Coagulopathy in a patient with nephrotic syndrome

Ghanny, Shari; Ross, Catherine; Chan, Anthony K.C.; Chan, Howard H.W.

doi:10.1002/ajh.21782

Cited by 8 publications

(7 citation statements)

References 26 publications

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“…11 Both thrombin time and reptilase time can be prolonged due to dysfibrinogenemia, decreased fibrinogen content, or presence of inhibitor. 12 Although the average APTT was normal in our study, the paradoxically prolonged APTT was found in 3 patients. Dysfibrinogenemia, characterized by malfunctional fibrinogen, can be clinically asymptomatic, or cause bleeding, thrombosis, or both, with an approximated prevalence of .8% in patients with venous thrombosis.…”

Section: Article In Presscontrasting

confidence: 58%

Nephrotic Syndrome May Be One of the Important Etiologies of Cerebral Venous Sinus Thrombosis

Wang

Duan

et al. 2016

Journal of Stroke and Cerebrovascular Diseases

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Section: Article In Presscontrasting

confidence: 58%

Nephrotic Syndrome May Be One of the Important Etiologies of Cerebral Venous Sinus Thrombosis

Wang

Duan

et al. 2016

Journal of Stroke and Cerebrovascular Diseases

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“…Albuminuria can lead to some changes in the levels of numerous biomarkers in blood circulation, which could be applied to diagnosis and the risk evaluation of progression of kidney diseases [ 90 , 91 ]. Several studies have shown that MPV and PDW values are higher in DM patients with DN when compared with those without DN.…”

Section: Discussionmentioning

confidence: 99%

The association of neutrophil to lymphocyte ratio, mean platelet volume, and platelet distribution width with diabetic retinopathy and nephropathy: a meta-analysis

Liu

Li³

et al. 2018

Bioscience Reports

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The aim of the present study was to investigate the correlation of neutrophil to lymphocyte ratio (NLR), mean platelet volume (MPV), and platelet distribution width (PDW) with diabetic nephropathy (DN) and diabetic retinopathy (DR). We searched for eligible studies from PubMed, Embase, Web of Science, and CNKI up to 1 December 2017. Standardized mean difference (SMD) was calculated with a confidence interval (CI) of 95%. A total of 48 studies were included in our meta-analysis. Compared with patients with type Ⅱ diabetes mellitus (T2DM) and without DR, NLR, MPV, and PDW were higher in patients with DR (SMD = 0.77; 95% CI: 0.49–1.05; P<0.001; SMD = 0.68; 95% CI: 0.36–0.99; P<0.001; SMD = 0.52; 95% CI: 0.28–0.76; P<0.01). Compared with patients with T2DM and without DN, NLR, MPV, and PDW were higher in patients with DN (SMD = 0.63; 95% CI: 0.43–0.83; P<0.001; SMD = 0.81; 95% CI: 0.36–1.25; P<0.001; SMD = 0.70; 95% CI: 0.50–0.90; P<0.001). We also found that MPV was strongly associated with the severity of DR, and NLR was closely related to the degree of DN. Our findings indicated that NLR, MPV, and PDW could be recommended as inexpensive diagnostic biomarkers for DN and DR. However, considering several limitations in the present study, further high-quality clinical studies should be performed to investigate the relationship of NLR, MPV, and PDW to DN and DR.

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“…Nephrotic syndrome is the most common clinical manifestation of these two subtypes of glomerular disease [36]. Patients with nephrotic syndrome are always in a state of hypercoagulability and hyperfibrinolysis [37,38], which could be caused by the increased synthesis of blood coagulation factors in liver, the increased consumption of antithrombin, and the decreased levels of protein S, protein C and plasminogen [39,40]. Therefore, as Factor I, serum fibrinogen level was higher in non-IgAN characterized by the predominance of nephrotic syndrome than in IgAN, and accordingly had discerning power between the two groups, as well as D-dimer.…”

Section: Discussionmentioning

confidence: 99%

A novel differential diagnostic model based on multiple biological parameters for immunoglobulin A nephropathy

Gao

Wang

Dong

et al. 2012

BMC Med Inform Decis Mak

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BackgroundImmunoglobulin A nephropathy (IgAN) is the most common form of glomerulonephritis in China. An accurate diagnosis of IgAN is dependent on renal biopsies, and there is lack of non-invasive and practical classification methods for discriminating IgAN from other primary kidney diseases. The objective of this study was to develop a classification model for the auxiliary diagnosis of IgAN using multiparameter analysis with various biological parameters.MethodsTo establish an optimal classification model, 121 cases (58 IgAN vs. 63 non-IgAN) were recruited and statistically analyzed. The model was then validated in another 180 cases.ResultsOf the 57 biological parameters, there were 16 parameters that were significantly different (P < 0.05) between IgAN and non-IgAN. The combination of fibrinogen, serum immunoglobulin A level, and manifestation was found to be significant in predicting IgAN. The validation accuracies of the logistic regression and discriminant analysis models were 77.5 and 77.0%, respectively at a predictive probability cut-off of 0.5, and 81.1 and 79.9%, respectively, at a predictive probability cut-off of 0.40. When the predicted probability of the equation containing the combination of fibrinogen, serum IgA level, and manifestation was more than 0.59, a patient had at least an 85.0% probability of having IgAN. When the predicted probability was lower than 0.26, a patient had at least an 88.5% probability of having non-IgAN. The results of the net reclassification improvement certificated serum Immunoglobulin A and fibrinogen had classification power for discriminating IgAN from non-IgAN.ConclusionsThese models possess potential clinical applications in distinguishing IgAN from other primary kidney diseases.

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Coagulopathy in a patient with nephrotic syndrome

Cited by 8 publications

References 26 publications

Nephrotic Syndrome May Be One of the Important Etiologies of Cerebral Venous Sinus Thrombosis

Nephrotic Syndrome May Be One of the Important Etiologies of Cerebral Venous Sinus Thrombosis

The association of neutrophil to lymphocyte ratio, mean platelet volume, and platelet distribution width with diabetic retinopathy and nephropathy: a meta-analysis

A novel differential diagnostic model based on multiple biological parameters for immunoglobulin A nephropathy

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