The association between the severity of cognitive impairment and the risk of falls in patients with dementia
Bibliographic record
Abstract
Background.Falls are a significant cause of morbidity and mortality in older individuals with dementia, presenting a complex and multifactorial challenge.Cognitive impairment in dementia further exacerbates this risk, as it impairs judgment, attention, and motor coordination, while also reducing the ability to recognize and avoid potential hazards in the environment.Objectives.To investigate the association between the severity of cognitive impairment and the risk of falls in patients with dementia.Material and methods.We conducted a cross-sectional study using a consecutive sampling method involving 30 dementia patients at the Neurology Clinic of USU Hospital in Medan Indonesia from January until July 2024.We assessed cognitive function using the Montreal Cognitive Indonesian Version (MoCA-INA) and the severity of cognitive impairment with the Clinical Dementia Rating Scale (CDR).The Timed Up and Go (TUG) test was used to evaluate the risk of falls.Data were analyzed using SPSS version 26 with a p-value < 0.05 considered significant.Results.We enrolled 30 dementia patients with a mean age of 64.3 7.8 years.Half of the participants (50%) had mild dementia, and 56.7% were categorized as having a mild fall risk.We found a significant association between dementia severity and cognitive impairment with fall risk using the Kruskall-Wallis test (p = 0.036) and a one-way ANOVA test (p = 0.005), respectively.Conclusions.Our findings indicate that the severity of cognitive impairment was significantly associated with an increased risk of falls in patients with dementia.Fall risk screening should be an integral part of the management and prevention strategies for dementia patients.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".