The Prevalence of Comorbidities and Associated Factors among Patients with Dementia in the Indian Setting: Meta-analysis of Observational Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Patients with dementia usually have multiple comorbidities. The presence of comorbidities may exacerbate the progression of dementia and decreases the patient's ability to participate in health maintenance activities. However, there is hardly any meta-analysis estimating the magnitude of comorbidities among patients with dementia in the Indian context. Methods: statistics were calculated to measure heterogeneity among studies. Results: Fourteen studies were included in the meta-analysis based on the inclusion and exclusion criteria. Altogether, we found the coexistence of comorbid conditions such as hypertension (51.10%), diabetes (27.58%), stroke (15.99%), and factors like tobacco use (26.81 %) and alcohol use (9.19%) among patients with dementia in this setting. The level of heterogeneity was high due to differences in the methodologies in the included studies. Conclusions: Our study found hypertension as the most common comorbid condition among patients with dementia in India. The observed lacuna of methodological limitations in the studies included in the current meta-analysis provides the urgent need for good quality research to successfully meet the challenges ahead while devising appropriate strategies to treat the comorbidities among patients with dementia.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it