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The association between nutritional status and mortality in critically ill children admitted to the pediatric intensive care unit (1024.11)

2014· article· en· W1576128045 on OpenAlexaff
Lori J. Bechard, Christopher Duggan, Riva Touger‐Decker, J. Scott Parrott, Pamela Rothpletz‐Puglia, Laura Byham‐Gray, Daren K. Heyland, Nilesh Mehta

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsQueen's University
Fundersnot available
KeywordsUnderweightMedicineOverweightObesityOdds ratioIntensive care unitPediatricsRisk of mortalityPediatric intensive care unitEpidemiologyLogistic regressionIntensive careMechanical ventilationIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Critically ill children requiring mechanical ventilation in pediatric intensive care units (PICUs) are at high risk for mortality. Prior research regarding the impact of nutritional status on morbidity and mortality in PICU patients has been limited to single centers, small populations, or narrowly defined disease groups. We performed a multicenter, international cohort study to determine the unique contribution of nutritional status to mortality risk in mechanically ventilated children in PICUs. Nutritional status of subjects (age 1 month ‐18 years, N=1622) was 17.9% underweight (BMI Z score < ‐2), 54.2% normal weight (BMI Z score > ‐2 and < 1), 14.5% overweight (BMI Z score > 1 and < 2), and 13.4% obese (BMI Z score > 2). The impact of nutritional status on mortality was evaluated using multilevel logistic regression. PICU size and location, admission type, and diagnosis were significantly associated with nutritional status category and used as covariates in the analysis. Compared to normal weight children, the odds ratio for mortality was significantly higher in underweight (OR 1.64; 95% CI 1.23, 2.19; p=.001), overweight (OR 1.67; 95% CI 1.12, 2.50; p=.01), and obese children (OR 1.72; 95% CI 1.10, 2.69; p=.02). Underweight, overweight, and obesity are important risk factors for mortality in PICUs. Longitudinal investigations of nutritional status in critically ill children are warranted. Grant Funding Source : Supported by the Jean Hankin Nutritional Epidemiology award from the Academy of Nutrition and Dietet

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.003
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
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.333
Teacher spread0.302 · 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

Labeled directly by 2 models reading the full record.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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