Comprehensive Analysis of Dementia Types and Risk Factors: A Study From a Tertiary Care Center in India
Bibliographic record
Abstract
Background and objective Dementia is a prevalent clinical syndrome characterized by memory impairment and cognitive dysfunction. Its global burden is expected to rise significantly, particularly in low- and middle-income countries. Understanding the spectrum of dementia types and associated risk factors is crucial for effective management. This study aims to elucidate the demographic profiles, clinical types, and risk factors of newly diagnosed dementia cases at a tertiary care hospital in India. Methods and materials A cross-sectional, hospital-based observational study was conducted on 81 patients at the Department of Medicine, Dr. D. Y. Patil Medical College, Hospital, and Research Centre, Pimpri, Pune, from February 2022 to January 2024. Ethical approval was obtained, and written consent was obtained from participants. Clinical diagnosis was based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) criteria, supported by cognitive assessment tools and laboratory/radiological investigations. Inclusion criteria encompassed individuals aged 18 years or older, presenting with clinical symptoms suggestive of dementia, having a Mini-Mental State Examination (MMSE) score of less than 24 and Montreal Cognitive Assessment (MoCA) score of less than 25, according to DSM-V criteria for dementia. Exclusion criteria included individuals with a history of head trauma or those below 18 years of age. Results Of the 81 participants, the majority (74.1%) were over 60 years old, with females comprising 59.3% of the sample. Alzheimer's disease was the most prevalent dementia subtype (34.5%), followed by vascular dementia (19.7%) and mixed dementia (13.5%). Other causes included Lewy body dementia (2.46%), Parkinson's dementia (4.9%), frontotemporal dementia (4.9%), and Creutzfeldt-Jakob disease (1.2%). Reversible causes accounted for a significant proportion of cases: alcohol-associated dementia (6.1%), hypothyroid-associated dementia (3.7%), HIV-associated dementia (2.46%), herpes simplex dementia (1.2%), neurosyphilis-associated dementia (1.2%), and normal pressure hydrocephalus (NPH)-associated dementia (2.4%). Analysis of risk factors revealed distinct patterns among different dementia types, emphasizing the role of cardiovascular and metabolic health. Conclusion This study provides insights into the demographic profiles, clinical types, and dementia risk factors in India. Addressing causes and managing cardiovascular/metabolic health is crucial for dementia prevention and management. Comprehensive care strategies and ongoing research efforts are essential for improving dementia outcomes and enhancing the quality of life for affected individuals and their families.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".