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

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. 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. 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.

Post-mortem investigation of deaths due to pneumonia in children aged 1-59 months in sub-Saharan Africa and South Asia from 2016 to 2022: an observational study.

BACKGROUND: The Child Health and Mortality Prevention Surveillance (CHAMPS) Network programme undertakes post-mortem minimally invasive tissue sampling (MITS), together with collection of ante-mortem clinical information, to investigate causes of childhood deaths across multiple countries. We aimed to evaluate the overall contribution of pneumonia in the causal pathway to death and the causative pathogens of fatal pneumonia in children aged 1-59 months enrolled in the CHAMPS Network. METHODS: In this observational study we analysed deaths occurring between Dec 16, 2016, and Dec 31, 2022, in the CHAMPS Network across six countries in sub-Saharan Africa (Ethiopia, Kenya, Mali, Mozambique, Sierra Leone, and South Africa) and one in South Asia (Bangladesh). A standardised approach of MITS was undertaken on decedents within 24-72 h of death. Diagnostic tests included blood culture, multi-organism targeted nucleic acid amplifications tests (NAATs) of blood and lung tissue, and histopathology examination of various organ tissue samples. An interdisciplinary expert panel at each site reviewed case data to attribute the cause of death and pathogenesis thereof on the basis of WHO-recommended reporting standards. FINDINGS: Pneumonia was attributed in the causal pathway of death in 455 (40·6%) of 1120 decedents, with a median age at death of 9 (IQR 4-19) months. Causative pathogens were identified in 377 (82·9%) of 455 pneumonia deaths, and multiple pathogens were implicated in 218 (57·8%) of 377 deaths. 306 (67·3%) of 455 deaths occurred in the community or within 72 h of hospital admission (presumed to be community-acquired pneumonia), with the leading bacterial pathogens being Streptococcus pneumoniae (108 [35·3%]), Klebsiella pneumoniae (78 [25·5%]), and non-typeable Haemophilus influenzae (37 [12·1%]). 149 (32·7%) deaths occurred 72 h or more after hospital admission (presumed to be hospital-acquired pneumonia), with the most common pathogens being K pneumoniae (64 [43·0%]), Acinetobacter baumannii (19 [12·8%]), S pneumoniae (15 [10·1%]), and Pseudomonas aeruginosa (15 [10·1%]). Overall, viruses were implicated in 145 (31·9%) of 455 pneumonia-related deaths, including 54 (11·9%) of 455 attributed to cytomegalovirus and 29 (6·4%) of 455 attributed to respiratory syncytial virus. INTERPRETATION: Pneumonia contributed to 40·6% of all childhood deaths in this analysis. The use of post-mortem MITS enabled biological ascertainment of the cause of death in the majority (82·9%) of childhood deaths attributed to pneumonia, with more than one pathogen being commonly implicated in the same case. The prominent role of K pneumoniae, non-typable H influenzae, and S pneumoniae highlight the need to review empirical management guidelines for management of very severe pneumonia in low-income and middle-income settings, and the need for research into new or improved vaccines against these pathogens. FUNDING: Bill & Melinda Gates Foundation.

Comparison of logistic regression with regularized machine learning methods for the prediction of tuberculosis disease in people living with HIV: cross-sectional hospital-based study in Kisumu County, Kenya.

Background: Tuberculosis (TB) is a major public health concern, particularly among people living with the Human immunodeficiency Virus (PLWH). Accurate prediction of TB disease in this population is crucial for early diagnosis and effective treatment. Logistic regression and regularized machine learning methods have been used to predict TB, but their comparative performance in HIV patients remains unclear. The study aims to compare the predictive performance of logistic regression with that of regularized machine learning methods for TB disease in HIV patients. Methods: Retrospective analysis of data from HIV patients diagnosed with TB in three hospitals in Kisumu County (JOOTRH, Kisumu sub-county hospital, Lumumba health center) between [dates]. Logistic regression, Lasso, Ridge, Elastic net regression were used to develop predictive models for TB disease. Model performance was evaluated using accuracy, and area under the receiver operating characteristic curve (AUC-ROC). Results: Of the 927 PLWH included in the study, 107 (12.6%) were diagnosed with TB. Being in WHO disease stage III/IV (aOR: 7.13; 95%CI: 3.86-13.33) and having a cough in the last 4 weeks (aOR: 2.34;95%CI: 1.43-3.89) were significant associated with the TB. Logistic regression achieved accuracy of 0.868, and AUC-ROC of 0.744. Elastic net regression also showed good predictive performance with accuracy, and AUC-ROC values of 0.874 and 0.762, respectively. Conclusions: Our results suggest that logistic regression, Lasso, Ridge regression, and Elastic net can all be effective methods for predicting TB disease in HIV patients. These findings may have important implications for the development of accurate and reliable models for TB prediction in HIV patients.

