Validation of the Euroscore and the ACEF score on cardiac surgery patients at Kenyatta National Hospital Nairobi, Kenya.

Transcription

1 Validation of the Euroscore and the ACEF score on cardiac surgery patients at Kenyatta National Hospital Nairobi, Kenya. Awori MN, Mehta NP, Mitema F, Kebba N Division of Thoracic & Cardiovascular Surgery University of Nairobi KCS Congress: Impact through collaboration CONTACT: Tel kcardiacs@gmail.com Web:

2 Disclosures I have no conflicts of interest for this talk I have no relationships to disclose

3 Can I ask you something Daktari? How many of these operations have you done? How many were successful?

4 These are loaded questions The ideal desire of any health care worker is to offer the best care to their patients Confirmation of the delivery of good quality care can only happen if quality can be measured The quality measurements must be valid

5 Validity You can use it and other people will accept it (the Oxford primary dictionary for Eastern Africa) Discrimination: can it predict the difference in outcome between high and low risk patients? Calibration: is the outcome it predicted really what is experienced?

6 Measures of quality (outcomes) Crude Mortality rate (CMR) Erroneous conclusions are possible as this metric does not account for patient related risk factors. For example: a higher crude operative mortality rate in one institution could be deemed as a poorer performance by that institution despite the fact that it may have operated on a greater proportion of high-risk patients than an institution with a lower crude mortality rate

7 Scoring System Region Year (Published) Patient (Number) Parsonnet 22 Tuman 23 Cleveland 24 Veterans Affairs 25 Tremblay 26 Lots of tools Canada STS (1 st System) 27 NYS 28 Ontario 29 French Score 30 Magovern 31 Cabdeal 32 Parsonnet (Modified) 33 Pons 34 STS (2 nd System) 35 UK National Score 36 STS (3 rd System) 37 NNE 38 Toronto 39 Euroscore (additive) 40 Toronto (Modified) 41 Care score 42 Euroscore (Logistic) 43 Amphiascore 44 STS (4 th System) 45 Motomura 46 ACEF Score 47 STS (5 th System) 48,49,50 ASCTS score 51 Euroscore II 52 Inscor 53 USA USA USA USA USA USA Canada France USA Finland France Spain USA UK USA USA Canada Europe Canada Canada Europe Netherlands USA Japan Italy USA Australia Global Brazil

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9 Euroscore

10 ACEF score A- Age(years) C- creatinine EF- ejection fraction(lv) ACEF = age/ef + 1(if creatinine > 177umol/L)

11 Method DESIGN analytical retrospective; case notes examined The Euroscore (additive and Logistic) and the ACEF score were calculated and respective ROC curves were generated. If discrimination was good the Hosmer-Lemeshow test would be used to assess calibration

12 Method STUDY LOCATION Records department at the Kenyatta National Hospital (KNH) in Nairobi, Kenya. (KNH is a 2000 bed hospital that serves as the national teaching and referral hospital).

13 Method DURATION A 5-year retrospective study carried out between 1 st January 2011 and 31 st December 2015.

14 Method INCLUSION CRITERIA Age of 18 years or older Have undergone cardiac valve surgery or coronary artery surgery or both on cardiopulmonary bypass at KNH during the study period EXCLUSION CRITERIA Aged younger than 18 years old

15 Results-demographics. Risk Factor Prevalence(%) Number of Patients (N) 109 Age (mean in years) 35.1(+/- 11) Pulmonary hypertension (PHT) 58.7 Left Ventricular dysfunction (LVD) 37.6 Double valve replacement (DVR) 17.4 Impaired renal Function (IRF) 1.8 Female 67.9 Isolated CABG 4.6

16 Results 1Discrimination: area under ROC (AUC) 2Comparison of risk factors 1Risk factor analysis

17 True Positive Rate Good Discrimination. 100% 0% 0% False Positive Rate 100%

18 True Positive Rate Poor discrimination 100% 0% 0% False Positive Rate 100%

19 True Positive Rate True Positive Rate Poor discrimination vs AUC % 100% 0 % 0 % False Positive Rate 100% 0 % 0 % False Positive Rate 100%

20 Additive Euroscore-AUC 0.59

21 Logistic Euroscore- AUC 0.59

22 ACEF-AUC (0.44)

23 Risk factor comparison Risk Factor Prevalence-Kenya (%) Prevalence- Europe(%) P-value N ,030 Age (mean in years) 35.1(+/- 11) 62.5 (+/- 10.7) <0.001 PHT LVD DVR IRF Female <0.001 Isolated CABG <0.001

24 Risk factor analysis. Risk factor Odd ratio (95% confidence interval) P- valve DVR 5.98 (1.83 to 19.49) 0.003

25 Discussion.. AUC: additive 0.59; logistic 0.59; ACEF 0.44 Poor discrimination No point calculating calibration Tests not valid in this patient set

26 Why could this be? Populations significantly different in at least 3 key areas: Age (Kenya-younger; 35 vs 62 yrs) Sex (Kenya-more females; 67 vs 27 %) CABG (Kenya-less CABG; 4.6 vs 65%)

27 Are our patients sicker?

28 Are our patients sicker?

29 Are our patients sicker? KNH mean expected mortality rate for additive Euroscore was 5.7 Our patients don t seem to be sicker than the European patients as has been suggested by some. Our observed mortality rate was 13.8%. European observed mortality rate was 2.9%. Something seems to be going on.

30 What else? DVR incidence the same In KNH and Europe DVR is the only significant risk factor for mortality in Kenya It has been suggested that sicker patients do worse in low volume institutions DVR patients are sicker so may do worse in our situation (low volume)

31 Conclusions: 1. Euroscore and ACEF score may not be valid for Kenyan patients 2. We need to develop our own local Risk stratification score

32 THANK YOU