0,1)
In hypoxic-ischemic coma, the % distribution in the age groups (in descending order as above) were 1,1.5 and 2.5 respectively with the youth
forming the majority.
These were due to cardiac arrest (0,0.5,2); hypovolemic shock (1,0,0.5) and status epilepticus (0,1,0)
Unknown cause: (0.5%) in a middle age man only.
In the miscellaneous group, majority of the cases occurred in the middle aged as shown by the % distribution of 0.5, 2.5 and 1.5 in the descending
order of age groups (as above). These were due to CNS lymphoma (0,1.5,1.0), hypertensive encephalopathy (0.5,0,0); osmotic demyelination
syndrome (0,0.5,0); and gamalline poisoning(0,0,0.5) respectively
xxxix
4.3.5 Distribution of causes of coma according to socioeconomic status (see figure 6)
The dominance of the self employed group mostly artisans, taxi drivers and the petty traders over the others was seen in all the coma groups
except the hypoxic-ischemic coma, where the none gainfully employed was in majority with 3%, to the 1.5% and 0.5% for self employed and
government employed groups respectively. Put together the self employed and unemployed constituted 90% of the study population thereby
giving a statistically significant result. This is illustrated in figure 6 below.
Fig 5:Distribution of grouped causes of coma according to age groups
11.5
3.5
8.5
2.5 1.5
11.5 12.5
10.5
1.5 2.5
12.5
17
3
1 1
0
2
4
6
8
10
12
14
16
18
Metabolic Cerebrovascular Infection Hypoxic Others Causes
Percentage <=39 40-59 >=60
xl
4.4 DISTRIBUTION OF PREDISPOSING FACTORS
Multiple responses analysis of predisposing factors in table 4 revealed the presence of hypertension (38.5%), diabetes mellitus (14%),
HIV(11.5%), alcohol abuse (8.5%), old age (7%), obesity (7%), hepatitis B surface antigen (6%) and substances abuse (tobacco, marijuana, herbal
remedies) (4%) as the significant factors.
4.4.1 Sex: There was an overall predominance of these factors in males with the exception of old age. Alcohol and substance abuse were absent
in females. This is shown in table 4.
Table 4: Distribution of predisposing factors according to sex
Characteristics HT (%) DM
(%)
HIV
(%)
Alcohol
Abuse
(%)
Old
Age
(%)
Obesity
(%)
HbsAg
(%)
Subst
Abuse
(%)
Sex
Male
55(27.5)
19(9.5)
16(8)
17(8.5)
6(3)
9(4.5)
8(4)
8(4)
Fig 6:Distribution of grouped causes of coma according to socioeconomic status
18.5
17
12
1.5
3.5
7.5
6
4.5
0.5 0.5
9.5 10
5.5
3
0.5 0
2
4
6
8
10
12
14
16
18
20
Metabolic Cerebrovascular Infection Hypoxic Others Causes
Percentage Self employed Govt employed None
xli
Female
Total
22(11)
77(38.5)
9(4.5)
28(14)
7(3.5)
23(11.5)
-
17(8.5)
8(4)
14(7)
7(3.5)
14(7)
4(2)
12(6)
-
8(4)
4.4.2 Age group: hypertension, substance abuse, alcohol abuse and hepatitis B surface antigen were seen in all age groups except the <20yrs.
This is shown in table 5 below.
Table 5 : Distribution of predisposing factors according to age group
Characteristics HT (%) DM
(%)
HIV
(%)
Alcohol
Abuse
(%)
Old
Age
(%)
Obesity
(%)
HbsAg
(%)
Subst
Abuse
(%)
Age
<20
20 -39
40-59
>60
Total
-
9(4.5)
31(15.5)
37(18.5)
77(38.5)
-
3(1.5)
9(4.5)
16(8)
28(14)
-
12(6)
11(5.5)
-
23(11.5)
-
3(1.5)
12(6)
2(1)
17(8.5)
-
-
-
14(7)
14(7)
-
-
6(3)
8(4)
14(7)
-
3(1.5)
6(3)
3(1.5)
12(6)
-
2(1)
3(1.5)
3(1.5)
8(4)
4.4.3 Socioeconomic status: All the factors were seen in the 3 groups of self-employed, government employed and none employed. Old age was
absent in the government employed. The self-employed had an overall higher risk for all the factors followed by the none employed. This is shown
in table 6 below.
Table 6: Distribution of predisposing factors according to socioeconomic status
Characteristics HT (%) DM
(%)
HIV
(%)
Alcohol
Abuse
(%)
Old
Age
(%)
Obesity
(%)
HbsAg
(%)
Subst
Abuse
(%)
xlii
Socioeconomic
status
Self employed
Govt.employed
None
Total
40(20)
11(5.5)
26(13)
77(38.5)
14(7)
7(3.5)
7(3.5)
28(14)
11(5.5)
9(4.5)
3(1.5)
23(11.50
11(5.5)
4(2)
2(1)
17(8.5)
10(5)
-
4(2)
14(7)
8(4)
2(1)
4(2)
14(7)
7(3.5)
4(2)
1(0.5)
12(6)
3(1.5)
3(1.5)
2(1)
8(4)
4.4.3 Predisposing/Associated Diseases (see table 7 below)
Hypertension and diabetes mellitus were strongly associated with metabolic coma and stroke. Other conditions were hepatitis B surface
antigens, substance abuse including alcohol , obesity and old age.
HIV was strongly associated with mening-encephalitidis and CNS lymphoma. This is shown in detail in table 7 below.
Table 7: Distribution of associated medical condition in medical coma groups
Characteristics HT (%) DM
(%)
HIV
(%)
Alcohol
Abuse
(%)
Old
age
(%)
Obesity
(%)
HbsAg
(%)
Subst
abuse
(%)
Cause of Coma
Metabolic
CVD
Infection
Hypoxic-
ischemic
Others
11(5.5)
66(33)
-
-
-
16(8)
9(4.5)
2(1)
1(0.5)
-
3(1.5)
-
15(7.5)
-
5(2.5)
3(1.5)
9(4.5)
3(1.5)
-
2(1)
2(1)
8(4)
4(2)
-
-
2(1)
12(6)
-
-
-
13(6.5)
-
-
-
-
3(1.5)
2(1)
3(1.5)
-
-
xliii
4.5 DISTRIBUTION OF CO-MORBID ILLNESS(ES) COMPLICATING MEDICAL COMA(MULTIPLE RESPONSES
ANALYSIS)
4.5.1 Stroke: Aspiration pneumonia was the commonest co-morbid illness (18%), followed by recurrent seizures (5.5%), hyperglycemia (5%),
sepsis(4%). Other co-morbid illness were <4%. This is shown in table 8 below.
Table 8: Co-morbid illnesses associated with stroke.
Co-morbidity Stroke
Aspiration pneumonia 36(18)
Recurrent seizures 11(5.5)
Hyperglycemia 10(5)
Sepsis 8(4)
Chest urinary tract infection 6(3)
Acute pulmonary edema 5(2.5)
Acute renal failure 4(2)
Recurrent stroke 3(1.5)
Anaemia 2 (1)
Liver cirrhosis 2(1)
4.5.2 Metabolic Coma: Hypertension was the commonest co-morbidity (11%) followed by sepsis (6.5%), liver cirrhosis (6%), acute pulmonary
oedema and anemia (4.5% each). The other illnesses occurred in frequencies <4%. This is shown in table 9 below.
Table 9: Co-morbid illnesses associated with metabolic coma
Co-morbidity Metabolic
Hypertension 22 (11)
Sepsis 13 (6.5)
Liver cirrhosis 12 (6)
Recurrent seizures 9 (4.5)
xliv
Anaemia 9 (4.5)
Acute pulmonary edema 9 (4.5)
Acute renal failure 6 (3)
Aspiration pneumonia 6(3)
Chest urinary tract infection 5 (2.5)
Hyperglycemia 2 (1)
Recurrent stroke 1 (0.5)
4.5.3. Coma due to infectious cases: Hyperglycemia was the commonest co-morbid illness (4%), followed closely by acute renal failure and
anemia with 3.5% each, aspiration pneumonia and recurrent seizures with 3% each. Liver cirrhosis, acute pulmonary edema and chest/urinary tract
infections occurred in 2%, 1% and 0.5% respectively.
