Primary Thromboprophylaxis in Individuals without Cancer Admitted to a Geriatric Palliative Care Unit
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: The prevalence of individuals with advanced noncancer disease is increasing on palliative care units (PCUs), but there are no current guidelines to direct venous thromboembolism (VTE) prophylaxis decisions in these individuals. The aim of this study was to compare primary VTE prophylaxis in elderly adults with advanced noncancer diagnoses with that of those with advanced cancer on a dedicated geriatric PCU. DESIGN: Single-center retrospective chart review. SETTING: Baycrest Health Sciences PCU, Toronto, Ontario, Canada. PARTICIPANTS: All 317 individuals admitted to and discharged in 2015 were included in the initial analysis. RESULTS: Three hundred sixteen individuals were included in the final analysis, 56 (17.7%) of whom had a noncancer diagnosis. VTE prophylaxis was administered in 31.8% of participants with cancer and 26.8% of those without (P = .28). Two hundred eleven (66.6%) participants were admitted from the hospital, and 96 (30.3%) were admitted from home. Participants admitted from the hospital were more likely to receive VTE prophylaxis (39.8% vs 13.7%; P < .05). Mean admission PPS score was 31.4 for participants without cancer and 36.0 for those with cancer (P < .05). Length of stay was shorter for participants with a PPS score less than 30 (18.6 vs 33.6 days; P < .05). The rate of VTE prophylaxis in participants who were bedbound was similar to that in those who were ambulatory (29.8% vs 32.2%; P = .36). CONCLUSION: VTE prophylaxis rates were similar in participants with and without cancer on a geriatric PCU. The rate was not significantly less for nonambulatory participants. Further research would help to better guide VTE prophylaxis decisions and minimize suffering at the end of life.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".