Accidental Falls and Risk of Mortality among Older Adults on Chronic Peritoneal Dialysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: More than 40% of elderly hemodialysis patients experience one or more accidental falls within a 1-year period. Such falls are associated with higher mortality. The objectives of this study were to assess whether falls are also common in elderly patients established on peritoneal dialysis and evaluate if patients with falls have a higher risk of mortality than patients who do not experience a fall. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Using a prospective cohort study design, patients ages ≥ 65 years on chronic peritoneal dialysis from April 2002 to April 2003 at the University Health Network were recruited. Patients were followed biweekly, and falls occurring within the first 15 months were recorded. Outcome data were collected until death, study end (July 31, 2012), transplantation, or transfer to another dialysis center. RESULTS: Seventy-four of seventy-six potential patients were recruited, assessed at baseline, and followed biweekly for falls; 40 of 74 (54%) peritoneal dialysis patients experienced 89 falls (adjusted mean fall rate, 1.7 falls per patient-year; 95% confidence interval, 1.0 to 2.7). Patients with falls were more likely to have had previous falls, be more recently initiated onto dialysis, be men, be older, and have higher comorbidity. Twenty-eight patients died during the follow-up period. After adjustment for known risk factors, each successive fall was associated with a 1.62-fold higher mortality (hazard ratio, 1.62; 95% confidence interval, 1.29 to 2.02; P<0.001). CONCLUSIONS: Accidental falls are common in the peritoneal dialysis population and often go unrecognized. Falls were associated with higher mortality risk. Because fall interventions are effective in other populations, screening peritoneal dialysis patients for falls may be a simple measure of clinical importance.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".