Department of Surgical Sciences

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Browsing Department of Surgical Sciences by browse.metadata.advisor "Hesseling, P. B."

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    The development and evaluation of an outcome predictive score for a neonatal intensive care unit in South Africa
    (Stellenbosch : Stellenbosch University, 2003-12) Pieper, C. H. (Clarissa Hildegaard); Hesseling, P. B.; De Villiers, B.; Stellenbosch University. Faculty of Medicine & Health Sciences. Dept. of Paediatrics & Child Health.
    ENGLISH ABSTRACT: Background The care of children is one of the cornerstones of social philosophy. In first world countries most children survive to adulthood. In South Africa the infant mortality rate is much higher than it should be, if compared to the gross capital income per person. The ability to deliver neonatal intensive care (NIC) in South Africa has decreased in the past decade. Therefore it is necessary to choose which babies will receive care. This choice is mainly based on a birth weight (BW) of at least 1000 grams and or a gestational age (GA) of 28 weeks. The only other variable taken into consideration is antenatal care. International scoring systems, like the Clinical Risk Index for Babies (CRIB) score, have been found lacking in accuracy. Aim: The aim of this study was to devise a scoring system which could accurately predict outcome of individual patients before admission to the Neonatal ICU. Patients and methods: Data on the patients enrolled in the CRIB study (1992-1995) were collected retrospectively for the initial cohort (IC). Variables examined were: Maternal risks like age, parity, type of delivery, prolonged rupture of membranes, syphilis and socio-economic status. Neonatal risk factors like BW, GA, gender, ethnic group, ante natal visits, multiple gestations, place of birth, early or late admission to NIC and the one and five minute Apgar counts. Outcome variables examined were mortality, length of hospital stay, duration of ventilation and the development ofbroncho-pulmonary dysplasia. The scoring system was developed with data from the CRIB cohort. A prospective study obtained data for a validation cohort (VC) (1999-2002). Statistical analysis: Descriptive, parametric and non-parametric methods were used. Kaplan&Meier life tables, multivariate analysis and CART analysis were used. Results: The IC consisted of 455 babies with a mean BW of 1198g and mean GA of 30.3 weeks. The VC included 272 babies with a mean BW of 1169g and mean GA of29.8 weeks. The mean maternal income had changed from R892 in the IC to R613 in the VC. These variables were all significantly different. The mortality rate in the IC was 26.1 % and significantly less in the VC of 21.6% (p<0.05). Variables which were the most valuable in predicting outcome were the BW and GA, which were interchangeable. BW had a 63% predictive value for survival. The only outcome variable predictable was survival. BW, antenatal care, gender, place of birth and maternal income were important predictors. Maternal income of zero however nullified all other predictive variables of outcome. In the Cart analysis of the IC the most important predictors were BW > 1037g, maternal income of less than 1206 South African Rand, antenatal care and gender. Survival could be predicted in 94% of cases. In the VC the predictive accuracy was 84% with the CART analysis. The alternative CART analysis was based on place of birth (babies from outlying areas did better), BW «855g) and gender, but did not improve predictability. Discussion Babies admitted to the NICU in this study are chosen by means of non-validated variables. It remains difficult to identify a single prognosticating variable of outcome as the IC was already chosen and the variables are interdependent. Comparable results were obtained in identifying prognosticators when using different statistical methods. The ranking of the variables differed, but the most important variables were similar. Variables currently used to restrict access to the ICU like poor antenatal care and delivery in a peripheral hospital, are no longer justifiable, because babies with these variables did not have a poorer survival rate in this study. A birth weight of more than 855g has the same survival chance as a baby of 1001 grams, which is the current norm for admission. In conclusion, a method by means of the CART analysis was devised that can predict individual survival by 84% or more which is much better than the 63% achieved by using BW.