Outcome Measures and Statistical Analysis
Outcome Measures
The primary outcome was survival to hospital discharge with satisfactory functional status, defined as a score of 3 or less on the modified Rankin scale. This is a validated scale, ranging from 0 to 6, that is commonly used for measuring the performance of daily activities by people who have had a stroke. Lower scores represent better performance; scores of 4 or higher represent severe disability or death. Secondary outcomes were survival to discharge, survival to hospital admission, and return of spontaneous circulation at the time of arrival at the emergency department.
Statistical Analysis
We estimated that with enrollment of 13,239 patients who could be evaluated, the study would have 99.6% power to detect an improvement in the primary outcome from 5.4% with early analysis of heart rhythm to 7.4% with later analysis, assuming a group-sequential stopping rule at a two-sided alpha level of 0.05 with up to three interim analyses (O’Brien–Fleming boundaries). This calculation took into consideration the concurrent ITD portion of the trial, which required the enrollment of 14,154 patients who could be evaluated, in order to have 90% power to detect a 25% difference in the outcome between the two groups in that trial.
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Analyses of the primary and secondary effectiveness outcomes were performed on the basis of a modified intention-to-treat principle with data from eligible patients in whom the cardiac arrest was not due to drowning, strangulation, or electrocution and for whom the primary outcome was known. An independent data and safety monitoring board reviewed the data at prespecified intervals and used a group-sequential stopping rule. The primary analysis compared the outcomes between the groups with the use of the Wald statistic for the treatment group in a generalized linear mixed model. The model included random effects for each of the clusters, accommodated the binary distribution of the outcome variable, and used a linear-link function to estimate an absolute difference in risk.
The between-group difference in the primary outcome, adjusted for baseline characteristics, was calculated with the use of a multiple linear regression model, with robust standard errors to accommodate clustering and the binary distribution of the outcome. Analyses of binary secondary outcomes and subgroup analyses were performed with the use of generalized-estimating-equation models to estimate differences in risk. Mean scores on the modified Rankin scale were compared between the two treatment groups with the use of a linear model.
We conducted further exploratory analyses of the data using kernel density estimators to estimate the distribution of time from the start of CPR to the actual analysis of cardiac rhythm, separately within treatment groups. The association between the primary outcome and the time of cardiac-rhythm analysis was explored with the use of smoothing splines, and confidence intervals were computed with the use of the bootstrap method.