Association between glycated hemoglobin and cognitive impairment in older adults with coronary heart disease: a multicenter prospective cohort Study
Bibliographic record
Abstract
<sec><strong>Background</strong> The relationship between glycated hemoglobin (HbA1c) and cognitive impairment in older adults with coronary heart disease (CHD) remains unclear. </sec><sec><strong>Methods</strong> The present study used a prospective cohort study design and included 3244 participants aged ≥ 65 years in Beijing, China. The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess cognitive function. Serum HbA1c was detected at admission. All patients were divided into high HbA1c group (≥ 6.5 mmol/L) and low HbA1c group (< 6.5 mmol/L) based on their HbA1c levels. Logistic regression analyses were used to evaluate the association between HbA1c and cognitive impairment. </sec><sec><strong>Results</strong> In this study of 3244 participants, 1201 (37.0%) patients were in high HbA1c group and 2045 (63.0%) patients were in a state of cognitive impairment. Logistic regression analyses demonstrated that HbA1c was an independent risk factor for cognitive impairment regardless of whether the HbA1c was a continuous or categorical variable (OR = 1.27, 95% CI: 1.15–1.40, <i>P</i> < 0.001; OR = 1.79, 95% CI: 1.41–2.26, <i>P</i> ≤ 0.001, respectively). The restricted cubic spline curve exhibited that the relationship between the HbA1c and cognitive impairment was linear (p for non-linear = 0.323, <i>P</i> < 0.001). </sec><sec><strong>Conclusion</strong> Elevated levels of HbA1c were associated with an increased risk of cognitive impairment in older patients with CHD. These insights could be used to improve the accuracy and sensitivity of cognitive screening in these patient populations. </sec>
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".