Spss statistics version 13

This retrospective study enrolled 103 patients who underwent LC for benign gallbladder disease (gallbladder stone, gallbladder polyp, adenomyomatosis) at Uijeongbu St. Mary’s Hospital, Korea, between January 2013 and January 2015. Among them, 33 patients underwent pSILC, 35 underwent nSILC, and 35 underwent TPLC. All patients were older than 18 years of age who were classified as American Society of Anesthetists (ASA) classification 1 to 3 and excluded emergency gallbladder disease.
We collected patient demographic information and medical data from the patient medical charts including operation time, inoperative blood loss, visual analogue scale score, conversion to open, postoperative complications, ASA classification, and length of hospital stay.
This study was approved by Institutional Review Board (IRB) and assigned study number UC19RESI0068. All analyses were done with IBM SPSS statistics version 13.0 program. Continuous and categorical values were presented as the number (%) and mean±standard deviation. The results were statistically significant difference when the p value was less than 0.05.

All of the data were analyzed using IBM SPSS Statistics, version 13.0 (IBM, Armonk, NY, USA). The continuous variables were analyzed by Student t-test and the categorical variables were examined by the Pearson’s chi-squared test. Stenosis group and control group were matched one by one based on the estimated propensity scores of each patient, using nearest neighbor matching with no replacement [30 ]. With the Propensity Score (PS) model, the following variables were considered as the covariates: age, gender, time from onset to initial treatment, Glasgow Coma Scale, medical history, location of hematoma, baseline hematoma volume, systolic blood pressure, diastolic blood pressure, mean arterial pressure (MAP), heartbeat, left hemisphere site of hematoma and intraventricular extension. The clinical outcome was divided into good outcome (mRS <3) and poor outcome (mRS ≥3). The subgroup analysis were performed by age, Glasgow Coma Scale location of hematoma, baseline hematoma volume, MAP, left hemisphere site of hematoma, intraventricular extension, absolute decrease of CBF, and relative decrease of CBF (relative decrease=1-(peri-hematoma CBF/contralateral homologous regions CBF)). Statistical significance was defined as p<0.05.

Statistical analysis of data was performed using IBM SPSS Statistics version 13.0 (IBM Corp., Armonk, NY, USA). The specificity and sensitivity of biomarkers in the prediction of decompensation were examined using the receiver operating characteristic (ROC) curve. Independent predictors of decompensation were examined using logistic regression analysis. The Kaplan–Meier survival curve, with respect to the examined variables, was used. We used the logrank test to compare the average survival of the patient in relation to the examined parameters. Accepted statistical significance was at the level of P < 0.05.