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Record W2891095664 · doi:10.1177/0009922818796661

Bronchodilator Use for Acute Chest Syndrome Among Large Pediatric Hospitals in North America

2018· article· en· W2891095664 on OpenAlexaff
Lianne S. Kopel, Elizabeth S. Klings, Michael C. Monuteaux, Jonathan M. Gaffin, Matthew M. Heeney, Wanda Phipatanakul

Bibliographic record

VenueClinical Pediatrics · 2018
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsMontreal Children's Hospital
FundersNational Center for Advancing Translational SciencesNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood InstituteNational Institutes of HealthHarvard Catalyst
KeywordsMedicineInterquartile rangeBronchodilatorConfidence intervalAcute chest syndromeAsthmaBronchodilator AgentsProspective cohort studyPediatricsInternal medicineEmergency medicineAnesthesiaDisease

Abstract

fetched live from OpenAlex

The utility of bronchodilators to treat acute chest syndrome (ACS) in patients with sickle cell disease is unknown. Our objectives were to examine the variability in bronchodilator use for ACS among pediatric hospitals contributing to a large database and to examine the relationship between bronchodilator use and length of stay (LOS) and mortality. Between 2005 and 2011, bronchodilators were used during 6812/11 328 hospitalizations (60.1%) and use varied from 0.0% to 97.0% (median = 46.0%, interquartile range = 37.0% to 74.0%). Median LOS was 4 days, and interquartile range was 2 to 6 days. Bronchodilator use was associated with a 13.2% increase in LOS (95% confidence interval = 9.2% to 17.3%, P < .001). However, in the subgroup with asthma, bronchodilator use was associated with a 17.9% decrease in LOS (95% confidence interval = 1.7% to 31.4%, P = .03). There is wide variability in bronchodilator use for ACS, and it has variable association with LOS, depending on comorbid asthma. Prospective trials are needed to evaluate bronchodilators for ACS.

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)0.003
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 score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.023
GPT teacher head0.327
Teacher spread0.305 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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