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Record W4388127673 · doi:10.1097/ccm.0000000000006092

The Relationship Between Metabolic Syndrome and Mortality Among Patients With Acute Respiratory Distress Syndrome in Acute Respiratory Distress Syndrome Network and Prevention and Early Treatment of Acute Lung Injury Network Trials*

2023· article· en· W4388127673 on OpenAlexaff
Kevin Tea, Yuanhao Zu, Cheng Han Chung, Jaclyn Pagliaro, Prakriti Mehta, Himmat Grewal, Ivor S. Douglas, Yasín A. Khan, Jeffrey G. Shaffer, Joshua L. Denson

Bibliographic record

VenueCritical Care Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersNational Institute of General Medical Sciences
KeywordsMedicineAcute respiratory distressIntensive care medicineDiffuse alveolar damageRespiratory distressRespiratory systemMetabolic syndromeInternal medicineLungAnesthesiaObesity

Abstract

fetched live from OpenAlex

OBJECTIVES: Metabolic syndrome is known to predict outcomes in COVID-19 acute respiratory distress syndrome (ARDS) but has never been studied in non-COVID-19 ARDS. We therefore aimed to determine the association of metabolic syndrome with mortality among ARDS trial subjects. DESIGN: Retrospective cohort study of ARDS trials' data. SETTING: An ancillary analysis was conducted using data from seven ARDS Network and Prevention and Early Treatment of Acute Lung Injury Network randomized trials within the Biologic Specimen and Data Repository Information Coordinating Center database. PATIENTS: Hospitalized patients with ARDS and metabolic syndrome (defined by obesity, diabetes, and hypertension) were compared with similar patients without metabolic syndrome (those with less than three criteria). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was 28-day mortality. Among 4288 ARDS trial participants, 454 (10.6%) with metabolic syndrome were compared with 3834 controls (89.4%). In adjusted analyses, the metabolic syndrome group was associated with lower 28-day and 90-day mortality when compared with control (adjusted odds ratio [aOR], 0.70 [95% CI, 0.55-0.89] and 0.75 [95% CI, 0.60-0.95], respectively). With each additional metabolic criterion from 0 to 3, adjusted 28-day mortality was reduced by 18%, 22%, and 40%, respectively. In subgroup analyses stratifying by ARDS etiology, mortality was lower for metabolic syndrome vs. control in ARDS caused by sepsis or pneumonia (at 28 d, aOR 0.64 [95% CI, 0.48-0.84] and 90 d, aOR 0.69 [95% CI, 0.53-0.89]), but not in ARDS from noninfectious causes (at 28 d, aOR 1.18 [95% CI, 0.70-1.99] and 90 d, aOR 1.26 [95% CI, 0.77-2.06]). Interaction p = 0.04 and p = 0.02 for 28- and 90-day comparisons, respectively. CONCLUSIONS: Metabolic syndrome in ARDS was associated with a lower risk of mortality in non-COVID-19 ARDS. The relationship between metabolic inflammation and ARDS may provide a novel biological pathway to be explored in precision medicine-based trials.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.007
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.048
GPT teacher head0.353
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

Citations7
Published2023
Admission routes1
Has abstractyes

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