Risk factors for the alzheimer's disease. Systematic review and meta-analysis
Bibliographic record
Abstract
The “aging” of the population increased the importance of researches in the field of the epidemiology of chronic diseases, including Alzheimer's disease (AD) -the most common cause of dementia in the population. Aim . The role of potential risk factors for AD through a systematic review and meta-analysis. The “aging” of the population has updated research in the field of the epidemiology of chronic diseases, incl. Alzheimer's disease (AD) is the most common cause of dementia in the population. The aim of the study was to assess the role of potential risk factors for AD through a systematic review and meta-analysis. Materials and Methods . Using the electronic databases PubMed, Scopus, E-library, a search was made for articles in Russian and English, published from 1995 to 2022. In accordance with the clinical question, using the PECO formula, papers were selected in which the authors investigated the role of various risk factors in groups with and without AD. The study was carried out in accordance with the international guidelines for writing systematic reviews and meta-analyses "PRISMA". Study quality was analyzed using the Newcastle-Ottawa scale for cohort and case-control studies. The degree of heterogeneity was assessed using the chi-square test and the I2 coefficient. Publication bias was analyzed using a funnel plot. We used the software Review Manager 5.3 and Microsoft Office Excel 2010. Results . Initially, 3197 articles were retrieved from the databases; After screening and eligibility analysis, 17 studies were included in the me-ta-analysis (11 case-control studies and 6 cohort studies). Totally, these publications included data from 134,732 people with a confirmed diagnosis of AD and 1,058,143 respondents without AD (control group). According to the results of the meta-analysis, significant risk factors were: heredity (odds ratio (OR) 1.82; 95% confidence interval (95% CI) 1.66-1.99), arterial hypertension (OR 1.65; 95% CI 1.29-2.13), hypercholesterolemia (OR 1.25; 95% CI 1.13-1.38), obesity (OR 1.13; 95% CI 1.09-1.17), presence of diabetes mellitus 2 type (OR 1.36; 95%; CI 1.15-1.62), low level of education (OR 1.61; 95% CI 1.18-2.18), depression (OR 1.35; 95% CI 1.03-1.76). There was no relationship with alcohol consumption, smoking, a history of myocardial infarction and / or coronary heart disease, a history of acute cerebrovascular accident, insomnia, female gender, traumatic brain injury. Conclusion . The conducted meta-analysis allowed to obtain confirmation of the role of various potential risk factors for AD; at the same time, many of them are modifiable and are associated with metabolic disorders, which can probably be involved into the process of accumulation and deposition of beta-amyloid in the cells of the nervous system. Continued research on this issue could contribute to the development of prognostic scales and personalized recommendations for the prevention of this currently incurable disease.
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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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.027 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".