Statistical method

Overall^{a}

Primary outcome^{a}

Secondary outcome^{a}


n = 56

n = 48

n = 8


Twosample test for proportions^{b}

51 (91)

45 (94)

6 (75)

Twosample test for means^{c}

1 (2)

1 (2)

0 (0)

Nonparametric test^{d}

2 (4)

1 (2)

1 (13)

Binomial regression model^{e}

1 (2)

0 (0)

1 (13)

Longitudinal regression model^{f}

2 (4)

1 (2)

1 (13)

Survival analysis^{g}

9 (16)

6 (13)

3 (38)

Competing risk survival analysis^{h}

1 (2)

1 (2)

0 (0)

Joint model^{i}

1 (2)

1 (2)

0 (0)

 Values in the table are count (%). Several statistical methods may be reported for each outcome; therefore, column counts (%s) will not sum to the number of primary or secondary outcomes or 100%
 ^{a}The sample size, n, reported as “overall” is the total number of delirium incidence outcomes, both primary and secondary, whereas the sample size reported for primary and secondary delirium incidence outcomes is the number of trials. A trial may report multiple delirium incidence outcomes, e.g., delirium incidence by 14 or 28 days as the primary and secondary outcomes, respectively. There were a total of 56 delirium incidence outcomes reported by 50 of the 65 trials; 42, 6, and 2 trials reported only a primary, both a primary and secondary, or only a secondary delirium incidence outcome, respectively
 ^{b}Twosample test for proportions includes twosample test for proportions assuming normally distributed sample proportions, Fisher’s exact test, chisquare test, and logistic regression model
 ^{c}Twosample test for means includes twosample t test, analysis of variance, or linear regression model
 ^{d}Nonparametric test for continuous or ordinal outcomes includes MannWhitney test, Wilcoxon ranksum test, KruskalWallis test, and the proportional odds logistic regression model
 ^{e}Binomial regression model defines the number of days with delirium as the binomial outcome and the number of days in the ICU as the offset/denominator
 ^{f}Longitudinal regression model includes marginal longitudinal logistic regression models for daily delirium and random effects logistic regression models for daily delirium
 ^{g}Survival analysis defined the outcome as time from randomization to delirium onset with patients censored at ICU discharge or death; statistical comparisons were made using the logrank test or the Cox proportional hazards regression model
 ^{h}Competing risk survival analysis defined the outcome as time from randomization to delirium onset with (i) patients censored at ICU discharge and death defined as a competing risk or (ii) ICU discharge and death defined as competing risks; statistical comparisons were made using the Fine and Gray competing risk model
 ^{i}Joint model refers to the joint model for recurrent event outcomes (e.g., recurrent delirium events) with terminating event (e.g., ICU discharge or death) proposed by Rondeau [23]