Statistical analysis
T1–T3
Normality of the distribution of these variables was assessed with the Kolmogorov–Smirnov test. Normally distributed, continuous data are presented as mean ± standard deviation, whereas non-normally distributed data are presented as median and interquartile range. Categorical variables are presented as absolute numbers of patients (%). The effects of changes in volume expansion on hemodynamic and respiratory variables were assessed with paired t test for normally distributed data or Wilcoxon rank sum test for non-normally distributed data. Responder and non-responder groups were compared with independent t-test (if normally distributed) or Mann–Whiney U-test (if non-normally distributed). The hemodynamic and respiratory variables of all patients from T1–T3 were analyzed separately with repeated measures analysis of variance or a generalized linear mixed model test. Spearman’s correlation coefficients or Pearson correlation tests were used to analyze the relationship between dynamic parameters and the increase in SVI after volume expansion. ROC curve analysis was used to assess the following variables potentially predicting fluid responsiveness: (1) IJVV, PPV, and SVV at T2, and (2) the combination of IJVV and PVV at T2. Comparisons of the areas under the ROC curves (AUCs) were conducted with the Delong method [Because IJVV had not previously been studied in surgical patients in prone position with low Vt ventilation, we assumed an AUC for IJVV of at least 0.75, the minimum threshold necessary to consider a diagnostic test accurate [Statistical analyses were performed using SPSS27 (IBM, Armonk, NY, USA) and MedCalc (version 20.100; MedCalc Software Ltd., Ostend, Belgium). For all comparisons, a two-tailed 