Table 10: Co-morbid illness associated with infectious causes of coma
Co-morbidity Infection
Hyperglycemia 8 (4)
Anaemia 7 (3.5)
Acute renal failure 7 (3.5)
Aspiration pneumonia 6(3)
Recurrent seizures 6 (3)
Hypertension 5 (2.5)
Liver cirrhosis 4 (2)
Acute pulmonary edema 2 (1)
Chest urinary tract infection 1 (0.5)
4.5.4. Hypoxic-ischemic coma: Aspiration pneumonia, hypertension and sepsis were found in each of 1.5% of patients while hyperglycemia,
anaemia and liver cirrhosis occurred in 1%, 0.5% and 0.5% of the patients respectively as shown below.
Table 11: Co-morbid illnesses associated with hypoxic-ischemic coma
Co-morbidity Hypoxic-ischemic coma
Aspiration pneumonia 3 (1.5)
xlv
Hypertension 3 (1.5)
Sepsis 3 (1.5)
Hyperglycemia 2 (1)
Anaemia 1 (0.5)
Liver cirrhosis 1 (0.5)
4.5.5 Others: Recurrent seizures was the commonest co-morbid illness, (2%) followed by sepsis (1.5%), aspiration pneumonia (1%),
hypertension (0.5%), anemia (0.5%) and liver cirrhosis (0.5%).
Table 12: Co-morbid illnesses associated with “other” causes of coma
Co-morbidity Others
Recurrent seizures 4 (2)
Sepsis 3 (1.5)
Aspiration pneumonia 2 (1)
Hypertension 1 (0.5)
Anaemia 1 (0.5)
Liver cirrhosis 1 (0.5)
4.6 OUTCOME OF MEDICAL COMA
4.6.1 General outcome (according to functional levels) see fig 7
152 of the 200 patients studied died giving an overall mortality rate of 76%. Among the forty eight (24%) patients that survived, twenty
two (11%) had good recovery with no functional deficit, ten (5%) had moderate disability, twelve (6%) had severe disability and four (2%) went
into vegetable state.
xlvi
4.6.2 Sociodemographic characteristics
i. Outcome of coma based on place of onset. Mortality was higher in the patients who became unconscious in the hospital at the rate
of 80.6% compared to 73.4% recorded for those who were brought unconscious from outside the hospital. Figure 8 below illustrates this
difference which was not statistically significant. X2 = 1.28, P = 0.258.
Fig 7:Outcome according to functional levels
11
5 6 2
76
0
10
20
30
40
50
60
70
80
Good recovery Recovery+mod. disability Recovery+severe disability Vegetative Death Outcome
Percentage
xlvii
ii. Outcome of coma according time to present to UCH Mortality was higher at 76.7% for the patients who were brought after 6hours in
contrast to 63.2% mortality rate in those who were brought in within 6hours. However, this difference was not statistically significant.
X2 2.45, P = 0.117. Figure 9 below illustrates this distribution.
Fig 8:Distribution according to place of onset of coma
26.6
19.4
73.4
80.6
0
10
20
30
40
50
60
70
80
90
Out of hospital Inside hospital Place of onset P>0.05
Percentage
Alive Dead
xlviii
iii. Outcome of coma according to mode of referral to UCH (see figure 10 below)
The mortality rate of 75.7% recorded in patients who were referred from private hospitals was higher than 68.5% recorded in those who were
brought in by their relatives, although the difference was not significant. (X2 = 0.8, P = 0.37)
Fig 9: Distribution of outcome according to time of presentation
36.8
23.3
63.2
76.7
0
10
20
30
40
50
60
70
80
90
<6hrs >6hrs Presentation time P>0.05
Percentage
Alive Dead
xlix
4.6.3 Distribution of outcome based on patients characteristics
i. Sex: Of the one hundred and fifty two (76%) deaths recorded, one hundred and four (52%) were males while forty eight (24%)
were females giving a mortality rate of 78.8% and 70.6% respectively. However, the difference was not statistically significant, (X2 =1.65,
P = 0.198) as shown in figure 11 below.
Fig10:Distrbution of outcome according to mode of referral
31.5
24.3
68.5
75.7
0
10
20
30
40
50
60
70
80
Relatives Private hospitals Mode of referral P>0.05
Percentage
Alive Dead
l
ii. Age group Mortality was highest in the 40-59 age group with 80.5% followed closely by the > 60 years old with 76.5% and those <39
years with 69.1%. However there was no significant difference in the mortality rate, as they were a reflection of the population of the age groups
in the study. Figure 12 below illustrates the outcome according to age group.
Fig 11:Distribution of outcome according to sex
21.2
29.4
78.8
70.6
0
10
20
30
40
50
60
70
80
90
male female Sex P>0.05
Percentage
Alive Dead
li
iii. Socioeconomic status: The mortality rates also reflected the proportional representation of the different groups. The self-employed had the
highest rate of 81% followed by the civil servants with 79% and the none employed with the lowest rate of 65%. (X2 = 5.45, P = 0.66) as shown in
figure 13 below.
Fig 12: Distribution of outcome according to age group
30.9
19.5 23.5
69.1
80.5 76.5
0
10
20
30
40
50
60
70
80
90
<=39 40-59 >=60 Age group P>0.05
Percentage
Alive Dead
lii
4.6.4 Distribution of outcome according to grouped causes
Infections had the highest mortality rate of 86.6%, followed closely by stroke (83.3%), metabolic coma (67.6%), hypoxic ischaemic coma
(60%) and lastly the miscellaneous group (44.4%) as shown in figure 14.
Fig 13:Distribution of socioeconomic status according to outcome
19 21
35
81 79
65
0
10
20
30
40
50
60
70
80
90
Self employed Govt employed None Socioeconomic status P>0.005
Percentage
Alive Dead
liii
4.6.5 Distribution of outcome of individual causes of medical coma
Hepatic coma, para-meningitides, hypovolemic shock and unknown cause had mortality of 100% while meningitides had mortality of
91.7%, followed by hemorrhagic stroke (88.5%), uremic coma and sepsis syndrome with 83.3% each. Infarctive stroke, diabetic coma and cardiac
arrest had 60% each. Others had less than 50% mortality as shown in table 13.
Table 13: Distribution of outcome of individual causes of medical coma
CAUSES Alive Dead Total % Mortality %
1. aHepatic coma - 12 12 6 100
2. cPara meningitides - 6 6 3 100
3. dHypovolemic shock - 3 3 1.5 100
4. eUnknown - 1 1 0.5 100
5. cMeningitides 2 22 24 12 91.7
6. B Hemorrhagic stroke 6 46 52 26 88.5
7. aUremic coma 4 20 24 12 83.3
Fig 14:Distribution of outcome according to grouped causes
32.4
16.7 13.4
40
55.6
67.6
83.3 86.6
60
44.4
0
10
20
30
40
50
60
70
80
90
100
Metabolic Cerebrovascular Infection Hypoxic Others Causes
Percentage
Alive Dead
liv
8. cSepsis syndrome 2 10 12 6 83.3
9. bInfarctive stroke 5 9 14 7 64.3
10. a1DM coma 10 15 25 12.5 60
11. dCardiac arrest 2 3 5 2.5 60
12 eCNS lymphoma 2 3 5 2.5 60
13. cCerebral malaria 1 1 2 1 50
14. aHypoglycemia 9 1 10 5 10
15. eHypertensive
encephalopathy
1 1 0.5
16. eGamalline poisoning 1 1 0.5
17. dStatus epilepticus 2 2 1
18. eOsmotic demyelination
syndrome
1 1 0.5
Alive Dead
a = metabolic a1 = DKA = 4: 0
b = stroke HONK = 6: 15
c = infections
d = hypoxic-ischemic. e = others
4.6.6 Multiple response analysis of outcome associated with presence of predisposing factors
i. Substance abuse was associated with a worst outcome of 100% followed by HIV with 95.2%, hepatitis B surface antigen, (92.3%),
diabetes mellitus (86%), hypertension (83.1%), alcohol abuse (82.4%), old age (78.6%) and lastly obesity with 64.3%. This is shown in
table 14 below.
