Do Outpatient Podiatry Evaluations Reduce the Risk of Falls in Elderly Patients With Diabetes Mellitus?
Bibliographic record
Abstract
BACKGROUND: Elderly patients with diabetes mellitus (DM) are faced with potential changes in their lower extremities, such as peripheral neuropathy and peripheral arterial disease, making them vulnerable to falls. We hypothesized that evaluations by podiatrists would lower the events of falls. METHODS: A retrospective chart review of a cohort of patients with DM, 65 years or older, was performed, who visited our primary care office between January 1, 2019 and June 30, 2019. Patients were divided into those who had podiatrist evaluations (PODEVAL), and those who did not (no PODEVAL). Events of falls and comorbid medical conditions were compared between the two groups. We also compared the associations of risk factors between the patients who had falls and those who did not. RESULTS: Among 197 patients (PODEVAL = 92; no PODEVAL = 105), the mean ages of the two groups were comparable (76.9 years for PODEVAL, 75.5 years for no PODEVAL; P = 0.151). There was no significant difference in the events of falls in a 6-month follow-up period between PODEVAL and no PODEVAL groups (35.9% vs. 32.4%; P = 0.606). We found significantly higher frequencies of association of several disorders of the lower extremities in PODEVAL group compared to no PODEVAL group, such as bunions and calluses (48.9% vs. 27.6%; P = 0.002), peripheral arterial disease (50.0% vs. 26.7%; P < 0.001), and peripheral neuropathy (75.0% vs. 47.6%; P < 0.001). Patients with falls had higher frequencies of associations of some comorbidities compared to the patients without reported falls, such as coronary artery disease, peripheral arterial disease, dementia, congestive heart failure, carotid stenosis, and syncope. CONCLUSIONS: Among elderly patients with DM, there is no significant difference in the events of falls between the groups of patients who had podiatrist evaluations and who did not.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".