A Prognostic Index to Predict Long-Term Mortality in Patients with Mild to Moderate Chronic Heart Failure Stabilised on Angiotensin Converting Enzyme Inhibitors
Bibliographic record
Abstract
BACKGROUND: Mortality in patients with mild to moderate chronic heart failure remains high. At present there is no easy way of identifying patients within this population at increased risk of death in the medium to long term. AIMS: To develop a prognostic index to identify outpatients with mild to moderate chronic heart failure at increased risk of death. METHODS AND RESULTS: Five hundred and fifty-three outpatients mean (S.D.) age 63(+/-10) years with symptoms of chronic heart failure (mean New York Heart Association functional class, 2.3(+/-0.5)), were recruited between December 1993 and April 1995. By April 2000, 201 patients had died. Using data from non-invasive measurements of cardiac size, electrical and autonomic function, renal function and plasma biochemistry we identified eight independent predictors of mortality (all P<0.01). To develop a prognostic index, predictors were dichotomised by group median and awarded 0 or 1 point accordingly. Serum sodium </=140 mmol/l (1 point), creatinine >/=111 micromol/l (1 point), cardiothoracic ratio >/=0.52 (1 point), SDNN </=112 ms (1 point), maximum corrected QT interval >/=487 ms (1 point), QRS dispersion>/=42.7 ms (1 point), the presence of non-sustained ventricular tachycardia (1 point) and voltage criteria for left ventricular hypertrophy on 12-lead ECG (1 point). We calculated risk scores for patients by adding the points of each independent risk factor. In the low-risk group (0-3 points) mortality at 5 years was 20% and in the high-risk group (4-8 points) 53%. The area under the receiver-operator characteristic curve using dichotomised variables was 0.74 and for continuous model 0.78. CONCLUSIONS: Our prognostic index which uses eight non-invasive measurements and a straightforward additive points system, has good discrimination and stratifies outpatients with chronic heart failure into high and low risk. This index may be useful in clinical care and risk stratification.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".