Evidence map›Paper›PMID 29129186›Full record

ArticleBMC medicine2017

An exploration of mortality risk factors in non-severe pneumonia in children using clinical data from Kenya.

Timothy Tuti, Ambrose Agweyu, Paul Mwaniki, Niels Peek, Mike English, Clinical Information Network Author Group

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.

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  9. Heightened Local TMediators of inflammation · 2021
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  13. CLINICAL PROFILE OF CHILDREN WITH AND WITHOUT COMORBIDITIES HOSPITALIZED WITH COMMUNITY-ACQUIRED PNEUMONIA.Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo · 2020
    Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Timothy TutiKEMRI - Wellcome Trust Research Programme, Nairobi, Kenya. TTuti@kemri-wellcome.org.ORCID 0000-0002-7915-3004
Ambrose AgweyuKEMRI - Wellcome Trust Research Programme, Nairobi, Kenya.
Paul MwanikiKEMRI - Wellcome Trust Research Programme, Nairobi, Kenya.
Niels PeekCentre for Health Informatics, Division of Informatics, Imaging & Data Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Mike EnglishKEMRI - Wellcome Trust Research Programme, Nairobi, Kenya.
Clinical Information Network Author Group
Kenya Medical Research Institute · KEManchester Academic Health Science Centre · GB

Funding

Wellcome Trust 097170Wellcome Trust 106823Wellcome Trust 203077
6 · The paper itself

Abstract

backgroundChildhood pneumonia is the leading infectious cause of mortality in children younger than 5 years old. Recent updates to World Health Organization pneumonia guidelines recommend outpatient care for a population of children previously classified as high risk. This revision has been challenged by policymakers in Africa, where mortality related to pneumonia is higher than in other regions and often complicated by comorbidities. This study aimed to identify factors that best discriminate inpatient mortality risk in non-severe pneumonia and explore whether these factors offer any added benefit over the current criteria used to identify children with pneumonia requiring inpatient care.

methodsWe undertook a retrospective cohort study of children aged 2-59 months admitted with a clinical diagnosis of pneumonia at 14 public hospitals in Kenya between February 2014 and February 2016. Using machine learning techniques, we analysed whether clinical characteristics and common comorbidities increased the risk of inpatient mortality for non-severe pneumonia. The topmost risk factors were subjected to decision curve analysis to explore if using them as admission criteria had any net benefit above the current criteria.

resultsOut of 16,162 children admitted with pneumonia during the study period, 10,687 were eligible for subsequent analysis. Inpatient mortality within this non-severe group was 252/10,687 (2.36%). Models demonstrated moderately good performance; the partial least squares discriminant analysis model had higher sensitivity for predicting mortality in comparison to logistic regression. Elevated respiratory rate (≥70 bpm), age 2-11 months and weight-for-age Z-score (WAZ) < -3SD were highly discriminative of mortality. These factors ranked consistently across the different models. For a risk threshold probability of 7-14%, there is a net benefit to admitting the patient sub-populations with these features as additional criteria alongside those currently used to classify severe pneumonia. Of the population studied, 70.54% met at least one of these criteria. Sensitivity analyses indicated that the overall results were not significantly affected by variations in pneumonia severity classification criteria.

conclusionsChildren with non-severe pneumonia aged 2-11 months or with respiratory rate ≥ 70 bpm or very low WAZ experience risks of inpatient mortality comparable to severe pneumonia. Inpatient care is warranted in these high-risk groups of children.

Indexed as

Child, PreschoolCohort StudiesFemaleHumansInfantKenyaMalePneumoniaRetrospective StudiesRisk FactorsSurvival AnalysisDecision support techniquesGuidelinesMachine learningPediatricsPneumoniaRisk factors

Identifiers

PMID29129186
PMCPMC5682642
OpenAlexW2767669634

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.