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Postmortem investigations and identification of multiple causes of child deaths: An analysis of findings from the Child Health and Mortality Prevention Surveillance (CHAMPS) network.

Authors :
Breiman RF
Blau DM
Mutevedzi P
Akelo V
Mandomando I
Ogbuanu IU
Sow SO
Madrid L
El Arifeen S
Garel M
Thwala NB
Onyango D
Sitoe A
Bassey IA
Keita AM
Alemu A
Alam M
Mahtab S
Gethi D
Varo R
Ojulong J
Samura S
Mehta A
Ibrahim AM
Rahman A
Vitorino P
Baillie VL
Agaya J
Tapia MD
Assefa N
Chowdhury AI
Scott JAG
Gurley ES
Kotloff KL
Jambai A
Bassat Q
Tippett-Barr BA
Madhi SA
Whitney CG
Source :
PLoS medicine [PLoS Med] 2021 Sep 30; Vol. 18 (9), pp. e1003814. Date of Electronic Publication: 2021 Sep 30 (Print Publication: 2021).
Publication Year :
2021

Abstract

Background: The current burden of >5 million deaths yearly is the focus of the Sustainable Development Goal (SDG) to end preventable deaths of newborns and children under 5 years old by 2030. To accelerate progression toward this goal, data are needed that accurately quantify the leading causes of death, so that interventions can target the common causes. By adding postmortem pathology and microbiology studies to other available data, the Child Health and Mortality Prevention Surveillance (CHAMPS) network provides comprehensive evaluations of conditions leading to death, in contrast to standard methods that rely on data from medical records and verbal autopsy and report only a single underlying condition. We analyzed CHAMPS data to characterize the value of considering multiple causes of death.<br />Methods and Findings: We examined deaths identified from December 2016 through November 2020 from 7 CHAMPS sites (in Bangladesh, Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa), including 741 neonatal, 278 infant, and 241 child <5 years deaths for which results from Determination of Cause of Death (DeCoDe) panels were complete. DeCoDe panelists included all conditions in the causal chain according to the ICD-10 guidelines and assessed if prevention or effective management of the condition would have prevented the death. We analyzed the distribution of all conditions listed as causal, including underlying, antecedent, and immediate causes of death. Among 1,232 deaths with an underlying condition determined, we found a range of 0 to 6 (mean 1.5, IQR 0 to 2) additional conditions in the causal chain leading to death. While pathology provides very helpful clues, we cannot always be certain that conditions identified led to death or occurred in an agonal stage of death. For neonates, preterm birth complications (most commonly respiratory distress syndrome) were the most common underlying condition (n = 282, 38%); among those with preterm birth complications, 256 (91%) had additional conditions in causal chains, including 184 (65%) with a different preterm birth complication, 128 (45%) with neonatal sepsis, 69 (24%) with lower respiratory infection (LRI), 60 (21%) with meningitis, and 25 (9%) with perinatal asphyxia/hypoxia. Of the 278 infant deaths, 212 (79%) had ≥1 additional cause of death (CoD) beyond the underlying cause. The 2 most common underlying conditions in infants were malnutrition and congenital birth defects; LRI and sepsis were the most common additional conditions in causal chains, each accounting for approximately half of deaths with either underlying condition. Of the 241 child deaths, 178 (75%) had ≥1 additional condition. Among 46 child deaths with malnutrition as the underlying condition, all had ≥1 other condition in the causal chain, most commonly sepsis, followed by LRI, malaria, and diarrheal disease. Including all positions in the causal chain for neonatal deaths resulted in 19-fold and 11-fold increases in attributable roles for meningitis and LRI, respectively. For infant deaths, the proportion caused by meningitis and sepsis increased by 16-fold and 11-fold, respectively; for child deaths, sepsis and LRI are increased 12-fold and 10-fold, respectively. While comprehensive CoD determinations were done for a substantial number of deaths, there is potential for bias regarding which deaths in surveillance areas underwent minimally invasive tissue sampling (MITS), potentially reducing representativeness of findings.<br />Conclusions: Including conditions that appear anywhere in the causal chain, rather than considering underlying condition alone, markedly changed the proportion of deaths attributed to various diagnoses, especially LRI, sepsis, and meningitis. While CHAMPS methods cannot determine when 2 conditions cause death independently or may be synergistic, our findings suggest that considering the chain of events leading to death can better guide research and prevention priorities aimed at reducing child deaths.<br />Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: QB, a co-author of this paper is also a Guest Editor on this special issue on Global Child Health: From Birth to Adolescence and Beyond. QB was not directly involved in editorial decisions regarding this paper. JAGS reports current funding for other projects to his institution (London School of Hygiene & Tropical Medicine) from the UK Medical Research Council, Wellcome Trust, Gavi, Bill & Melinda Gates Foundation, and the UK National Institute for Health Research.

Details

Language :
English
ISSN :
1549-1676
Volume :
18
Issue :
9
Database :
MEDLINE
Journal :
PLoS medicine
Publication Type :
Academic Journal
Accession number :
34591862
Full Text :
https://doi.org/10.1371/journal.pmed.1003814