[Increased incidence of coronary artery disease and cardiac death in elderly diabetic nephropathy patients undergoing chronic hemodialysis therapy].
Bibliographic record
Abstract
OBJECTIVES: The incidence of coronary artery disease and cardiac death was investigated in elderly diabetic patients undergoing chronic hemodialysis therapy. METHODS: Three hundred thirty-five patients who began hemodialysis therapy since 1992 were followed up by echocardiography and treadmill exercise testing. Coronary angiography was also performed in patients with angina pectoris. Angina pectoris was defined as clinical symptoms > Canadian Cardiovascular Society classification II, and asynergy findings by echocardiography or ST depression > 0.1 mV during the treadmill exercise test. Coronary artery stenosis was defined as narrowing > or = 75%. Patients were divided into 4 groups: diabetic nephropathy (DN) > or = 65 years old (Group O/DN, n = 56), DN < 65 years old (Group Y/DN, n = 84), non-DN > or = 65 years old (Group O/non-DN, n = 76) and non-DN < 65 years old (Group Y/non-DN, n = 119). RESULTS: Between 1992 and 1998, there were 137 patients with angina pectoris (40.9%), 79 with coronary artery stenosis (23.6%) and 37 with cardiac death (11.0%). Cumulative incidences of angina pectoris, coronary artery stenosis and cardiac death were significantly higher in the following order of groups; O/DN > Y/DN > O/non-DN > Y/non-DN. Five-year cumulative incidences of angina pectoris, coronary artery stenosis and cardiac death in Groups O/DN vs Y/non-DN were 72.2% vs 38.6%, 53.7% vs 12.2% and 50.6% vs 3.5%, respectively. Relative risks of aging and diabetic nephropathy for angina pectoris, coronary artery stenosis and cardiac death were 3.8, 7.9 and 22.4, respectively (p < 0.0001). CONCLUSIONS: Aging and the presence of diabetes are strong risk factors for coronary artery disease and cardiac death in hemodialysis patients. Therefore, diagnosis and treatment of coronary artery disease should be achieved at the early stage of hemodialysis therapy.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".