Length of Delay in Seeking Medical Care by Patients with Heart Failure Symptoms and the Role of Symptom-Related Factors: A Narrative Review
Bibliographic record
Abstract
AIMS: The delay in seeking timely medical care by patients with acute coronary syndrome and stroke is well established. Less is known about the delay in patients with heart failure (HF). Reducing the delay in seeking care and the early initiation of treatment is associated with improved outcomes in patients with HF. The purpose of this narrative review was to describe the length of the delay in seeking care for HF symptoms and identify symptom-related factors that contribute to the delay in seeking medical care. METHODS AND RESULTS: A literature search was conducted to identify English language studies that (i) describe the length of care-seeking delay for HF symptoms and/or (ii) identify symptom-related factors that contribute to delay in seeking medical care. The results of this review demonstrate that upon hospital admission patients report wide variations in median symptom time course from 2 h to 7 days from the onset of symptoms to hospital admission. The ability of patients to recognize, interpret, and appraise HF symptoms has been demonstrated to be limited. Symptom characteristics such as dyspnoea, oedema, orthopnoea, higher somatic awareness, higher symptom distress, nocturnal symptom onset, and the pattern of symptom onset were related to longer delay in care-seeking for HF symptoms. Furthermore, cognitive responses to HF may also play an important role in symptom appraisal. CONCLUSION: Delays in seeking care for HF symptoms have been shown to range from hours to days from symptom onset to hospital admission. Healthcare professionals should therefore be more vigilant in identifying high-risk individuals and educating them about the warning signs of HF. Moreover, access to outpatient chronic disease management programmes may have the potential to reduce these delays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".