Spss 26 software for windows

Data were analyzed using the SPSS 26 software for Windows (IBM Corp., Armonk, NY, USA). First, the risk factors that may affect postoperative blood transfusion were classified. Student’s t test or the Mann-Whitney U test was used to perform transfusion and non-transfusion group comparisons for quantitative variables. Categorical variables were compared using the chi-square or Fisher’s exact test. Second, all the training set factors were included in the univariate and multivariate logistic regression analyses to exclude unrelated risk factors. The independent risk factors obtained based on the multivariate regression method were used to construct a nomogram model with the “rms” package of R software (version 3.6.1).
Finally, the C-index, the area under the ROC curve (AUC), calibration curve, and DCA were used to evaluate the predictive ability and performance of the risk model. The C-index enables evaluation of the predictive accuracy and discriminative ability of nomograms [13 (link)]. The C-index values ranged from 0.5-1.0, with low accuracy (< 0.5), moderate accuracy (0.5- 0.7), high accuracy (0.7 -0.9), and extreme accuracy (> 0.9). A calibration curve was used to compare the actual risk and predicted risk. The clinical usefulness of the nomogram was estimated by DCA based on the net benefit and threshold probabilities. Statistical tests used p <0.05 as a significance level.

Statistical analysis was conducted using SPSS 26 software for Windows (IBM, Armonk, NY). The regional distribution map was created using ArcGIS Desktop 10.5 (Esri Inc., Redlands, CA). Descriptive statistics were used for continuous variables, while categorical variables were expressed as frequency and percentages. Comparison of clinical characteristics and hematological profiles between the children with DF and DHF was performed using Chi (χ)-square or Fisher’s exact test, independent samples t test, and Mann-Whitney U test, as appropriate.