Characterising paediatric mortality during and after acute illness in Sub-Saharan Africa and South Asia: a secondary analysis of the CHAIN cohort using a machine learning approach

Diallo, Abdoulaye Hama; Shahid, Abu Sadat Mohammad Sayeem Bin; Khan, Azharul Islam; Saleem, Ali Faisal; Singa, Benson; Gnoumou, Blaise Siezanga; Tigoi, Caroline; Otieno, Catherine Achieng; Bourdon, Céline; Oduol, Chris Odhiambo; Lancioni, Christina; Manyasi, Christine; McGrath, Christine J.; Maronga, Christopher; Lwanga, Christopher; Brals, Daniëlla; Ahmed, Dilruba; Mondal, Dinesh; Denno, Donna M.; Mangale, Dorothy I.; Chimezi, Emmanuel; Mbale, Emmie; Mupere, Ezekiel; Mamun, Gazi Md. Salahuddin; Ouédraogo, Issaka; Githinji, George; Berkley, James A.; Njirammadzi, Jenala; Mukisa, John; Thitiri, Johnstone; Häggström, Jonas; Carreon, Joseph D.; Walson, Judd L.; Jemutai, Julie; Tickell, Kirkby D; Shahrin, Lubaba; Mallewa, Macpherson; Hossain, Md. Iqbal; Chisti, Mohammod Jobayer; Timbwa, Molly; Mburu, Moses; Ngari, Moses; Ngao, Narshion; Aber, Peace; Harawa, Philliness Prisca; Sukhtankar, Priya; Bandsma, Robert; Bamouni, Roseline Maimouna; Molyneux, Sassy; Feldman, Sergey; Mwaringa, Shalton; Shaima, Shamsun Nahar; Ali, Syed Asad; Afsana, Syeda Momena; Banu, Syera; Ahmed, Tahmeed; Voskuijl, Wieger; Kazi, Zaubina

doi:10.1016/j.eclinm.2023.101838

Cited by 7 publications

(3 citation statements)

References 21 publications

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“…The use of MUAC as a key predictor in risk of death is also supported by a recent prospective cohort study (CHAIN) of children 2–23 months of age who presented to care for acute illness in 6 LMICs. The authors found that nutritional status was directly associated with death 30 days from admission, capturing a range of underlying risks [ 6 ], and that MUAC was a top predictor of death [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Ahmed

Brintz

Talbert

et al. 2023

PLOS Glob Public Health

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Diarrhea continues to be a leading cause of death for children under-five. Amongst children treated for acute diarrhea, mortality risk remains elevated during and after acute medical management. Identification of those at highest risk would enable better targeting of interventions, but available prognostic tools lack validation. We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build clinical prognostic models (CPMs) to predict death (in-treatment, after discharge, or either) in children aged ≤59 months presenting with moderate-to-severe diarrhea (MSD), in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using repeated cross-validation. We used data from the Kilifi Health and Demographic Surveillance System (KHDSS) and Kilifi County Hospital (KCH) in Kenya to externally validate our GEMS-derived CPM. Of 8060 MSD cases, 43 (0.5%) children died in treatment and 122 (1.5% of remaining) died after discharge. MUAC at presentation, respiratory rate, age, temperature, number of days with diarrhea at presentation, number of people living in household, number of children <60 months old living in household, and how much the child had been offered to drink since diarrhea started were predictive of death both in treatment and after discharge. Using a parsimonious 2-variable prediction model, we achieved an area under the ROC curve (AUC) of 0.84 (95% CI: 0.82, 0.86) in the derivation dataset, and an AUC = 0.74 (95% CI 0.71, 0.77) in the external dataset. Our findings suggest it is possible to identify children most likely to die after presenting to care for acute diarrhea. This could represent a novel and cost-effective way to target resources for the prevention of childhood mortality.

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Section: Discussionmentioning

confidence: 99%

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Ahmed

Brintz

Talbert

et al. 2023

PLOS Glob Public Health

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“…Abiodun et al 98 found decreased levels of alpha 2 HS-glycoprotein were associated with decreased ALP levels. Bandsma et al 99 observed that subnormal ALP levels in severely malnourished children were related to the degree of hypoalbuminemia. 99…”

Section: Conditions Associated With Subnormal Alp Levelsmentioning

confidence: 99%

“…Bandsma et al 99 observed that subnormal ALP levels in severely malnourished children were related to the degree of hypoalbuminemia. 99…”

Section: Conditions Associated With Subnormal Alp Levelsmentioning

confidence: 99%

Subnormal Serum Liver Enzyme Levels: A Review of Pathophysiology and Clinical Significance

Youssef,

2024

J Clin Transl Hepatol

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Subnormal levels of liver enzymes, below the lower limit of normal on local laboratory reports, can be useful diagnostically. For instance, subnormal levels of aminotransferases can be observed in vitamin B 6 deficiency and chronic kidney disease. Subnormal alkaline phosphatase levels may indicate the presence of hypophosphatasia, Wilson’s disease, deficiencies of divalent ions, or malnutrition. Subnormal levels of gamma glutamyl transferase may be seen in cases of acute intrahepatic cholestasis, the use of certain medications, and in bone disease. Finally, subnormal levels of 5′-nucleotidase have been reported in lead poisoning and nonspherocytic hemolytic anemia. The aim of this review is to bring attention to the fact that subnormal levels of these enzymes should not be ignored as they may indicate pathological conditions and provide a means of early diagnosis.

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Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Ahmed

Brintz

Talbert

et al. 2023

Preprint

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Diarrhea continues to be a leading cause of death for children under-five. Amongst children treated for acute diarrhea, mortality risk remains elevated during and after acute medical management. Identification of those at highest risk would enable better targeting of interventions, but available prognostic tools lack validation. We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build predictive models for death (in-treatment, after discharge, or either) in children aged ≤59 months presenting with moderate-to-severe diarrhea (MSD), in Africa and Asia. We screened variables using random forests, and assessed predictive performance with random forest regression and logistic regression using repeated cross-validation. We used data from the Kilifi Health and Demographic Surveillance System (KHDSS) and Kilifi County Hospital (KCH) in Kenya to externally validate our GEMS-derived clinical prognostic model (CPM). Of 8060 MSD cases, 43 (0.5%) children died in treatment and 122 (1.5% of remaining) died after discharge. MUAC at presentation, respiratory rate, age, temperature, number of days with diarrhea at presentation, number of people living in household, number of children <60 months old living in household, and how much the child had been offered to drink since diarrhea started were predictive of death both in treatment and after discharge. Using a parsimonious 2-variable prediction model, we achieve an AUC=0.84 (95% CI: 0.82, 0.86) in the derivation dataset, and an AUC=0.74 (95% CI 0.71, 0.77) in the external dataset. Our findings suggest it is possible to identify children most likely to die after presenting to care for acute diarrhea. This could represent a novel and cost-effective way to target resources for the prevention of childhood mortality.

show abstract

Characterising paediatric mortality during and after acute illness in Sub-Saharan Africa and South Asia: a secondary analysis of the CHAIN cohort using a machine learning approach

Cited by 7 publications

References 21 publications

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

Subnormal Serum Liver Enzyme Levels: A Review of Pathophysiology and Clinical Significance

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care

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