Table 14: Outcome associated with predisposing factors
Characteristics HT (%) DM
(%)
HIV (%) Alcohol
(%)
Old
age(%)
Obesity
(%)
HbsAg(%) Subst
abuse(%)
Outcome
Alive
Dead
Total
13(6.5)
64(32)
77(38.5)
4(2)
24(12)
28(14)
2(1)
21(10.5)
23(11.5)
3(1.5)
14(7)
17(8.5)
3(1.5)
11(5.5)
14(7)
5(2.5)
9(4.5)
14(7)
1(0.5)
12(6)
13(6.5)
-
8(4)
8(4)
lv
Good outcome %
Poor outcome %
16.9
83.1
14
86.0
4.8
95.2
17.6
82.4
21.4
78.6
35.7
64.3
7.7
92.3
-
100
4.6.7 Comparison of outcome between patients with and those without predisposing factors.
In general, when the outcome between patients with predisposing factors was compared with those without those factors, it was found to
be statistically insignificant (p >0.05). This is shown figure 15.
4.6.8 Multiple response analysis of co-morbid illness: Liver cirrhosis was associated with the worst outcome rate of 95.0%, followed by acute
renal failure (88.2%), aspiration pneumonia (84.9%); sepsis (81.5%), anaemia and chest/urinary tract infections (80% each), hyperglycemia
(77.3%) hypertension (64.5%), acute pulmonary edema (55.6%) and recurrent stroke (50%). This is shown in table 15
Table 15: Multiple response analysis outcome associated with co-morbid illnesses in medical coma
Co-morbidity Alive
(%)
Dead (%) Total (%) Good
outcome %
Poor
outcome %
Fig 15: Distribution of outcome according to presence/absence of predisposing factors
23.4
37.5
76.6
62.5
0
10
20
30
40
50
60
70
80
90
present absent Risk factors P>0.05
Percentage
Alive Dead
lvi
Liver cirrhosis 1 (0.5) 9 (9.5) 20 (10) 5 95
Acute renal failure 2 (1) 15 (7.5) 17 (8.5) 18.8 88.2
Aspiration pneumonia 8 (4) 45 (22.5) 53 (26.5) 15.1 84.9
Sepsis 5 (2.5) 22 911) 27 (13.5) 18.5 81.5
Anaemia 4 92) 16 (8) 20 (10) 20 80
Chest/urinary tract
infection
2 (1) 8 (4) 10 (5) 20 80
Hyperglycemia 5 (2.5) 17 (8.5) 22 911) 22.7 77.3
Hypertension 11 (5.5) 20 (10) 31 (15.5) 35.5 64.5
Recurrent seizures 11 (5.) 19 (9.5) 30 (15) 36.7 63.3
Acute pulmonary edema 4 (2) 5 (7.5) 9 (4.5) 45.4 55.6
11.Recurrent stroke 2 (1) 2 (1) 4 (2) 50 50
4.6.9 Comparison of outcome in patients with and those without co-morbid illnesses
In general, a total of one hundred and eighty four (92%) of the patients had a co-morbid illness while sixteen (8%) had none. However the
difference in the outcome in term of survival was statistically insignificant between the 2 groups. (X2 = 0.501, P=0.479) as shown in fig 16.
lvii
4.6.10 Outcome of medical intervention:
i. Hospital admission: Of the 84.5% of the patients admitted in to the medical ward, 63.5% of them died while 21% survived, giving a
mortality rate of 75.1%. 10% of the 12.5% admitted in the A & E died, giving a mortality rate of 80%, while 2.5% of the 3% admitted in
the ICU died, giving a mortality rate of 83.3%. However, these was not significantly different, x2 = 0.464, p=0.793. The distribution of
outcome according to hospital admission is shown in fig 17.
Fig 16: Distribution of outcome according to presence/absence of co-morbidity
23.4
31.2
76.6
68.8
0
10
20
30
40
50
60
70
80
90
present absent Co-morbidity P>0.005
Percentage
Alive Dead
lviii
ii. Time before clinical diagnosis and onset of resuscitation
More than two third (79.5%) of the patients had their medical condition diagnosed within 24 hours, yet about 58.5% of this number died
giving a mortality rate of 73.6%. Of the 20.5% that has delayed diagnosis of more than 24 hours, 17.5% died, giving a mortality of 85.4%,
however this difference was not statistically significant to the outcome of coma. (X2 = 2.48, P = 0.115) Also, almost all the patients (99%)
had resuscitative measures started < 1 hour of becoming unconscious in the wards or presentation to A & E or ICU, but this did not
translate into lower mortality as 75.5% of them died. (X2 = 0.749, P =0.382). See table 16 for details
Table 16 Outcome due to delay before clinical diagnosis and onset of resuscitation
Hours before diagnosis Alive (%) Dead (%)
Total Mortality
rate
X2 P-value
<24hrs
>24hrs
Total
42(21)
6(3)
48(24)
117(58.5)
35(17.5)
152(76)
159(79.5)
41(20.5)
200(100)
73.6
85.4
2.48
0.115
Fig 17:Distribution of outcome according to hospital admission
24.9 20
16.7
75.1 80
83.3
0
10
20
30
40
50
60
70
80
90
MW A&E ICU Hospital admission P>0.05
Percentage
Alive Dead
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Hours before resuscitation Alive Dead Total Mortality
rate
X2 P-value
<1hour
>1hour
Total
47(23.5)
1(0.5)
48(24)
151(75.5)
1(0.5)
152(76)
198(99)
2(1)
200(100)
75.5
24.5
0.749 0.382
iii. Relevant investigations
One hundred and sixty five (82.5%) patients had some or all the relevant investigations needed to confirm the cause of coma. Forty eight
(24%) in this group survived while one hundred and eleven (55.5%) died, giving a mortality rate of 67.3%. On the other hand, all the thirty five
(17.5%) patients who had no investigations died, giving a mortality rate of 100% in fig. 18 below. This result was statistically significant
(X2=14.04, P = 0.000). However, there was a weak correlation between outcome and investigation (Pearson’s R = 0.232, Spearman Correlation
= 0.232).
lx
iv. Family support/knowledge of cause of coma.
Family support had a strong influence on outcome. (X2=27.07, P=0.000). The mortality rate of 56.8% in patients who had excellent (80-
100%) family support was lower than 86.1% and 97.1% respectively for those who had good (50-79%) and poor (<50%) family support.
Family knowledge of cause of coma also had some influence on coma outcome, as it was statistically significant (X2=7.84, P=0.02).
Mortality was highest (84.1%) in patients whose family members had the least knowledge (80.3%) and lowest (64.8%) in those whose family
members had excellent knowledge. However, spearman correlation for family knowledge was weaker (0.164) than that for family support (0.356).
See table 17 below for more details.
Table 17 Influence of the family support/ knowledge of cause of coma on outcome
Family support
Alive (%)
Dead(%)
Total
(%)
Mortality
rate
X2
P-
value
Fig 18: Distribution of outcome according to ability to do relevant investigations
32.7
0
67.3
100
0
20
40
60
80
100
120
All/some None Relevant investigation P>0.05
Percentage
Alive Dead
lxi
Excellent(80-100%)
Very good/good(50-79%)
Poor/ very poor(<50%)
Total
36(18)
11(5.5)
1(0.5)
48(24)
51(25.5)
68(34)
33(16.5)
152(76)
87(43.5)
79(39.5)
34(17)
200(100)
56.8
86.1
97.1
27.07
0.000
Family knowledge of cause
of coma
Alive
Dead
Total
Mortality
rate
X2
P-
value
Excellent(80-100%)
Very good/good(50-79%)
Poor/ very poor(<50%)
Total
25(12.5)
13(6.5)
10(5)
48(24)
46(23)
53(26.5)
53(26.5)
152(76) 200(100)
71(35.5)
66(33)
63(31.5)
64.8
80.3
84.1
7.84
0.020
v. UCH social welfare support
17% of patients who were offered <50% social welfare support had the highest mortality rate of 82.4%, while those with 50-79% had the
least mortality rate of 61%. However, the mortality rate of 7.5% was observed in the very few (2%) who had excellent support and the majority
(71.5%) who for various reasons had none. Thus the influence of UCH social welfare support on outcome of coma was statistically insignificant
(x2=0.591, p=0.74) as shown in table 18 below.
