Gender-Related Difference in D-Dimer Level Predicts In-Hospital Heart Failure after Primary PCI for ST-Segment Elevation Myocardial Infarction

The value of D-dimer to lymphocyte ratio in predicting clinical outcomes after percutaneous coronary intervention in ST-segment elevation myocardial infarction patients: A retrospective study

BACKGROUND

D-dimer to lymphocyte ratio (DLR) is a novel composite metric. This study investigated the association between DLR and major adverse cardiovascular events (MACEs) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention.

MATERIALS AND METHODS

This retrospective study included 683 STEMI cases treated between January 2018 and June 2021 at a single center. DLR was calculated for each patient. Receiver operating characteristic curves assessed the predictive value of in-hospital and long-term MACEs, with calculated AUC. Based on the optimal DLR cutoff value, the population was categorized into groups for clinical characteristic analysis. Multivariate logistic and COX regression analyses determined factors independently associated with MACEs. Kaplan-Meier estimation method and log-rank tests assessed event-free survival among different DLR groups. Spearman's test explored the correlation between DLR and Gensini score.

RESULTS

DLR demonstrated an AUC of 0.792 for predicting in-hospital MACEs and 0.708 for long-term MACEs in patients with STEMI. Multivariate logistic regression analysis revealed that a high DLR (cutoff value, 0.47) independently increased the risk of MACEs during hospitalization in patients with STEMI (P = 0.003; odds ratio: 3.015; 95 % CI: 1.438-6.321). Multivariate COX regression showed that a high DLR (cutoff value, 0.34) independently predicted MACEs during long-term follow-up in patients with STEMI (P = 0.011; hazard ratio: 1.724; 95 % CI: 1.135-2.619). Furthermore, DLR exhibited a positive correlation with the Gensini score (P < 0.001).

CONCLUSIONS

DLR is a valuable predictor for MACEs occurrence in patients with STEMI during hospitalization and long-term follow-up after PCI.

Sex differences in the association between D-dimer and the incidence of acute kidney injury in patients admitted with ST-segment elevation myocardial infarction: a retrospective observational study

Identifying the predictors of acute kidney injury (AKI) in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI) remains important. We aimed to investigate the predictive value of D-dimer levels for the incidence of AKI in such a population, with particular attention paid to sex differences. A total of 2668 patients with STEMI who underwent PPCI were retrospectively included in this study and divided into quartiles according to their plasma D-dimer levels upon admission (Q1: < 0.36; Q2: 0.36-0.67; Q3: 0.68-1.17; Q4: > 1.17 mg/L). The primary endpoint was the occurrence of AKI during hospitalization. AKI was observed in 503 (18.8%) patients. The mean age of the patients was 63.0 ± 13.2 years, 2155 (80.8%) of whom were men. Multivariate analysis indicated that higher D-dimer levels were associated with a significantly increased risk of AKI (Q4 vs. Q1: OR: 1.57; 95% CI 1.11-2.23; P = 0.011). However, the prognostic effect of D-dimer was only observed in male patients (Q4 vs. Q1: OR: 2.07; 95% CI 1.37-3.13; P < 0.001), not in female patients (Q4 vs. Q1: OR: 0.72; 95% CI 0.37-1.41; P = 0.342) (P for interaction = 0.003). We demonstrated a notable sex difference in the association between D-dimer level upon admission and AKI in a large STEMI patient sample. A higher D-dimer level was associated with an increased risk of AKI in male patients but not in female patients.

Development and comparison of machine learning-based models for predicting heart failure after acute myocardial infarction

AIMS

Heart failure (HF) is one of the common adverse cardiovascular events after acute myocardial infarction (AMI), but the predictive efficacy of numerous machine learning (ML) built models is unclear. This study aimed to build an optimal model to predict the occurrence of HF in AMI patients by comparing seven ML algorithms.

METHODS

Cohort 1 included AMI patients from 2018 to 2019 divided into HF and control groups. All first routine test data of the study subjects were collected as the features to be selected for the model, and seven ML algorithms with screenable features were evaluated. Cohort 2 contains AMI patients from 2020 to 2021 to establish an early warning model with external validation. ROC curve and DCA curve to analyze the diagnostic efficacy and clinical benefit of the model respectively.

RESULTS

The best performer among the seven ML algorithms was XgBoost, and the features of XgBoost algorithm for troponin I, triglycerides, urine red blood cell count, γ-glutamyl transpeptidase, glucose, urine specific gravity, prothrombin time, prealbumin, and urea were ranked high in importance. The AUC of the HF-Lab9 prediction model built by the XgBoost algorithm was 0.966 and had good clinical benefits.

