Poster (Clinical/Best Practice Implementation) ID 1984967
Bibliographic record
Abstract
Background Assessment of physical activity (PA) prescription recall and serum screening for dyslipidemia are critical to describe and mitigate Cardiometabolic Disease (CMD) risk among adults with spinal cord injury or disease (SCI/D). Objectives To report: 1) the frequency of PA prescription recall; and, 2) the frequency of lipid profile assessment and interpretation recall among inpatients with SCI/D during rehabilitation. Methods Adults with SCI/D completed the SCI-HIGH CMD intermediary outcome indicators. A Kinesiologist collected data via interview and chart abstraction among UHN inpatients. Survey responses were scored using Reachlite’s optical character recognition software. Descriptive statistics were used to characterize the participant’s age, sex, impairment characteristics, and report recall rates and the frequency of lipid screening/interpretation. Based on the participant’s needs, either educational materials to increase future adherence to PA guidelines and/or a Mediterranean diet were provided. Results Adult inpatients (n=124), mean age 59 years, 64% paraplegic, and 36% female participated. In total, 14% of participants (16/117) reported being taught the benefits of PA for their heart health; of whom 69% (11/16) recalled exercise instruction. Similarly, 15% of inpatients (17/114) recalled lipid screening during rehabilitation, although chart abstraction revealed that 30% (37/124) had completed lipid screening. Clinical interpretation of their lipid values was recalled by 30% of inpatients. Conclusion There is a significant opportunity to advance PA instruction and lipid profile education and management among inpatients with SCI/D to reduce CMD risk. Inclusion of PA and lipid management instructions in patient-oriented discharge summaries may enhance patient recall/adherence.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.875 | 0.789 |
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".