Length of hospital stay, diuretic dosing, and regression strategies

In previous issues of the journal, we read with great interest the article by Kato et al. (1) entitled “Higher diuretic dosing within the first 72 h is predictive of longer length of stay in patients with acute heart failure” published in Anatol J Cardiol 2018; 20: 110-6. The study included 333 patients with acute heart failure, and the authors demonstrated that higher diuretic dosing in the first 72 h of hospitalization was an independent predictor for a longer length of stay. However, we have major concerns regarding the methodology and statistical design of the study. First, it is well known that the “length of stay” has a right skewed distribution (2, 3). Accordingly, the mean length of stay was 7.9±6.4 days, which was found to be not distributed normally [large standard deviation (SD)]. In this case, it is possible to have incorrect results if an ordinary least square (OLS) is performed for a prediction model. It is more reasonable to perform a Poisson regression or negative binomial regression analysis instead of OLS for evaluating the length of stay data. In addition, the percentage of patients was discharged from hospital is not known because a histogram for length of stay was not provided by the authors. Thus, it is not possible to extrapolate the data used for analysis regarding the percentage of patients discharged from the hospital and the diuretic dosing of the patients in the first 72 h.