Liaño F, Gallego A, Pascual J, García-Martín F, Teruel J L, Marcén R, Orofino L, Orte L, Rivera M, Gallego N
Department of Nephrology, Hospital Ramón y Cajal, Madrid, Spain.
Nephron. 1993;63(1):21-31. doi: 10.1159/000187139.
The ability to predict the outcome in acute tubular necrosis (ATN) remains elusive despite considerable efforts. Accurate prediction is a crucial priority and has large economical and ethical implications, mainly to judge when treatment is futile and further efforts only prolong miserable agony. To analyze the influence of risk factors in the prognosis of ATN, we applied, in an initial phase, a prospective protocol of demographic data, cause of renal failure, diuresis, need of dialysis and clinical conditions in 228 patients using multiple linear and logistic regression models. In a control phase with 100 consecutive patients, we checked the accuracy of the results previously obtained, evaluating further the overall population of 328 patients in a synthetic phase. Finally, the validation of the equations obtained was verified in 25 patients from another hospital. As a complement of this 4-phase study, detailed statistical comparisons between both linear and logistic multiple regression models were undertaken. Correlation between probability of death obtained with equations from the initial phase applied to control patients and real evolution of these patients, survival or death, was excellent. The study of the synthetic phase revealed coma, assisted respiration, hypotension, oliguria and jaundice as having an independent positive influence on mortality and nephrotoxic etiology and normal consciousness on good prognosis. For the linear model, the same cut-off point of discriminant score (0.9) above which there were no chances for survival could be established in the 4 phases. With the logistic model, it only was found at later phases. The multiple linear was better than the logistic regression model in terms of better correlation with real mortality, better sensitivity and specificity intervals, easier use of discriminant cut-off point and better adjustment of distribution of standardized residuals to expected normal function. Early prognosis of ATN is possible and can be given using simple clinical features. A discriminant score allows to distinguish patients without chances for survival. The multiple linear is better than the logistic regression model in the prediction of the outcome in ATN.
尽管付出了巨大努力，但预测急性肾小管坏死（ATN）结局的能力仍然难以捉摸。准确的预测是至关重要的优先事项，具有重大的经济和伦理意义，主要用于判断治疗何时无效，以及进一步的努力只会延长痛苦。为了分析风险因素对ATN预后的影响，我们在初始阶段应用了前瞻性方案，对228例患者的人口统计学数据、肾衰竭原因、利尿情况、透析需求和临床状况进行分析，采用多元线性和逻辑回归模型。在一个有100例连续患者的对照阶段，我们检查了先前获得结果的准确性，并在综合阶段进一步评估了328例患者的总体情况。最后，在另一家医院的25例患者中验证了所得方程的有效性。作为这项4阶段研究的补充，我们对线性和逻辑多元回归模型进行了详细的统计比较。将初始阶段方程得出的死亡概率与这些对照患者的实际转归（生存或死亡）之间的相关性非常好。综合阶段的研究表明，昏迷、辅助呼吸、低血压、少尿和黄疸对死亡率有独立的正向影响，而肾毒性病因和意识正常则提示预后良好。对于线性模型，在4个阶段都可以确定相同的判别分数截断点（0.9），高于该点则无生存机会。对于逻辑模型，仅在后期阶段发现了该截断点。在与实际死亡率的更好相关性、更好的敏感性和特异性区间、判别截断点的更易使用以及标准化残差分布与预期正态函数的更好拟合方面，多元线性模型优于逻辑回归模型。ATN的早期预后是可能的，并且可以通过简单的临床特征得出。判别分数可以区分没有生存机会的患者。在预测ATN结局方面，多元线性模型优于逻辑回归模型。
