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

Kotbi, Souad; Mjabber, Amal; Chadli, A.; Hammiri, Ayoub El; Aziz, S. El; Oukkache, Bouchra; Mifdal, Hassan; Nourichafi, Nadia; Kamal, Nabiha; Habbal, Rachida; Ghalim, Norredine; Farouqi, A.; Kabine, Mostafa

doi:10.1016/j.ando.2015.02.004

Cited by 12 publications

(9 citation statements)

References 36 publications

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“…First, FIB is a protein involved in platelet aggregation and blood coagulation which is the risk factor for vascular events (27). Kotbi et al defined that the plasma FIB concentration in Moroccan population was significantly correlated with the coronary heart disease severity (28). Besides, the elevated serum levels of FIB were also associated with diabetic end-stage renal disease in T2DM patients (29).…”

Section: Discussionmentioning

confidence: 99%

Prealbumin to fibrinogen ratio is closely associated with diabetic peripheral neuropathy

Zang

Shi

Zhao

et al. 2020

Endocrine Connections

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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. Firstly, 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.

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Section: Discussionmentioning

confidence: 99%

Prealbumin to fibrinogen ratio is closely associated with diabetic peripheral neuropathy

Zang

Shi

Zhao

et al. 2020

Endocrine Connections

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“…Apart from inflammatory processes, fibrinogen may also play a role in endothelial injury [20], the formation of low permeability fibrin clot [21], thrombosis [22], abnormalities of blood flow [23], and platelet hyperactivity [24] and contribute to the development of subclinical atherosclerosis [25]. Fibrinogen has recently been generally investigated in arterial coronary arterial disease and peripheral artery disease in people with diabetes [26, 27]. Data suggested that patients with diabetic foot disease have higher fibrinogen levels than those without ulcers [9].…”

Section: Discussionmentioning

confidence: 99%

Fibrinogen: A Marker in Predicting Diabetic Foot Ulcer Severity

Guan

Lin

et al. 2016

Journal of Diabetes Research

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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.

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“…B) The nutritional status, as indicated by albumin, total protein, and the albumin globulin ratio, is prone to be poor. C) The risk of having cardiovascular disease is high, as shown by frequent low values of HDL-cholesterol and high values of fibrinogen [ 21 , 22 ]. The results show that the complications that diabetic patients easily develop, such as hypertension, hyperlipoidaemia, coronary heart disease, and other vascular lesions, are most relevant to the reduced HDL-cholesterol rather than the increased LDL-cholesterol [ 23 ] and increased triglycerides [ 24 , 25 ].…”

Section: Resultsmentioning

confidence: 99%

Diabetes classification model based on boosting algorithms

Chen

Pan

2018

BMC Bioinformatics

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BackgroundDiabetes 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.ResultsNon-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.ConclusionsThe 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.

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

Cited by 12 publications

References 36 publications

Prealbumin to fibrinogen ratio is closely associated with diabetic peripheral neuropathy

Prealbumin to fibrinogen ratio is closely associated with diabetic peripheral neuropathy

Fibrinogen: A Marker in Predicting Diabetic Foot Ulcer Severity

Diabetes classification model based on boosting algorithms

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