Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care.
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 pro...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-01-01
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| Series: | PLOS Global Public Health |
| Online Access: | https://doi.org/10.1371/journal.pgph.0001937 |
| _version_ | 1827829606371033088 |
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| author | Sharia M Ahmed Ben J Brintz Alison Talbert Moses Ngari Patricia B Pavlinac James A Platts-Mills Adam C Levine Eric J Nelson Judd L Walson Karen L Kotloff James A Berkley Daniel T Leung |
| author_facet | Sharia M Ahmed Ben J Brintz Alison Talbert Moses Ngari Patricia B Pavlinac James A Platts-Mills Adam C Levine Eric J Nelson Judd L Walson Karen L Kotloff James A Berkley Daniel T Leung |
| author_sort | Sharia M Ahmed |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T04:07:03Z |
| format | Article |
| id | doaj.art-ad260ec47b144a6cb7f2fecbf7e4f479 |
| institution | Directory Open Access Journal |
| issn | 2767-3375 |
| language | English |
| last_indexed | 2024-03-12T04:07:03Z |
| publishDate | 2023-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLOS Global Public Health |
| spelling | doaj.art-ad260ec47b144a6cb7f2fecbf7e4f4792023-09-03T11:15:14ZengPublic Library of Science (PLoS)PLOS Global Public Health2767-33752023-01-0136e000193710.1371/journal.pgph.0001937Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care.Sharia M AhmedBen J BrintzAlison TalbertMoses NgariPatricia B PavlinacJames A Platts-MillsAdam C LevineEric J NelsonJudd L WalsonKaren L KotloffJames A BerkleyDaniel T LeungDiarrhea 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.https://doi.org/10.1371/journal.pgph.0001937 |
| spellingShingle | Sharia M Ahmed Ben J Brintz Alison Talbert Moses Ngari Patricia B Pavlinac James A Platts-Mills Adam C Levine Eric J Nelson Judd L Walson Karen L Kotloff James A Berkley Daniel T Leung Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care. PLOS Global Public Health |
| title | Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care. |
| title_full | Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care. |
| title_fullStr | Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care. |
| title_full_unstemmed | Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care. |
| title_short | Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care. |
| title_sort | derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care |
| url | https://doi.org/10.1371/journal.pgph.0001937 |
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