Table 18. Influence of UCH social welfare support on outcome of coma
UCH social welfare
support
Alive(%) Dead(%) Total(%) Mortality
rate
X2 P-
value
Excellent(80-100%)
Very good/good(50-79%)
Poor/ very poor(<50%)
Not sought for
Total
1(0.5)
5(2.5)
6(3)
36(18)
48(24)
3(1.5)
14(7)
28(14)
107(53.5)
152(76)
4(2)
23(11.5)
34(17)
143(71.5)
200(100)
75
61
82.4
74.8
0.591
0.744
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4.7 PREDICTION OF THE OUTCOME OF MEDICAL COMA USING THE GLASGOW COMA SCALE (GCS) AND
BRAINSTEM SIGNS SCORE (BSS)
The positive predictive value (PPV) is the % correct prediction of deaths and is > 50% when more deaths than recovery are recorded,
especially if those deaths occurred at scores equal or lower than the critical score, and vice versa.
The negative predictive value (NPV) is the % correct prediction of survival and is >50% when more survivors than deaths are recorded especially
at scores higher than the critical score, and vice versa. For the calculation of PPV and NPV, see appendix 1.
4.7.1 The predictive value of the Glasgow Coma Scale (see table 19)
The PPV was < 50% for all the coma groups on the day of admission (DI). It improved to 53.5% and 55.6% for cerebrovascular and
metabolic coma respectively, but remained <50% for the rest on the third day of admission (D3). On the seventh day (D7), it remained <50%
except for cerebrovascular, (52.4%) and hypoxic-ischemic (50%) coma. On the fourteenth day, (D14), it remained <50% for all except infectious
coma where it was 66.7%. On the twenty-eight day (D28), it was zero for all the coma groups.
The NPV on D1 ranged from 63.6% for cerebrovascular coma to 100% for hypoxic-ischemic coma. On D3, the range was 72.7% for
cerebrosvacular; 83.3% for the “other” causes and 100% for the rest. On D7 through D28, the NPV was 100% for all the coma groups.
lxiii
4.7.2 The predictive value of the brainstem sign score (see table 20)
The PPV on D1 was 100% for all the coma groups. On D3 it was 100% for all the groups except metabolic coma where it was 97.1%. On
D7, it was 92% for metabolic and cerebrovascular each and 100% for the rest. On D14, it was zero for infectious and hypoxic-ischemic, 87.5% for
cerebrovascular and 100% for the rest. On D28, it was zero for all, except cerebrovascular where it was 100%.
The NPV was zero for all the coma groups on DI. On D3, it was <30% for the groups except metabolic with 68.2%. On D7, it remained up to 88%
lxiv
for metabolic, 100% for other causes; and < 50% for the rest. On D14, it was 100% for both metabolic and hypoxic-schemic coma, and < 50% for
the rest. On D28, it was zero to 50% for all except metabolic (75%) and hypoxic-ischemic (100%).
lxv
4.8 MULTIPLE LOGISTIC REGRESSION ANALYSIS TO DETERMINE MOST SIGNIFICANT PROGNOSTIC VARIABLES
An SPSS logistic regression output of the analysis of significant prognostic factors in medical coma as follows (see table 21).
1) On day 1, presentation to UCH after <6hrs of coma was the most significant factor (Sig of 0.727, S.E. of 0.132, 95% CI of 0.81-1.36),
followed by family knowledge of cause of coma (Sig of 0.575, S.E. of 0.263, 95% CI of 0.52-1.45), GCS (Sig of 0.355, S.E of 0.185, 95%
CI of 0.83-1.71) and family support (Sig of 0.322, S.E of 0.377, 95% CI of 0.69-3.04).
2) On day 3, cause of coma was most significant (Sig of 0.830; SE of 0.068, 95%, CI of 0.89-1.16), followed by family knowledge of cause
of coma (Sig of 0.759, SE of 0.359, 95% CI of 0.44-1.81), family support (Sig of 0.597, SE of 0.55, 95% CI of 0.46-3.9) and ability to do
the relevant investigations (Sig of 0.314, SE of 0.023, 95% CI of 0.98-1.07)
3) On day 7, ability to do the relevant investigations was most significant (Sig of 0.94; SE of 1.1, 95% CI of 0.11-7.51), followed by
lxvi
knowledge of cause of coma (Sig of 0.681, SE of 0.0.57, 95% CI of 0.26-2.4), age of patients (Sig of 0.615, SE of 0.033, 95% CI of 0.95-
1.1), cause of coma (Sig of 0.567, SE of 0.097, 95% CI of 0.78-1.15) family . support (Sig of 0.355, SE of 0.18, 95% CI of 0.59-1.21).
4) On day 14 all the factors had similar significant value of 1.0
CHAPTER FIVE
DISCUSSION AND CONCLUSIONS
5.1 DISCUSSION
5.1.1 Epidemiology of medical coma in University College Hospital Ibadan
i. General incidence: In general, medical coma constituted 9.8% of emergency admissions and 3.1% of total hospital admissions in UCH
Ibadan during the study period.
The most common coma group in this study was metabolic coma with an incidence of 35.5%. This contrasts with many report which
placed cerebral infections above metabolic coma as the commonest cause of medical coma in developing countries in general and Africa in
particular.42,43,45-48 However, the incidence of 22% which placed cerebral infections third after stroke with 33% in this study may indicate a
decreasing frequency of the devastating effect of infections, probably due to availability of powerful antibiotics in Africa.45 As a group,
cerebrovascular diseases or stroke were second to metabolic coma in this study, but hemorrhagic stroke as an entity constituted about 26% of all
cases, thereby becoming the single most common cause of medical coma during the period of the study. This result agrees with earlier ones on
stroke29,53,99,100,102 and coma. However, it accounted for 79% of all strokes in this study, a figure which is higher than the 65% reported by Ogun in
Lagos29. Many reasons could account for this difference. One reasons could be because Ogun’s study was a retrospective one with its attendant
limitations. Another reason could be that UCH being a centre for WHO stroke research centre and with CT scan and other laboratory facilities for
stroke diagnosis and management attracted many cases of stroke.
Hypoxic-ischemic coma accounted for only 5% of cases in this study, with cardiac arrest being responsible in half of the cases. This result
confirms that this group is still not a significant cause of coma in this part of the world yet, unlike in developed countries,49,50,88. Other causes such
lxvii
as status epilepticus, shock, hypertensive encephalopathy and CNS lymphoma were very few in number. All the CNS lymphoma cases were HIV
seropositive as part of the acquired immunodeficiency syndrome (AIDS) complex82,103.
The increased incidence of diabetic coma (12.5%) in this study, second only to hemorrhagic stroke shows that diabetes as a disease entity,
is becoming an important prevalent disease in Nigeria,59 which should not be ignored but must be recognized as a major source of morbidity and
mortality51.
Uremic coma came third after diabetes as cause of medical coma. Many of the cases came in end-stage renal failure possibly as a result of a
combination of ignorance, poverty, herbal drugs ingestion, unavailability or unaffordability of drugs or poor drug compliance. Most cases were
due to hypertensive nephrosclerosis and diabetic nephropathy, while some were associated with HIV and hepatitis B viral infections. Few cases
presented in pre-renal acute renal failure. Uremic coma has not been reported as a major cause of nontraumatic coma. In the developed world, it
could be the result of good patient care in the pre-end-stage renal failure stage so that few go into uremic coma. In the developing countries, lack
of or inadequate renal dialysis units coupled with high cost of drugs and dialysis might preclude many patients from presenting to hospitals earlier.
