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

BMC Medicine

Abdel G. Babiker³  Kathryn Maitland⁸  Diana M. Gibb³  Jane Crawley⁹  Michael Levin⁸  Ayub Mpoya²  James A. Berkley²  Hugh Reyburn¹  George Mtove¹  Richard Nyeko⁴  Samuel O. Akech²  Charles Engoru⁷  Robert O. Opoka⁵  Peter Olupot-Olupot⁶  Sarah Kiguli⁵  A. Sarah Walker³  Elizabeth C. George³ 

[1] Department of Paediatrics, Joint Malaria Programme, Teule Hospital, Muheza, Tanzania;Kilifi Clinical Trials Facility, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya;Medical Research Council Clinical Trials Unit (MRC CTU) at UCL, London, UK;Department of Paediatrics, St Mary’s Hospital, Lacor, Uganda;Department of Paediatrics, Mulago Hospital, Makerere University, Kampala, Uganda;Department of Paediatrics, Mbale Regional Referral Hospital, Mbale, Uganda;Department of Paediatrics, Soroti Regional Referral Hospital, Soroti, Uganda;Wellcome Trust Centre for Clinical Tropical Medicine and Department of Paediatrics, Faculty of Medicine, Imperial College, London, UK;Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

关键词: Risk score;    Mortality;    FEAST trial;    Children;    Africa;   

Others  :  1221508
DOI  :  10.1186/s12916-015-0407-3

 received in 2015-04-01, accepted in 2015-06-23,  发布年份 2015

【 摘 要 】

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.

【 授权许可】

   
2015 George et al.

【 图 表 】

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