Correlation between the plasma fibrinogen concentration and coronary heart disease severity in Moroccan patients with type 2 diabetes. Prospective study

Circulating mir-199-3p screens the onset of type 2 diabetes mellitus and the complication of coronary heart disease and predicts the occurrence of major adverse cardiovascular events

BACKGROUND

Coronary heart disease (CHD) is a major complication of type 2 diabetes mellitus (T2DM), which causes an adverse prognosis. There is an urgent need to explore effective biomarkers to evaluate the patients' adverse outcomes.

OBJECTIVE

This study aimed to identify a novel indicator for screening T2DM and T2DM-CHD and predicting adverse prognosis.

MATERIALS AND METHODS

The study enrolled 52 healthy individuals, 85 T2DM patients, and 97 T2DM patients combined with CHD. Serum miR-199-3p levels in all study subjects were detected with PCR, and its diagnostic significance was evaluated by receiver operating curve (ROC) analysis. The involvement of miR-199-3p in disease development was assessed by the Chi-square test, and the logistic regression analysis was performed to estimate the risk factor for major adverse cardiovascular events (MACE) in T2DM-CHD patients.

RESULTS

Significant downregulation of miR-199-3p was observed in the serum of both T2DM and T2DM-CHD patients, which discriminated patients from healthy individuals and distinguished T2DM and T2DM-CHD patients. Reduced serum miR-199-3p was associated with the increasing blood glucose, glycated hemoglobin (HbA1c), and homeostasis model assessment-insulin resistance index (HOMA-IR) of T2DM patients and the increasing triglycerides (TG), low-density lipoprotein (LDL), fibrinogen, and total cholesterol (TC) and decreasing high-density lipoprotein (HDL) of T2DM-CHD patients. miR-199-3p was also identified as a biomarker predicting the occurrence of MACE.

CONCLUSION

Downregulated miR-199-3p could screen the onset of T2DM and its complication with CHD. Reduced serum miR-199-3p was associated with the severe development of T2DM and T2DM-CHD and predicted the adverse outcomes of T2DM-CHD patients.

Correlation Between Fibrinogen/Albumin and Diabetic Peripheral Neuropathy

Purpose

This study aimed to examine the correlation between fibrinogen/albumin (FAR) and diabetic peripheral neuropathy (DPN).

Patients and Methods

A total of 342 patients were included and categorized into either the DPN group or the Non-DPN (NDPN) group based on their DPN status. The FAR index was determined by calculating the ratio of fibrinogen (FIB) to serum albumin (ALB), multiplied by 100. The participants were then divided into a High-FAR group and a Low-FAR group using the median FAR value as the threshold. Neurophysiological data were collected from the participants, which included motor conduction velocity (MCV) and sensory conduction velocity (SCV).

Results

The DPN group displayed higher FAR levels [(DPN vs NDPN:6.72 (5.89,7.74) vs 5.94±1.14], in addition to slower SCV and MCV data compared to the NDPN group. The high FAR group had a higher prevalence of DPN (78.9% vs 55.6%) (P<0.05). There was a negative correlation between FAR and NCV, including bilateral median nerve SCV, left ulnar nerve SCV, bilateral median nerve MCV, bilateral common peroneal nerve MCV, bilateral tibial nerve MCV, and left ulnar nerve MCV. FAR was revealed to be an independent risk factor for the development of DPN in patients and demonstrated a greater predictive value for DPN development in Type 2 diabetes mellitus (T2DM) compared with FIB, HbA1c.

Conclusion

The results suggest that monitoring FAR levels in patients with T2DM could identify those at higher risk for developing DPN, making the FAR index a valuable predictor of DPN development. Furthermore, since FAR has an inverse relationship with NCV, it stands to reason that high FAR levels may indicate nerve damage and slower conduction velocities. Thus, managing FAR could prove beneficial in both preventing and delaying the onset of DPN in T2DM patients.

Mathematical Analysis of the Healthcare Treatment of 215 Patients with Coronary Heart Disease

The main risk factors for CHD and the comorbidity include hyperlipidemia (HL), hypertension, smoking, dietary factors, and genetic factors. In this work, 215 patients with coronary heart disease, including 128 males and 87 females, were analyzed for a better understanding of the related clinical pharmacology. Nonparametric test, analysis of variance, chi-square test, correlation analysis, and other methods were used to sort out the data. From the analysis, there are significant differences in age among different gender samples. The incidence of coronary heart disease in men is five years younger than that in women. The sample pairs from different regions showed differences in the presence of family history of diabetes, indicating that a series of patients in some regions concentrated on the disease status of family history of diabetes. Age has a significant positive effect on cardiac functional classification. The older you are, the larger the cardiac functional classification is and the worse the cardiac function is. Age was negatively correlated with VTE score, diastolic blood pressure, CAR, TG, neutrophil, and TC. The older you are, the lower these six values are. Samples of different types of CHD showed significant differences in the presence of comorbidity and family history of CHD. The most significant are unstable angina pectoris and ischemic cardiomyopathy. Samples of different CHD types showed significant effects on VTE score, creatine kinase, low-density lipoprotein cholesterol (LDL⁃C), and lactate dehydrogenase. The highest lactate dehydrogenase is ischemic cardiomyopathy. The highest LDL cholesterol is ST-segment elevation angina. The highest creatine kinase is ischemic cardiomyopathy. The VTE score was the highest for ischemic cardiomyopathy, followed by non-ST-segment elevation angina. Samples taken with or without lipid-lowering drugs showed significant differences in lactate dehydrogenase, creatinine, and TC. There was a significant positive correlation between VTE scores and lactate dehydrogenase, myoglobin, and creatine kinase. High VTE score indicates high lactate dehydrogenase, myoglobin, and creatine kinase. TC has a significant positive correlation with HDL⁃C and TG, respectively. Higher TC values indicate higher HDL⁃C and TG values.

