CYCLE RCT Participant Retention During the Pandemic: Assessing Protocol Fidelity
Bibliographic record
Abstract
Introduction: CYCLE (NCT03471247) is the largest international randomized controlled trial (RCT) of early in-bed cycling with mechanically ventilated patients in the world. It relies on ICU physical therapists for in-person intervention delivery, acute care therapists (including physical and occupational therapists, and therapy assistants) for primary outcomes assessments, and research coordinators (RCs) for 90-day telephone followup. Like many studies, CYCLE recruitment was abruptly interrupted by the COVID-19 pandemic, posing immediate threats to study internal validity. Amidst much uncertainty, we aimed to honor our research commitment to those enrolled before the pandemic. Methods: On March 17, 2020, the province of Ontario declared a state of emergency. Most participating CYCLE institutions halted enrolment to non-COVID research activities. We conducted a cross-sectional standardized email survey to determine the number of patients currently enrolled in the ICU or hospital and the status of patients pending 90-day assessment up to April 30, 2020. We assessed protocol fidelity in the following ways: For patients in ICU, we documented any attempt to provide the randomized intervention. For patients in hospital, we documented any attempt for physical outcomes assessments, prioritizing the primary outcome. For patients discharged from hospital, we documented whether a 90-day phone call was attempted. We also sought feedback to address needs identified by RCs to complete 90-day follow-up remotely. Results: As of March 17, 2020, we enrolled 197 patients in CYCLE overall, and 24 (12.2%) were in hospital or pending 90-day follow-up by April 30. From 15 active sites (12 Canada, 2 US, 1 Australia), 11 (73%) had 24 unique patients of immediate concern (4 ICU, 9 hospital, 16 for 90-day follow-up). All ICU (4/4) interventions and all 90-day calls (17/17) were attempted. Of hospital outcomes assessments, 89% (8/9) were attempted. One site could not complete primary outcomes assessment in hospital due to institutional pandemic policy. We developed guidance to conduct remote 90-day follow up calls from RC personal phones, considering study integrity, and patient and staff confidentiality. Conclusions: We used methodologically rigorous, time-sensitive strategies to address uncertainty during the first wave of the pandemic. We successfully retained almost all patients of immediate concern during the initial period of COVID-19. Protocol fidelity and cohort retention will be important considerations for all trials interrupted by the COVID-19 pandemic. Proactive strategies, learned from the first wave, will be critical as non-COVID research resumes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.441 | 0.463 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".