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Record W2037470544 · doi:10.1097/mco.0b013e32833e3453

Respiratory function and the obesity paradox

2010· review· en· W2037470544 on OpenAlexaff
Jordan A. Guenette, Dennis Jensen, Denis E. O’Donnell

Bibliographic record

VenueCurrent Opinion in Clinical Nutrition & Metabolic Care · 2010
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsObesityRespiratory systemMedicineFunction (biology)Intensive care medicineInternal medicineBiologyCell biology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Obese individuals have impaired respiratory function relative to their normal-weight counterparts. Despite these negative effects, obesity is paradoxically associated with better survival in individuals with chronic obstructive pulmonary disease (COPD). The purpose of this review is to describe this 'obesity paradox', to discuss the effects of obesity on respiratory function, and to speculate as to whether obesity-related alterations in respiratory mechanics can influence the natural history of COPD. RECENT FINDINGS: Given the known negative effects of obesity on respiratory physiology, it is reasonable to predict that obese COPD patients would be more likely to experience greater dyspnea and exercise intolerance relative to COPD patients of normal weight. However, recent evidence suggests that obese COPD patients have similar or better dyspnea scores during exercise and do not have diminished exercise capacity. These observations may be attributable to the fact that obese COPD patients have reduced operating lung volumes and higher inspiratory capacity to total lung capacity ratios than their lean COPD counterparts. SUMMARY: Obese patients with COPD do not appear to be at a disadvantage during exercise relative to lean COPD patients. Obesity may be associated with improved survival in COPD but specific mechanisms for this paradox remain to be elucidated.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
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 head0.151
GPT teacher head0.473
Teacher spread0.322 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations72
Published2010
Admission routes1
Has abstractyes

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