Hepatic coma accounted for 6% of causes in this study and its occurrence has been attributed to the high prevalence of chronic liver
diseases and hepatitis B viral infection in the environment98. The causes of hypoglycemia in this study were in consonance with the report by other
workers especially in African65,66
Meningitides, sepsis syndrome and parameningitides/brain abscesses and cerebral malaria were the infections identified in this study. The
first three groups of infections were seen mainly in HIV seropositive patients especially TB and viral meningitides. This agrees with many studies
linking the high incidence of TB meningitis with the resurgence of the HIV pandemic,104,105. The pyogenic meningitides were due to
Streptococcus pneumoniae and no case of meningococcal meningitis was seen. This is not surprising because Ibadan is located in the forest zone
and not the hot dry savannah meningitic belt of Nigeria and Streptococcal pneumoniae still remains the commonest cause of sporadic cause of
bacteria meningitis23
ii. Sex and age incidence: There was a 2:1 male to female ratio in this study, which agrees with most studies in nontraumatic coma all over
the world50,53. The reasons adduced for this include the possible presence of more risk factors for the various causes of coma25,51,52 or the tendency
for more males to attend hospitals53,59,63,75. The age group 40-59 was the most commonly affected but this was evident only in coma due to
lxviii
infections. In metabolic and cerebrovascular causes, the >60 age group was the dominant group, followed by the 40-59 group. This is similar to
many earlier results in the developed world41,49,50 but different from those of Africa where the mean age was usually lower42,43,48,103 This trend
may represent a gradual prominence of diseases of the developed world in Africa.
iii. Socioeconomic grouping: The self employed (made up of traders, artisans and commercial taxi drivers, farmers etc) and the unemployed
constituted more than 70% of the study population while the government employed were in minority. This is the trend in many earlier studies53,76
too. Many reasons can be adduced for this disparity, which may include the possible occurrence of more risk factors for the various causes of
coma. The self employed are people with possible low educational attainment,53,65 poor financial background29,47 high ignorance level65, and
therefore more prone to high risk lifestyle43,75. On the other hand, the public servant with a steady income and possibly higher literacy level and
awareness was able to control or avoid risk factors for stroke, diabetes mellitus and other causes of coma. However, it must be pointed out that no
high level public servant, prominent politician, traditional ruler, doctors and other professionals was seen through out the period of this study. The
reasons for this are not known to the author, but may be a subject for another research.
5.1.2 Outcome of medical coma
i. General consideration
Medical coma accounted for about 16.8% of all UCH patient deaths during the study period. This figure is higher than the annual death
rate of between 300, 400 per 4568 cases recorded in UCH more than 2 decades ago103.
The best one month outcome of coma in this study in terms of the 5 functional levels described in the literature50 showed that 76% of the
patients died, 2% went into vegetative state, 6% recovered with severe disability, 5% recovered with mild disability and 11% had good recovery.
This report compares well with those published by Bates D et al40 and Bates D and Caronna JJ et al50 in which they reported 61% deaths, 12%
vegetative state, 12% severe disability and 15% mild to good recovery respectively in their patients.
The medical coma group with the worst outcome was infections with 86.6% mortality rate. This must be related to the underlying
retroviral infection associated with many of them as reported in many earlier series,96,104,105 otherwise infections were reported to have the best
outcome in the absence of retroviral infection.40,43,50 Hypoxic-ischemic coma had a good outcome of 40% followed by metabolic coma with
32.4%. This agrees with earlier predictions by Levy DE, et al40 and Bates D et al50. The fair outcome of metabolic coma was mainly due to
lxix
hypoglycemia and diabetic coma, because the other component i.e. hepatic coma and uremic coma had 100% and 83.3% mortality rate
respectively. The survival rate of diabetic ketoacidotic coma was 100% in this study while that of hyperosmolar nonketotic coma was 29%. This
was a great improvement from the 100% case fatality in hyperosmolar nonketotic coma reported in UCH Ibadan by Osuntokun et al many years
ago63. Many factors may account for this including availability of glucometers and human insulin106.
ii. Co-morbidity/complications
One hundred and eighty four (92%) of the patients had one or more co-morbid illness(es), common among which were aspiration
pneumonia, hypertension, recurrent seizures, sepsis, anemia, liver cirrhosis, acute renal failure, hyperglycemia, acute renal failure. None of these
illnesses was associated with a mortality rate of less than 50%. Liver cirrhosis had the highest rate of 95%, followed by acute pulmonary edema
with 93.8%. These findings are also in conformity with some of those described by other workers84,98.
It is important to note the absence of decubitus ulcers, deep venous thrombosis, malnutrition and contractures as major co-morbid illness
complicating coma in this study.
This may reflect either good medical and nursing care or that the patients died soon after admission and did not live long enough to develop those
complications.
iii. Predisposing factors
Hypertension was the commonest predisposing factor identified in this study. It was present in 33.5% and 5.5% of coma due to stroke and
metabolic coma, (mainly diabetic and uremic) respectively. In stroke, it occurred in association with obesity in 6%, alcohol and substance abuse in
5.5%, diabetes mellitus in 4.5% and old age in 4% of cases respectively. It was also associated with the probability of 83% mortality. These
observations are in agreement with those of many workers in Nigeria51,53,59,102 and other countries61, 100
Diabetes Mellitus was present in 14% of the patients. It was a strong factor in diabetic nephrosclerosis (8%) and in stroke especially in
association with alcohol abuse and obesity with attendant poor prognosis63,106. It was a predisposing factor in one of the 2 cases of status
epilepticus in the study.
Underlying HIV infection was a strong factor in the prognosis of the meningitides, parameningitis, sepsis syndrome, and CNS lymphoma.
The almost 95% mortality associated with its presence in this study has been reported by other workers,52,104,105. HBsAg was associated with all
lxx
the hepatic coma and some of the uremic coma cases with a overall mortality rate of 83%, but a specific rate of 100% in hepatic coma. These
figures agree with those obtained in studies on hepatic coma in Ibadan107 and uremic coma in Ethiopia108respectively many years ago.
iv. Sociological factors
The result obtained in this study showed that patients who had above 50% family support and were able to pay for some relevant
investigations had a better outcome than those who had poor or less than 50% family support or failed to pay for investigations. This report is in
consonance with those of Hammed MB and Goldman L et al55 and Jorgensen HS et al54.
Delayed presentation to hospital was a major factor in this study. About 45% of the patients were brought to hospital more than 6hours after onset
of coma and this group had higher mortality. Many of these patients were referred from private hospitals where they were first seen and most of
the times presented to UCH with co-morbid illnesses, hence the higher mortality. This also agrees with the observations of other workers,
particularly with respect to stroke29,53 and hypoglycemia64,65 especially in Africa.
v. Prognostic value of the Glasgow Coma Scale (GCS)
The GCS as an index of assessing levels of consciousness in this study was very useful as it ensured uniformity93 and standardization of
patient monitoring43. But it had a poor positive predictive value and a higher negative predictive value. This may suggest that it has a higher ability
to accurately predict survival than death. This feature of GCS was uniform in all the groups of medical coma but was best in hypoxic-ischemic
coma. This observation agrees with those of other researchers of traumatic and nontraumatic coma41,87. Many of these researchers have
circumvented the limitations of the GCS by applying the components separately and not summing up the scores40,41,50 but this also has its pitfall
10. However, others have modified them for use in conjunction with brainstem responses38,91. The GCS was more useful for monitoring or
detecting clinical improvement and not very useful for predicting outcome from initial evaluation of comatose patients.
vi. Prognostic value of brainstem signs
Brainstem signs score had both high positive predictive value and good negative predictive value. Therefore it seems to be able to predict
both survival and death at initial evaluation of coma patient. This feature was recognized by many workers who had used it in various ways to
predict outcome of coma,38,40-41. In this study, most of the patients with abnormal brainstem functions below the critical score died and vice versa,
irrespective of cause of coma, which is in consonance with several earlier reports40,49.
lxxi
vii. Coma as an independent poor prognostic factor
The high mortality of 76% recorded in this study irrespective of early diagnosis, resuscitative measures and treatment, presence or absence
of risk factors or co-morbid illnesses, excellent or poor family support confirm that coma, irrespective of cause has an independent prognostic
value. This observation has been supported by reports of many other workers86,88.
5.2 CONCLUSIONS
The following conclusions can be made from the results of this study.
