The relationship between triglyceride/high-density lipoprotein cholesterol ratio and coronary slow-flow phenomenon

Baseline characteristics and seven-year follow-up of patients with coronary slow flow: A cohort study in northeastern Iran

Introduction

An angiographic finding known as "coronary slow flow phenomenon" (CSFP) occurs when there is no discernible stenosis but the contrast flow is slower than usual. Although the prognosis for the majority of CSFP cases is favorable, frequent angina significantly lowers their quality of life. Therefore, this study aimed to explore the potential contributing risk factors and prognostic implications of CSFP on long-term cardiovascular outcomes.

Methods

This retrospective, cohort study was conducted between years 2014-2022 and included a total of 65 CSFP patients and 65 controls with normal coronary flow, as evidenced by coronary angiography. These two groups were examined in terms of future cardiovascular consequences due to this phenomenon, baseline demographic characteristics, and laboratory findings. A P value<0.05 was considered significant.

Results

In this study 130 people including 73 men and 57 women, who because of the typical chest pain and at least a noninvasive test took angiography, were explored. The median triglyceride (200.80±48.51 vs 131.79±34.22, P<0.001), total cholesterol (189.46±10.84 vs 103.43±8.13, P<0.001), and low-density lipoprotein (153.28±34.28 vs 103.34±19.70, P=0.01) were significantly higher in the affected people. During clinical follow-up, a higher number of major adverse cardiac events (8.97±2.95 vs 4.52±2.12, P<0.001) was observed in the CSFP cases. Moreover, a one-unit increase in body mass index raised the probability of adverse cardiac events by 0.912 in CSFP cases.

Conclusion

Our research indicated that individuals with CSFP were more likely to develop cardiac events including unstable angina. Furthermore, obesity and dyslipidemia could provoke this phenomenon.

Identification of potential biomarkers for coronary slow flow using untargeted metabolomics

BACKGROUND

Coronary slow flow (CSF) is associated with poor cardiovascular prognosis. However, its pathogenesis is unclear. This study aimed to identify potential characteristic biomarkers in patients with CSF using untargeted metabolomics.

METHODS

We prospectively enrolled 30 patients with CSF, 30 with coronary artery disease (CAD), and 30 with normal coronary arteries (NCA), all of whom were age-matched, according to the results of coronary angiography. Serum metabolomics were analyzed using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Differentially expressed metabolites were identified through orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with univariate fold-change and VIP value analysis. Pathway enrichment of these metabolites was performed using the KEGG database, and ROC curves were plotted to assess the diagnostic value of the metabolites in CSF patients.

RESULTS

Compared to the CAD and NCA groups, 256 metabolites showed specific expression in CSF, with 18 meeting stringent screening criteria (VIP > 1, FC ≥ 2, or FC ≤ 0.5, and P < 0.05). Seven metabolites demonstrated high diagnostic value for CSF: inositol 1,3,4-trisphosphate (AUC: 1.0), Cer (d24:1/18:0 (2OH)) (AUC: 0.984), Creosol (AUC: 0.976), Chaps (AUC: 0.904), Arg-Thr-Lys-Arg (AUC: 0.929), Ser-Tyr-Arg (AUC: 0.912), and Methyl Indole-3-Acetate (AUC: 0.909). Pathway analysis highlighted the HIF-1 signaling pathway as the most significant metabolic pathway.

CONCLUSIONS

We identified seven metabolites that may serve as serum biomarkers for predicting and diagnosing CSF through untargeted metabolomics. The HIF-1 signaling pathway appears to be crucial in the development of CSF.

