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Record W4390964591 · doi:10.1164/rccm.202311-2068le

Reply to: Asthma–Chronic Obstructive Pulmonary Disease Overlap versus Chronic Obstructive Pulmonary Disease: Comparing Apples and Oranges

2024· letter· en· W4390964591 on OpenAlexafffund
Emily D. Gerstein, Jared Bierbrier, G. À. Whitmore, Shawn D. Aaron

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2024
Typeletter
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill UniversityOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicinePulmonary diseaseCOPDAsthmaInternal medicineIntensive care medicineRespiratory diseaseLung

Abstract

fetched live from OpenAlex

asthma-COPD overlap syndrome (ACOS), including persistent yet reversible airflow limitation (post-bronchodilator FEV 1 to FVC ratio of ,70% and FEV 1 improvement of .12%and .400ml from baseline after bronchodilator therapy).However, the term "syndrome" was dropped because it is not a single phenomenon but is caused by a variety of mechanisms.Growing evidence shows distinctions between ACO and COPD.Karayama and colleagues (2) evaluated 167 patients with COPD and divided them into a COPD group and an ACO group.The authors analyzed respiratory resistance and reactance and three-dimensional computed tomography data between COPD and ACO.They found that patients with ACO had higher respiratory resistance and reactance during tidal breathing and a smaller gap between the inspiratory and expiratory phases than patients with COPD, suggesting that patients with ACO had greater airway narrowing and more severe small airway disease than those with COPD.Similarly, in the review by Leung and Sin, the authors concluded that patients with ACOS had greater decrement in quality of life and their healthcare utilization was significantly higher compared with asthma or COPD alone (3).In addition, the FEV 1 annual decline was 46.5 ml/yr in the COPD group and 36.5 ml/yr in the ACO group in the study by Mannino (4).Baarnes and colleagues defined ACOS as post-bronchodilator FEV 1 /FVC , 0.70, combined with wheeze and/or significant bronchodilator reversibility.In the cohort, the authors discovered that, compared with COPD only, patients with ACOS had more dyspnea and lower FEV 1 % predicted, whereas no difference was found in bronchodilator reversibility (5).In conclusion, the abovementioned study indicates that ACO and COPD exhibit differences in lung function.Upon reviewing the article by Gerstein and colleagues (1), it is inadvisable for the author to classify patients with ACO into the COPD group, because they exhibit differences in lung function and varying degrees of disease severity.This could affect the reliability of the results.In addition, considering the unequal distribution of ACO cases between the undiagnosed and diagnosed groups, it may result in a lack of comparability between these groups.However, there are still some issues that require further discussion.In some aspects, the outcomes of ACO and COPD are consistent.Modak and colleagues used the Healthcare Cost and Utilization Project Nationwide Readmissions Database and analyzed outcomes of index admissions and 30-day readmissions in asthma, COPD, and ACO.They concluded that although ACO was linked to higher rates of baseline comorbidities, an extended length of stay, and increased healthcare costs during the index admission compared with asthma or COPD, this did not result in higher in-hospital mortality, complication rates, or an increased risk of readmission (6).To sum up, despite its limitations, ACO differs from COPD in symptoms.Therefore, we recommend that patients with ACO should be separated from COPD and analyzed as an independent group to preserve the homogeneity of the study population.

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)0.005
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.038
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0380.031
Insufficient payload (model declined to judge)0.0130.010

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 head0.024
GPT teacher head0.322
Teacher spread0.298 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2024
Admission routes2
Has abstractyes

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