Poster (Knowledge Generation) ID 2001062
Bibliographic record
Abstract
Background/objectives Research participation for individuals with spinal cord injury (SCI) is important to develop and receive promising interventions. It has been suggested that consenting to participate may also be associated with improved long-term outcomes. The objectives of this study are twofold and consisted of 1) verifying whether consenting to participate in a national SCI registry is associated with improved outcomes, and 2) determining predictors of enrolling in the registry. Methods/overview This population-based retrospective cohort study was performed on 3854 individuals with acute traumatic SCI approached to participate in the Canadian patient registry (Rick Hansen SCI Registry) between 2014 and 2019. The status of consent (consent vs. declined/withdrew) consisted in the main independent variable. Outcomes included length of stay, in-hospital mortality, discharge destination, occurrence of complications. Multivariable analyses were performed to identify predictors of consenting and its association with each outcome, while accounting for important covariables (demographic-, trauma- and institution-related). Results 2998 individuals provided consent and 856 individuals declined/withdrew. Older age at injury and living farther away was associated with decreased likelihood for enrollment. While adjusting for covariables, declining participation was associated with increased acute length of stay, higher incidence of acute complications during acute care and decrease likelihood of being discharged home. Conclusions Approximately 20% of individuals declined participation in a national registry following an acute SCI, particularly elderly individuals and those living away from the hospital. It is possible that engagement in care and/or care delivery was altered for these individuals, leading to poorer patient outcomes. Enhanced opportunities should be given to subgroups not inclined to participate in research to optimize inclusivity in care delivery, therefore improving outcomes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.939 | 0.790 |
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".