Myocardial infarction with nonobstructive coronary arteries (MINOCA) remains a puzzling clinical entity that is characterized by clinical evidence of myocardial infarction (MI) with normal or near-normal coronary arteries on angiography (stenosis <50%). Major advances in understanding this condition have been made in recent years. The precise pathogenesis is poorly understood and is being studied and examined further. Guidelines indicate that MINOCA is a group of heterogeneous diseases with different mechanisms of pathology. Since there are multiple possible pathological mechanisms, it is not certain that the classical secondary prevention and treatment strategy for MI with obstructive coronary artery disease (MI-CAD) is optimal for MINOCA patients. The prognosis and predictors for MINOCA patients remain unclear. Although the prognosis is slightly better for MINOCA patients than for MI-CAD patients, MINOCA isn’t always benign. The aim of this paper was to review the literature and evaluate MINOCA epidemiology, clinical features, etiology, diagnosis, treatment, and prognosis.

Background: The Atherogenic Index of Plasma (AIP) is a newly identified biomarker associated with lipid metabolism, demonstrating significant prognostic capabilities in individuals diagnosed with cardiovascular disease. However, its impact within the context of chronic coronary syndromes (CCS) remains unexplored. Thus, the present investigation sought to examine the potential association between AIP levels and long-term clinical outcomes in patients diagnosed with CCS. Methods: A total of 404 patients diagnosed with CCS and who underwent coronary angiography were included in this study. The AIP index was calculated as log (triglycerides / high-density lipoprotein-cholesterol). The patients were categorized into four groups based on their AIP values: Q1 (< -0.064), Q2 (-0.064 to 0.130), Q3 (0.130 to 0.328), and Q4 (> 0.328). The occurrence of major adverse cardiovascular events (MACE) was monitored during the follow-up period for all patients. Cox regression analysis and Kaplan-Meier curve analysis were employed to examine the relationship between AIP and MACE. Furthermore, ROC analysis was utilized to determine the optimal cut-off value of AIP for predicting clinical MACE. Results: During the median 35 months of follow-up, a total of 88 patients experienced MACE. Notably, the group of patients with higher AIP values (Q4 group) exhibited a significantly higher incidence of MACE compared to those with lower AIP values (Q1, Q2, and Q3 groups) (31.7% vs. 16.8%, 15.7%, and 23.0% respectively; P = 0.023). The Kaplan-Meier curves illustrated those patients in the Q4 group had the highest risk of MACE relative to patients in the other groups (log-rank P = 0.014). Furthermore, the multivariate Cox regression analysis demonstrated that individuals in the Q4 group had a 7.892-fold increased risk of MACE compared to those in the Q1 group (adjusted HR, 7.892; 95% CI 1.818–34.269; P = 0.006). Additionally, the ROC curve analysis revealed an optimal AIP cut-off value of 0.24 for predicting clinical MACE in patients with CCS. Conclusion: Our data indicate, for the first time, that AIP is independently associated with poor long-term prognosis in patients suffering from CCS. The optimal AIP cut-off value for predicting clinical MACE among CCS patients was 0.24.

This study aimed to analyze the associations of cardiometabolic index (CMI) with diabetic statuses and insulin resistance (IR) using data from the National Health and Nutrition Examination Survey (NHANES) and examined the potential mediating role of inflammation in these correlations. This study enrolled 9477 participants across four NHANES cycles from 2011 to 2018. The primary outcomes of the study included the risk of having prediabetes, diabetes and the level of the homeostasis model assessment of IR (HOMA-IR). Other outcomes including the levels of fasting blood glucose (FBG), hemoglobin A1c (HbA1c), oral glucose tolerance test (OGTT) results, fasting insulin, the risk of oral hypoglycemic medicine use, insulin use, and retinopathy were also collected and analyzed. Logistic regression model, subgroup analysis, restricted cubic spine (RCS), and Pearson correlation coefficients were conducted to assess the associations of CMI with diabetic statuses and IR. The mediating role of inflammation was evaluated to investigate the potential mechanism of the associations between CMI and diabetic statuses. Among included participants, the CMI levels in normal participants, prediabetes and diabetes in this study were 0.48, 0.73 and 1.07. After multivariable adjustment, CMI was positively associated with the risk of prediabetes (OR = 1.49, 95% CI = 1.24–1.79), diabetes (OR = 2.14, 95% CI = 1.82–2.50) and the level of HOMA-IR (β = 2.57, 95% CI = 2.14–3.01). Besides, an increased CMI was correlated with higher levels of FBG, HBA1c, OGTT results and fasting insulin as well as the greater risk of oral hypoglycemic medicine use and insulin use. The RCS showed an inverted L-shaped association of CMI with prediabetes and diabetes (P for non-linearity < 0.001). According to Pearson correlation coefficients, higher CMI was linked to higher rises in HOMA-IR (r = 0.224, P < 0.001). Inflammation-related indicators including leukocyte and neutrophil demonstrated significant mediating effects in the associations of CMI with prediabetes (15.5%, 9.8%), diabetes (5.1%, 6.0%) and HOMA-IR (3.3%, 2.6%). CMI was positively associated with the risk of worse diabetic statuses and higher level of IR while the associations may be partially mediated by inflammation-related indicators, suggesting that CMI could be a promising indicator for the prediction of severe diabetes and IR.

