Global prevalence of mild cognitive impairment among older adults living in nursing homes: a meta-analysis and systematic review of epidemiological surveys
Bibliographic record
Abstract
Mild cognitive impairment (MCI) is the early stage of cognitive impairment between the expected cognitive decline of normal aging and the more serious decline of dementia. This meta-analysis and systematic review explored the pooled global prevalence of MCI among older adults living in nursing homes and its relevant factors. The review protocol was registered in INPLASY (INPLASY202250098). PubMed, Web of Science, Embase, PsycINFO, and CINAHL databases were systematically searched from their respective inception dates to 8 January 2022. The inclusion criteria were made based on the PICOS acronym, as follows: Participants (P): Older adults living in nursing homes; Intervention (I): not applicable; Comparison (C): not applicable; Outcome (O): prevalence of MCI or the data can generate the prevalence of MCI according to study-defined criteria; Study design (S): cohort studies (only baseline data were extracted) and cross-sectional studies with accessible data published in a peer-reviewed journal. Studies involving mixed resources, reviews, systematic reviews, meta-analyses, case studies, and commentaries were excluded. Data analyses were performed using Stata Version 15.0. Random effects model was used to synthesize the overall prevalence of MCI. An 8-item instrument for epidemiological studies was used to assess the quality of included studies. A total of 53 articles were included involving 376,039 participants with a mean age ranging from 64.42 to 86.90 years from 17 countries. The pooled prevalence of MCI in older adults in nursing homes was 21.2% (95% CI: 18.7-23.6%). Subgroup and meta-regression analyses revealed that the screening tools used were significantly associated with MCI prevalence. Studies using the Montreal Cognitive Assessment (49.8%) had a higher prevalence of MCI than those using other instruments. No significant publication bias was found. Several limitations warrant attention in this study; for example, significant heterogeneity between studies remained and some factors associated with the prevalence of MCI were not examined due to insufficient data. Adequate screening measures and allocation of resources are needed to address the high global prevalence of MCI among older adults living in nursing homes.
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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 | 0.027 | 0.062 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".