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Record W3164170867 · doi:10.2196/28708

Telerehabilitation for Lung Transplant Candidates and Recipients During the COVID-19 Pandemic: Program Evaluation

2021· article· en· W3164170867 on OpenAlexafffundvenue
Lisa Wickerson, Denise Helm, Chaya Gottesman, Dmitry Rozenberg, L.G. Singer, Shaf Keshavjee, Aman Sidhu

Bibliographic record

VenueJMIR mhealth and uhealth · 2021
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersUniversity Health Network
KeywordsTelerehabilitationMedicinePhysical therapyTelehealthLung transplantationRehabilitationTelemedicinePulmonary rehabilitationTransplantationInternal medicineHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic resulted in a rapid shift from center-based rehabilitation to telerehabilitation for chronic respiratory disease and lung transplantation due to infection control precautions. Clinical experience with this delivery model on a large scale has not been described. OBJECTIVE: The aim of this study is to describe usage and satisfaction of providers and lung transplant (LTx) candidates and recipients and functional outcomes following the broad implementation of telerehabilitation with remote patient monitoring during the first wave of the COVID-19 pandemic. METHODS: This study was a program evaluation of providers, LTx candidates, and early LTx recipients who used a web-based, remote monitoring app for at least four weeks between March 16 and September 1, 2020, to participate in telerehabilitation. Within-subjects analysis was performed for physical activity, Self-efficacy For Exercise (SEE) scale score, aerobic and resistance exercise volumes, 6-minute walk test results, and Short Physical Performance Battery (SPPB) results. RESULTS: In total, 78 LTx candidates and 33 recipients were included (57 [51%] males, mean age 58 [SD 12] years, 58 [52%] with interstitial lung disease, 34 [31%] with chronic obstructive pulmonary disease). A total of 50 (64%) LTx candidates and 17 (51%) LTx recipients entered ≥10 prescribed exercise sessions into the app during the study time frame. In addition, 35/42 (83%) candidates agreed the app helped prepare them for surgery and 18/21 (85%) recipients found the app helpful in their self-recovery. The strongest barrier perceived by physiotherapists delivering the telerehabilitation was patient access to home exercise and monitoring equipment. Between the time of app registration and ≥4 weeks on the waiting list, 26 LTx candidates used a treadmill, with sessions increasing in mean duration (from 16 to 22 minutes, P=.002) but not speed (from 1.7 to 1.75 mph, P=.31). Quadriceps weight (pounds) for leg extension did not change (median 3.5, IQR 2.4-5 versus median 4.3, IQR 3-5; P=.08; n=37). On the Rapid Assessment of Physical Activity questionnaire (RAPA), 57% of LTx candidates scored as active, which improved to 87% (P=.02; n=23). There was a decrease in pretransplant 6-minute walk distance (6MWD) from 346 (SD 84) meters to 307 (SD 85) meters (P=.002; n=45) and no change in the SPPB result (12 [IQR 9.5-12] versus 12 [IQR 10-12]; P=.90; n=42). A total of 9 LTx recipients used a treadmill that increased in speed (from 1.9 to 2.7 mph; P=.003) between hospital discharge and three months posttransplant. Quadriceps weight increased (3 [IQR 0-3] pounds versus 5 [IQR 3.8-6.5] pounds; P<.001; n=15). At three months posttransplant, 76% of LTx recipients scored as active (n=17), with a high total SEE score of 74 (SD 11; n=12). In addition, three months posttransplant, 6MWD was 62% (SD 18%) predicted (n=8). CONCLUSIONS: We were able to provide telerehabilitation despite challenges around exercise equipment. This early experience will inform the development of a robust and equitable telerehabilitation model beyond the COVID-19 pandemic.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.115
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.139
GPT teacher head0.496
Teacher spread0.358 · 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.

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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Citations58
Published2021
Admission routes3
Has abstractyes

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