Fibrinogen and Atherosclerotic Cardiovascular Diseases-Review of the Literature and Clinical Studies

Atherosclerotic cardiovascular diseases (ASCVD), including coronary artery disease, cerebrovascular disease, and peripheral arterial disease, represent a significant cause of premature death worldwide. Biomarkers, the evaluation of which would allow the detection of ASCVD at the earliest stage of development, are intensively sought. Moreover, from a clinical point of view, a valuable biomarker should also enable the assessment of the patient’s prognosis. It has been known for many years that the concentration of fibrinogen in plasma increases, inter alia, in patients with ASCVD. On the one hand, an increased plasma fibrinogen concentration may be the cause of the development of atherosclerotic lesions (increased risk of atherothrombosis); on the other hand, it may be a biomarker of ASCVD, as it is an acute phase protein. In addition, a number of genetic polymorphisms and post-translational modifications of fibrinogen were demonstrated that may contribute to the risk of ASCVD. This review summarizes the current data on the importance of fibrinogen as a biomarker of ASCVD, and also presents the relationship between molecular modifications of this protein in the context of ASCVD.

Fibrinogen Level Predicts Outcomes in Critically Ill Patients with Acute Exacerbation of Chronic Heart Failure

Background

Heart failure (HF) is a common cardiovascular disease, which is related to systemic inflammation for decades. Fibrinogen (FIB) is a sign of thrombosis and inflammation, which is associated with the prognosis of many diseases. Nevertheless, the role of fibrinogen level in the prognosis of critically ill patients with acute exacerbation of chronic heart failure is unclear.

Methods

The data are from the Medical Information Mart for Intensive Care III (MIMIC III) database, which is a freely accessible critical care database. The primary outcome in our study was 90-day mortality. The prognostic value of fibrinogen was analyzed with receiver operating characteristic (ROC) curve analysis, Kaplan-Meier curve, and Cox model.

Results

A total of 554 patients were included. Patients were divided into two groups, low fibrinogen level (<284 mg/dl) and high fibrinogen level (≥284 mg/dl), through the cut-off value of the ROC curve. The area under the ROC curve of fibrinogen for predicting 90-day mortality was 0.65 (95% CI: 0.59-0.70). In the unadjusted Cox model, compared with the low fibrinogen level (<284 mg/dl), the 90-day mortality of the hazard ratio (HR) with 95% confidence intervals (CI) of the high fibrinogen level is 3.33 (95% CI 2.15-5.15). In different multivariable Cox models, compared with the low fibrinogen level (<284 mg/dl), the 90-day mortality of the hazard ratio of the high fibrinogen level is from 2.83 to 3.13. In subgroup analyses, significant interactions were observed only in age, chronic kidney disease (CKD), and APS III scores.

Conclusion

Our data suggest that high fibrinogen levels (≥284 mg/dl) independently predict mortality in critically ill patients with acute exacerbation of chronic heart failure. Our findings need to be further validated by large prospective studies and longer follow-up time.

The Fibrinogen-to-Albumin Ratio Is Associated With Outcomes in Patients With Coronary Artery Disease Who Underwent Percutaneous Coronary Intervention

Coronary artery disease (CAD) is a systemic chronic inflammatory disease, and serum fibrinogen and albumin are 2 important factors in systemic inflammation. We aimed to investigate the relationship between the fibrinogen–albumin ratio (FAR) and outcomes in patients with CAD who underwent percutaneous coronary intervention (PCI). All patients were from the Clinical Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI (CORFCHD-PCI) study, which is a retrospective cohort study (Identifier: ChiCTR-ORC-16010153) that includes a total of 6050 patients with CAD after PCI from January 2008 to December 2016. A total of 5829 patients with CAD after PCI were recruited in the present study. They were divided into 2 groups according to the FAR cutoff value, which was calculated using a receiver operating characteristic curve, a low group (FAR < 0.095, n = 3811), and a high group (FAR ≥ 0.095, n = 2018). The average follow-up time was 35.9 ± 22.6 months. The multivariate Cox proportional hazards model showed that FAR was independently correlated with all-cause mortality (adjusted hazard ratio [HR] = 1.432 [1.134-1.808], P = .003), cardiac mortality (adjusted HR = 1.579 [1.218-2.047], P = .001), major adverse cardiac and cerebrovascular events (adjusted HR = 1.296 [1.125-1.494], P < .001), major adverse cardiac events (adjusted HR = 1.357 [1.170-1.572], P < .001), and heart failure (adjusted HR = 1.540 [1.135-2.091], P = .006). The present study indicated that the FAR was associated with adverse outcomes in patients with CAD who underwent PCI.

