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Spss v27.0j

Manufactured by IBM
Sourced in United States, Japan

SPSS v27.0J is a statistical software package developed by IBM. It is designed for advanced analytics, data management, and reporting. The software provides a comprehensive set of tools for data exploration, model building, and result interpretation. SPSS v27.0J is compatible with a wide range of data formats and can be used across various industries and research fields.

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Lab products found in correlation

2 protocols using spss v27.0j

1

Assessing BLS Outcomes in OHCA

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Among eligible patients with OHCA, the change over time in the proportion of the types of BLS performed was assessed using the χ2 test. Differences in patient characteristics and outcomes between groups were assessed using the χ2 test or Fisher's exact test for categorical variables and analysis of variance for numerical variables. The proportions of prehospital ROSC, 1-month survival, and 1-month survival with favorable neurological outcomes were calculated by group. Univariate and multivariate logistic regression analyses were performed to assess the effect of BLS on 1-month survival with favorable neurological outcomes. In the multivariate analysis, odds ratios (ORs) and their associated 95% confidence intervals (CIs) were calculated after adjusting for potential confounders, including education level, location of arrest, type of sports event, situation at the time of arrest, sex, origin of arrest, witness status of arrest, dispatcher instruction of CPR, and time from emergency call to patient contact by EMS personnel. All tests were two-tailed, and a P-value of <0.05 was considered statistically significant. All statistical analyses were performed using SPSS v27.0J (IBM Corp., Armonk, NY, USA).
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2

Assessing Frailty Risk Factors

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The differences between the robust, prefrailty and frailty groups for all variables were examined using one-way analysis of variance for continuous variables and the χ2 test for categorical variables. We conducted logistic regression analysis using the prefrailty and robust versus frailty as the dependent variable. We examined the Crude model (each DW parameter), model 1 (adjusted for the number of steps) and model 2 (model 1+age, sex and the number of chronic diseases) to assess the associations between each DW parameter and frailty. SPSS V.27.0 J (IBM Japan) was used for all statistical analyses, and the significance level was set at 5%.
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