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Record W3109838332 · doi:10.1371/journal.pone.0243128

Clinical and laboratory characteristics of children under five hospitalized with diarrhea and bacteremia

2020· article· en· W3109838332 on OpenAlexfundno aff
K. M. Shahunja, Tahmeed Ahmed, Md Iqbal Hossain, Md Munirul Islam, Mahmuda Monjory, Abu Sadat Mohammad Sayeem Bin Shahid, Abu Syed Golam Faruque, Mohammod Jobayer Chisti

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
FundersGlobal Affairs CanadaDepartment for International DevelopmentInternational Centre for Diarrhoeal Disease Research, BangladeshStyrelsen för Internationellt Utvecklingssamarbete
KeywordsBacteremiaMedicineDiarrheaGentamicinCeftriaxoneAmpicillinInternal medicineKlebsiellaPediatricsAntibioticsMicrobiologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Diarrhea is one of the leading causes of mortality in children under five globally. When it is associated with bacteremia, mortality is even higher. However, bacteraemia in diarrheal children has gained little attention in spite of its deleterious impact in under-five mortality. So, we aimed to evaluate associated clinical and laboratory factors for death in under-five children hospitalized with both diarrhea and bacteremia. METHODS: In this retrospective cross-sectional study, we used patients' electronic database of Dhaka Hospital of 'icddr,b', and enrolled all under-five children with diarrhea and bacterial growth in their blood samples on admission between June-2014 and May-2017. Clinical and laboratory characteristics were compared between those who died and who survived with a special attention to bacterial pathogens related to deaths and their sensitivity pattern. RESULTS: In a total of 401 diarrheal children with bacteraemia, 45 (11%) died. Although Salmonella Typhi (34%) was the most predominant isolate followed by Staphylococcus species (16%) and Pseudomonas species (9%), children who died more often had E. coli (OR = 5.69, 95% CI = 2.42-13.39, p = <0.001) and Klebsiella bacteraemia (OR = 4.59, 95% CI = 1.84-11.46, p = 0.001) compared to those who survived. However, none of them was significantly associated with deaths in regression analysis when adjusted with other potential confounders. E. coli was 100% resistant to ampicillin, 41% to gentamicin, and 73% to ceftriaxone and Klebsiella species was 96% resistant to ampicillin, 42% to gentamicin, and 62% to ceftriaxone. Study children who died had significantly higher overall resistance pattern shown in World Health Organization (WHO) recommended one of the first line antibiotics in treating childhood sepsis such as ampicillin (80% vs. 50%, p = 0.001) and in second line antibiotic such as ceftriaxone (49% vs. 22%, p = 0.001) compared to the survivors. In logistic regression analysis, after adjusting for potential confounders, we found that clinical sepsis (aOR 3.79, 95% CI 1.60-8.96, p = 0.002), hypoxemia (aOR 4.20, 95% CI 1.74-10.12, p = 0.001), and hyperkalaemia (aOR 2.69, 95% CI 1.05-6.91, p = 0.039) were found to be independent predictors of deaths and receipt of sensitive antibiotic (aOR 0.42, 95% CI 0.18-0.99, p = 0.048) was revealed as the independent protective factor for deaths in this population. CONCLUSION AND SIGNIFICANCE: The results of our data suggest that diarrheal children with bacteremia who died more often had gram negative bacteremia compared to those who survived and these pathogens are highly resistant to WHO recommended first line and second line antibiotics. The results further emphasize the critical importance of early identification of important clinical problems such as clinical sepsis, hypoxemia and hyperkalaemia in diarrheal children and treat them with potential sensitive antibiotic(s) in order to reduce bacteremia related mortality in children with diarrhea, especially in resource limited settings.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.295
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2020
Admission routes1
Has abstractyes

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