Patient-reported outcomes are independent predictors of one-year mortality and cardiac events across cardiac diagnoses: Findings from the national DenHeart survey
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Patient-reported quality of life and anxiety/depression scores provide important prognostic information independently of traditional clinical data. The aims of this study were to describe: (a) mortality and cardiac events one year after hospital discharge across cardiac diagnoses; (b) patient-reported outcomes at hospital discharge as a predictor of mortality and cardiac events. DESIGN: A cross-sectional survey with register follow-up. METHODS: Participants: All patients discharged from April 2013 to April 2014 from five national heart centres in Denmark. MAIN OUTCOMES: Patient-reported outcomes: anxiety and depression (Hospital Anxiety and Depression Scale); perceived health (Short Form-12); quality of life (HeartQoL and EQ-5D); symptom burden (Edmonton Symptom Assessment Scale). Register data: mortality and cardiac events within one year following discharge. RESULTS: There were 471 deaths among the 16,689 respondents in the first year after discharge. Across diagnostic groups, patients reporting symptoms of anxiety had a two-fold greater mortality risk when adjusted for age, sex, marital status, educational level, comorbidity, smoking, body mass index and alcohol intake (hazard ratio (HR) 1.92, 95% confidence interval (CI) 1.52-2.42). Similar increased mortality risks were found for patients reporting symptoms of depression (HR 2.29, 95% CI 1.81-2.90), poor quality of life (HR 0.46, 95% CI 0.39-0.54) and severe symptom distress (HR 2.47, 95% CI 1.92-3.19). Cardiac events were predicted by poor quality of life (HR 0.71, 95% CI 0.65-0.77) and severe symptom distress (HR 1.58, 95% CI 1.35-1.85). CONCLUSIONS: Patient-reported mental and physical health outcomes are independent predictors of one-year mortality and cardiac events across cardiac diagnoses.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it