CONCLUSIONS

This study screened the optimal ML algorithm as XgBoost and developed the model HF-Lab9 will improve the accuracy of clinicians in assessing the occurrence of HF after AMI and provide a reference for the selection of subsequent model-building algorithms.

Sex difference in the relationship of the Atherogenic index of plasma with coronary artery lesions in diabetes: a cross-sectional study

BACKGROUND

Coronary artery disease (CAD) tends to progress more rapidly in the type 2 diabetes mellitus (T2DM) population and may be associated with dyslipidemia. This study explored the relationship of the atherogenic index of plasma (AIP) to coronary artery lesions in the T2DM population of different sexes.

METHODS

The research included 737 individuals who underwent coronary angiography from 2018 to 2019. The included clinical data and coronary angiographic findings were analyzed in the study.

RESULTS

Among the included male patients, those with coronary artery disease had a higher adjusted AIP (aAIP). In correlation analysis, the Gensini score was positively and linearly correlated with the aAIP in male T2DM patients. An aAIP cutoff value of 1.17 was determined from the receiver operating characteristic (ROC) curve of aAIP versus CAD risk in the study population. After dividing the aAIP into two groups by the cutoff value of aAIP, the group with the lower value was used as the control for logistic regression analysis. The results showed that the risk of CAD and multivessel lesions was higher when the aAIP was higher in men with T2DM, and this positive association was not affected by HbA1c, age, or the presence of glucose-lowering therapy. The ROC curve suggested that the aAIP can predict CAD risk in male T2DM patients. However, no relationship was found in the included female patients.

CONCLUSION

In male T2DM patients, AIP may serve as a reliable marker for coronary artery lesions.

Association of D-dimer with long-term prognosis in type 2 diabetes mellitus patients with acute coronary syndrome

BACKGROUND AND AIMS

Type 2 diabetes mellitus (DM) accounts for more and more individuals worldwide. D-dimer has been demonstrated to be associated with cardiovascular diseases. The aim is to study the potential impact of D-dimer on the long-term prognosis of acute coronary syndrome (ACS) in the special population with type 2 DM.

METHODS AND RESULTS

A total of 2265 consecutive patients with DM and ACS were eligible in the study. Patients were divided into four groups according to quartiles of D-dimer concentration. Univariate and multivariate Cox regression analysis were conducted to explore the prognostic value of D-dimer for future outcomes. Patients with higher level of D-dimer presented with higher percentage of major adverse cardiovascular events (MACEs) (23.7%), all-cause death (18.3%) and cardiovascular (CV) death (9.4%) in Quartile 4. In multivariate Cox regression analysis, D-dimer was demonstrated to be independently associated with MACEs, all-cause death and CV death. The prognostic value of D-dimer is still significant in subgroups of HbA1C <7% and ≥7%. In Kaplan-Meier analysis, higher D-dimer showed poorer prognosis in MACEs, all-cause death and CV death (all log rank p < 0.001). The area under the curve (AUC) by receiver operating characteristic (ROC) curve analysis is 0.609 for MACEs, 0.708 for all-cause death, 0.747 for CV death (p < 0.001).

CONCLUSION

The present study demonstrated the independent predictive value of D-dimer for outcomes in DM patients with ACS. In addition, for the first time, we explored the prognostic value in different glucose control status.

D-dimer: an analyte with increasing application in Covid-19 infection

INTRODUCTION

: D- Dimer levels from peripheral blood are increasingly used to assess various pathological conditions. Initially an area for haematologists, now this analyte is evaluated more extensively from many specialities of medicine. Covid-19 infection has not only added a new dimension to D-Dimer level assessment in this disease but has also shed newer lights to the underlying pathophysiological mechanisms for its elevation in this disease.

AREAS COVERED

Innate variability in measuring D- Dimer levels, Impact of various techniques in measuring D- Dimer, non availability of uniform controls and standards, molecular heterogeneity of the product, how it is produced. Reasons for raised D- Dimer in covid-19 infection. D- Dimer in other pathological states. Articles with relevant key words from 1990 searched in PubMed were utilized for review.

EXPERT OPINION

: D-Dimer has important application in diagnosis, prognosis, management and understanding various conditions. Its level can rise with increased coagulability of blood, sepsis, cytokine storm and snake bite etc. Renal function, age influences its reference ranges. Units of measurement, its expression varies in different reports needing international standardization. In Covid-19 infection its levels correlate with stage of the disease, pathology and complications.