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Aims This study aimed to investigate the correlations between estimated small dense low-density lipoprotein-cholesterol (esd-LDL-c) and the development of end-stage kidney disease (ESKD), cardiovascular mortality, and all-cause mortality in individuals with diabetic kidney disease (DKD) or diabetes mellitus (DM) concomitant chronic kidney disease (CKD).Methods We analyzed the data from a biopsy-proven DKD cohort conducted at West China Hospital of Sichuan University between 2009 and 2021 (the DKD cohort) and participants with DM and CKD in the National Health and Nutrition Examination Survey (NHANES) 2011–2014 (the NHANES DM-CKD cohort). Cox regression analysis was also used to estimate associations between esd-LDL-c and the incidence of ESKD, cardiovascular mortality, and all-cause mortality.Results There were 175 ESKD events among 338 participants in the DKD cohort. Patients were divided into three groups based on esd-LDL-c tertiles (T1

Abstract Background Thrombotic thrombocytopenic purpura (TTP) is rare and severe thrombotic microangiopathy characterized by thrombocytopenia, hemolytic anemia, and renal dysfunction. In contrast, essential thrombocythemia (ET) is a myeloproliferative disease associated with an abnormal increase in platelet numbers. Previous studies reported several cases of the development of ET in patients with TTP. However, the case of an ET patient complicated with TTP has not been previously reported. In this case study, we present a patient with TTP who was previously diagnosed with ET. Therefore, to the best of our knowledge, this is the first report of TTP in ET. Case presentation A 31-year-old Chinese female who was previously diagnosed with ET presented with anemia and renal dysfunction. The patient had been on long-term treatment with hydroxyurea, aspirin, and alpha interferon (INF-α) for ten years. The diagnosis of TTP was confirmed by clinical features, schistocytes noted on the peripheral blood smear, and lower ADAMTS13 activity (8.5%), together with the renal biopsy results. INF-α was discontinued, and the patient was then treated with plasma exchange and corticosteroids. After one year of follow-up, the patient had a normal hemoglobin level and platelet numbers, and her ADAMTS13 activity had improved. However, the patient’s renal function remains impaired. Conclusions We report a case of an ET patient complicated with TTP that was possibly due to INF-α, highlighting the potential complications associated with long-term ET therapy. The case also highlights the importance of considering TTP in patients with pre-existing ET who present with anemia and renal dysfunction, extending the spectrum of known studies.

Aims Diabetic kidney disease (DKD) is the most common cause of end-stage renal disease (ESRD) and is associated with increased morbidity and mortality in patients with diabetes. Identification of risk factors involved in the progression of DKD to ESRD is expected to result in early detection and appropriate intervention and improve prognosis. Therefore, this study aimed to establish a risk prediction model for ESRD resulting from DKD in patients with type 2 diabetes mellitus (T2DM).Methods Between January 2008 and July 2019, a total of 390 Chinese patients with T2DM and DKD confirmed by percutaneous renal biopsy were enrolled and followed up for at least 1 year. Four machine learning algorithms (gradient boosting machine, support vector machine, logistic regression, and random forest (RF)) were used to identify the critical clinical and pathological features and to build a risk prediction model for ESRD.Results There were 158 renal outcome events (ESRD) (40.51%) during the 3-year median follow up. The RF algorithm showed the best performance at predicting progression to ESRD, showing the highest AUC (0.90) and ACC (82.65%). The RF algorithm identified five major factors: Cystatin-C, serum albumin (sAlb), hemoglobin (Hb), 24-hour urine urinary total protein, and estimated glomerular filtration rate. A nomogram according to the aforementioned five predictive factors was constructed to predict the incidence of ESRD.Conclusion Machine learning algorithms can efficiently predict the incident ESRD in DKD participants. Compared with the previous models, the importance of sAlb and Hb were highlighted in the current model.HighlightsWhat is already known? Identification of risk factors for the progression of DKD to ESRD is expected to improve the prognosis by early detection and appropriate intervention.What this study has found? Machine learning algorithms were used to construct a risk prediction model of ESRD in patients with T2DM and DKD. The major predictive factors were found to be CysC, sAlb, Hb, eGFR, and UTP.What are the implications of the study? In contrast with the treatment of participants with early-phase T2DM with or without mild kidney damage, major emphasis should be placed on indicators of kidney function, nutrition, anemia, and proteinuria for participants with T2DM and advanced DKD to delay ESRD, rather than age, sex, and control of hypertension and glycemia.

