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Rehabilitation for People with Respiratory Disease and Frailty: An Official American Thoracic Society Workshop Report

2023· article· en· W4378952087 on OpenAlexfundno aff
Matthew Maddocks, Lisa Jane Brighton, Jennifer Alison, Lies ter Beek, Surya P. Bhatt, Nathan E. Brummel, Chris Burtin, Matteo Cesari, Rachael A Evans, Lauren E. Ferrante, Oscar Flores-Flores, Frits M.E. Franssen, Chris Garvey, Samantha Harrison, Anand Iyer, Lies Lahouse, Suzanne C. Lareau, Annemarie L. Lee, William D‐C Man, Alessandra Marengoni, Hamish McAuley, Dmitry Rozenberg, Jonathan P. Singer, Martijn A. Spruit, Christian Osadnik

Bibliographic record

VenueAnnals of the American Thoracic Society · 2023
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersFogarty International CenterNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteEconomic and Social Research CouncilUniversity of California, San FranciscoRegeneron PharmaceuticalsNational Institutes of HealthVlaamse regeringUniversiteit GentNovartis AustraliaKarolinska InstitutetUniversity of Colorado DenverUniversity of TorontoKing's College Hospital NHS Foundation TrustAustralian Physiotherapy AssociationPhysiotherapy Research FoundationStichting Astma BestrijdingKing's College LondonTeesside UniversityGlaxoSmithKlineImperial College LondonSunovionEuropean Respiratory SocietyNational Institute for Health Research Applied Research Collaboration South LondonSanofiMedical Research CouncilTeva Pharmaceutical IndustriesNational Institute on AgingNational Institute for Health and Care ResearchUniversità degli Studi di BresciaRoyal Australian College of General PractitionersAmerican Thoracic SocietyNational Health and Medical Research CouncilAstraZeneca
KeywordsMedicinePulmonary rehabilitationRehabilitationPopulationDiseaseHealth careTelerehabilitationMEDLINEReferralGerontologyPhysical therapyPhysical medicine and rehabilitationFamily medicineTelemedicine

Abstract

fetched live from OpenAlex

People with respiratory disease have increased risk of developing frailty, which is associated with worse health outcomes. There is growing evidence of the role of rehabilitation in managing frailty in people with respiratory disease. However, several challenges remain regarding optimal methods of identifying frailty and delivering rehabilitation for this population. The aims of this American Thoracic Society workshop were to outline key definitions and concepts around rehabilitation for people with respiratory disease and frailty, synthesize available evidence, and explore how programs may be adapted to align to the needs and experiences of this population. Across two half-day virtual workshops, 20 professionals from diverse disciplines, professions, and countries discussed key developments and identified opportunities for future research, with additional input via online correspondence. Participants highlighted a "frailty rehabilitation paradox" whereby pulmonary rehabilitation can effectively reduce frailty, but programs are challenging for some individuals with frailty to complete. Frailty should not limit access to rehabilitation; instead, the identification of frailty should prompt comprehensive assessment and tailored support, including onward referral for additional specialist input. Exercise prescriptions that explicitly consider symptom burden and comorbidities, integration of additional geriatric or palliative care expertise, and/or preemptive planning for disruptions to participation may support engagement and outcomes. To identify and measure frailty in people with respiratory disease, tools should be selected on the basis of sensitivity, specificity, responsiveness, and feasibility for their intended purpose. Research is required to expand understanding beyond the physical dimensions of frailty and to explore the merits and limitations of telerehabilitation or home-based pulmonary rehabilitation for people with chronic respiratory disease and frailty.

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)0.018
metaresearch head score (Gemma)0.010
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: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0040.003
Open science0.0020.011
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0100.004

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 head0.098
GPT teacher head0.429
Teacher spread0.331 · 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
GenreOther

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

Citations34
Published2023
Admission routes1
Has abstractyes

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