BACKGROUND: Periprocedural myocardial injury (PMI) with or without type 4a myocardial infarction (MI) might occur in patients with non–ST-segment–elevation MI (NSTEMI) after percutaneous coronary intervention (PCI). This study investigated the incidence and prognostic relevance of these events, according to current definitions, in patients with NSTEMI undergoing PCI. The best cardiac troponin I (cTnI) threshold of PMI for prognostic stratification is also suggested. METHODS: Consecutive patients with NSTEMI from January 2017 to April 2022 undergoing PCI with stable or falling pre-PCI cTnI levels were enrolled. According to the Fourth Universal Definition of Myocardial Infarction, the study population was stratified into those experiencing (1) PMI with type 4a MI, (2) PMI without type 4a MI, or (3) no PMI. Post-PCI cTnI increase >20% with an absolute postprocedural value of ≥5 times the 99th percentile upper reference limit within 48 hours after PCI was used to define PMI. The primary end point was 1-year all-cause mortality, and the secondary end point consisted of major adverse cardiovascular events at 1 year, including all-cause mortality, nonfatal reinfarction, urgent revascularization, nonfatal ischemic stroke, and hospitalization for heart failure. Internal validation was performed in patients enrolled between May 2022 and April 2023. RESULTS: Among 1412 patients with NSTEMI undergoing PCI with stable or falling cTnI levels at baseline, 240 (17%) experienced PMI with type 4a MI, 288 (20.4%) experienced PMI without type 4a MI, and 884 (62.6%) experienced no PMI. PMI was associated with an increased risk of adverse clinical outcomes, with patients with type 4a MI demonstrating the highest rates of 1-year all-cause mortality and major adverse cardiovascular events. A post-PCI ΔcTnI >20% but ≤40% showed similar outcomes to patients without PMI, whereas >40% was identified as the optimal threshold for prognostically relevant PMI, confirmed in an internal validation cohort of 305 patients. CONCLUSIONS: Periprocedural ischemic events were frequent in patients with NSTEMI undergoing PCI with prognostic implications. A post-PCI ΔcTnI >40%, combined with an absolute postprocedural value of ≥5 times the 99th percentile upper reference limit, was identified as the optimal threshold for diagnosing prognostically relevant PMI. Recognizing these events may improve risk stratification and management of patients with NSTEMI.

BACKGROUND: Multimodality imaging is currently suggested for the noninvasive diagnosis of cardiac masses. The identification of cardiac masses’ malignant nature is essential to guide proper treatment. We aimed to develop a cardiac magnetic resonance (CMR)-derived model including mass localization, morphology, and tissue characterization to predict malignancy (with histology as gold standard), to compare its accuracy versus the diagnostic echocardiographic mass score, and to evaluate its prognostic ability. METHODS: Observational cohort study of 167 consecutive patients undergoing comprehensive echocardiogram and CMR within 1-month time interval for suspected cardiac mass. A definitive diagnosis was achieved by histological examination or, in the case of cardiac thrombi, by histology or radiological resolution after adequate anticoagulation treatment. Logistic regression was performed to assess CMR-derived independent predictors of malignancy, which were included in a predictive model to derive the CMR mass score. Kaplan-Meier curves and Cox regression were used to investigate the prognostic ability of predictors. RESULTS: In CMR, mass morphological features (non-left localization, sessile, polylobate, inhomogeneity, infiltration, and pericardial effusion) and mass tissue characterization features (first-pass perfusion and heterogeneity enhancement) were independent predictors of malignancy. The CMR mass score (range, 0–8 and cutoff, ≥5), including sessile appearance, polylobate shape, infiltration, pericardial effusion, first-pass contrast perfusion, and heterogeneity enhancement, showed excellent accuracy in predicting malignancy (areas under the curve, 0.976 [95% CI, 0.96–0.99]), significantly higher than diagnostic echocardiographic mass score (areas under the curve, 0.932; P =0.040). The agreement between the diagnostic echocardiographic mass and CMR mass scores was good (κ=0.66). A CMR mass score of ≥5 predicted a higher risk of all-cause death ( P <0.001; hazard ratio, 5.70) at follow-up. CONCLUSIONS: A CMR-derived model, including mass morphology and tissue characterization, showed excellent accuracy, superior to echocardiography, in predicting cardiac masses malignancy, with prognostic implications.

