Association of Heart Rate Recovery With Microalbuminuria in Non-Obstructive Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Non-obstructive coronary artery disease (CAD) is associated with significantly increased risk for myocardial infarction. Heart rate recovery (HRR), a measure of autonomic function, is a strong predictor of all-cause mortality. Microalbuminuria, a marker of early arterial disease, is an independent risk factor for cardiovascular disease and mortality. We aimed to investigate HRR and determine its relationship with microalbuminuria in patients with non-obstructive CAD. METHODS: We prospectively studied 565 patients who underwent elective coronary angiography. All participants underwent urinary analysis and then an exercise test. Microalbuminuria was defined as an urinary albumin-to-creatinine ratio (UACR) of 30 - 299 mg/g. The HRR was abnormal if ≤ 12 beats/min during the first minute after exercise. First, all patients were divided into two groups, patients with microalbuminuria (n = 152) and patients without microalbuminuria (n = 413). Then, all patients were re-divided into two groups, those with lower HRR (≤ 12 beats/min, n = 126) and those with higher HRR (> 12 beats/min, n = 439). RESULTS: Patients with microalbuminuria had lower HRR and patients with lower HRR had higher UACR. While UACR was negatively correlated with HRR in patients with microalbuminuria (r = -0.424; P < 0.001) and in patients with lower HRR (r = -0.192; P= 0.042), there was no correlation of UACR with HRR in neither patients with normoalbuminuria nor patients with higher HRR, respectively. In the all study population, there was a significant inverse association between UACR and HRR (r = -0.445, P < 0.001), and UACR independently predicted the presence of lower HRR (P < 0.001). CONCLUSIONS: Our findings showed that there was a significant inverse association between UACR and HRR in patients especially with microalbuminuria, and that albuminuria might predict cardiac autonomic imbalance evaluated by HRR in patients with non-obstructive CAD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".