Effect of Anticholinergic Medications on the Risk of Dementia: A Systematic Review and Meta-analysis Protocol
Bibliographic record
Abstract
Introduction: The most frequent dementia is senile dementia or Alzheimer disease. Meanwhile, anticholinergic drugs can potentially modify the risk factors. As different studies have achieved dissimilar results and the clinical findings of these interventions have not been conclusive, the objective of this research will be to evaluate the effect of anticholinergic drugs on the risk of dementia. Methods: This systematic review and meta-analysis with no language limitation will search WoS, EMBASE, and MEDLINE via PubMed, Scopus, ProQuest electronic databases, and Grey Literature between December 15, 1988, and December 15, 2021. Our search strategy with suitability criteria covers cohort, case-control, nested case-control, randomized, and non-randomized clinical trial studies evaluating the effect of anticholinergic drugs on the risk of dementia. Two authors will independently implement the selection phase, data extraction, and quality assessment. The reviewers will evaluate the risk of bias using the Newcastle-Ottawa, Cochrane risk of bias tool and ROBINS-I (risk of bias in non-randomized studies - of interventions) quality assessment scale. We will conduct a meta-analysis with a random or fixed effect model according to the severity of methodological heterogeneity. The results will be presented via the forest plot for the final studies' data composition, demonstrating the separated and combined frequency and their corresponding 95% CIs, summary tables, and narrative summaries. Conclusion: The results of different studies in this field are various. This study's findings and other studies will help physicians and other health professionals before prescribing these drugs. Older people, especially those with polypharmacy, should be carefully assessed for the risk of dementia, Alzheimer or a variety of cognitive disorders.
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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 | 0.076 | 0.098 |
| Meta-epidemiology (narrow) | 0.008 | 0.007 |
| Meta-epidemiology (broad) | 0.025 | 0.030 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.061 | 0.007 |
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".