Development and validation of a nomogram diagnostic model for coronary slow flow patients: A cross-sectional study

In this study, risk factors for coronary slow flow (CSF) patients were examined, and a clinical prediction model was created. This study involved 573 patients who underwent coronary angiography at our hospital because of chest pain from January 2020 to April 2022. They were divided into CSF group (249 cases) and noncoronary slow flow (NCF) group (324 cases) according to the coronary blood flow results. According to a 7:3 ratio, the patients were categorized into a training group consisting of 402 cases and a validation group consisting of 171 cases. The outcome was assessed by employing multiple logistic regression analysis to examine the factors that influenced it. The model's recognizability was assessed by calculating the consistency index and plotting the receiver operating characteristic curve. Its consistency was assessed by calibration curve, decision curve, and Hosmer-Lemeshow testing goodness-of-fit. The multivariate model included factors such as male, BMI, smoking, diabetes, ursolic acid, and high-density lipoprotein cholesterol. The model validation showed that the consistency index was 0.714, and the external validation set had a consistency index of 0.741. The areas under the curve for the training and external validation sets were respectively 0.730 (95% CI: 0.681-0.779) and 0.770 (95%CI: 0.699-0.841). Nomogram calibration curves indicated intense calibration, and the results of the Hosmer-Lemeshow goodness-of-fit test indicated that χ² = 1.118, P = .572. The nomogram combining various risk factors can be used for individualized predictions of CSF patients and then facilitate prompt and specific treatment.

Predictors and clinical outcomes of slow flow phenomenon in diabetic patients with chronic coronary syndrome

BACKGROUND

Coronary slow flow (CSF) is characterized by late distal coronary perfusion of coronary arteries at the time of angiography despite the vessels appearing normal. The importance of CSF is still debatable. Therefore, this study aimed to investigate CSF's predictors and clinical outcomes in diabetic patients with chronic coronary syndrome (CCS).

PATIENT AND METHODS

This retrospective study included 250 diabetic patients diagnosed with chronic stable angina and referred for coronary angiography (CAG), showing normal coronaries with CSF (Group I) and 240 diabetic patients with normal coronaries and normal flow (Group II). The patients in both groups were followed up for one year to evaluate clinical outcomes.

RESULTS

The incidence of major adverse cardiac events (MACE) was higher in Group I than in Group II, but the difference was not statistically significant except when the composite endpoints of STEMI, NSTEMI, and unstable angina were combined under the term ACS. The independent predictors of CSF, as detected by multivariate regression analysis, were body mass index (BMI) (OR = 0.694, 95% CI = 0.295-0.842, P = 0.010), blood glucose during catheterization (OR = 0.647, 95% CI = 0.298-0.874, P = 0.008), serum triglycerides (OR = 0.574, 95% CI = 0.289-0.746, P = 0.010), and the neutrophil/lymphocyte ratio (NLR) (OR = 0.618, 95% CI = 0.479-0.892, P = 0.001).

CONCLUSION

Serum triglyceride levels, BMI, NLR, and high blood glucose levels at the time of catheterization were independent predictors of CSF in diabetic patients. MACE levels were higher in diabetic patients with CSF.

Effect of nano-curcumin supplementation on angina status, and traditional and novel cardiovascular risk factors in overweight or obese patients with coronary slow flow phenomenon: a randomized double-blind placebo-controlled clinical trial

BACKGROUND

Cardiovascular events and poor quality of life are frequently observed in patients with coronary slow flow phenomenon (CSFP). This trial evaluated the effect of nano-curcumin supplement containing curcuminoids, as multifunctional nutraceuticals, on angina status, and some traditional and novel cardiovascular risk factors in overweight or obese patients with CSFP.

METHODS

In this double-blind, randomized, placebo-controlled clinical trial, 42 overweight or obese patients with CSFP received either 80 mg/day of nano-curcumin or placebo for 12 weeks. Seattle angina questionnaire (SAQ) as a clinical measure of angina status, circulating endocan, adropin, homocysteine, lipid profile, and the novel scores of visceral adiposity index (VAI) and waist-triglyceride index (WTI) were assessed before and after the intervention. The independent samples t-test, Mann-Whitney test, analysis of covariance, Chi-square, and Fisher's exact tests were used where appropriate.

