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Record W3100224618 · doi:10.1101/2020.11.11.20230045

Impacts of the COVID-19 Pandemic on Cardiac Rehabilitation Delivery around the World

2020· preprint· en· W3100224618 on OpenAlexaff
Gabriela Lima de Melo Ghisi, Zhiming Xu, Xia Liu, Ana Mola, Robyn Gallagher, Abraham Samuel Babu, Colin Yeung, Susan Marzolini, John Buckley, Paul Oh, Aashish Contractor, Sherry L. Grace

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsYork UniversityUniversity Health NetworkUniversity of Saskatchewan
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicWorkloadMedicineAnxietyRehabilitationFamily medicinePhysical therapyDiseaseInternal medicineManagement

Abstract

fetched live from OpenAlex

Abstract Background To investigate impacts of COVID-19 on CR delivery around the globe, including effects on providers and patients. Methods In this cross-sectional study, a piloted survey was administered to CR programs globally via REDCap from April-June/2020. The 50 members of the ICCPR and personal contacts facilitated program identification. Results Overall, 1062(18.3% program response rate) responses were received from 70/111(63.1% country response rate) countries in the world with existent CR programs. Of these, 367(49.1%) programs reported they had stopped CR delivery, and 203(27.1%) stopped temporarily (mean=8.3±2.8weeks). Alternative models were delivered in 322(39.7%) programs, primarily through low-tech modes (n=226,19.3%). 353(30.2%) respondents were re-deployed, and 276 (37.3%) felt the need to work due to fear of losing their job, despite the perceived risk of contracting COVID-19 (mean=30.0%±27.4/100). 266(22.5%) reported anxiety, 241(20.4%) were concerned about exposing their family, 113(9.7%) reported increased workload to transition to remote delivery, and 105(9.0%) were juggling caregiving responsibilities during business hours. Patients were often contacting staff regarding grocery shopping for heart-healthy foods (n=333,28.4%), how to use technology to interact with the program (n=329,27.9%), having to stop their exercise because they have no place to exercise (n=303,25.7%), and their risk of death from COVID-19 due to pre-existing cardiovascular disease (n=249,21.2%). Respondents perceived staff (n=488,41.3%) and patient (n=453,38.6%) personal protective equipment, as well as COVID-19 screening (n=414,35.2%) and testing (n=411,35.0%) as paramount to in-person service resumption. Conclusion Approximately 4400 programs ceased service delivery. Those that remain open are implementing new technologies to ensure their patients receive CR safely, despite the challenges. Highlights - COVID-19 has impacted cardiac rehabilitation (CR) delivery around the globe. - In this cross-sectional study, a survey was completed by 1062 (18.3%) CR programs from 70 (63.1%) countries. - The pandemic has resulted in cessation of ∼75% of CR programs, with others ceasing initiation of new patients, reducing components delivered, and/or changing of mode delivery with little opportunity for planning and training. - There is also significant psychosocial and economic impact on CR providers. - Alternative CR model (e.g. home-based, virtual) reimbursement advocacy is needed, to ensure safe, accessible secondary prevention delivery.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.109
GPT teacher head0.399
Teacher spread0.290 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations19
Published2020
Admission routes1
Has abstractyes

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