Lower cognitive function in patients with age-related macular degeneration: a meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To investigate the cognitive impairment in patients with age-related macular degeneration (AMD). METHODS: Relevant articles were identified through a search of the following electronic databases through October 2015, without language restriction: 1) PubMed; 2) the Cochrane Library; 3) EMBASE; 4) ScienceDirect. Meta-analysis was conducted using STATA 12.0 software. Standardized mean differences with corresponding 95% confidence intervals were calculated. All of the included studies met the following four criteria: 1) the study design was a case-control or randomized controlled trial (RCT) study; 2) the study investigated cognitive function in the patient with AMD; 3) the diagnoses of AMD must be provided; 4) there were sufficient scores data to extract for evaluating cognitive function between cases and controls. The Newcastle-Ottawa Scale criteria were used to assess the methodological quality of the studies. RESULTS: Of the initial 278 literatures, only six case-control and one RCT studies met all of the inclusion criteria. A total of 794 AMD patients and 1,227 controls were included in this study. Five studies were performed with mini-mental state examination (MMSE), two studies with animal fluency, two studies with trail making test (TMT)-A and -B, one study with Mini-Cog. Results of the meta-analysis revealed lower cognitive function test scores in patients with AMD, especially with MMSE and Mini-Cog test (P≤0.001 for all). The results also showed that differences in the TMT-A (except AMD [total] vs controls) and TMT-B test had no statistical significance (P>0.01). The Newcastle-Ottawa Scale score was ≥5 for all of the included studies. Based on the sensitivity analysis, no single study influenced the overall pooled estimates. CONCLUSION: This meta-analysis suggests lower cognitive function test scores in patients with AMD, especially with MMSE and Mini-Cog test. The other cognitive impairment screening tests, such as animal fluency test and TMT, need more studies to assess.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.040 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".