![]() ![]() 10, 11 Unlike propensity score matching, this strategy has the advantage of including all patients in the analysis 11 28, 29įirst, the data were analyzed using inverse probability of treatment weighting (IPTW), which is an alternative approach to propensity score matching to account for indication bias in nonrandomized design. 27 As a measure of between study heterogeneity, the between study variance was provided for each outcome. The analysis also adjusted for continent and for heterogeneity between studies by using random-effects modeling. 16 Findings were expressed as odds ratios (ORs), and 95% confidence intervals (CIs). 10 Individual participant data meta-analyses were conducted as a 1-stage approach of binary outcomes via conditional logistic regression analysis, using the matched cohorts to test the association between each treatment groups and outcomes. The balance between the treatment groups for each covariate was assessed with a standardized difference less than 0.1 considered acceptable. Given the lower number of cases in the glucocorticoids alone group, the ratio was 1 patient from glucocorticoids alone group matched with 2 patients receiving IVIG alone and with 2 patients receiving IVIG plus glucocorticoids. ![]() ![]() 26 The ratio was 1 patient from IVIG plus glucocorticoids group matched with 1 patient receiving IVIG alone. Patients from each treatment group were matched by their propensity score using nearest-neighbor matching without replacement, with a minimum caliper of 0.2.
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