1. Medical coma constituted 9.8% of emergency admissions, 3.1% of total hospital admissions and 16.8% of hospital deaths in UCH, Ibadan
during the study period.
2. The four most common causes of medical coma in UCH Ibadan were hemorrhagic stroke, diabetic coma, uremic coma and meningitides.
3. The four strongest predisposing factors identified were hypertension, diabetes mellitus, H.I.V/Hepatitis B viral infection and obesity
4. The four commonest co-morbid illnesses were aspiration pneumonia, hypertension, recurrent seizures and sepsis.
5. The Glasgow Coma Scale when used in conjunction with the brainstem signs score were useful both for initial evaluation and continuous
monitoring of medical coma patients for the purpose of predicting outcome.
5.3 LIMITATIONS OF THE STUDY
(i) Inadequate funds for investigations and ICU management. 35 of the 200 patients could not be investigated because of lack of fund. Some
could not afford the cost of I.C.U admission and computerized tomography scan of the head/brain.
(ii) Lack of laboratory facilities for identification of specific viral agents causing meningitis and encephalitis.
lxxii
(iii) Lack of CSF diagnostic tests for Mycobacterium tuberculosis (polymerase chain reaction, tuberculostearic acid, detection of antibodies or
immune complexes)
(iv) Serum drug and alcohol levels monitoring was not possible due to lack of facilities.
(v) Inadequate facilities in the I.C.U including limited bed spaces.
(vi) Lack of post mortem for confirmation of causes of death. Only 5 autopsies were done to confirm cause of death in this study. Dislike for
post mortem was very strong among the population for cultural and religious reasons.
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APPENDIX I
The Predictive value of GCS and Brainstem sign scores (BSS) in medical coma
(Calculated using the 2 by 2 contigency table).
GCS Brainstem sign score Dead Alive
3 < 13 True positive
(a)
False negative (c )
> 3 > 13 False positive
(b)
True negative (d)
Positive predictive value (PPV) = a x 100%
(% correct prediction of death) a + b
Negative predictive (NPV) = d x 100%
(% correct prediction of survival) d + c
APPENDIX II
BRAINSTEM FUNCTIONS AS PROGNOSTIC INDICES
Brainstem sign Location of lesion / dysfunction
i
Pupillary size / light responses
Symmetrically round, reactive (2.5–5.0mm
diameter) pupils
Symmetrically dilated, unreactive (>5.0mm
diameter) pupils
Unilaterally dilated, unreactive pupil
Normal size pupils; excludes midbrain
damage.
Severe midbrain damage, usually from
transtentorial herniation
Compression / stretching of third cranial
nerve by ipsilateral midbrain mass or
contralaterally against the opposite
tentorial margin
lxxxii
ii
iii
iv
Symmetrically small, reactive
(1.0-2.5mm diameter) pupils
Symmetrically pinpoint reactive
(< 1.0mm diameter) pupils
Unilaterally small, unreactive
(failure to dilate in the dark) pupil
Eye movements
Spontaneous conjugate horizontal roving
Horizontal ocular divergence at rest
Unilateral abducted eye at rest + ipsilateral
mydriasis
Vertical ocular axes divergence or “skewed
deviation”
“Ocular bobbing” – a brisk downward and slow
upward movements of the eyes with loss of
horizontal eye movements
“Ocular dipping”-slower, arrhythmic downward
movement followed by a faster upward
movement + normal reflex horizontal eye
movements.
Corneal reflexes – mediated by the fifth nerve
(afferent) and seventh nerve (efferent) in the
pons.
Oculocephalic reflexes (Doll’s eyes)
Full and conjugate eye movements
Metabolic encephalopathy
Thalamic hemorrhage / hydrocephalus
compressing sympathetic efferents
emerging from posterior hypothalamus
Acute, extensive bilateral pontine
hemorrhage. Narcotic drugs
Horner’s syndrome
Massive ipsilateral thalamic hemorrhage.
Intact midbrain / pons
Metabolic encephalopathy
Drowsiness
Increased intracranial pressure causing
bilateral sixth cranial nerve palsy
Third cranial nerve palsy causing medial
rectus paresis + parasympathetic damage
Pontine or cerebellar lesions
Bilateral pontine damage
Bilateral pontine damage
Lost in pontine damage
CNS depressants
Diffuse cerebral hemispheric lesion
Intact brainstem pathways extending from
lxxxiii
v
vi
Incomplete conjugate eye movements with head
turning
No eye movement. Eyes move with the head as
if they are locked in the sockets
Oculovestibular response (Caloric test)
(Done if patient has cervical spine fracture)
Respiratory pattern
Classic Cheyne – Stokes
Rapid deep (Kussmaul) breathing (40-70 cycles
minute)
Apneustic breathing (slow breathing with long
pause in between inspiration and inspiration)
Cluster respiration
Shallow, regular 25-40cycles/minute
(eupnea) breathing)
Agonal gasps(irregular / ataxic breathing)
Shallow, respiratory-like movements with
irregular, non repetitive back-arching
the high cervical spinal cord and medulla
(where vestibular and proprioceptive input
from head turning originates) to the origin
of the third nerve in the midbrain
Damage to pontine gaze centre on the side
of gaze paresis or contralateral frontal
lobe
Massive brainstem damage or drug
intoxication (eg diazepam, barbiturates,
pancuronium)
Adjunct to the Doll’s eye test, acting as a
stronger stimulus to the reflex eye
movements but giving the same
information
Inconsistent localizing value
Mild bihemispheric damage
Metabolic encephalopathy
Pontomescencephalic damage
Metabolic encephalopathy
Mid pontine lesions
Midpontine lesions
Lower brainstem damage
Diffuse anoxia
Lower medulla and cervical spinal cord
lxxxiv
APPENDIX III
lxxxv
APPENDIX IV
A. GENERAL INFORMATION
Serial No ----------------------------------------------------------------------
Hospital No--------------------------------------------------------------------
Name (initials only) ----------------------------------------------------------
Age/Sex ------------------------------------------------------------------------
Marital status/socioeconomic status-----------------------------------------
lxxxvi
Religion -------------------------------------------------------------------------
Mode of referral Relatives Hospital/Clinic
Prayer house
Place of Onset of coma
Out-of hospital ICU
General Ward A&E
Time/date of onset of present illness
Presenting complaints--------------------------------------------------------------
Time/date of onset of coma--------------------------------------------------------
Time/date of presentation:---------------------------------------------------------
Time/date of onset of treatment:--------------------------------------------------
Co-morbidities/complications -------------------------------------------------------
Predisposing factors ----------------------------------------------------------------------
B. GENERAL PHYSICAL EXAMINATION
DAYS ON ADMISSION
1 2 3 4 5 6 7 14 21 28
Pallor
Cyanosis
Jaundice
Dehydration
Oedema
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Lymphadenopathy
Temp
Respiratory rate
Respiratory pattern
Pulse rate
Pulse rhythm
Blood pressure
Liver size
Kidney size
Ascites
C. NEUROLOGIC EXAMINATION
1. GLASGOW COMA SCALE GCS
Score
1 2 3 4 5 6 7 14 21 28
a. Motor Responses (best limb)
Obeys command
Localizes pain
Withdraws from pain
Flexes to pain
6
5
4
3
lxxxviii
Extension to pain
No response to pain
2
1
b. Verbal Response
Oriented
Confused conversation
Inappropriate speech
Incomprehensible - speech
No speech
5
4
3
2
1
c. Eye Opening
Spontaneous
To noise or speech
To pain
None
4
3
2
1
2. BRAINSTEM SIGN91
a. Pupillary Light Response
Sufficient in both eyes
Sufficient in one eye only
Reduced in both eyes
Reduced in one eye only
Absent
SCORE
4
2
2
1
0
b. Corneal Reflexes
lxxxix
Present in both eyes
Present in one eye only
Absent
2
1
0
c. Oculocephalic Reflexes
Full
Minimal
None or eyes fixed
2
1
0
d. Spontaneous eye movements
Orienting
Roving conjugate
Roving dysconjugate
Other abnormal movements
None, fixed or immobile
4
3
2
1
0
e. Pupil size
Normal in both eyes
Normal in one eye only
Decreased in both eyes
Decreased in one eye
Increased in both eyes
Increased in one eyes
Increased and fixed in both eyes
6
3
4
2
2
1
0
xc
f. Motor Posturing
Normal
Decorticate
Decerebrate
Flaccid
3
2
1
0
3. FUNDOSCOPY
Normal
Papilloedema
Subhyaloid haemorrhage
Exudates
Disc atrophy
4. TWITCHINGS
None
Localized
Generalized
3
2
1
5. SKELETAL MUSCLE
TONE
Normal
Increased
Paratonic
Decreased
R L
xci
None
6. DEEP TENDON REFLEX
Normal
Increased
Decreased
None
R L
D LABORATORY/OTHER INVESTIGATION REPORTS
Blood sugar
Electrolytes
Urea
Full blood count (FBC)
Erythrocyte sedimentation rate (ESR)
Acute phase reactants
Liver functions test
Serum proteins
Blood gases (Sa02, Pa02, PaCo2, pH)
Cerebrospinal fluid (CSF)
Electroencephalogram (EEG)
Computerized scan (CTs)
Blood Drug level
Autopsy
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E. CLINICAL INFORMATION
Date of definitive diagnosis ……………………………..
