Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
Sci Rep. 2017 Aug 11;7(1):7862. doi: 10.1038/s41598-017-08440-w.
Currently, little information is available to stratify the risks and predict acute kidney injury (AKI)-associated death. In this present cross-sectional study, a novel scoring model was established to predict the probability of death within 90 days in patients with AKI diagnosis. For establishment of predictive scoring model, clinical data of 1169 hospitalized patients with AKI were retrospectively collected, and 731 patients of them as the first group were analyzed by the method of multivariate logistic regression analysis to create a scoring model and further predict patient death. Then 438 patients of them as the second group were used for validating this prediction model according to the established scoring method. Our results showed that Patient's age, AKI types, respiratory failure, central nervous system failure, hypotension, and acute tubular necrosis-individual severity index (ATN-ISI) score are independent risk factors for predicting the death of AKI patients in the created scoring model. Moreover, our scoring model could accurately predict cumulative AKI and mortality rate in the second group. In conclusion, this study identified the risk factors of 90-day mortality for hospitalized AKI patients and established a scoring model for predicting 90-day prognosis, which could help to interfere in advance for improving the quality of life and reduce mortality rate of AKI patients.
目前，用于分层风险和预测急性肾损伤（AKI）相关死亡的信息很少。在本横断面研究中，建立了一种新的评分模型，以预测 AKI 诊断后 90 天内死亡的概率。为了建立预测评分模型，回顾性收集了 1169 例住院 AKI 患者的临床数据，其中 731 例作为第一组，采用多变量逻辑回归分析方法建立评分模型，进一步预测患者死亡。然后，根据建立的评分方法，将其中的 438 例作为第二组用于验证该预测模型。结果表明，患者年龄、AKI 类型、呼吸衰竭、中枢神经系统衰竭、低血压和急性肾小管坏死-个体严重指数（ATN-ISI）评分是预测 AKI 患者死亡的独立危险因素。此外，我们的评分模型可以准确预测第二组的累积 AKI 和死亡率。总之，本研究确定了住院 AKI 患者 90 天死亡率的危险因素，并建立了预测 90 天预后的评分模型，这有助于提前干预，提高 AKI 患者的生活质量并降低死亡率。
