Frequency and factors associated with falls in patients with advanced cancer presenting to an outpatient supportive care clinic
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the frequency and factors associated with fall episodes in advanced cancer patients. METHOD: We analyzed data that included demographic characteristics, utilization of assistive devices, cancer diagnosis, metastatic site, performance status, medications including hypnotics and opioids, Edmonton Symptom Assessment Scale (ESAS) score, and Memorial Delirium Assessment Scale (MDAS) score in 384 consecutive patients who were newly referred to the Supportive Care Clinic at the MD Anderson Cancer Center from January 1 to December 31, 2009. All patients completed standardized forms to report falls within the last month. Multivariate backward regression analyses were employed to identify factors predictive of falls in advanced cancer. RESULTS: The mean age of patients was 58 years, and 192 (50%) were male. Mean (SD)/median score for pain was 5 (2.8), 5; fatigue 5.6 (2.6), 6; sleep disturbance 5(2.7), 5; drowsiness 3.7(3), 3; and anorexia 5(3), 5. Some 31 patients (8%) reported fall episodes within the past month, 17 (55%) of whom reported the use of assistive devices. Using assist devices (OR = 5.5, 95% CI: 2.6-11.9, p < 0.0001) and taking zolpidem (OR = 3.39, 95% CI: 1.39-7.7, p = 0.008) were associated with an enhanced chance of falling. Higher MDAS score (4.00 vs. 1.42, p = 0.001) and MDAS positive screening for delirium (21 vs. 3.6%, p < 0.001) were also associated with falls. However, severity on the ESAS at the initial consult was not associated with falls. SIGNIFICANCE OF RESULTS: We conclude that 31 of 384 patients (8%) with advanced cancer receiving outpatient supportive care reported falls in the previous month. Patients with assistive devices, taking zolpidem, and with a higher MDAS score, and a positive delirium screening reported more frequent falls. Further studies are warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".