Purpose: This study aimed to investigate the effects of intravitreal (IVT) VEGFi on long-term renal outcomes in patients with biopsy-proven diabetic kidney disease (DKD).Patients and methods: Patients prescribed IVT VEGFi (VEGFi group) were enrolled from a retrospective cohort with biopsy-proven DKD, and those not prescribed VEGFi (non-VEGFi group) were enrolled by 1:3 propensity score matching, adjusted for clinical and pathological baseline indicators. The primary endpoint is defined as end-stage renal disease (ESRD) and the secondary endpoint is defined as all-cause mortality.Results: Compared with patients in non-VEGFi group, patients with VEGFi had a higher proportion of diabetic retinopathy (DR) (50.9% vs 100%, p < 0.001) before matching. Standardized mean difference (SMD) of age, DR, duration of diabetes, the proportion of hypertension, eGFR, initial proteinuria, serum albumin, hemoglobin, the proportion of RAAS inhibitor and interstitial fibrosis and tubular atrophy (IFTA) were >10%. After matching, there was no significant difference in clinical pathology between the two groups. Except for the proportion of hypertension, the SMD of other indicators was

AimsAbnormalities of glucolipid metabolism are critical mechanisms involved in the progression of diabetic kidney disease (DKD). Bile acids have an essential role in regulating glucolipid metabolism. This study investigated the clinicopathological characteristics of DKD patients with different bile acid levels and explored the relationship between bile acids and renal outcomes of DKD patients.MethodsWe retrospectively reviewed and evaluated the histopathological features and clinical features of our cohort of 184 patients with type 2 diabetes mellitus and biopsy-proven DKD. Patients were divided into the lower bile acids group (≤2.8 mmol/L) and higher bile acids group (>2.8 mmol/L) based on the cutoff value of bile acids obtained using the time-dependent receiver-operating characteristic curve. Renal outcomes were defined as end-stage renal disease (ESRD). The influence of bile acids on renal outcomes and correlations between bile acids and clinicopathological indicators were evaluated.ResultsBile acids were positively correlated with age (r = 0.152; P = 0.040) and serum albumin (r = 0.148; P = 0.045) and negatively correlated with total cholesterol (r = -0.151; P = 0.041) and glomerular class (r = -0.164; P =0.027). During follow-up, 64 of 184 patients (34.78%) experienced progression to ESRD. Lower levels of proteinuria, serum albumin, and bile acids were independently associated with an increased risk of ESRD (hazard ratio, R=5.319; 95% confidence interval, 1.208–23.425).ConclusionsBile acids are an independent risk factor for adverse renal outcomes of DKD patients. The serum level of bile acids should be maintained at more than 2.8 mmol/L in DKD patients. Bile acid analogs or their downstream signaling pathway agonists may offer a promising strategy for treating DKD.

Aims: Abnormalities of glucolipid metabolism are critical mechanisms involved in the progression of diabetic kidney disease (DKD). Bile acids have an essential role in regulating glucolipid metabolism. This study investigated the clinicopathological characteristics of DKD patients with different bile acid levels and explored the relationship between bile acids and renal outcomes of DKD patients. Methods: We retrospectively reviewed and evaluated the histopathological features and clinical features of our cohort of 184 patients with type 2 diabetes mellitus and biopsy-proven DKD. Patients were divided into the lower bile acids group (=2.8 mmol/L) and higher bile acids group (>2.8 mmol/L) based on the cutoff value of bile acids obtained using the time-dependent receiveroperating characteristic curve. Renal outcomes were defined as end-stage renal disease (ESRD). The influence of bile acids on renal outcomes and correlations between bile acids and clinicopathological indicators were evaluated. Results: Bile acids were positively correlated with age (r = 0.152; P = 0.040) and serum albumin (r = 0.148; P = 0.045) and negatively correlated with total cholesterol (r = -0.151; P = 0.041) and glomerular class (r = -0.164; P =0.027). During follow-up, 64 of 184 patients (34.78%) experienced progression to ESRD. Lower levels of proteinuria, serum albumin, and bile acids were independently associated with an increased risk of ESRD (hazard ratio, R=5.319; 95% confidence interval, 1.208-23.425). Conclusions: Bile acids are an independent risk factor for adverse renal outcomes of DKD patients. The serum level of bile acids should be maintained at more than 2.8 mmol/L in DKD patients. Bile acid analogs or their downstream signaling pathway agonists may offer a promising strategy for treating DKD. [ABSTRACT FROM AUTHOR]