Clinical Characteristics and Disease Predictors of a Large Chinese Cohort of Patients with Autosomal Dominant Polycystic Kidney DiseaseReportar como inadecuado




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Objective

Autosomal dominant polycystic kidney disease ADPKD is a relentlessly progressing form of chronic kidney disease for which there is no cure. The aim of this study was to characterize Chinese patients with ADPKD and to identify the factors which predict cyst growth and renal functional deterioration.

Methods

To analyze disease predicting factors we performed a prospective longitudinal observational study in a cohort of 541 Chinese patients with ADPKD and an eGFR ≥30 ml-min-1.73 m2. Patients were followed clinically and radiologically with sequential abdominal magnetic resonance imaging MRI. Clinical characteristics and laboratory data were related to changes in estimated glomerular filtration rate eGFR and total kidney volume TKV. A linear regression model was developed to analyze the factors which determine eGFR and TKV changes.

Results

The age range of this unselected cohort ranged from 4 to 77 years. Median follow-up time was 14.3±10.6 months. Although inter-individual differences in eGFR and TKV were large, there was a consistent link between these two parameters. Baseline log10-transformed TKV and urinary protein-creatinine ratio were identified as the major predictors for a faster eGFR decline and were associated with a higher TKV growth rate. Interestingly, a lower thrombocyte count correlated significantly with lower eGFR r = 0.222 and higher TKV r = 0.134.

Conclusions

This large cohort of Chinese patients with ADPKD provides unique epidemiological data for comparison with other cohorts of different ethnicity. In Chinese patients we identified a lower thrombocyte count as a significant predictor of disease progression. These results are important for the design of future clinical trials to retard polycystic kidney disease progression.



Autor: Dongping Chen , Yiyi Ma , Xueqi Wang, Shengqiang Yu, Lin Li, Bing Dai, Zhiguo Mao, Lijun Sun, Chenggang Xu, Shu Rong, Mengjun Tan

Fuente: http://plos.srce.hr/



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