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Record W4307958530 · doi:10.1016/j.arr.2022.101762

Association of kidney function and brain health: A systematic review and meta-analysis of cohort studies

2022· review· en· W4307958530 on OpenAlexaboutno aff
Xingyao Tang, Yipeng Han, Yin-He Chai, Hongjian Gong, Hui Xu, Ikramulhaq Patel, Yu-Shun Qiao, Jinyan Zhang, Marly Augusto Cardoso, Jianbo Zhou

Bibliographic record

VenueAgeing Research Reviews · 2022
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMeta-analysisMedicineRenal functionCochrane LibraryKidney diseaseInternal medicineSubgroup analysisDementiaConfidence intervalSystematic reviewCohort studyRelative riskPopulationMEDLINEDiseaseBiologyEnvironmental health

Abstract

fetched live from OpenAlex

This study aimed to evaluate the bidirectional association between the kidney dysfunction and the brain health, including structural and functional abnormalities. Systematic review and meta-analysis with network meta-analysis for outcomes with different estimated glomerular filtration rate (eGFR) ranges. PubMed, Embase database, Cochrane library and Web of Science (up to Dec. 2021). Longitudinal studies that provided evidence of the impact of kidney function estimated from eGFR and urine albumin-to-creatinine ratio (UACR) or chronic kidney disease (CKD) on structural and functional brain abnormalities, and those that provided evidence of the opposite relationship. Studies with study population mean age under 18 years old were excluded. Two independent reviewers screened the included studies, extracted the data, and assessed the risk of bias. We performed a random-effects meta-analysis and a network meta-analysis for outcomes with compatible data. We assessed the risk of bias using the Newcastle–Ottawa Quality Assessment Scale criteria (NOS). Subgroup and sensitivity analyses were conducted to explore heterogeneity in the meta-analyses. Inconsistency analyses using the node-splitting method were performed to confirm the results of network meta-analysis. A total of 53 studies with 3037,357 participants were included in the current systematic review. Among these, 16 provided evidence of structural brain abnormalities, and 38 provided evidence of cognitive impairment and dementia. Analysis of evidence of categorical kidney function showed a positive association between kidney dysfunction and cerebral small vessel disease (cSVD) (relative risk (RR) 1.77, 95% confidence interval (CI) 1.40–2.24, I2 = 0.0%), but such results were not found in the analyses of evidence where the kidney function was measured as a continuous variable. Meanwhile, analysis of 28 prior longitudinal studies with 194 compatible sets of data showed that the worse kidney function as categorical variables was related to a greater risk of global brain cognitive disorder (RR 1.28, 95% CI 1.20–1.36, I2 = 82.5%). In this systematic review and meta-analysis, we found a positive association between CKD and functional brain disorders. However, the relationship between the kidney dysfunction and structural abnormalities in the brain remains controversial. As for the opposite relationship, structural brain abnormalities, especially cerebral microbleeds and silent infarction, but not functional brain abnormalities, are associated with worse renal function. In addition, a higher UACR, but not a lower eGFR, was associated with a higher risk of Alzheimer’s disease and vascular dementia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.037
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.587
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0370.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0180.003
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.381
GPT teacher head0.508
Teacher spread0.126 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations55
Published2022
Admission routes1
Has abstractyes

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