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Spss version 23.0 statistics program

Manufactured by IBM

SPSS version 23.0 is a statistics program that allows users to analyze and interpret data. It provides a wide range of statistical procedures for data management, analysis, and presentation.

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Lab products found in correlation

2 protocols using spss version 23.0 statistics program

1

Predicting Radiofrequency Procedure Success

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The SPSS version 23.0 statistics program (IBM Co., Armonk, NY) was used. Patients in the study were classified as responders or non-responders based on the predefined success criteria. Patient demographic and clinical characteristics were reported using descriptive statistics. Descriptive statistics were summarized by means and standard deviations for continuous outcomes, and frequencies (%) for categorical outcomes.
Univariate logistic regression analyses were performed using the patient’s demographic, clinical factors, and technical factors as a potential predictor to quantify the outcome of procedure success. Fifteen predictive factors were entered into the univariate analysis. Then multivariate logistic regression analysis was applied with factors showing a trend towards statistical significance (P < 0.200) in univariate analysis. Factors such as depression, baseline NRS score, performing prognostic block, opioid use, degree of degeneration, prior surgery history, lesion time, and number of nerves targeted (three or five nerves), were selected as the most explanatory variables in univariate analysis and were used in the multivariate model to predict the outcome of the RF procedure success. An odds ratio (OR) with 95% confidence interval (CI) was calculated and P < 0.05 was considered statistically significant.
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2

Efficacy of Pain Management Intervention

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Sample size calculations were performed using G*Power software version 3.1.9.7 (Heinrich-Heine-Universität, Düsseldorf, Germany) according to our preliminary study data. In this study, we found the mean NRS score 2.5± 0.8 at 6 weeks. Using the results of this previous study and considering the NRS as a primary outcome, a sample size of 30 patients was determined to be necessary in order to detect a %20 difference, an α level of .05, and power of 80%.
Data were analyzed using the SPSS version 23.0 statistics program (IBM Corporation, Armonk, NY). Continuous quantitative data with normal distribution were presented as numbers, mean ± standard deviation, with abnormal distribution were presented as median (interquartile range). The compatibility of the variables to normal distribution was checked with a Kolmogorov–Smirnov test. The paired sample test was applied to parametric data for the statistical evaluation of repeated measurements. For abnormally distributed variables, intragroup distribution was compared using Friedman’s test. If present, within group comparisons of the differences were evaluated using the Bonferroni adjusted Wilcoxon signed ranks for post hoc analysis. P < 0.05 was considered statistically significant.
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