| アブストラクト | BACKGROUND: Whether the accuracy of the phenotype ascribed to patients in electronic health records (EHRs) is associated with variation in prognosis and care provision is unknown. We investigated this for heart failure (HF, characterised as HF with preserved ejection fraction [HFpEF], HF with reduced ejection fraction [HFrEF] and unspecified HF). METHODS: We included individuals aged 16 years and older with a new diagnosis of HF between January 2, 1998 and February 28, 2022 from linked primary and secondary care records in the Clinical Practice Research Datalink in England. We investigated the provision of guideline-recommended diagnostic investigations and pharmacological treatments. The primary outcome was a composite of HF hospitalisation or all-cause death, and secondary outcomes were time to HF hospitalisation, all-cause death and death from cardiovascular causes. We used Kaplan-Meier curves and log rank tests to compare survival across HF phenotypes and adjusted for potential confounders in Cox proportional hazards regression analyses. FINDINGS: Of a cohort of 95,262 individuals, 1271 (1.3%) were recorded as having HFpEF, 10,793 (11.3%) as HFrEF and 83,198 (87.3%) as unspecified HF. Individuals recorded as unspecified HF were older with a higher prevalence of dementia. Unspecified HF, compared to patients with a recorded HF phenotype, were less likely to receive specialist assessment, echocardiography or natriuretic peptide testing in the peri-diagnostic period, or receive angiotensin-converting enzyme inhibitors, beta blockers or mineralocorticoid receptor antagonists up to 12 months after diagnosis (risk ratios compared to HFrEF, 0.64, 95% CI 0.63-0.64; 0.59, 0.58-0.60; 0.57, 0.55-0.59; respectively) and had significantly worse outcomes (adjusted hazard ratios compared to HFrEF, HF hospitalisation and death 1.66, 95% CI 1.59-1.74; all-cause mortality 2.00, 1.90-2.10; cardiovascular death 1.77, 1.65-1.90). INTERPRETATION: Our findings suggested that absence of specification of HF phenotype in routine EHRs is inversely associated with clinical investigations, treatments and survival, representing an actionable target to mitigate prognostic and health resource burden. FUNDING: Japan Research Foundation for Healthy Aging and British Heart Foundation. |
|---|
| 投稿者 | Nakao, Yoko M; Nakao, Kazuhiro; Nadarajah, Ramesh; Banerjee, Amitava; Fonarow, Gregg C; Petrie, Mark C; Rahimi, Kazem; Wu, Jianhua; Gale, Chris P |
|---|
| 組織名 | Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds,;Leeds, UK.;Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.;Department of Pharmacoepidemiology, Graduate School of Medicine and Public;Health, Kyoto University, Kyoto, Japan.;Department of Cardiovascular Medicine, National Cerebral and Cardiovascular;Center, Suita, Japan.;Department of Cardiology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.;Institute of Health Informatics, University College London, London, UK.;Department of Cardiology, Barts Health NHS Trust, London, UK.;Division of Cardiology, Department of Medicine, University of California at Los;Angeles, Los Angeles, USA.;Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow,;UK.;Nuffield Department of Women's and Reproductive Health, University of Oxford,;Oxford, UK.;National Institute of Health Research Oxford Biomedical Research Centre, Oxford;University Hospitals NHS Foundation Trust, Oxford, UK.;Deep Medicine, Oxford Martin School, University of Oxford, Oxford, UK.;Oxford University Hospitals NHS Foundation Trust, Oxford, UK.;Wolfson Institute of Population Health, Queen Mary University of London, London, |
|---|
