Abstract 16532: Sedentary Time in Hospitalized Older Adults With Acute Cardiovascular Disease
Bibliographic record
Abstract
Background: Older adults may be subject to prolonged bedrest during hospitalization for acute cardiovascular (CV) disease, which can contribute to poor functional outcomes posthospitalization. Our objective was to describe mobility status in hospitalized older adults with acute CV disease. Methods: Patients aged ≥ 60 years old in the cardiac ICU and CV ward at a tertiary care academic centre in Montreal, Quebec were prospectively enrolled from April 2019 to March 2020. Activity levels were measured with an accelerometer (ActiGraph GT9 Link). Sedentary was defined as lying in bed or in a sitting position. Health-related quality of life (HRQoL) was measured with the Short-Form 36 (SF-36) questionnaire by telephone at 1 month post-hospital discharge. The primary outcome was percentage of sedentary time during hospital stay. Secondary outcomes were step counts, steps per minute, and kcal/day consumption. Results: There were 35 patients included in the analysis (75.7 6.9 years old; 45.7% females; 22.9% ischemic heart disease; 20.0% heart failure). Patients spent 91.2% ± 5.5 in the sedentary position during their hospital stay (range 80.0-100%; Figure ). There was no difference in percentage sedentary time by primary diagnosis or sex. Mean steps per minute were 1.0 ± 1.2 and mean kcals consumed per day were 116.6 ± 124.5. In the multivariable analysis, a lower percentage of sedentary time and lower steps per minute were each associated with lower total SF-36 scores at 1-month posthospitalization (both P<0.05). Conclusion: Older adults with acute CV disease are sedentary for a large part of their hospital stay. Increased sedentary time is associated with worse self-reported posthospital HRQoL. Future studies are needed to determine whether interventions to increase activity during hospitalization improve posthospital HRQoL and functional 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".