Predicting mortality in sick African children: the FEAST Paediatric Emergency Triage (PET) Score

Abstract

Background: Mortality in paediatric emergency care units in Africa often occurs within the first 24 h of admission and remains high. Alongside effective triage systems, a practical clinical bedside risk score to identify those at greatest risk could contribute to reducing mortality.

Methods: Data collected during the Fluid As Expansive Supportive Therapy (FEAST) trial, a multi-centre trial involving 3,170 severely ill African children, were analysed to identify clinical and laboratory prognostic factors for mortality. Multivariable Cox regression was used to build a model in this derivation dataset based on clinical parameters that could be quickly and easily assessed at the bedside. A score developed from the model coefficients was externally validated in two admissions datasets from Kilifi District Hospital, Kenya, and compared to published risk scores using Area Under the Receiver Operating Curve (AUROC) and Hosmer-Lemeshow tests. The Net Reclassification Index (NRI) was used to identify additional laboratory prognostic factors.

Results: A risk score using 8 clinical variables (temperature, heart rate, capillary refill time, conscious level, severe pallor, respiratory distress, lung crepitations, and weak pulse volume) was developed. The score ranged from 0-10 and had an AUROC of 0.82 (95 % CI, 0.77-0.87) in the FEAST trial derivation set. In the independent validation datasets, the score had an AUROC of 0.77 (95 % CI, 0.72-0.82) amongst admissions to a paediatric high dependency ward and 0.86 (95 % CI, 0.82-0.89) amongst general paediatric admissions. This discriminative ability was similar to, or better than other risk scores in the validation datasets. NRI identified lactate, blood urea nitrogen, and pH to be important prognostic laboratory variables that could add information to the clinical score.

Conclusions: Eight clinical prognostic factors that could be rapidly assessed by healthcare staff for triage were combined to create the FEAST Paediatric Emergency Triage (PET) score and externally validated. The score discriminated those at highest risk of fatal outcome at the point of hospital admission and compared well to other published risk scores. Further laboratory tests were also identified as prognostic factors which could be added if resources were available or as indices of severity for comparison between centres in future research studies.

Fig. 1

Plots of the relationship between haemoglobin and lactate and mortality estimated from the adjusted Cox regression model. a Contour plot of mortality risk by baseline haemoglobin and lactate estimated from Cox regression model. This shows in contrast to risk uniformly increasing with increasing lactate and uniformly decreasing with haemoglobin as might have been expected, we have observed increased risk (green to red) when haemoglobin is increasing and lactate is increasing relative to an average child enrolled who had a lactate of 5 mmol/L and a haemoglobin of 7 g/dL. b Scatter plot of observed baseline haemoglobin and lactate values

Fig. 2

Receiver operating characteristic curves for the FEAST PET score in (a) the Kilifi high dependency unit and (b) the Kilifi general admissions dataset

Fig. 3

Discriminatory ability of different scores when applied to data from FEAST and Kilifi