High-sensitivity cardiac troponin I and risk of dementia: the 25-year longitudinal Whitehall II study
Bibliographic record
Abstract
BACKGROUND AND AIMS: This study hypothesizes that subclinical myocardial injury during midlife, indexed by increases in cardiac troponin I, is associated with accelerated cognitive decline, smaller structural brain volume, and higher risk of dementia. METHODS: Overall, 5985 participants in the Whitehall II study, aged 45-69 who had cardiac troponin I measured by a high-sensitivity assay at baseline (1997-99), were followed until March 2023. The outcome measure was incident dementia; cognitive testing was performed at six waves; and neuroimaging metrics were obtained from magnetic resonance imaging scans in 2012-16. Cox model and linear mixed model were used to examine the association of cardiac troponin with incident dementia and cognitive trajectory. A nested case-control sample of 3475 participants (695 dementia cases and 2780 matched controls) was used for backward trajectory analysis for cardiac troponin, measured at three waves (1997-99, 2007-09, 2012-13). RESULTS: A total of 606 (10.1%) cases of dementia were recorded over a median follow-up of 24.8 years. Doubling of cardiac troponin was associated with 10% (95% confidence interval 3%-17%) higher risk of dementia. Participants with increased cardiac troponin at baseline had a faster decline of cognitive function. Participants with dementia had increased cardiac troponin concentrations compared with those without dementia between 7 and 25 years before diagnosis. Compared with those with cardiac troponin levels < 2.5 ng/L at baseline, those with concentrations > 5.2 ng/L had lower grey matter volume and higher hippocampal atrophy 15 years later, equivalent to ageing effects of 2.7 and 3 years, respectively. CONCLUSIONS: Subclinical myocardial injury at midlife was associated with higher dementia risk in later life.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".