RESULTS

All domains of SAQ including physical limitation, angina stability, angina frequency-severity, treatment satisfaction, and disease perception and quality of life improved significantly in the nano-curcumin compared with the placebo group. No significant changes were observed in serum endocan, adropin, and homocysteine following the intervention. Triglycerides, triglyceride/high-density lipoprotein cholesterol ratio, WTI and VAI values improved significantly only within the nano-curcumin group.

CONCLUSIONS

Supplementation with 80 mg/day nano-curcumin (containing curcuminoids) for 12 weeks significantly improved clinically important disease-specific aspects of health in patients with CSFP. Some traditional and novel cardiovascular risk factors improved significantly only compared with the baseline values, which need further investigation.

TRIAL REGISTRATION

This study was approved by the Ethics Committee of Tehran University of Medical Sciences (IR.TUMS.VCR.REC.1398.794). The study protocol was registered at Iranian Registry of Clinical Trials by IRCT20131125015536N8 registration ID at 19.06.2019.

Could Pan-Immune-Inflammation Value be a Marker for the Diagnosis of Coronary Slow Flow Phenomenon?

Inflammation plays a key role in the pathogenesis of the coronary slow flow phenomenon (CSFP). The newly developed inflammatory marker, pan-immune-inflammation value (PIV), is associated with adverse cardiovascular events. This study investigated the predictive value of PIV for diagnosing CSFP in comparison to other inflammation-based markers. A total of 214 patients, 109 in the CSFP group and 105 in the normal coronary flow (NCF) group, were retrospectively included in the study. Coronary flow was calculated using the Thrombolysis in Myocardial Infarction frame count method. In addition to PIV, other inflammatory markers such as neutrophil-lymphocyte ratio, platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) were calculated for the patients. The average age of patients was 50.3 ± 8.4, with a male ratio of 55.1%. Compared to the NCF group, patients in the CSFP group had higher levels of hyperlipidemia, glucose, triglyceride, NLR, PLR, SII, and PIV, while their high-density lipoprotein cholesterol (HDL-C), was lower (p < 0.05). Logistic regression analysis demonstrated that HDL-C, glucose, triglyceride, and PIV were independent predictor factors for CSFP (p < 0.05). PIV is a strong and independent predictor factor for CSFP and superior in predicting CSFP compared to other inflammatory markers.

The MAPH Score Predicts Coronary Slow Flow. A Retrospective Case-Controlled Study

AIM

The MAPH score is a new score that combines mean platelet volume (MPV), hematocrit, and total protein, which are markers of whole blood viscosity (WBV). We aimed to investigate the relationship between the MAPH score and the coronary slow flow phenomenon (CSF).

MATERIAL AND METHODS

A total of 201 patients were included in the study. 105 had CSF and 96 had normal coronary flow (NCF). Coronary flow was measured by the Thrombolysis in Myocardial Infarction frame count (TFC) method. The patients' MPV, age, hematocrit, and total protein were recorded. High (HSR) and low shear rates (LSR) were calculated, based on total protein and hematocrit values. Cut-off values for CSF were determined using the Youden's index, and the score was determined as 0 or 1 according to the cut-off values. The sum of these scores was the MAPH score.

RESULTS

The mean age of the patients included in the study was 51.1±7.9 (n=201, 54.2 % male). Hyperlipidemia, DM, and HT rates of both groups were similar, but the mean age of the CSF group was higher (p=0.773; p=0.549; p=0.848; p <0.001, respectively). Total protein, MPV, hematocrit, HSR and LSR were higher in the CSF group (p< 0.001, for all values). Comparative receiver operating characteristic (ROC) curve analysis showed that the performance of the MAPH score in predicting CSF is better than the performance of these parameters separately.

CONCLUSION

A new score, the MAPH score, may be used to identify the presence of CSF.

Long-Term Change in Flow Rates in Patients with Coronary Slow Flow

INTRODUCTION

Coronary slow flow (CSF) is a condition characterized by impaired blood flow rates in the coronary arteries. It can result in severe cardiovascular outcomes. There is no sufficient evidence regarding the certain etiology and reversibility of slow flow patterns and changes in frame counts with long-term management.

