Falls and Fall-Related Injuries in Older Dialysis Patients
Bibliographic record
Abstract
Dialysis patients are increasingly older and more disabled. In community-dwelling seniors without kidney disease, falls commonly predict hospitalization, the onset of frailty, and the need for institutional care. Effective fall prevention strategies are available. On the basis of retrospective data, it was hypothesized that the fall rates of older (> or =65 yr) chronic outpatient hemodialysis (HD) patients would be higher than published rates for community-dwelling seniors (0.6 to 0.8 falls/patient-year). It also was hypothesized that risk factors for falls in dialysis outpatients would include polypharmacy, dialysis-related hypotension, cognitive impairment, and decreased functional status. Using a prospective cohort study design, HD patients who were > or =65 yr of age at a large academic dialysis unit were recruited. All study participants underwent baseline screening for fall risk factors. Patients were followed prospectively for a minimum of 1 yr. Falls were identified through biweekly patient interviews in the HD unit. A total of 162 patients (mean age 74.7 yr) were recruited; 57% were male. A total of 305 falls occurred in 76 (47%) patients over 190.5 person-years of follow-up (fall-incidence 1.60 falls/person-year). Injuries occurred in 19% of falls; 41 patients had multiple falls. Associated risk factors included age, comorbidity, mean predialysis systolic BP, and a history of falls. In the HD population, the fall risk is higher than in the general community, and fall-related morbidity is high. Better identification of HD patients who are at risk for falls and targeted fall intervention strategies are required.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".