Benefits of heart valve clinics for patients: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of heart valve clinics (HVCs) versus standard of care (SOC) on disease detection, timing of intervention and clinical outcomes in patients with valvular heart disease (VHD). DESIGN: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and registered in PROSPERO (CRD42024518787). DATA SOURCES: PubMed, Embase, Web of Science, Scopus and the Cochrane Library from inception to 1 May 2025. ELIGIBILITY CRITERIA: Randomised controlled trials or cohort studies comparing patients managed in HVCs with those receiving SOC, and reporting on outcomes such as mortality, cardiac events, time to symptom reporting or symptom severity. Studies were excluded if they lacked detailed HVC protocols, single-arm designs or were published as abstracts only. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened titles, abstracts and full texts, with discrepancies resolved by a senior adjudicator. The Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias. Meta-analysis was not conducted due to heterogeneity among studies. RESULTS: Three high-quality prospective cohort studies (N=1082) were included. Two studies reported mortality and cardiac events: one, a before-and-after controlled trial (n=382), recorded 11 deaths in the HVC group; the other reported 4 deaths in the HVC group (n=156) versus 17 deaths in the SOC group (n=156) (p<0.05). Additionally, two studies found that HVCs significantly reduced the interval between symptom onset and reporting (p<0.05), as well as the proportion of patients presenting with severe symptoms (defined as New York Heart Association (NYHA) class or Canadian Cardiovascular Society (CCS) class ≥III). CONCLUSION: HVCs facilitate stratified and precise management of the whole-life cycle of patients with VHD, enhancing early detection and referral, and leading to reduced mortality and major cardiac events compared with SOC.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".