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In the present study, propensity score analysis in matched population reported that NIV use was not associated with changes in mortality rates or in any secondary endpoint.
We introduce a very useful tool developed by Harrowell and co-workers (2004) [1] to study propensity to movement and the use of the Pearson's coefficient to characterize the correlation among the different kinds of ion.
To reduce potential confounding effects in this retrospective study, propensity score based matching analysis was performed.
Given the observational nature of the study, propensity scores were used as an adjustment in the model to help minimize bias related to differences in baseline risk factors, as those with and without CPB may differ in important prognostic factors related to outcome [ 12].
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Similar to the first study, propensity-score matching achieved a nearly equal distribution of available pre-operative patient characteristics between cases and controls (Table 2).
In observational studies, propensity analysis with such a matching procedure ensures to be as close as possible to a randomized clinical trial by selecting patient with comparable characteristics.
42 As confirmed in our studies, propensity score analysis does not overcome unmeasured confounding.
In observational studies, propensity score matching functions to balance baseline characteristics between two groups in order to isolate and estimate the effect of treatment [ 29].
In these latter studies propensity score adjustment estimates were consistent with multivariate adjusted results while instrumental variable analyses were marginally different suggesting some residual unmeasured confounding in the propensity score and multivariate adjusted analyses.
Given the typically small number of events in HIV incidence studies, propensity score weighting permits adjustment for a large number of time-varying covariates that may be on confounding paths, resulting in a precise effect estimate.
As with all studies utilizing propensity score matching, this study is limited by the assumption that all covariates are accounted for in the matching.
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