Predicting Hospitalised Paediatric Pneumonia Mortality Risk: An External Validation of RISC and mRISC, and Local Tool Development (RISC-Malawi) from Malawi

RESEARCH ARTICLE Predicting Hospitalised Paediatric Pneumonia Mortality Risk: An External Validation of RISC and mRISC, and Local Tool Development (RISC-Malawi) from Malawi Shubhada Hooli1,2*, Tim Colbourn3, Norman Lufesi4, Anthony Costello3, Bejoy Nambiar3, Satid Thammasitboon1, Charles Makwenda5, Charles Mwansambo4, Eric D. McCollum3,6, Carina King3* a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 1 Department of Pediatrics, Section of Critical Care Medicine, Baylor College of Medicine and Texas Children’s Hospital, Houston, United States of America, 2 Department of Pediatrics, Section of Emergency Medicine, Baylor College of Medicine and Texas Children’s Hospital, Houston, United States of America, 3 Institute for Global Health, University College London, London, United Kingdom, 4 Ministry of Health, Lilongwe, Malawi, 5 Parent and Child Health Initiative, Lilongwe, Malawi, 6 Department of Pediatrics, Division of Pulmonology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America * (SH); (CK) OPEN ACCESS Citation: Hooli S, Colbourn T, Lufesi N, Costello A, Nambiar B, Thammasitboon S, et al. (2016) Predicting Hospitalised Paediatric Pneumonia Mortality Risk: An External Validation of RISC and mRISC, and Local Tool Development (RISCMalawi) from Malawi. PLoS ONE 11(12): e0168126. doi:10.1371/journal.pone.0168126 Editor: Kevin Mortimer, Liverpool School of Tropical Medicine, UNITED KINGDOM Received: July 26, 2016 Accepted: November 24, 2016 Published: December 28, 2016 Copyright: © 2016 Hooli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: This is routine clinical data, belonging to the Malawi Ministry of Health. Therefore sharing of data must be approved by the Malawi Ministry of Health and the National Health Sciences Research Committee of Malawi. Please contact Dr. Carina King, Research Associate, University College London for data sharing requests and additional information. Funding: Funding was provided by the Bill and Melinda Gates Foundation [#23591] www. Abstract Background Pneumonia is the leading infectious cause of under-5 mortality in sub-Saharan Africa. Clinical prediction tools may aide case classification, triage, and allocation of hospital resources. We performed an external validation of two published prediction tools and compared this to a locally developed tool to identify children admitted with pneumonia at increased risk for inhospital mortality in Malawi. Methods We retrospectively analyzed the performance of the Respiratory Index of Severity in Children (RISC) and modified RISC (mRISC) scores in a child pneumonia dataset prospectively collected during routine care at seven hospitals in Malawi between 2011–2014. RISC has both an HIV-infected and HIV-uninfected tool. A local score (RISC-Malawi) was developed using multivariable logistic regression with missing data multiply imputed using chained equations. Score performances were assessed using c-statistics, sensitivity, specificity, positive predictive value, negative predictive value, and likelihood statistics. Results 16,475 in-patient pneumonia episodes were recorded (case-fatality rate (CFR): 3.2%), 9,533 with complete data (CFR: 2.0%). The c-statistic for the RISC (HIV-uninfected) score, used to assess its ability to differentiate between children who survived to discharge and those that died, was 0.72. The RISC-Malawi score, using mid-upper arm circumference as an indicator of malnutrition severity, had a c-statistic of 0.79. We were unable to perform a PLOS ONE | DOI:10.1371/journal.pone.0168126 December 28, 2016 1 / 13 Predicting Pneumonia in-Hospital Mortality in Malawi gatesfoundation.org. Funding was received by AC, TC, EDM, BN, and C Makwenda. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. comprehensive external validation of RISC (HIV-infected) and mRISC as both scores include parameters that were not routinely documented variables in our dataset. Competing Interests: The authors have declared that no competing interests exist. In our population of Malawian children with WHO-defined pneumonia, the RISC (HIV-uninfected) score identified those at high risk for in-hospital mortality. However the refinement of parameters and resultant creation of RISC-Malawi improved performance. Next steps include prospectively studying both scores to determine if incorporation into routine care delivery can have a meaningful impact on in-hospital CFRs of children with WHO-defined pneumonia. Conclusion Introduction Pneumonia is the number one cause of infectious under-5 child mortality in sub-Saharan Africa, attributed to 935,000 child deaths (14.9% of total) annually [1]. Malawi is a small landlocked country in southern Africa. Despite being one of the poorest countries in the world [2] it has achieved Millennium Development Goal (MDG) 4, a two-thirds reduction in under-5 child mortality [3]. In an effort to reduce child pneumonia mortality the Malawi Ministry of Health implemented the Child Lung Health Programme (CLHP) in 2000 [4]. The CLHP included the introduction of national clinical pneumonia diagnosis and management guidelines (adapted from the 2000 World Health Organization (WHO) guidelines) and a nationwide case report form for all children admitted to hospitals with pneumonia [5]. Although there has been an overall reduction in the pneumonia case fatality rate (CFR) since implementing the CLHP, minimal declines were seen in subpopulations of higher risk children with clinical danger signs and severe acute malnutrition [6]. Multiple factors may contribute to this lack of improvement, including case misclassification with resultant incorrect antibiotic usage [7], inconsistent adherence to guidelines [8], human resource constraints, medication stockouts [9] and lack of pulse oximetry and oxygen availability [10]. Therefore, one priority area could be the improved allocation of limited resources. Clinical prediction tools may aid case classification and be used to initiate earlier escalation of care in high-risk cases, rapid in-hospital triage for resuscitation and targeted therapies or intensive care admission. Two tools have been proposed to identify hospitalized children at risk of death due to acute respiratory illness: the Respiratory Index of Severity in Children (RISC) [11] and modified Respiratory Index of Severity in Children (mRISC) [12]. RISC was developed retrospectively from a dataset collected in Soweto, South Africa from 1998–2001 in hospitalized children aged 0–24 months enrolled in a pneumococcal conjugate vaccine (PCV) randomized controlled trial, post Haemophilus influenzae type b (Hib) vaccine introduction with known HIV diseas (...truncated)