Cause of coma ………………………………………….
Type of outcome (good recovery with no disability, recovery with mild/moderate disability; recovery with severe disability,
vegetative state, death)
Date of outcome. ……………………………………………
APPENDIX V
QUESTIONNAIRE TO EVALUATE RESPONSE OF PATIENTS RELATIONS TO OUTCOME OF COMA
Please tick as your appropriate response
1. SERIAL NO 2. PATIENT’S HOSPTIAL NO
3. AGE 12-30 31-60 >60
4. SEX M F
5 OUTCOME ON DISCHARGE
Good recovery with no disability
xciii
Recovery with mild/moderate disability
Recovery with severe disability
Vegetative state
Death
6. LIKELY REASONS FOR OUTCOME
Presented to hospital early ( < 6 hours of onset)
Presented to hospital late ( > 6 hours of onset)
Received prompt medical attention
Did not receive prompt medical attention
There was inadequate financial support
7. WHAT DO YOU KNOW ABOUT CAUSE OF COMA IN THIS PATIENT.
It is caused by enemies of progress
It is an act of God
It is caused by disease
It can treated
It cannot be treated
xciv
APPENDIX VI
CONSENT FORM
My name is ………………………………………………………………… I am a staff of the department of Medicine, University Hospital (UCH),
Ibadan.
I am carrying out a study to find out the prognostic factors in medical coma patients.
This questionnaire is to find out your own opinion on what determined the outcome of the illness of your patient or relation as the case may be.
All information given by you will be treated with utmost confidence. However, you are free to refuse to take part in the programme
xcv
……………………………………………… ……………………………………..
Signature/thumbprint of participant/Date Signature of Interviewer/Date
APPENDIX VII
SPECIFIC TREATMENTS GIVEN TO THE PATIENTS
i. Acute pyogenic meningitis. These patients were treated with empirical intravenous ceftriaxone 2-4g 12hourly while the result of the
sensitivity pattern was being awaited. After the antibiotic sensitivity pattern of the organisms was known, the most effective antibiotic was
used. Duration of therapy ranged from 7-21/days, depending of the pathogens involved e.g. N. meningitides and H. influenzae 7-10 days,
for S. pneumoniae 10-14 days; for gram negative aerobic bacilli, 21 days.
ii. Tuberculous meningitis
These patients were treated with 4 drugs given via nasogastric tube:- isoniazid 5-10mg/kg (max 300) daily with pyridoxine 50-100mg;
rifampicin 10mg/kg (max 600mg) daily,
pyrazinamide 25mg/kg (max. 2.5g) daily, ethambutol 15-20mg/kg (max 1.5g) daily
All the 4 anti TB drugs were to be used for 2 months (intensive period), so that if patient improved, isoniazid and rifampicin would be
xcvi
continued for 10-16 months. Tab dexamethasone 8-16mg/daily was prescribed for the initial 1-2 months, after initial 48 hours intravenous
doses.
iii. Viral meningoencephalitis
These patients were treated with empirical acyclovir 10mg/kg/dose (max 500mg) 8 hourly by slow infusion for 14-21 days, mannitol,
0.25g/kg every 3 hours or 0.5g/kg every 6hour in 20% solution intravenously over 20 minutes if there were signs of raised intracranial
pressure. Phenytoin 300mg daily for control of seizures
iv. Cerebral malaria The patients were given I.M Artemether (Paluther) 3.2mg/kg (max 160mg) stat, then 1.6mg/kg (max 80mg) 12 hourly
for 3 days.
v. Diabetic keto acidotic coma The treatment consisted of fluid replacement, hourly solube insulin, potassium replacement, correction of
metabolic acidosis and control of infection.
(b) Fluid replacement: 1 litre of 0.9% saline stat, then 1 litre in 1 hour, 1 litre over 2 hours, 1 liter over 4 hours, then 1 litre 6hourly, so that
patients got atleast 8-10 litres in the first 24 hours. The rate of infusion was adjusted according to renal status and level of hyperglycemic
reduction. 5% dextrose-saline was introduced when the blood glucose was < 15mmol/L
(c) Insulin therapy control: Intravenous soluble human insulin, 6-10 U bolus, then 6U hourly till the blood glucose was < 15mmol/L (blood
sugar monitored hourly), then 6U intramuscularly every 4 hours, (adjusted 4+2 hourly according to blood glucose) until patients regained
consciousness. The estimated patients daily insulin requirements were then determined either from amount of insulin used over the previous 24
hours or 0.1-1.0 U/kg/day given subcutaneously.
(d) Potassium replacement: The amount of potassium chloride (KCL) added to 1L of 0.9% saline was based on serum K+ level and the renal
status of patients. Once the patients had made >500mls of urine, the K+ replacement was commenced as follows: serum K+ (mmo/L) of <3.0,
<4.0, <5.0 were corrected with KCL (mmol/L) of 40, 30 and 20 respectively every 6 hours. When patients regained consciousness they were
given slow K tablets in appropriate doses (8mmol per tablet).
(e) Metabolic acidosis may correct spontaneously but if urine pH was still < 7.0 and the HCO3- level was <10mmol/L, 1ml/kg of 4.8% NaHCO3
was given in 0.9% saline over 1hour.
xcvii
(f) Infection was controlled by giving empiric ceftriaxone 1-2g IV 12hourly and metronidazole 100ml (500mg) 6-8hourly.
vi. Hyper osmolar nonketotic coma: Same principles as in DKA with the following modifications
(a) Fluid replacement: rapid (up to 10L in the first 24hours) monitored via pulse, BP, urine output and jugular venous pressure, then slower
rehydration (half of DKA rate) over 48hours.
(b) Insulin therapy: was usually delayed, as hyperglycemia was reduced by rehydration. Insulin was given at 1-2U/hourly after iv 4-6U bolus
(higher in obesity) till blood glucose became < 15mmol/L; then at 1-2U/4 hourly I.M until patient regained consciousness. After stabilization,
patient may continue subcutaneous insulin or recommence oral hypoglycemia drugs.
(c) Potassium replacement as above, but may be delayed
(d) NaHCO3 may not be needed.
