insufficienza cardiaca aspetti epidemiologici: metodologia ... · insufficienza cardiaca aspetti...

Simona Giampaoli

Centro Nazionale di Epidemiologia,Sorveglianza e Promozione della Salute

Insufficienza cardiaca Aspetti epidemiologici:

metodologia e dati preliminari

Cardiovascular IndicatorsSurveillance Set in EuropeCardiovascular IndicatorsSurveillance Set in Europe

2000/IND/2061 Simona Giampaoli

2004-2007: PROPOSAL N. 791133

Istituto Superiore di Sanità � Rome, Italy

1. To identify cardiovascular diseases of major interest

2. To summarise specific indicators and sources of information for EU countries

3. To provide recommendations for the collection of the data easily applicable in different countries

OBJECTIVESEUROCISS I

1. To identify cardiovascular diseases of major interest

! high frequency ! possibility of prevention

ischaemic heart diseases myocardial infarctionheart failurecerebrovascular diseases

Major criteria include:- Paroxysmal nocturnal dyspnea- Neck vein distension- Rales- Radiographic cardiomegaly- Acute pulmonary oedema- Third sound gallop- Increased central venous pressure (>16 cm water in

the right atrium)- Circulation time > 25 s- Hepatojugular reflux- Pulmonary oedema, visceral congestion or

cardiomegaly at autopsy- Weight loss > 4.5 Kg in 5 days in response to

treatment of CHF

HEART FAILURE - 1

Minor criteria include:- Bilateral ankle oedema- Nocturnal cough- Dyspnea on ordinary exertion- Hepatomegaly- Pleural effusion- Decrease in vital capacity by 33% from maximal

value recorded- Tachycardia (rate > 120 beats/min)

Diagnosis of CHF is given for two major or one major and two minor criteria

HEART FAILURE - 2

Health status of a population:

� morbidity

� mortality

� risk factors

2. To summarise indicators and sources of information

! Hospital discharge records

! Surveys

! Population-based registries

Myocardial Infarction Registers: population characteristics

GSF �KORA40025-741985RegionalGermany

Ministry Health1,80035-741985RegionalFrance

KTL23235-1001991RegionalFinland

Aarhus University493All1977RegionalNorthern

Denmark

University of Ghent15125-741998RegionalBelgium Bruges

School of Public Health

23025-691983RegionalBelgium Charleroi, Ghent

Available from

Population x 1000

Age rangeYearsArea coveredCountry

European Journal of Public Health 2003; 13 (3 Suppl): 55-60

Nat. Board of Health and Welfare

51025-741985 RegionalNorthern Sweden

MONICA76625-741985-1998RegionalSpain

Kirkenes Hospital58152000RegionalNorway

Institute Health3,36035-741996RegionalItaly

Available fromPopulation

X 1000Age rangeYearsArea

coveredCountry

Myocardial Infarction Registers: population characteristics


MONICAName, date of birth

410-414, 428, PTCA,

CABG

410-414, 428,798XGermany

MONICAName, date of birth410-414,428410-414XFrance

MONICA, TroponinePIN410,411,413410-414,

428,798XFinland

-PIN 410410VIII-XNorthern Denmark

MONICA, Troponine

Name, date of birth

410-414, PTCA, CABG

410-414IXBelgium

ValidationLinkage

Mortality / HDR

HDRICD codes(*)

Mortality ICD codes(*)

ICD versionCountry

(*) all codes are presented in the ICD-9 revision to facilitate the comparison

Myocardial Infarction Registers: case definition


MONICAPIN410410IX, XNorthern Sweden � MONICA

MONICAName, date of birth410-414410-414, 428,

798, otherIXSpain

MONICA, TroponinePIN410-414,

428, PTCA410-414, 428,798XNorway

MONICAName, date of birth410-414, 410-414, 798,

otherIXItaly

ValidationLinkage

Mortality / HDR

HDRICD

codes(*)

Mortality ICD codes(*)

ICD versionCountry

(*) all codes are presented in the ICD-9 revision to facilitate the comparison

Myocardial Infarction Registers: case definition


MORTALITYSUSPECTED CAUSES

HOSPITAL DISCHARGESUSPECTED EVENTS

Discharged beforethe 28th day Alive at the 28th

day

Death certificates withsuspected causes

Alive at the 28th day

FATAL EVENT NON-FATAL EVENT

Cross-check with the mortality register

NON-FATAL EVENT

Figure 1: Data flow in a population-based register

3. To provide recommendations

Step-wise procedure for the implementation

Recommended indicators have been divided into:

