MétaCan
Menu
← Back to cohort

Clinical characteristics and predictors of mortality in patients with refractory angina due to obstructive and non-obstructive chronic coronary syndromes: a contemporary retrospective cohort study

2025· article· en· W7128016186 on OpenAlexaboutno aff
Kevin Cheng, B Marlie, H Rajabali, P Collins, Ranil de Silva

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAnginaRetrospective cohort studyMyocardial infarctionConventional PCIProportional hazards modelHazard ratioDiabetes mellitusUnstable anginaObservational studyPopulation

Abstract

fetched live from OpenAlex

Abstract Background Refractory angina (RA) is a major global cardiovascular healthcare challenge due to the increasing burden of chronic coronary syndromes (CCS) worldwide and an ageing population [1, 2]. Patients suffer from persistent life-limiting angina despite maximal guideline-directed treatment; experience a poor quality of life; and incur significant excess healthcare costs. RA represents a large unmet clinical need with few contemporary data on the clinical characteristics and outcomes of these patients. Purpose This study investigated the characteristics and prognosis of patients with RA due to both obstructive and non-obstructive CCS. Methods Retrospective single-centre observational cohort study of patients diagnosed with RA, managed in a tertiary cardiac centre with a dedicated specialist angina service, between May 1995 to August 2023. Mortality was obtained from a national healthcare database and patient characteristics from hospital electronic records. Statistical analyses included descriptive statistics, Kaplan-Meier survival, univariate and multivariate Cox proportional hazard regression analyses. Results 558 patients (mean age 61±12) were included (Table 1). Most were males (n=350; 63%), had raised BMI (median 28 [25-31]), and a Canadian Cardiovascular Society Class of ≥2 (n=495; 85%). Hypertension (63%), dyslipidaemia (61%) and current/former smoking (63%) were the most common cardiovascular risk factors. Rates of diabetes mellitus (40%) and previous myocardial infarction (MI, 41%) were similar. Previous CABG±PCI (43%) was more prevalent than PCI alone (27%). 87% had a normal LVEF ≥50%. 68 patients died over a median follow-up of 6 years. 5-year mortality rate was 7.4% (95%CI: 0.89-0.95) and 10-years, 14% (95%CI: 0.82-0.89). On multivariate analysis, age (hazard ratio [HR] 1.1; P<0.01), diabetes mellitus (HR 2.2; P<0.01) and a reduced LVEF (41-49%: HR 2.4; <40%: HR 2.7; both P<0.01) were independent predictors of mortality. Prior revascularisation (PCI or CABG) was associated with a worse 5-year (9.3 vs. 2.8%) and 10-year (18 vs. 2.8%) mortality compared to those with no revascularisation (P=0.0001; Figure 1). Conclusion In an analysis of the clinical characteristics and outcomes of patients with RA from a contemporary single centre cohort, diabetes mellitus, a modifiable risk factor and impaired left ventricular function were major predictors of mortality. Prior revascularisation also conferred a significantly worse prognosis. Compared to previous US and European cohorts [3, 4], we observed lower rates of MI and revascularisation. Whilst patients with RA with no obstructive epicardial coronary disease contributed to an overall improved mortality rate, mortality in patients with prior revascularisation and obstructive CCS was also better than previously reported and support the favourable prognosis of RA. These findings inform the understanding of the treatment priorities for patients with RA.Table 1.Patient demographics Figure 1.Kaplan-Meier survival analysis

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.019
GPT teacher head0.305
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicCardiac Imaging and Diagnostics→French-language works237,207→