Impact of comorbid anxiety and depression on heart failure diagnosis, hospitalisation, and survival outcomes: an observational study of over 400,000 patients in England
Bibliographic record
Abstract
Abstract Background Multimorbidity of mental health conditions and heart failure (HF) are common but the impact of these comorbidities on HF diagnosis and outcomes is not well understood. Purpose To investigate trends in comorbid anxiety and/or depression over time in patients newly diagnosed with HF and their impact on diagnosis timing, location, and survival after diagnosis. Methods Using primary care and hospital records from England (2000–2021), we identified adults newly diagnosed with HF. We examined first primary care indicators suggestive of HF (e.g., shortness of breath, ankle swelling, loop diuretic use) within 5 years before diagnosis and mental health conditions (depression only, anxiety only or depression and anxiety) in the year before diagnosis of HF. Diagnosis location (outpatient or inpatient) was also assessed. Mortality associations were adjusted for patient characteristics. Results Among 412,173 new HF diagnoses (median age 78 years, 47% women), 16.8% had depression only, 4.1% had anxiety only, and 5% had both anxiety and depression. Women had higher rates of mental health comorbidities than men (Figure 1), with significant increases between 2000 and 2020 in depression (up 10% in women, 5% in men) and combined anxiety and depression (up 5% in women, 2% in men). Approximately 50% of patients had recorded HF symptoms within 5 years before diagnosis and 45% were prescribed loop diuretics. Patients with mental health conditions experienced longer delays to diagnosis; those with depression alone waited 11 months (men) or 8 months (women) longer than those without mental health conditions. Men with anxiety or depression were more than 20% more likely to be diagnosed as an inpatient, and 43% more likely when both conditions were present (adjOR 1.43; 1.36 to 1.51). For women, anxiety alone was strongly associated with inpatient diagnosis (adjOR 1.29; 1.23 to 1.36), as was depression alone (adjOR 1.16; 1.13 to 1.19), with the strongest association in those with both (adjOR 1.54; 1.47 to 1.61). The risk of mortality within 1 year after Hf diagnosis was similarly increased in the presence of anxiety or depression alone, but highest for those with both conditions. This pattern was stronger in men, where combined anxiety and depression was associated with a 36% increase in risk of mortality (adjHR 1.36; 1.28, 1.44), compared to 16% in women (adjHR 1.16; 1.11 to 1.22) (interaction p =0.001). In longer follow-up, men with depression (with or without anxiety) had the lowest survival (Figure 2). Conclusion Anxiety and depression are very prevalent in patients prior to new diagnosis of HF and associated with longer delays to diagnosis and poorer survival outcomes following diagnosis.Figure 1:Trends in MH conditions Figure 2:Age adjusted survival
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".