Prealbumin to fibrinogen ratio is closely associated with diabetic peripheral neuropathy

The aim of our study was to explore the diagnostic value of prealbumin to fibrinogen ratio (PFR) for predicting prognosis with the optimal cut-off value in diabetic peripheral neuropathy (DPN) patients. A total of 568 type 2 diabetes mellitus (T2DM) patients were enrolled in this study. The values including Toronto clinical neuropathy score (TCNS), nerve conduction velocity (NCV), vibration perception threshold (VPT), blood cells count, biochemical parameters, fibrinogen and PFR were recorded. The patients were divided into tertiles based on admission PFR value. First, clinical parameters were compared among the groups. Secondly, a logistic regression and ROC analysis were performed as the statistical model. The percentage of DPN, TCNS and VPT were significantly higher in the lowest PFR tertile than in the middle PFR tertile and the highest PFR tertile (P < 0.01-0.001). NCV was significantly lower in lowest PFR tertile than in the middle PFR tertile and the highest PFR tertile (P < 0.01-0.001). The Spearman correlation analysis showed that PFR was negatively correlated with TCNS and VPT (P < 0.001), while PFR was positively correlated with median motor NCV (P < 0.001), peroneal motor NCV (P < 0.001), median sensory NCV (P < 0.001), and peroneal sensory NCV (P < 0.001). After adjusting these potentially related factors, PFR was independently related to DPN (P = 0.007). The area under ROC curve was 0.627. This study finds the first evidence to suggest PFR may be the key component associated with DPN in T2DM, while PFR might underlie the pathophysiologic features of DPN.

Diabetes classification model based on boosting algorithms

BACKGROUND

Diabetes mellitus is a common and complicated chronic lifelong disease. Hence, it is of high clinical significance to find the most relevant clinical indexes and to perform efficient computer-aided pre-diagnoses and diagnoses.

RESULTS

Non-parametric statistical testing is performed on hundreds of medical measurement index results between diabetic and non-diabetic populations. Two common boosting algorithms, Adaboost.M1 and LogitBoost, are selected to establish a machine model for diabetes diagnosis based on these clinical test data, involving a total of 35,669 individuals. The machine classification models built by these two algorithms have very good classification ability. Here, the LogitBoost classification model is slightly better than the Adaboost.M1 classification model. The overall accuracy of the LogitBoost classification model reached 95.30% when using 10-fold cross validation. The true positive, true negative, false positive, and false negative rates of the binary classification model were 0.921, 0.969, 0.031, and 0.079, respectively, and the area under the receiver operating characteristic curve reached 0.99.

CONCLUSIONS

The boosting algorithms show excellent performance for the diabetes classification models based on clinical medical data. The coefficient matrix of the original data is a sparse matrix, because some of the test results were missing, including some that were directly related to disease diagnosis. Therefore, the model is robust and has a degree of pre-diagnosis function. In the process of selecting the preferred test items, the most statistically significant discriminating factors between the diabetic and general populations were obtained and can be used as reference risk factors for diabetes mellitus.

Fibrinogen: A Marker in Predicting Diabetic Foot Ulcer Severity

Aims. To examine whether fibrinogen levels are a valuable biomarker for assessing disease severity and monitoring disease progression in patients with diabetic foot ulcer (DFU). Methods. A retrospective study was designed to examine the utility of fibrinogen in estimating disease severity in patients with DFU admitted to our hospital between January 2015 and January 2016. In total, 152 patients with DFU were enrolled in the study group, and 52 age and gender matched people with diabetes but no DFU were included as the control group. DFU severity was assessed using Wagner criteria. Results. Patients with DFU were divided into 2 subgroups based on the Wagner criteria. Mean fibrinogen values were significantly higher in patients with DFU grade ≧ 3 compared to those with DFU grades 1-2 (5.23 ± 1.37 g/L versus 3.61 ± 1.04 g/L). Using ROC statistic, a cut-off value of 5.13 g/L indicated the possible amputation with a sensitivity of 81.8% and a specificity of 78.9% (positive predictive value [PPV] 78.6%, negative predictive value [89.0%]). Fibrinogen values were found to be correlated with CRP levels, neutrophil, and WBC count. Conclusions. Fibrinogen levels might be a valuable tool for assessing the disease severity and monitoring the disease progression in patients with DFU.