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Record W2100006057 · doi:10.1164/rccm.2107031

Midthigh Muscle Cross-Sectional Area Is a Better Predictor of Mortality than Body Mass Index in Patients with Chronic Obstructive Pulmonary Disease

2002· article· en· W2100006057 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineConfidence intervalBody mass indexCOPDInternal medicineOdds ratioAnthropometryCross-sectional studyCardiologyProportional hazards modelPathology

Abstract

fetched live from OpenAlex

This study was undertaken to test the hypothesis that a reduction in midthigh muscle cross-sectional area obtained by CT scan (MTCSA(CT)) is a better predictor of mortality in chronic obstructive pulmonary disease (COPD) than low body mass index (BMI). We also wished to evaluate whether anthropometric measurements could be used to estimate MTCSA(CT). One hundred forty-two patients with COPD (age = 65 +/- 9 years, mean +/- SD, 26 F, BMI = 26 +/- 6 kg/m(2), FEV(1) = 42 +/- 16% predicted) were recruited from September 1995 to April 2000 with a mean follow-up of 41 +/- 18 months. The primary end-point was all-cause mortality during the study period. A Cox proportional hazards regression model was used to predict mortality using the following independent variables: age, sex, daily use of corticosteroid, FEV(1), DL(CO), BMI, thigh circumference, MTCSA(CT), peak exercise workrate, Pa(O2), and Pa(CO2). Only MTCSA(CT) and FEV(1) were found to be significant predictors of mortality (p = 0.0008 and p = 0.01, respectively). A second analysis was also performed with FEV(1) and MTCSA(CT) dichotomized. Patients were divided into four subgroups based on FEV(1) (< or >or= 50% predicted) and MTCSA(CT) (< or >or= 70 cm(2)). Compared with patients with an FEV(1) >or= 50% predicted and a MTCSA(CT) >or= 70 cm(2), those with an FEV(1) < 50% predicted and a MTCSA(CT) >or= 70 cm(2) had a mortality odds ratio of 3.37 (95% confidence interval, 0.41-28.00), whereas patients with an FEV(1) < 50% predicted and a MTCSA(CT) < 70 cm(2) had a mortality odds ratio of 13.16 (95% confidence interval, 1.74-99.20). MTCSA(CT) could not be estimated with sufficient accuracy from anthropometric measurements. In summary, we found in this cohort of patients with COPD that (1) MTCSA(CT) was a better predictor of mortality than BMI, and (2) MTCSA had a strong impact on mortality in patients with an FEV(1) < 50% predicted. These findings suggest that the assessment of body composition may be useful in the clinical evaluation of these patients.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.302
Teacher spread0.283 · 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