Differences in infection rates with Blastocystis sp. between samples collected at different times were analyzed using 95% confidence intervals (CI) and the chi–squared test, which were bast on the SPSS software 22.0 version (SPSS Inc., United States). Significant differences were considered when P < 0.05.
Spss software 22.0 version
Manufactured by IBM
Sourced in United States
SPSS software, version 22.0, is a data analysis tool developed by IBM. It provides statistical analysis capabilities to support decision-making processes. The software offers a range of features for data management, visualization, and modeling.
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Lab products found in correlation
7 protocols using spss software 22.0 version
1
Blastocystis sp. Infection Rates
2
Comparative Analysis of Surgical Outcomes
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Clinical data were collected, and comparative analysis was conducted. We extracted the main indicators, including surgery duration, blood loss, hospitalization, wound healing, hospitalization expenses, and follow-up information, including fracture healing, pain experience, and patient satisfaction scores, in the three groups. We also recorded the reasons for incomplete follow-up. The variance and t test analysis were used for quantitative variables that were approximately normally distributed, and dichotomous data were compared used Pearson χ2 or Fisher’s exact test. All statistical analyses were performed using SPSS software 22.0 version, and P<0.05 was considered to indicate a statistical difference.
3
Multiplex PCR for C. perfringens
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The C. perfringens isolates identified from fecal samples of the control group and diseased group of animals were screened by multiplex PCR (mPCR) and the results were presented in a tabularized form. The health status-wise prevalence of C. perfringens types in different groups was compared by Pearson’s chi-square test (χ2) using SPSS software, 22.0 version (IBM, New York, NY, USA).
4
Vascular Damage in NASH Patients
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Statistical analysis of quantitative and qualitative data, including descriptive statistics, was performed for all items. Continuous data are expressed as mean ± SD, unless otherwise specified. Baseline differences between groups were assessed by the Chi square test or Fisher exact test, as needed for categorical variables, and by the independent Student t test for continuous parameters.
The analysis of variance (ANOVA) was performed for parametric variables in univariable and multivariable model to evaluate the difference between NASH vs no NASH patients. In both models the data were adjusted for BMI, dyslipidaemia, hypertension, sex, diabetes, cardiovascular disease and age.
Simple linear regression analysis was used to assess histological hepatic damage markers (Kleiner classification indexes) independently associated with vascular damage indexes in NASH and no NASH patients, respectively. B coefficients (B) and their 95% confidence intervals (CIs) were also calculated and adjusted for BMI, dyslipidaemia, hypertension, sex, diabetes, cardiovascular disease and age. In the model, the dependent variables were RHI, PWV, Aix and MMSE. Data were analyzed by the SPSS Software 22.0 version (IBM Corp., Armonk, NY, USA). All p-values were two-sided, and p-values less than 0.05 were considered statistically significant.
The analysis of variance (ANOVA) was performed for parametric variables in univariable and multivariable model to evaluate the difference between NASH vs no NASH patients. In both models the data were adjusted for BMI, dyslipidaemia, hypertension, sex, diabetes, cardiovascular disease and age.
Simple linear regression analysis was used to assess histological hepatic damage markers (Kleiner classification indexes) independently associated with vascular damage indexes in NASH and no NASH patients, respectively. B coefficients (B) and their 95% confidence intervals (CIs) were also calculated and adjusted for BMI, dyslipidaemia, hypertension, sex, diabetes, cardiovascular disease and age. In the model, the dependent variables were RHI, PWV, Aix and MMSE. Data were analyzed by the SPSS Software 22.0 version (IBM Corp., Armonk, NY, USA). All p-values were two-sided, and p-values less than 0.05 were considered statistically significant.
5
Lean PCOS: Evaluating Cardiometabolic Risk
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Data were expressed as median (interquartile range), IQR or frequency (percentages, %) as appropriate. Comparison between groups was done by Mann–Whitney U-test or Pearson's Chi-square/Fisher's exact test. Multivariate linear regression of the manifestations with VAI and LAP as independent variable was done. Predictive associations of VAI and LAP (independent variables) with manifestations of PCOS (dependent variable) were analysed by binary logistic regression. Receiver operating characteristic (ROC) curve analyses were done to see the discriminating index of VAI, LAP along with BMI and WC for IR and MetS amongst patients with lean PCOS. A two-tailed P < 0.05 was set as statistically significant. We used SPSS software 22.0 version for statistical analysis of data (Armonk, NY: IBM Corp).
6
Comparative Analysis of TIRADS Systems
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IBM SPSS software, 22.0 version (IBM Corm., Armonk, NY, USA), MS Excel 2010 software were used to analyse statistical data and create graphs. Pearson correlation was used for correlation between Bethesda categories and all four TIRADS systems that were included in the study. Sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), accuracy (ACC), 95% confidence interval (CI), area under curve (AUC) were calculated for each TIRADS system—L-TIRADS, EU-TIRADS, K-TIRADS, and ACR-TIRADS. Cronbach’s Alpha was calculated for reliability between L-TIRADS and EU-TIRADS, L-TIRADS and K-TIRADS, L-TIRADS and ACR-TIRADS. The statistical significance level of this study was assumed to be p-value < 0.05.
7
Statistical Analysis of Experimental Data
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Data processing and statistical analysis were implemented with the SPSS software 22.0 version (IBM Corp, USA). At least three replicates were done for all experiments, and all data were described as mean ± standard deviation (SD). The comparisons of two groups or multiple groups for continuous data were analyzed by Student's t-test or one-way ANOVA test followed by Tukey's post-hoc test, respectively. The statistically significant difference between groups was defined as a two-tailed p value of < 0.05.
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