(e) Infection as above
vii. Hypoglycemia: Patients received intravenous (IV) 50mls of 50% dextrose in double dilutions boluses, then continuous IV 5-10%
dextrose in saline IL 4-6hourly until recovery.
viii Hepatic coma: treatment consisted of low dietary protein of about 40g/days and high carbohydrate diet, daily rectal washout with soap and
water enema, IV metronidazole 500mg 6-8 hourly, crushed neomycin 1-2g 6hourly or syrup lactulose 20-30g hourly (until catharsis of 2-3 bowel
movements), then 20-30g 6hrly, all via nasogastic tube. Also had 5 – 10% dextrose infusions and vitamins.
ix Uremic coma Patients typically had hemodialysis 3 times a week, fluid retriction to 750mls plus previous days urine output, high doses
of frusemide 80-200mg/daily, antihypertensives, mainly ACE inhibitors, calcium channel blockers and correction of anemia with blood
transfusion
x. Alcohol coma (Osmotic demyelination syndrome)
Patient had continous 5% dextrose-saline IL 8hourly with vitamin. B complex 1ml/day; IV dexamethasone 8mg 6hourly
xi Gallamine poisoning (Gallamine is a competitive, nondepolarising neuromuscular end plate blocker. It therefore produces flaccid
paralysis that typically last for 30-60 minutes, and longer if larger doses are taken. CNS toxic effects include depression and coma. Antidote is
pralidoxime (cholinesterase regenerator) which was not available for patient. However patient had gastric lavage performed using normal saline
xcviii
and IV 5% dextrose-saline IL 6hourly + vit B complex 1ml in each IL of fluid until he became conscious.
xii Strokes (intracerebral hemorrhage, large infarctive)
The treatment regimes consisted of elevation of head of bed to 35 degrees to prevent regurgitation, maintenance of water and electrolyte balance
with IV 0.9% saline 3000ml/daily, feeding by nasogastric tube after 24hours; usually liquid diet 2000ml + 1000ml of water daily in divided doses
every 2 hours. When patients regained consciousness, swallowing mechanisms were tested daily and if normal, graduated diet was introduced.
Physiotherapy was introduce from the first day of admission, cerebral edema decompression was with IV infusion of 20% mannitol solution 1-
2g/kg (~ 500ml) over 10-20 minutes every 8hours for 48hours, and IV frusemide 40mg 12 hourly for > 48hours. Hypertension was not treated for
atleast 48 hours except when systolic and diastolic pressures were > 220mmHg and > 120mmHg respectively, otherwise nifedipine 20mg P.O
daily was given. Subcutaneous heparin 5000U 8hourly was given in infarctive stroke. All patients had supportive care and infection control with
antibiotics.
xiii Hypertensive encephalopathy: The aim of treatment was to reduce diastolic BP to ~ 100 – 110mmHg within 4hours. The drugs of
choice, sodium nitroprusside infusion and labetalol were not available. Therefore patient was given IV hydralazine 20mg slowly, repeated every
30 minutes to a maximum of 200mg dose. Then the BP was gradually reduced over several days with the following drugs: IV frusemide 40-80mg
daily, tab nifedipine 20mg 12hourly, tab atenolol 50-100mg.
xiv Status epilepticus: was controlled with 20mg of diazepam in normal saline infusion at the rate of 1.5mg/minute with maintenance dose of
IV phenytoin 20mg/kg at a rate of 20-30ml/minute.
xv Cardiac arrest patients were managed in the I.C.U with assisted mechanical ventilation and cardiac monitoring.
xvi Primary CNS lymphoma patients received: IV Dexamethasone 16mg stat, then tab 8mg 8hrly. They were also on antiretroviral therapy.
xvii Sepsis syndrome, patients received blood transfusions, intravenous fluids and metronidazole infusion 1500mg/daily in 3 divided doses
and various antibiotics according to sensitivity results. All had supportive care.
xcix
Table 19: Prediction of the outcome of medical coma using Glasgow Coma Scale
Days of
admission
GCS Metabolic Cerebrovascular Infection Hypoxic-ischemic Others
Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV
D A D A D A D A D A
1 3 9 2 18.8 91.3 22 4 40 63.6 7 1 17.9 80 2 - 33.3 100 - - 0 100
>3 39 21 33 7 32 4 4 4 1 2
3 3 20 - 55.6 100 23 3 53.5 72.7 11 - 47.8 100 1 - 20 100 - 1 0 83.3
>3 16 23 20 8 22 5 4 4 3 5
7 3 4 - 30.8 100 11 - 52.4 100 6 - 35.3 100 1 - 50 100 1 - 33.3 100
>3 9 18 10 10 11 5 1 4 2 5
14 3 1 - 33.3 100 2 - 40 100 2 - 66.7 100 - - 0 100 1 - 50 100
>3 2 7 3 9 1 3 - 3 1 3
28 3 - - 0 100 - - 0 100 - - 0 100 - - 0 100 - - 0 100
>3 5 5 2 8 - 2 3 3 1 2
A-Alive
D-Dead
c
Table 19: Prediction of the outcome of medical coma using Glasgow
Coma Scale
Days of
admission
GCS Metabolic Cerebrovascular Infection Hypoxic-ischemic Others
Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV
D A D A D A D A D A
1 3 9 2 18.8 91.3 22 4 40 63.6 7 1 17.9 80 2 - 33.3 100 - - 0 100
>3 39 21 33 7 32 4 4 4 1 2
3 3 20 - 55.6 100 23 3 53.5 72.7 11 - 47.8 100 1 - 20 100 - 1 0 83.3
>3 16 23 20 8 22 5 4 4 3 5
7 3 4 - 30.8 100 11 - 52.4 100 6 - 35.3 100 1 - 50 100 1 - 33.3 100
>3 9 18 10 10 11 5 1 4 2 5
14 3 1 - 33.3 100 2 - 40 100 2 - 66.7 100 - - 0 100 1 - 50 100
>3 2 7 3 9 1 3 - 3 1 3
28 3 - - 0 100 - - 0 100 - - 0 100 - - 0 100 - - 0 100
>3 5 5 2 8 - 2 3 3 1 2
A-Alive
D-Dead
ci
Table 20: Prediction of outcome of medical coma using the brainstem sign score
(BSS)
Days of
admission
Median
BSS
Metabolic Cerebrovascular Infection Hypoxic-ischemic Others
Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV Outcome PPV NPV
D A D A D A D A D A
1 ≤13 46 13 100 0 61 13 100 0 31 5 100 0 8 4 100 0 5 4 100 0
>13 - - - - - - 4 - - -
3 ≤13 33 7 97.1 68.2 48 10 100 23.1 27 5 100 0 6 3 100 25 5 3 100 25
>13 1 15 - 3 - - - 1 - 1
7 ≤13 13 2 92.6 88.2 23 7 92 41.7 13 3 100 40 3 2 100 50 2 - 100 100
>13 1 15 2 5 - 2 - - 2 - 4
14 ≤13 3 - 100 100 7 7 87.5 30 - 2 0 33.3 - - 0 100 1 1 100 50
>13 - 5 1 3 - 1 - 3 - 1
28 ≤13 - 1 0 75 2 4 100 50 - 1 0 0 - - 0 100 - 1 0 50
>13 - 3 - 4 - - - 1 - 1
A-Alive
D-Dead
Table 21: Multiple Regression Analysis
S/N Variables Day 1 Day 3 Day 7
Day 14
cii
Sig. = Significant value
S.E. = Standard error
CI = Confidence interval
Sig S.E 95%C1 Sig S.E 95%C1 Sig S.E 95%C1 Sig S.E
95%C1
lower upper lower upper lower upper lower upper
1 Relevant investigation 0.03 0.6 1.14 12.14 0.462 0.774 0.39 8.1 0.94 1.1 0.11 7.51 0.991 13580.4 0.000 0.000
2 Age of patients 0.112 0.018 0.993 1.065 0.314 0.023 0.98 1.07 0.615 0.033 0.95 1.1 0.991 500.6 0.000 0.000
3 Present after 6hrs of coma 0.727 0.132 0.81 1.36 0.212 0.160 0.6 1.12 0.246 0.24 0.47 1.21 0.994 2163.5 0.000 0.000
4 Family support 0.322 0.377 0.69 3.04 0.597 0.550 0.46 3.9 0.458 0.82 0.37 9.27 0.994 4128.2 0.000 0.000
5 Family knowledge 0.575 0.263 0.52 1.45 0.759 0.359 0.44 1.81 0.681 0.57 0.26 -2.4 0.991 5645.6 0.000 0.000
6 Cause of coma 0.16 0.052 0.84 1.03 0.83 0.068 0.89 1.16 0.567 0.097 0.78 1.15 0.990 2375.1 0.000 0.000
7 GCS 0.355 0.185 0.83 1.71 0.044 0.152 0.55 0.99 0.355 0.18 0.59 1.21 0.992 1368.7 0.000 0.000