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Trends in Use of Daily Chest Radiographs Among US Adults Receiving Mechanical Ventilation

2018· article· en· W2886709889 on OpenAlexaff
Hayley B. Gershengorn, Hannah Wunsch, Damon C. Scales, Gordon D. Rubenfeld

Bibliographic record

VenueJAMA Network Open · 2018
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMechanical ventilationRadiographyMedicineVentilation (architecture)Emergency medicineRadiologyInternal medicineEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Importance: Guidelines from December 2011 recommended against obtaining daily chest radiographs (CXRs) for patients requiring mechanical ventilation (MV). Daily CXR use for patients receiving MV in US hospitals is unknown and, if high, may represent an opportunity to reduce low-value care and unnecessary radiation. Objectives: To determine frequency of daily CXR use for US patients receiving MV, assess variability across hospitals, and evaluate whether use has decreased over time. Design, Setting, and Participants: Retrospective cohort study of hospitalized adults (aged ≥18 years) receiving MV for 3 days or longer. Mechanical ventilation was defined by having an International Classification of Diseases, Ninth Revision, Clinical Modification code of 96.7x and an MV charge on more than 1 hospital day. Hospital discharges in the Premier Perspectives database were examined from July 1, 2008, to December 31, 2014. Data analysis was conducted from July 28, 2017, to December 13, 2017. Exposures: Hospital discharge date (quarter of the year) and hospital in which patients received MV. Main Outcomes and Measures: The outcome was daily CXR use (up to 7 days) during MV. We used standard statistics to describe CXR use, multilevel multivariable regression modeling with adjusted median odds ratio (OR) to evaluate variability by hospital, and multivariable piecewise regression (breakpoint: fourth quarter of 2011) with adjusted OR to evaluate time trends and response to guideline recommendations. Results: The primary cohort included 512 518 patients receiving MV (mean [SD] age, 63.0 [16.1] years; 46% female) in 416 hospitals, of whom 321 093 (63%) received daily CXRs. Wide variability was seen across hospitals; hospitals performed daily CXRs on a median of 66% of patients (interquartile range, 50%-77%; full range, 12%-97%). The adjusted median OR was 2.43 (95% CI, 2.29-2.59), suggesting the same patient had 2.43-fold higher odds of receiving a daily CXR if admitted to a higher- vs lower-use hospital; the odds of receiving daily CXRs were unchanged through quarter 3 of 2011 (adjusted OR, 1.00; 95% CI, 0.99-1.01), after which there was a 3% relative reduction in the odds of daily CXR use per quarter (adjusted OR, 0.97; 95% CI, 0.96-0.98). Conclusions and Relevance: Three-fifths of US patients receiving MV also received daily CXRs from 2008 to 2014, although use declined slowly after new guidelines were published. The hospital at which a patient received care was associated with the odds of daily CXR receipt.

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
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.045
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.053
GPT teacher head0.341
Teacher spread0.288 · 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".

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Citations34
Published2018
Admission routes1
Has abstractyes

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