METHODS

We retrospectively enrolled 48 patients with chronic coronary syndrome and CSF who underwent a second angiography. A corrected coronary frame rate (CFR) >27 was defined as CSF. We created 3 groups according to the change in CSF status as the improved, not changed, and worsened groups. We compared the CFR and CSF status of the patients between the first and second angiographies within a median of 2.6 years.

RESULTS

We determined a nonsignificant change in cCFR in left anterior descending (LAD) artery (34.4 [18.9] vs. 31.59 [10.3], p = 0.35), circumflex (Cx) artery (42.84 [12.56] vs. 40.66 [13.2], p = 0.35), and right coronary artery (RCA) (57.80 [30.13] vs. 50.32 [19.5], p = 0.11). In the comparison of CSF status of LAD (75% vs. 63%, p = 0.27), Cx (96% vs. 83%, p = 0.09), RCA (94% vs. 94%, p = 1.0) between first and second angiographies, there was no significant change. In the comparison of the 3 groups according to the improvement of CSF status, there was no significant difference in demographic features, change in laboratory parameters, and time between the groups.

CONCLUSION

There was no significant change in the median CFR and CSF status in the overall group between the two angiographies after 3 years.

Mass-Spectrometry-Based Lipidomics Discriminates Specific Changes in Lipid Classes in Healthy and Dyslipidemic Adults

Triacylglycerols (TAGs) and cholesterol lipoprotein levels are widely used to predict cardiovascular risk and metabolic disorders. The aim of this study is to determine how the comprehensive lipidome (individual molecular lipid species) determined by mass spectrometry is correlated to the serum whole-lipidic profile of adults with different lipidemic conditions. The study included samples from 128 adults of both sexes, and they were separated into four groups according to their lipid profile: Group I-normolipidemic (TAG < 150 mg/dL, LDL-C < 160 mg/dL and HDL-c > 40 mg/dL); Group II-isolated hypertriglyceridemia (TAG ≥ 150 mg/dL); Group III-isolated hypercholesterolemia (LDL-C ≥ 160 mg/dL) and Group IV-mixed dyslipidemia. An untargeted mass spectrometry (MS)-based approach was applied to determine the lipidomic signature of 32 healthy and 96 dyslipidemic adults. Limma linear regression was used to predict the correlation of serum TAGs and cholesterol lipoprotein levels with the abundance of the identified MS-annotated lipids found in the subgroups of subjects. Serum TAG levels of dyslipidemic adults have a positive correlation with some of the MS-annotated specific TAGs and ceramides (Cer) and a negative correlation with sphingomyelins (SMs). High-density lipoprotein-cholesterol (HDL-C) levels are positively correlated with some groups of glycerophosphocholine, while low-density lipoprotein-cholesterol (LDL-C) has a positive correlation with SMs.

Relationship between increased systemic immune-inflammation index and coronary slow flow phenomenon

Background

Systemic immune-inflammation index (SII, platelet × neutrophil/lymphocyte ratio), a new marker of inflammation, is associated with adverse cardiovascular events, but its relationship with coronary slow flow phenomenon (CSFP) is unclear. Therefore, we aimed to investigate the relationship between SII and CSFP.

Methods

We enrolled consecutive patients who presented with chest pain, with normal/near-normal coronary angiography findings (n = 89 as CSFP group; n = 167 as control group). The baseline characteristics, laboratory parameters and angiographic characteristics of the two groups were compared.

Results

SII levels were significantly higher in the CSFP group than in the control group (409.7 ± 17.7 vs. 396.7 ± 12.7, p < 0.001). A significant positive correlation between SII and the mean thrombolysis in myocardial infarction frame count (mTFC) was found (r = 0.624, p < 0.001). SII increased with the number of coronary arteries involved in CSFP. In multivariate logistic regression analysis, SII/10 was an independent predictor of CSFP (odds ratio: 1.739, p < 0.001). In addition, the SII level > 404.29 was a predictor of CSFP with 67.4% sensitivity and 71.9% specificity.

Conclusions

SII can predict the occurrence of CSFP.