Impact of comorbid anxiety and depression on heart failure diagnosis, hospitalisation, and survival outcomes: an observational study of over 400,000 patients in England
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».