Developing a core indicator set for identifying people at risk of undiagnosed heart failure
Bibliographic record
Abstract
Abstract Background Most heart failure (HF) diagnoses occur during hospital admission, but the patient, clinical and service level factors underlying delayed diagnosis remain unclear Purpose This study aimed to establish a consensus core outcome set (COS) of patient, clinical and service level factors associated with delayed HF diagnosis and identify a set of indicators for identifying undiagnosed HF in primary care. Methods A three-round modified e-Delphi method involved patients and clinicians from primary and specialist care. All participants rated sociodemographic and clinical factors for their importance in delayed HF diagnosis and clinicians also rated service-level factors and identified indicators of undiagnosed HF. Consensus was defined as two-thirds agreement with stable opinions across rounds based on a McNemar test (p<0.05), with indicators of undiagnosed HF requiring additional ranking in the top 5 by >50% of clinicians. Results The first Delphi survey was completed by 18 patients and 27 clinicians (Table 1). Patient participants included 12 (67%) women with a median age of 61 (IQR 51-65) years. Clinician participants included 18 nurses or allied health professionals (67%) and 9 doctors (33%). Nearly all clinicians had over 10 years of experience post-professional registration (93%), and 52% had worked in heart failure care for more than 10 years. Regarding their practice settings, 12 (44%) worked in a HF community or general practice setting, 11 (41%) in a HF hospital setting, and 4 (15%) in non-HF or research roles. The second survey was returned by all 18 patients and 23 clinicians and the third by 17 patients and 17 clinicians. A COS was established, comprising 15 factors and 5 indicators of undiagnosed HF (Figure 1). Key sociodemographic factors included lack of HF knowledge, lack of access to general practitioners or cardiologists, symptom confusion, younger age (<50 years), and learning difficulties. Clinical factors included multimorbidity, respiratory/mental health conditions, obesity, and depression. Service-level factors included poor HF knowledge, inadequate HFpEF recognition, limited BNP testing and echocardiogram access in primary care, and fragmented care. The top five indicators of undiagnosed HF were elevated BNP with no referral, current loop diuretic use with or without cardiac history, and overlapping cardiac and respiratory histories. Conclusions This study highlights critical factors and indicators to aid earlier HF diagnosis in primary care. Targeted interventions, such as clinician education and diagnostic support tools, are essential to address delays and improve patient outcomes.Table 1:Participant information Figure 1:Top 5 ranked factors
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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 | 0.031 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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".