Background: Recent studies highlighted that stress hyperglycemia ratio (SHR) is a potential predictor for future risk in heart failure (HF) patients. However, its implications specifically in HF with preserved ejection fraction (HFpEF) are not yet fully elucidated. We aimed to investigate the association between SHR and long-term clinical outcomes in HFpEF patients. Methods: HFpEF patients enrolled between 2015 and 2023, were followed (mean 41 months) for a composite outcome of all-cause, cardiovascular mortality, and HF rehospitalization. SHR was established as the ratio of acute-chronic glycemia from admission blood glucose and glycated hemoglobin. The optimal cut-off for SHR to predict outcomes based on event prediction was determined through ROC analysis, and the cutoff was identified at 0.99. The effect of SHR on adverse risk was examined through the Cox hazards and Kaplan-Meier survival methods. A Pearson correlation analysis was conducted to assess the relationship between SHR and the severity of HF, as indicated by N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. Furthermore, the incremental prognostic value of SHR was further assessed by the integrated discrimination improvement (IDI) and the net reclassification improvement (NRI). Results: Among the 400 enrolled patients, 190 individuals (47.5%) encountered composite events over the 41-month follow-up period. SHR was significantly elevated in patients with events compared with those without (p < 0.001). All patients were stratified into high SHR (n = 124) and low SHR (n = 276) groups based on the SHR cutoff. The high SHR group had a significantly higher incidence of adverse events than the low SHR group (log-rank; p < 0.001). Additional analysis indicated a poorer prognosis in patients with low left ventricular EF (LVEF) levels (50 < LVEF < 60) and high SHR (SHR > 0.99) in comparison to the other groups (log-rank p < 0.001). In adjusted analysis, after accounting for age, sex, diabetes, and NT-proBNP, elevated SHR remained independently predictive of adverse outcomes (adjusted HR: 2.34, 95% CI 1.49–3.67; p < 0.001). Furthermore, adding SHR to a model with MAGGIC score provided an incremental improvement in predicting adverse events. Additionally, SHR displayed a slight correlation with NT-proBNP. Conclusion: Elevated SHR was independently associated with an increased risk for composite events of all-cause, cardiovascular mortality, and HF readmission than those with lower SHR. SHR is a valuable tool for predicting and stratifying long-term adverse risks among HFpEF patients.

Background: Coronary microvascular dysfunction (CMD) is common and is associated with unfavorable cardiovascular events in patients with diabetes mellitus (DM). Coronary angiography-derived index of microcirculatory resistance (caIMR) is a recently developed wire- and hyperemic agent-free method to assess CMD. We aimed to investigate the prognostic impact of CMD assessed by caIMR on clinical outcomes in patients with DM and chronic coronary syndrome (CCS). Methods: CCS patients who underwent coronary angiography between June 2015 to May 2018 were included. Coronary microvascular function was measured by caIMR, and CMD was defined as caIMR ≥ 25U. The primary endpoint was major adverse cardiac events (MACE). Kaplan-Meier analysis and Cox proportional hazards models were used to assess the relationship between caIMR and the risk of MACE. Results: Of 290 CCS patients, 102 patients had DM. Compared with non-diabetic patients, CMD (caIMR ≥ 25U) was higher among DM patients (57.8% vs. 38.3%; p = 0.001). During a mean 35 months follow-up, 40 MACE had occurred. Patients with caIMR ≥ 25 had a higher rate of MACE than patients with caIMR < 25 (20.6% vs. 8.2%, p = 0.002). Of these, the MACE rate was higher among DM patients with caIMR ≥ 25 than those with caIMR < 25 (33.9% vs. 14.0%; p = 0.022). In multivariable Cox analysis, caIMR ≥ 25 was independently associated with MACE in the DM patients but not in non-DM patients (HR, 2.760; 95% CI, 1.066–7.146; P = 0.036). Conclusion: CMD assessed by caIMR was common and is an independent predictor of MACE among diabetic patients with CCS. This finding potentially enables a triage of higher-risk patients to more intensive therapy.

Background: Coronary microvascular dysfunction (CMD) is a strong determinant of prognosis in patients with chronic coronary syndrome (CCS). The triglyceride-glucose index (TyG index), an alternative method to evaluate insulin resistance, is positively correlated with the incidence and adverse outcomes of cardiovascular diseases. However, the relationship between the TyG index and the presence and prognosis of CMD in CCS patients has not been investigated. Therefore, we aimed to evaluate the association between the TyG index and the presence and clinical outcomes of CMD among CCS patients. Methods: CCS patients who underwent coronary angiography between June 2015 to June 2019 were included. The TyG index was calculated as Ln[fasting triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. Coronary angiography‑derived index of microvascular resistance (caIMR) was used to measure microvascular function, and CMD was defined as caIMR ≥ 25U. Patients with CMD were divided into three groups (T1, T2, and T3 groups) according to TyG tertiles. The primary endpoint was major adverse cardiac event (MACE). Results: Of 430 CCS patients, 221 patients had CMD. CMD patients had significantly higher TyG index than those without CMD. Sixty-three MACE was recorded during the follow-up duration among CMD patients, and the incidence rate of MACE was higher in the T3 group compared to T1/T2 groups (39.2% vs. 20.5% vs. 25.7%; P = 0.035). Multivariable logistic regression analysis showed that the TyG index was an independent predictor of CMD (OR, 1.436; 95% CI, 1.014–2.034; P = 0.042). Compared to the T1 group, the T3 group strongly correlated with the risk of MACE in CMD patients even after adjusting for additional confounding risk factors (HR, 2.132; 95%CI, 1.066–4.261; P = 0.032). Conclusion: TyG index is significantly associated with the risk of CMD, and it is an independent predictor of MACE among CMD patients with CCS. This study suggests that the TyG index has important clinical significance for the early prevention and risk stratification of CMD.