Impact of anthropometry training and feasibility of 3D imaging on anthropometry data quality among children under five years in a postmortem setting.

BACKGROUND: The Child Health and Mortality Prevention Surveillance Network (CHAMPS) identifies causes of under-5 mortality in high mortality countries. OBJECTIVE: To address challenges in postmortem nutritional assessment, we evaluated the impact of anthropometry training and the feasibility of 3D imaging on data quality within the CHAMPS Kenya site. DESIGN: Staff were trained using World Health Organization (WHO)-recommended manual anthropometry equipment and novel 3D imaging methods to collect postmortem measurements. Following training, 76 deceased children were measured in duplicate and were compared to measurements of 75 pre-training deceased children. Outcomes included measures of data quality (standard deviations of anthropometric indices and digit preference scores (DPS)), precision (absolute and relative technical errors of measurement, TEMs or rTEMs), and accuracy (Bland-Altman plots). WHO growth standards were used to produce anthropometric indices. Post-training surveys and in-depth interviews collected qualitative feedback on measurer experience with performing manual anthropometry and ease of using 3D imaging software. RESULTS: Manual anthropometry data quality improved after training, as indicated by DPS. Standard deviations of anthropometric indices exceeded limits for high data quality when using the WHO growth standards. Reliability of measurements post-training was high as indicated by rTEMs below 1.5%. 3D imaging was highly correlated with manual measurements; however, on average 3D scans overestimated length and head circumference by 1.61 cm and 2.27 cm, respectively. Site staff preferred manual anthropometry to 3D imaging, as the imaging technology required adequate lighting and additional considerations when performing the measurements. CONCLUSIONS: Manual anthropometry was feasible and reliable postmortem in the presence of rigor mortis. 3D imaging may be an accurate alternative to manual anthropometry, but technology adjustments are needed to ensure accuracy and usability.

Prevalence and Missed Cases of Respiratory Distress Syndrome Disease Amongst Neonatal Deaths Enrolled in the Kenya Child Health and Mortality Prevention Surveillance Network (CHAMPS) Program Between 2017 and 2021.

Objectives. To describe RDS in neonatal deaths at the CHAMPS-Kenya site between 2017 and 2021. Methods. We included 165 neonatal deaths whose their Causes of death (COD) were determined by a panel of experts using data from post-mortem conducted through minimally invasive tissue specimen testing, clinical records, and verbal autopsy. Results. Twenty-six percent (43/165) of neonatal deaths were attributable to RDS. Most cases occurred in low birthweight and preterm neonates. From these cases, less than half of the hospitalizations were diagnosed with RDS before death, and essential diagnostic tests were not performed in most cases. Most cases received suboptimal levels of supplemental oxygen, and critical interventions like surfactant replacement therapy and mechanical ventilation were not adequately utilized when available. Conclusion. The study highlights the urgent need for improved diagnosis and management of RDS, emphasizing the importance of increasing clinical suspicion and enhancing training in its clinical management to reduce mortality rates.

Performance of Xpert MTB/RIF and Mycobacterial Culture on Multiple Specimen Types for Diagnosis of Tuberculosis Disease in Young Children and Clinical Characterization According to Standardized Research Case Definitions.

