Relationship Between Advanced Glycation End Products Tissue Accumulation and Frailty in Patients Undergoing Cardiac Rehabilitation
Bibliographic record
Abstract
Background: The advanced glycation end products (AGEs), which can be assessed through skin autofluorescence (SAF), have been linked to chronic kidney disease (CKD), diabetes mellitus (DM), and aging. However, it is unknown how frailty and SAF levels are associated with cardiovascular disease (CVD). Methods: We enrolled 1,000 consecutive CVD patients who participated in phase II cardiac rehabilitation (CR) and underwent assessment of SAF between November 2015 and September 2017 at Juntendo University Hospital. Of these, 48 patients were excluded as duplicate cases, and a deficiency in SAF data led to the exclusion of an additional 146 patients. The final analysis included 806 patients. Results: Seventy percent of patients were male, and the mean age was 67.0 ± 12.9 years. In this study, the patients were divided into two groups (high SAF group and low SAF group) based on the median SAF level (2.9 a.u.), which is known as a cutoff value to increase the risk of CVD in previous studies. Compared with the low SAF group (n = 368, 45.7%), the high SAF group (n = 438; 54.3%) was older, and the Kihon Checklist (KCL) total score and prevalence of DM and CKD were significantly higher (all, P < 0.05). Multivariate regression analyses demonstrated that age was the only independent associated factor (P < 0.05) in the low SAF group. Conversely, in the high SAF group, creatinine, hemoglobin A1c (HbA1c) and the sub-total KCL score (1 - 20) were independently associated with SAF levels (all, P < 0.05). Conclusions: Frailty assessed by KCL is one of the factors significantly correlated with the accumulation of AGEs as well as creatinine, HbA1c and brain natriuretic peptide (BNP) levels in the high SAF group of patients with CVD undergoing phase II CR, who have the higher risk of the onset of CVD and all-cause mortality.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".