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Record W4414941209 · doi:10.1371/journal.pone.0333580

Nutritional status and bacteremia patterns in children with diarrheal diseases: A comparative analysis of bacteremia from Salmonella Typhi versus other pathogens

2025· article· en· W4414941209 on OpenAlexfundno aff
Md. Rezaul Hossain, Monira Sarmin, Irin Parvin, Mst. Mahmuda Ackhter, Afsan Bulbul, Chidozie Declan Iwu, Mohammod Jobayer Chisti, Lubaba Shahrin

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsBacteremiaSalmonella typhiAntimicrobialSalmonellaDiarrhea

Abstract

fetched live from OpenAlex

BACKGROUND: Bacteremia remains a significant concern among under-five children with diarrheal diseases, particularly in resource-limited settings. Distribution of bacteremia patterns across the patient's nutritional status and outcomes have never been analyzed. This study aimed to investigate the association between nutritional status and bloodstream infections caused by Salmonella enterica serovar Typhi compared to other pathogenic bacteria in children with diarrheal diseases. METHODS: A retrospective case-control study was conducted using electronic medical records from icddr,b (Dhaka, Bangladesh) between 2019-20. Cases were defined as children (< 60 months) hospitalized with diarrheal disease and diagnosed with Salmonella Typhi bacteremia; controls included children with bloodstream infections caused by other than typhoidal bacteria, including Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Streptococcus spp. Nutritional status was categorized as well-nourished, Moderate Acute Malnutrition (MAM), or Severe Acute Malnutrition (SAM). Descriptive statistics and multiple logistic regression models were used to assess associations between nutritional status, bacteremia type, and clinical outcomes. RESULTS: Among 162 children with confirmed bloodstream infections, 74 (45.68%) had Salmonella Typhi bacteremia, while 88 (54.32%) had bacteremia caused by other bacterial isolates. SAM was more prevalent among children with other bacteremia (78.12%) than caused by Salmonella Typhi. Conversely, well- nourished children were more likely to develop Salmonella Typhi bacteremia (66.13%) compared to MAM (32.61%) and SAM (21.88%) cases. After adjusting for comorbidities and prior antibiotics use, logistic regression analysis found malnourished children had significantly lower odds of developing Salmonella Typhi bacteremia compared to well-nourished children (SAM: aOR 0.157, 95% CI: 0.045-0.548, p = 0.004; MAM: aOR 0.238, 95% CI: 0.089-0.640, p = 0.004). Mortality rates were significantly higher among controls (11.73%) compared to Salmonella Typhi cases (1.35%), particularly for infections caused by Klebsiella pneumoniae (66.67%) and E. coli (31.25%). CONCLUSION: Malnourished children are at higher risk for severe bloodstream infections caused by other bacterial species, leading to higher mortality rates and increased antimicrobial resistance. However, Salmonella Typhi bacteremia occurred more frequently in well-nourished children. These sort of distribution of bacteremia patterns across patients' nutritional status can provide insights and improve clinical management.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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