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Ischemia in non-obstructive CAD in Italy: the INOCA-IT multicenter registry

2025· article· en· W7127619318 on OpenAlexaboutno aff
A Chieffo, Luigi Di Serafino, Giuseppe Ghizzoni, G Botti, Domenico Galante, L Giannetti, L Ciaramella, C Giuliana, G Esposito, M Montorfano, A M Leone

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAnginaProvocation testChest painStress testing (software)Coronary angiogramFractional flow reserveCanadian Cardiovascular SocietyFunctional testingCoronary flow reserveCoronary vasospasm

Abstract

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Abstract Background Despite increasing awareness, INOCA is underdiagnosed. Our study aims to assess the prevalence of INOCA in 3 centers in Northern, Central, and Southern Italy, stratifying patients based on coronary microvascular dysfunction (CMD), vasospastic angina (VSA), microvascular spasm (MSA), or non-cardiac origins (NCO), implementing tailored medical therapy and evaluating impact on angina severity, quality of life, and cardiac outcomes at 1 year. Methods The INOCA IT Multicenter Registry is a prospective, multicenter, single-arm clinical study that included patients presenting with CCS symptoms and/or positive stress tests, and non-obstructive CAD on coronary angiography.Invasive coronary functional testing was performed, assessing Coronary Flow Reserve (CFR), Index of Microvascular Resistance (IMR). Acetylcholine (ACh) spasm provocation test was also conducted to identify abnormal vasoreactivity. Patients were consequently classified into different INOCA endotypes and received personalized medical therapy. Patients underwent 1-year clinical follow-up. Results A total of 212 patients were enrolled, the mean age was 61±11 years and 60.4% were female. Overall, 64.2% of patients suffered from hypertension, 15.6% had diabetes, the mean BMI was 26.8±4.7 and 72.6% suffered from dyslipidemia. Most patients presented with typical chest pain (86.8%), the median Canadian Cardiovascular Society (CCS) grade was 2(IQR 2-3) and the median New York Heart Association (NHYA) class median 2 (IQR 1-2). At invasive coronary functional testing (mean CFR: 3.25±1.78, mean IMR 22.1±15.0), 22.6% of patients were diagnosed with CMD, 22.2% with VSA, 14.2% with MSA, 16.0% were affected by both CMD and VSA, 3.8% had both CMD and MVA, 21.2% patients had NCO symptoms.The prevalence of INOCA endotypes showed geographical differences: the first endotype in northern Italy was VSA (27.5%), CMD was the first in central Italy (28.9%), whereas most patients from southern Italy had chest pain of NCO (32.1%) – p for overall comparisons =0.028. The latter also had the highest prevalence of hypertension (83.9%vs52.5% and 61.8% in the other areas, p<0.01) and dyslipidemia (85.7vs 65.0 and 71.1 in the other areas, p=0.026). Moreover, male patients were more frequently affected by VSA compared to other endotypes in northern Italy (37.5%, p for overall comparison=0.043). Finally, VSA was the most frequently misdiagnosed endotype upon non-invasive diagnostic work-up, with a false negative rate of 78.8%, whereas CMD was identified more frequently, with a true positive rate of 50%. The last patient was enrolled in March 2024, and 1-year follow will be available at the time of presentation. Conclusions This real-world analysis highlights the importance of providing accurate diagnosis and subsequent tailored therapy to INOCA patients with a safe and systematical approach. We expect to detect improved QOL and angina symptoms following optimization of medical therapy.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.307
Teacher spread0.292 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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