Propensity score matching (PSM) is a popular method in clinical researches to create a balanced covariate distribution between treated and untreated groups. However, the balance diagnostics are often not appropriately conducted and reported in the literature and therefore the validity of the findings from the PSM analysis is not warranted. The special article aims to outline the methods used for assessing balance in covariates after PSM. Standardized mean difference (SMD) is the most commonly used statistic to examine the balance of covariate distribution between treatment groups. Because SMD is independent of the unit of measurement, it allows comparison between variables with different unit of measurement. SMD can be reported with plot. Variance is the second central moment and should also be compared in the matched sample. Finally, a correct specification of the propensity score model (e.g., linearity and additivity) should be reassessed if there is evidence of imbalance between treated and untreated. R code for the implementation of balance diagnostics is provided and explained.

BACKGROUND: Enhanced Recovery After Surgery (ERAS) evidence-based protocols for perioperative care have led to improvements in outcomes in numerous surgical areas, through multimodal optimization of patient pathway, reduction of complications, improved patient experience and reduction in the length of stay. ERAS represent a relatively new paradigm in spine surgery. PURPOSE: This multidisciplinary consensus review summarizes the literature and proposes recommendations for the perioperative care of patients undergoing lumbar fusion surgery with an ERAS program.FDA device/drug status: not applicable.

There was no statistically significant difference in treatment effect between NRSs with PS analysis and RCTs. Prospective NRSs with suitable and careful PS analysis can be relied upon as evidence when RCTs are not possible.

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