Association of acute kidney injury with the risk of cognitive impairment or dementia: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Since previous studies have shown a paradoxical relationship between acute kidney injury (AKI) and risk of cognitive impairment, there is an urgent need for a meta-analysis to assess the relationship between AKI and risk of cognitive impairment or dementia. MATERIALS AND METHODS: From database inception to October 2023, we searched PubMed, OVID (Medline), Embase, Web of Science, and Cochrane Library. This study examined AKI and cognitive impairment or dementia observational studies. Two authors independently assessed cohort and cross-sectional study quality using the Newcastle-Ottawa Scale and AHRQ Scale. They also used ROBINS-I to assess bias. The meta-analysis used fixed effects. Sensitivity analysis verified results stability. The funnel plot, Egger test, and Begg test determined publication bias in the results. RESULTS: = 0.08). All subgroups showed a substantial connection between AKI and cognitive impairment. Compared to domestic research, the connection was stronger in overseas studies (OR = 2.18, 95% CI: 1.66-2.87). Both cognitive impairment and dementia outcomes showed a substantial connection between AKI and cognitive impairment, with OR values of 2.00 (95% CI: 1.44-2.76) and 2.04 (95% CI: 1.66-2.51). CONCLUSIONS: We found that AKI significantly increases cognitive impairment or dementia risk. Thus, early interventions to delay cognitive impairment and prevent adverse outcomes in AKI patients are needed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it