Aims: The aim of the study is to evaluate the impact of sex on acute myocardial infarction (AMI) patients’ clinical presentation and outcomes, comparing those with non-obstructive and obstructive coronary arteries (MINOCA vs. MIOCA). Methods and results: We enrolled 2455 patients with AMI undergoing coronary angiography from January 2017 to September 2021. Patients were divided according to the type of AMI and sex: male (n = 1593) and female (n = 607) in MIOCA and male (n = 87) and female (n = 168) in MINOCA. Each cohort was further stratified based on age (≤/> 70 years). The primary endpoint (MAE) was a composite of all-cause death, recurrent AMI, and hospitalization for heart failure (HF) at follow-up. Secondary outcomes included all-cause and cardiovascular death, recurrent AMI, HF re-hospitalization, and stroke. MINOCA patients were more likely to be females compared with MIOCA ones (P < 0.001). The median follow-up was 28 (15–41) months. The unadjusted incidence of MAE was significantly higher in females compared with males, both in MINOCA [45 (26.8%) vs. 12 (13.8%); P = 0.018] and MIOCA cohorts [203 (33.4%) vs. 428 (26.9%); P = 0.002]. Age was an independent predictor of MAE in both cohorts. Among MINOCA patients, females ≤70 years old had a higher incidence of MAE [18 (23.7%) vs. 4 (5.9%); P = 0.003] compared with male peers, mainly driven by a higher rate of re-hospitalization for HF (P = 0.045) and recurrence of AMI (P = 0.006). Only in this sub-group of MINOCA patients, female sex was an independent predictor of MAE (hazard ratio = 3.09; 95% confidence interval: 1.02–9.59; P = 0.040). MINOCA females ≤70 years old had worse outcomes than MIOCA female peers. Conclusion: MINOCA females ≤70 years old had a significantly higher incidence of MAE, compared with males and MIOCA female peers, likely due to the different pathophysiology of the ischaemic event. Trial registration: Data were part of the ongoing observational study ‘AMIPE: Acute Myocardial Infarction, Prognostic and Therapeutic Evaluation’ (ClinicalTrials.gov Identifier: NCT03883711).

Background: the prognosis of patients with myocardial infarction with non-obstructive coronary arteries (MINOCA) is not benign; thus, prompting the need to validate prognostic scoring systems for this population. Aim: to evaluate and compare the prognostic performance of GRACE, TIMI, HEART, and ACEF scores in MINOCA patients. Methods: A total of 250 MINOCA patients from January 2017 to September 2021 were included. For each patient, the four scores at admission were retrospectively calculated. The primary outcome was a composite of all-cause death and acute myocardial infarction (AMI) at 1-year follow-up. The ability to predict 1-year all-cause death was also tested. Results: Overall, the tested scores presented a sub-optimal performance in predicting the composite major adverse event in MINOCA patients, showing an AUC ranging between 0.7 and 0.8. Among them, the GRACE score appeared to be the best in predicting all-cause death, reaching high specificity with low sensitivity. The best cut-off identified for the GRACE score was 171, higher compared to the cut-off of 140 generally applied to identify high-risk patients with obstructive AMI. When the scores were tested for prediction of 1-year all-cause death, the GRACE and the ACEF score showed very good accuracy (AUC = 0.932 and 0.828, respectively). Conclusion: the prognostic scoring tools, validated in AMI cohorts, could be useful even in MINOCA patients, although their performance appeared sub-optimal, prompting the need for risk assessment tools specific to MINOCA patients.

Background: Type 2 myocardial infarction (T2MI) accounts for a substantial share of acute coronary syndromes but remains challenging to diagnose and manage due to its varied presentations and underlying profiles. This study aims to identify key differences and distinct clinical phenotypes in a large T2MI population. Methods: All consecutive patients with non–ST‐segment–elevation myocardial infarction undergoing coronary angiography with a confirmed T2MI diagnosis between January 1, 2017, and March 31, 2023, were analyzed. Precipitating factors of supply–demand mismatch were identified, and coronary burden was assessed using the Gensini score. Latent class analysis was used to identify clinical phenotypes, and multivariable analyses were performed to determine prognostic predictors. A composite of major adverse cardiovascular events was assessed during follow‐up, along with additional outcomes including cardiovascular death and nonfatal type 2 reinfarction. Results: Among 774 patients with T2MI, latent class analysis identified 2 phenotypes. Phenotype 1 (31.5%) was younger with a higher prevalence of nonatherosclerotic coronary causes and unknown pathogeneses. Phenotype 2 (68.5%) exhibited greater comorbidity and a higher atherosclerotic burden, reflected by elevated Gensini scores (median, 11 versus 1.5; P <0.001). Over a median follow‐up of 53 months, major adverse cardiovascular events occurred in 49.1% of patients, with a higher rate in phenotype 2 (60.8% versus 23.8%, P <0.001). Predictors of major adverse cardiovascular events included peak cardiac troponin levels for phenotype 1 and age, known cardiovascular disease, chronic obstructive pulmonary disease, peak cardiac troponin levels, and Gensini score for phenotype 2. Conclusions: This study identified 2 clinical phenotypes in T2MI, highlighting differences in characteristics, precipitating factors, outcomes, and prognostic predictors, emphasizing the potential for phenotype‐driven approaches in diagnosis and management.