【摘要】 目的 總結急性腎功能衰竭（acute renal failure， ARF）的病因特點、治療情況與預后的關系。 方法 回顧性分析2007年8月-2008年4月77例ARF的臨床資料，總結各種因素與患者預后的關系。 結果 腎性因素是最主要的致病病因，占77.92%，其中以藥物和中毒居多。老年患者、少尿型患者或合并多臟器功能衰竭患者病死率較高，分別為25.93%，29.55%，83.33%。 結論 ARF應早期診斷，積極給予綜合治療，包括腎臟替代治療，老年ARF患者易出現多臟器功能衰竭、合并感染等，應放寬透析指征，并注意去除高危因素以提高存活率。【Abstract】 Objective To explore the clinical features, treatment, and prognosis of acute renal failure (ARF). Methods The clinical data of 77 patients with ARF from Auguest 2007 to April 2008 were retrospectively analyzed. Results Renal factor was the most important cause of ARF, accounting for 77.92%. The mortalities of elderly patients, oliguric patients and with multiple organ failure were 25.93%, 29.55%, and 83.33%, respectively. Conclusion Patients with ARF should be diagnosed as early as possible and given comprehensive treatments, including renal replacement therapy; the elderly patients with multiple organ failure and infection should be relaxed dialysis indications. We should pay attention to the removal of risk factors to improve the survival rate.
The study on complexity of glucose fluctuation not only helps us understand the regulation of the glucose homeostasis system but also brings us a new insight of the research methodology on glucose regulation. In the experiments, we analyzed the complexity of the temporal structure of the 72 hours continuous glucose time series from a group of 93 subjects with type Ⅱ diabetes mellitus using the multi-scale entropy method. We adapted the most recently improved refined composite multi-scale entropy (RCMSE) algorithm which could overcome the shortcomings on the 72 hours short time series analysis. We then quantified and compared the complexity of continuous glucose time series between groups with type Ⅱ diabetes mellitus with different mean absolute glycemic excursion (MAGE) and glycated hemoglobin (HbA1c). The results implied that the complexity of glucose time series decreased on lower MAGE group compared to high MAGE group, and the entropy on scale 1 to 6 which corresponded to 5 to 30 min had significant differences between these two groups; the complexity of glucose time series decreased with the increasing HbA1c level but the entropy had no statistical difference among groups at different scales. Therefore, RCMSE provided us with a new prospect to analyze the glucose time series and it was proved that less complexity of glucose dynamics could indicate the impaired gluco-regulation function from the MAGE point of view or HbA1c for patients, and the glucose complexity had the potential to become a new biomarker to reflect the fluctuation of the glucose time series.
