Spss statistics version 27

Data analysis was done by using IBM SPSS statistics version 27. Mean and standard deviation were calculated for quantitative variables. Frequency and percentage were reported for qualitative variables. Chi-square/fisher exact tests were applied to determine the association between qualitative variables. Odds were calculated by binary logistic regression p-value less than 0.05 were considered as significant.

For clinical characterization, continuous variables were compared using a t-test (Satterthwaite method), while categorical variables were assessed with the chi² test. Non-normally distributed variables were compared using the Mann–Whitney U test. All variables are presented as medians (interquartile ranges (IQRs)) unless otherwise indicated. Categorical variables are expressed as numbers and percentages. Univariate logistic regression analysis was conducted to examine associations between the parameters of the SOFA score, lactate, and SAH, respectively, and in-hospital mortality. The performance of univariate logistic regression models was evaluated by the estimated coefficients and calculated odds ratios. The estimated coefficient used as an exponent to the basis of 2.7182 represents the factor by which the odds ratio of in-hospital death changes with a one-unit increase in the variable of interest. The predictive power of a variable of interest, i.e., its ability to distinguish between patients who survive and those who die, was assessed using AUROC curves. Differences in AUROCs within and between groups were calculated and tested for statistical significance. The semi-qualitative evaluation of the AUROCs’ performance followed the suggestions by Hosmer and Lemeshow [33 ]. For the analyses of correlations between lactate or SAH parameters and respective SOFA scores, Spearman’s rank and linear regression correlation coefficients were calculated. Except for the results in parenthesis in Figure 6, no outlier or extreme value corrections were applied, and no imputation of missing data points was performed for any directly measured or calculated variable. Despite the prediction of results according to hypotheses, all tests in this study were two-sided, and a p-value of less than 0.05 was considered statistically significant. In cases of multiple testing on two groups regarding the null hypothesis that the two groups are identical for a given variable in all comparisons, the level of statistical significance for rejection of the null hypothesis was corrected according to Bonferroni’s method [49 (link)]. Otherwise, Bonferroni correction was not applied due to the risk of an increase in type II errors. Statistical analyses were performed using SAS Software Version 9.4 (SAS Institute, Cary, NC, USA) or IBM SPSS Statistics Version 27 (IBM, Albany, NY, USA).

All experimental procedures were approved in accordance with the Guide for the Care and Use of Laboratory Animals (44 ) prepared by Okayama University (Okayama, Japan), by Kyoto Prefectural University of Medicine (Kyoto, Japan), by Toyama University (Toyama, Japan), and by the National Institute of Genetics (Shizuoka, Japan) and performed in accordance with the NIH guidelines on animal care. Adult wild-type Wistar rats and GRPR-mRFP transgenic rats were used in this study. To examine the effects of female sex steroid hormones, ovariectomized females were implanted with a blank capsule, a capsule containing physiological levels of 17β-estradiol, a capsule containing physiological levels of progesterone, or a capsule containing physiological levels of both hormones, for 1 to 2 mo. For itch behavioral analysis, rats received either saline, 3% histamine, or 10% CQ diphosphate salt diluted in saline via intradermal injection in the nape of the neck, cheek, or hind paw. Immediately after the injection, the rat was placed into the arena and videotaped from above for 60 min for scratching behavior. Mechanical sensitivity was assessed by the von Frey filament test, and thermal pain sensitivity was assessed by the Hargreaves test. For RT-PCR, enzyme-linked immunosorbent assay, Western blot, and the ChIP assay, the dorsal horns of the cervical spinal cords were collected and used for analysis. Complete methods are described in SI Appendix. Brain and spinal cord sections were used for immunofluorescence and immunoperoxidase histochemistry after perfusion with physiological saline followed by 4% paraformaldehyde in 0.1 M phosphate buffer. Antibody information is provided in SI Appendix, Fig. S2. In vivo extracellular single-unit recordings of superficial spinal dorsal horn (lamina I and II) neurons were performed in female rats. Statistical analyses were performed using SPSS Statistics version 27 (IBM). Graphs were made using GraphPad Prism 8 (GraphPad Software). Statistical analyses for each study are indicated in the figure legends. More detailed information on materials and methods is provided in SI Appendix.

We performed a multi‐site retrospective analysis, which included seven Southern California hospitals, on patients that had a COVID‐19 diagnosis verified by PCR from March through August 2020 (Figure 1). A total of 1143 patients were identified. Patients who were less than 18 years of age, had end of life bradycardia, were on AV nodal blocking agents, or left against medical advice were excluded from the study. Both the inclusion and exclusion criteria of a patient was verified by two physicians. A total of 1053 patients were included in final analysis. A trend of bradycardia was noted in our cohort population. Absolute bradycardia and profound bradycardia was defined as a sustained HR < 60 BPM and < 50 BPM, respectively, on two separate occasions, a minimum of 4 hours apart during hospitalization. Two physicians confirmed bradycardia events by reviewing telemetry strips as well as admission EKG to rule out any underlying arrhythmia. The oxygen saturation during the bradycardic event was noted to rule out any hypoxia‐driven bradycardia.
Chi‐square tests were performed in intergroup comparisons of categorical variables, and categorical variables were expressed as numbers, and percentages. Event rates as descriptive statistics were calculated by dividing the total number of events by total number of cases and were reported in percentages. A logistic regression analysis was performed to study the relationship between mortality and bradycardia in the study group and the effect of age, gender, race and BMI on that relationship. The effect was expressed in terms of Odds ratio with 95% CI. The calculations were performed using IBM SPSS Statistics version 27.