Statistical package for the social sciences version 21

The results are expressed as mean and standard deviation (SD), counts, or percentages. Based on the previous study,[10 (link)] the sample size was calculated before the patient recruitment by taking into account an expected higher degree of agreement (κ >0.80) between LUS and CXR imaging in detecting the lung abnormalities. A sample of at least 250 patients was required to achieve 85% power and Type I alpha error of 0.05. Continuous variables were expressed as mean ± SD, and qualitative data were expressed as numbers (n) and percentages (%). Agreement between CXR and LUS in detecting pathological findings was done using Cohen's Kappa statistics (44). κ value between 0.41 and 0.60 is moderate agreement, 0.61–0.80 is substantial agreement, and 0.81–1.0 is almost perfect agreement. The Statistical Package for the Social Sciences Version 21.0 (SPSS Inc., IBM, Chicago, IL, USA) was used to analyze the data.

Medians and interquartile ranges were determined for continuous participant characteristics and proportions for categorical characteristics. Biochemical parameters with a skewed distribution were logarithmically transformed (all amino acids, amino acid ratios and HVA). Univariate one-way analysis of variance was used to investigate the association between mean levels of amino acids, amino acid ratios and HVA (dependent variables) and the presence of delirium. Models were adjusted for age, gender and the Charlson Comorbidity Index. Additional analyses were performed for all amino acids, amino acid ratios and HVA after also adding MMSE score to the models. A two-tailed p <0.05 was defined as statistically significant.
Statistical Package for the Social Sciences, version 21.0 (SPSS Inc., Chicago, Ill., USA) was used to perform the statistical analyses. GraphPad Prism 5.01 for Windows (GraphPad Software, San Diego, Calif., USA) was used to draw all graphs.

All analyses were performed using the Statistical Package for the Social Sciences Version 21.0 and were two sided, with a P-value of <0.05 regarded as statistically significant. Associations between baseline differences were analyzed using Student’s t-test or χ² test. A Cox survival model was used to estimate survival in patients treated with four or more FRIDs compared to those treated with three or less FRIDs. In the regression analyses, adjustment was carried out for age, sex, and use of any kind of four or more drugs (including FRIDs), the categorical variables being age and four or more FRIDs. We analyzed the short-term mortality in the patients, which we set up as 6 months postfracture.
We adjusted for variations in mortality due to differences in age and sex using binary logistic regression. All odds ratios (ORs) for death were adjusted for age and sex. We present 95% confidence interval (CI) as a measure of precision for the differences in mortality.