BACKGROUND: Tuberculosis (TB) is a leading cause of illness and death in children globally. Improved bacteriologic and clinical diagnostic approaches in children are urgently needed. METHODS: In a prospective cohort study, a consecutive series of young (<5 years) children presenting with symptoms suggestive of TB and parenchymal abnormality on chest radiograph in inpatient and outpatient settings in Kisumu County, Kenya from October 2013 to August 2015 were evaluated at baseline and over 6 months. Up to 14 specimens per child were tested for the Mycobacterium tuberculosis complex by fluorescence microscopy, Xpert MTB/RIF and mycobacterial culture. Using detailed clinical characterization, cases were retrospectively classified according to standardized research case definitions and the sensitivity and specificity of microbiological tests on different specimen types were determined. RESULTS: Among 300 young children enrolled, 266 had sufficient information to be classified according to the research clinical case definition. Of these, 36% (96/266) had TB disease; 32% (31/96) with bacteriologically confirmed intrathoracic TB. Compared to culture, the sensitivity of a single Xpert test ranged from 60 to 67% and specificity from 97.5 to 100% for different specimen types. CONCLUSIONS: Despite extensive specimen collection and laboratory testing, TB could not be bacteriologically confirmed in almost two-thirds of children with intrathoracic TB classified by research clinical case definitions. Improved diagnostic tests are needed to identify children with TB and to exclude other potential causes of illness.

Sensitive and Feasible Specimen Collection and Testing Strategies for Diagnosing Tuberculosis in Young Children.

Importance: Criterion-standard specimens for tuberculosis diagnosis in young children, gastric aspirate (GA) and induced sputum, are invasive and rarely collected in resource-limited settings. A far less invasive approach to tuberculosis diagnostic testing in children younger than 5 years as sensitive as current reference standards is important to identify. Objective: To characterize the sensitivity of preferably minimally invasive specimen and assay combinations relative to maximum observed yield from all specimens and assays combined. Design, Setting, and Participants: In this prospective cross-sectional diagnostic study, the reference standard was a panel of up to 2 samples of each of 6 specimen types tested for Mycobacterium tuberculosis complex by Xpert MTB/RIF assay and mycobacteria growth indicator tube culture. Multiple different combinations of specimens and tests were evaluated as index tests. A consecutive series of children was recruited from inpatient and outpatient settings in Kisumu County, Kenya, between October 2013 and August 2015. Participants were children younger than 5 years who had symptoms of tuberculosis (unexplained cough, fever, malnutrition) and parenchymal abnormality on chest radiography or who had cervical lymphadenopathy. Children with 1 or more evaluable specimen for 4 or more primary study specimen types were included in the analysis. Data were analyzed from February 2015 to October 2020. Main Outcomes and Measures: Cumulative and incremental diagnostic yield of combinations of specimen types and tests relative to the maximum observed yield. Results: Of the 300 enrolled children, the median (interquartile range) age was 2.0 (1.0-3.6) years, and 151 (50.3%) were female. A total of 294 met criteria for analysis. Of 31 participants with confirmed tuberculosis (maximum observed yield), 24 (sensitivity, 77%; interdecile range, 68%-87%) had positive results on up to 2 GA samples and 20 (sensitivity, 64%; interdecile range, 53%-76%) had positive test results on up to 2 induced sputum samples. The yields of 2 nasopharyngeal aspirate (NPA) samples (23 of 31 [sensitivity, 74%; interdecile range, 64%-84%]), of 1 NPA sample and 1 stool sample (22 of 31 [sensitivity, 71%; interdecile range, 60%-81%]), or of 1 NPA sample and 1 urine sample (21.5 of 31 [sensitivity, 69%; interdecile range, 58%-80%]) were similar to reference-standard specimens. Combining up to 2 each of GA and NPA samples had an average yield of 90% (28 of 31). Conclusions and Relevance: NPA, in duplicate or in combination with stool or urine specimens, was readily obtainable and had diagnostic yield comparable with reference-standard specimens. This combination could improve tuberculosis diagnosis among children in resource-limited settings. Combining GA and NPA had greater yield than that of the current reference standards and may be useful in certain clinical and research settings.