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1.
Chinese Journal of Nephrology ; (12): 465-473, 2021.
Article in Chinese | WPRIM | ID: wpr-911875

ABSTRACT

Objective:To investigate the effects of hyperuricemia on the prognosis of IgA nephropathy (IgAN) using propensity score matching (PSM) method.Methods:IgAN patients proven by biopsy were included. PSM was used to match patients. Kaplan-Meier method was used for survival analysis, and Cox regression analysis was used to analyze the effects of hyperuricemia on IgAN prognosis. Primary outcome events were defined as death, or end-stage renal disease (dialysis, transplantation), or a decrease in estimated glomerular filtration rate (eGFR) greater than 40%. Renal outcome was defined as end-stage renal disease (dialysis, transplantation), or a decrease in eGFR greater than 40%.Results:A total of 1 454 IgAN patients were included in this study, including 850 females and 604 males. Uric acid level was (368.26±92.87) μmol/L in the males, and (277.23±92.71) μmol/L in the females. The median follow-up time was 85.00(56.10, 106.33) months. During the follow-up period, a total of 134 patients reached the primary outcome events, including 5 deaths, 24 dialysis patients, 5 kidney transplant patients, and 100 patients with eGFR decreased by more than 40%. After 1∶1 matching, 131 males and 159 females in the hyperuricemia group were successfully matched with 131 males and 159 females in the normal uric acid group, and there was no significant statistical difference in each parameter in baseline between the hyperuricemia group and normal uric acid group after matching. Kaplan-Meier survival analysis showed that either before or after matching, the incidence of primary outcome events in male or female patients with hyperuricemia was higher than those with normal uric acid, but there was no statistically significant difference in incidence of primary outcome events between female hyperuricemia group and female normal uric acid group after matching (Log-rank test, χ2=3.586, P=0.058). Cox proportional hazard regression model showed that, in the pre-match fully adjusted model, the hazard ratio ( HR) of entering primary outcome events was 2.29-fold (95% CI 1.27-4.11, P=0.006) for men with hyperuricemia and 1.85-fold (95% CI 1.01-3.37, P=0.045) for women with hyperuricemia compared with those with normal uric acid. In the post-match fully adjusted model, the HR of entering primary outcome events was 2.41-fold (95% CI 1.18-4.93, P=0.016) for men with hyperuricemia and 1.83-fold (95% CI 0.91-3.67, P=0.091) for women with hyperuricemia compared with those with normal uric acid. In the pre-match fully adjusted model, the HR of entering renal outcome events was 2.68-fold (95% CI 1.47-4.88, P=0.001) for men with hyperuricemia and 1.81-fold (95% CI 0.99-3.33, P=0.056) for women with hyperuricemia compared with those with normal uric acid. In the post-match fully adjusted model, the HR of entering renal outcome events was 2.89-fold (95% CI 1.36-6.15, P=0.006) for men with hyperuricemia and 1.81-fold (95% CI 0.88-3.72, P=0.106) for women with hyperuricemia compared with those with normal uric acid. Conclusion:Hyperuricemia may be associated with IgAN progression, and it has a more significant effect on male IgAN patients.

2.
Chinese Journal of Practical Nursing ; (36): 2263-2268, 2019.
Article in Chinese | WPRIM | ID: wpr-803490

ABSTRACT

Objective@#To analyze the risk factors for large renal hematoma caused by percutaneous renal biopsy (PRB) in order to provide evidence for early clinical prevention and Effective nursing.@*Methods@#The data of 707 patients who underwent PRB in nephrology department in Hangzhou Hospital of Traditional Chinese Medicine from January 2016 to January 2017 were retrospectively identified. Demographic and clinical data were collected, including general status (gender, age, body mass index, histological diagnosis, associated diseases), laboratory indexes and related examination during PRB (serum creatinine, estimated glomerular filtration rate, creatinineclearance rate, serumuricacid, serumalbumin, hemoglobin, platelet count, prothrombin time, activated partial thromboplastin time, kidney size), blood pressure(history of hypertension, systolic blood pressure, diastolic blood pressure and mean arterial blood pressure before PRB). Univariable logistic regression analysis, linear diagnosis, factor analysis, multivariable logistic regression analysis and receiver operating characteristic curve (ROC curve) were used to assess risk factors.@*Results@#Over the period, 707 native kidney biopsies were performed. Hematoma occurred in 609 biopsies (86.1%), including 558 minorhematomacases (78.9%), 51 largehematoma cases (7.2%), no severe complications were observed. Univariable logistic regression analysis of risk factors in 51 patients with large hematoma after PRB found that there were significant differences in renal tubulointerstitial fibrosis, crescents > 25%, serum creatinine, history of hypertension, systolic blood pressure, diastolic blood pressure and mean arterial pressure before PRB (P< 0.05). Compared with the non-hematoma/minor-hematoma group, the blood pressure before PRB increased significantly in large hematoma group (OR=1.414, 95%CI=1.007-1.985, P=0.045) . More patients with a history of hypertension in large hematoma group (OR=1.997, 95% CI=0.995-4.009, P=0.052) .The area under the ROC curve for predicting large hematoma after PRB was 0.634 for blood pressure before PRB and history of hypertension, the Youden index was 0.27. The blood pressure before PRB and hypertension history were used to predict the formation of large hematoma separately, and the Youden index was 0.28 vs. 0.22 (P> 0. 05).@*Conclusions@#History of hypertension and blood pressure before PRB were independent risk factors for large renal hematoma after PRB.Patients with history of hypertension were more likely to develop large hematoma than those with no history of hypertension, and those with higher blood pressure before PRB were more likely to develop large hematoma. The history of hypertension and the blood pressure before PRB have certain effect in predicting the formation of large hematoma after PRB. Each of them have a certain predictive effect on the formation of largehematoma after PRB, and the prediction effect trend of blood pressure before PRB is slightly better than that of history of hypertension.

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