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Record W3047138220 · doi:10.1097/mcp.0000000000000700

Pulmonary rehabilitation in interstitial lung diseases

2020· review· en· W3047138220 on OpenAlexaff
Nima Makhdami, Mohammed A. Farooqi, Cedel Thom-Fernandes, Natya Raghavan

Bibliographic record

VenueCurrent Opinion in Pulmonary Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinePulmonary rehabilitationModalitiesRehabilitationPhysical therapyQuality of life (healthcare)Intensive care medicineBreathingPhysical medicine and rehabilitationNursingAnesthesia

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This review will provide an overview of the components and current evidence to support pulmonary rehabilitation in patients with interstitial lung diseases (ILD), focusing on the latest findings in enhancing quality of life and functional capacity using exercise training and education. RECENT FINDINGS: Recent literature demonstrates a longer duration of pulmonary rehabilitation results in sustained improvements in functional capacity and quality of life in patients with ILD. Educational components tailored to ILD provide added value to supervised exercise training. Enhancing exercise training with hyperoxia merits further study and other modalities such as pursed-lip breathing have been shown to be counterproductive. SUMMARY: Recent evidence continues to support the use of tailored pulmonary rehabilitation programs in patients with ILD. Areas which require further investigation include identifying optimal exercise training regimens, educational topics, and breathing techniques that are specifically designed for ILD.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.055
GPT teacher head0.397
Teacher spread0.341 · 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
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

Citations9
Published2020
Admission routes1
Has abstractyes

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