Background: Over last 2 years, many trials have evaluated newly approved liposomal bupivacaine for periarticular infiltration in total knee arthroplasty (TKA) with mixed results. Our meta-analysis attempts to consolidate the results and make evidence-based conclusions.

Methods: Trails comparing periarticular infiltration of liposomal bupivacaine to conventional analgesic regimens for total knee arthroplasty published till June 2016 were searched in medical database. Comparisons were made for length of stay (LOS), postoperative pain scores, range of motion, and opioid consumption. Meta-regression was performed for LOS to evaluate various analgesic control subgroups.

Results: Sixteen trials were included in the final analysis. Liposomal bupivacaine group showed a shorter LOS (reported in 13 subgroups) than control group by 0.17 ± 0.04 days (random effects, P < .001, I² = 84.66%). Meta-regression for various types of control showed a predictability (R²) of 73%, τ² = 0.013 (random effects, P < .001, I² = 45.16). Only femoral block subgroup attained statistically significant shorter LOS on splitting the control group. Numeric pain scores were lower for pooled control group and local anesthetic infiltration subgroup in immediate postoperative phase. Second postoperative day analgesia was statistically superior to overall clubbed controls and femoral block subgroup. Superiority and/or inferiority of liposomal bupivacaine could not be proven for opioid consumption and range of motion because of a small pooled sample size. Publication bias is likely for LOS (Egger test, X intercept = 2.42, P < .001).

Conclusion: Liposomal bupivacaine infiltration has questionable clinical advantage, as it marginally shortens patient's hospital stay especially in comparison with patients receiving analgesic femoral nerve block. Compared with conventional regimens, it can provide slightly superior yet sustained (till second postoperative day) perioperative analgesia. High heterogeneity suggests need for standardization of infiltration techniques for better predictability of results.