� already available

� implemented in short-term

� implemented in long-term

Median length of stay

Aggregate bed-day rateMean length of stay

IN-PATIENT CARE

UTILISATION

Hearth transplant rateSURGICAL OPERATIONS

Functional disability and quality of life indicators

DISABILITY

� Validated hospital discharge rate

� Prevalence

Hospital dischargerate ICD-9 428 MORBIDITY

Validated mortality rateICD-9 428 rateMORTALITY

LONG-TERM IMPLEMENTATION

SHOR-TERM IMPLEMENTATIONAVAILABLE

Health Status Indicators for HEART FAILURE

Mortalità per insufficienza cardiaca

ICD-9 rev.: 428

Tutte le età

Ufficio di Statistica CNESPS-ISS

0

2

4

6

8

10

12

14

16

18

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

Anni

Tass

i sta

ndar

dizz

ati p

er 1

00.0

00

UominiDonne


ICD-9 rev.: 428

35-74 anni


0

2

4

6

8

10

12

14

16

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

Anni

Tass

i sta

ndar

dizz

ati p

er 1

00.0

00

UominiDonne


ICD-9 rev.: 428

75 anni ed oltre


0

50

100

150

200

250

300

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000

Anni

Tass

i sta

ndar

dizz

ati p

er 1

00.0

00

UominiDonne

INDICATORI PER INSUFFICIENZA CARDIACA

PAESE INDICATORE ETA' ANNO UOMINI DONNE FONTEScozia dimissioni ospedaliere tutte 1990 3,5x1000 3,7x1000

1996 5,1x1000 4,7x1000

letalità a 30 gg tutte 1990 20,3% 21,0%1996 14,9% 15,3%

letalità a 1 anno tutte 1990 37% 38%1996 30% 32%

Svezia ricovero ospedaliero 45-84 1988 267x 100.000 205x100.000

1993 237x100.000 171x100.000letalità a 30 gg

letalità a 1 annoOlanda prevalenza 55-64 1999 0,7% 0,6%

65-74 3,7% 1,6%75-84 14,4% 12,1%

65-74 1993 3,3% 2,9%

55-64 1990 4,9% 3,2%Galles prevalenza 0-85 1998 10,2x1000 8,5x1000 C. Ellis, University College London

A. Monsterd, Europ. Heart J., 1999; 20: 447-455

M. Schaufelberger, Europ Heart J, 2004; 25: 300-307

S. Stewart, Europ. Heart J. 2001; 22: 209-217

40%

16%


PAESE INDICATORE ETA' ANNO UOMINI DONNE FONTE

Stati Uniti mortalità 65-85 199575-84> 85

prevalenza 55-64 1992 4,5% 3,0%65-74 4,9% 4,3%

32,2x100.000WHO, International

Classification of Diseases, 9th Revision

130,8x100.000633,5x100.000

Prevalenza di insufficienza cardiaca normalizzata Prevalenza di insufficienza cardiaca normalizzata per età in soggetti con ipertensione arteriosaper età in soggetti con ipertensione arteriosa

Età (anni)Età (anni)

3030 3535 4040 4545 5050 5555 6060 6565 7070 7575 8080

22

66

44

88

1010

NHANES IIINHANES III(1988(1988--1991)1991)

NHANES INHANES I(1976(1976--1980)1980)

%%

Prevalence of Congestive Heart Failure Prevalence of Congestive Heart Failure by Age and Sex: United States: 1988by Age and Sex: United States: 1988--9494

2003 U.S.A. Heart Disease 2003 U.S.A. Heart Disease and Stroke Statistical Update and Stroke Statistical Update

The Epidemiology of Heart Failure: The Framingham StudyThe The EpidemiologyEpidemiology of of HeartHeart FailureFailure: : The The FraminghamFramingham StudyStudy

Età (anni) Uomini Donne50-59 3 280-89 27 22Tutte le età 2.3 1.4


Incidenza di scompenso cardiaco (per 1000 persone/anno)

9405 partecipanti (47% maschi) 9405 partecipanti (47% maschi) seguiti dal settembre 1948seguiti dal settembre 1948al giugno 1988al giugno 1988



Prevalenza di scompenso cardiaco (per 1000 persone)

Ho KK Ho KK etet al, J al, J AmAm CollColl CardiolCardiol 1993; 22(1993; 22(SupplementSupplement A):6AA):6A--13A13A

Comparative Comparative SurvivalSurvival FromFrom Common Common CancersCancers and and HeartHeart FailureFailure

BreastBreast

ProstateProstateHeartHeart FailureFailureColonColon

McMc MurrayMurray, E. , E. HeartHeart J 1998 (J 1998 (SupplSuppl. L). L)

YearsYears after after diagnosisdiagnosis

Sur

viva

l

Sur

viva

l %%

0102030405060708090

100

0 1 2 3 4 5


PAESE INDICATORE ETA' ANNO UOMINI DONNE FONTE

Trieste prevalenza <6565-7475-84

>85

mortalità 1997

Italia mortalità 0-85 2001 16,6 x 100.000 Ufficio di Statistica CNESPS-ISS

1997-2000

1,8x1000

A. Di Lenarda, Ital. Heart J., 2002; Suppl.3: 58-70

10,3x100022,3x100047,4x1000

12%

11,4 x 100.000

1. Pochi sono i dati epidemiologici disponibili

2. Non ci sono criteri diagnosticistandardizzati che permettano di raccogliere e confrontare i dati di diversi paesi

3. Dati ospedalieri devono essere integrati con dati dalle indagini su popolazione

CONCLUSIONI

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