Impact of non-cardiovascular disease comorbidity on cardiovascular disease symptom severity: A population-based study
Bibliographic record
Abstract
OBJECTIVES: Non-cardiovascular comorbidity is common in cardiovascular disease (CVD) populations but its influence on chest pain (CP) and shortness of breath (SOB) symptom-specific physical limitations is unknown. We wanted to test the a priori hypothesis that an unrelated comorbidity would influence symptom-specific physical limitations and to investigate this impact in different severities of CVD. METHOD AND RESULTS: The study was based on 5426 patients from ten family practices, organised into eight a priori exclusive severity groups: (i) no CVD or osteoarthritis (OA) (reference), (ii) index hypertension, ischaemic heart disease (IHD) and heart failure (HF) without OA, (iii) index OA without CVD and (iv) same CVD groups with comorbid OA. The measure of CP physical limitations was Seattle Angina Questionnaire and for SOB physical limitations was the Kansas City Cardiomyopathy Questionnaire. Adjusted baseline associations between the cohorts and symptom-specific physical limitations were assessed using linear regression methods. In the study population, 1443 (27%) reported CP and 2097 (39%) SOB. CP and SOB physical limitations increased with CVD severity in the index and comorbid groups. Compared with the respective index CVD group, the CP physical limitation scores for comorbid CVD groups with OA were lower by: -14.7 (95% CI -21.5, 7.8) for hypertension, -5.5 (-10.4, -0.7) for IHD and -22.1 (-31.0, -6.7) for HF. For SOB physical limitations, comorbid scores were lower by: -9.2 (-13.8, -4.6) for hypertension, -6.4 (-11.1, -1.8) for IHD and -8.8 (-19.3, 1.65) for HF. CONCLUSIONS: CP and SOB are common symptoms, and OA increases the CVD symptom-specific physical limitations additively. Comorbidity interventions need to be developed for CVD specific health outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| 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 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".