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Record W2093910338 · doi:10.1159/000315387

Co-Morbidity in COPD: The Effects of Cardiovascular Drug Therapies

2010· review· en· W2093910338 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRespiration · 2010
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineCOPDObservational studyPulmonary diseaseStatinIntensive care medicineDiseaseDrugMeta-analysisInternal medicinePharmacology

Abstract

fetched live from OpenAlex

Cardiovascular disease is a major co-morbidity in chronic obstructive pulmonary disease (COPD) patients and is a predictor of all-cause mortality. This paper reviews the study design and data analyses of observational studies of cardiovascular drug effects in patients with COPD and evaluates the potential for bias on the validity of their findings. Three recent observational studies of statin use in the setting of COPD show surprisingly high efficacy results which, by their magnitude, demand closer analysis. Such analysis reveals that immortal time and immeasurable time biases likely accounted for dramatic findings of reduced mortality with aggressive treatment for cardiovascular disease. After removing these sources of bias, the effects are mitigated or may disappear entirely. Investigation of methods and results in the statin studies reviewed in this article reveals significant bias that has skewed the results of these early studies. Correcting these methodological flaws with proper statistical analysis may attenuate or even eliminate these apparent benefits.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.349
Teacher spread0.315 · 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