Subclinical Cardiac Dysfunction and Cognitive Function: A Systematic Review
Bibliographic record
Abstract
Abstract Background: Cardiovascular disease, and more recently, subclinical cardiac dysfunction have both been implicated as important risk factors for cognitive decline. Several measures have been used to detect subclinical cardiac dysfunction, with global longitudinal strain (GLS) emerging as an important and more sensitive indicator than traditional measures. Yet, the association of GLS with cognitive function remains relatively unexplored. Objective: The aim of this review is to systematically summarize the literature exploring the association between GLS and cognitive function. Methods: We conducted a systematic review of the literature following PRISMA guidelines using the following databases: PubMed, OVID Medline, Embase, Web of Science, and CINAHL. Inclusion criteria were observational studies published in English, measuring GLS and assessing cognitive function through neuropsychiatric tests or brain imaging. Quality assessment was done using the Newcastle Ottawa Scale. Results: The initial search revealed 394 studies, of which three met inclusion criteria and were included for final review. The three studies included were cross-sectional and of high quality. They all reported that lower GLS scores were associated? with worse cognitive function and more brain abnormalities in both bivariate and multivariable analysis. Conclusion: Subclinical cardiac dysfunction, identified by GLS, was associated with worse cognitive function and presence of cerebral abnormality on brain imaging. The underlying mechanism could be attributed to dysfunctional autoregulatory and microvascular processes occurring in the brain vasculature. Further longitudinal studies are needed to better delineate the relationship between GLS and cognitive function.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".