Outcome of Congestive Heart Failure, Dilated Cardiomyopathy, Hypertrophic Hyperkinetic Disease, and Ischemic Heart Disease in Dialysis Patients
Bibliographic record
Abstract
Congestive heart failure in dialysis patients is associated with dilated cardiomyopathy, hypertrophic hyperkinetic disease and ischemic heart disease. To determine the natural history of these four diseases, 150 dialysis patients were prospectively followed for 3-5 years. The 2-year cumulative survival rate was 33% in those with recurrent or persistent congestive heart failure vs. 80% in dialysis patients without. Survival was significantly worse in patients with an echocardiographic diagnosis of dilated cardiomyopathy compared to patients with normal echo-cardiogram (2-year survival rate 67 vs. 90%). In hypertrophic hyperkinetic disease the 2-year survival rate was 30% after entry into the study, and 43% after first admission with congestive heart failure. Symptomatic ischemic heart disease did not have an adverse impact on mortality when compared to those without ischemic heart disease. We conclude that congestive heart failure in dialysis patients has a bad prognosis. Its associated disorders include dilated cardiomyopathy and hypertrophic hyperkinetic disease, the latter being associated with a high mortality. As the prognosis for patients with overt ischemic heart disease was not different from patients without, it is likely that the underlying cardiomyopathy directly influenced survival.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".