Comparative perioperative outcomes associated with neuraxial versus general anesthesia for simultaneous bilateral total knee arthroplasty

Abstract

Background and objectives: The influence of the type of anesthesia on perioperative outcomes after bilateral total knee arthroplasty (BTKA) remains unknown. Therefore, we examined a large sample of BTKA recipients, hypothesizing that neuraxial anesthesia would favorably impact on outcomes.

Methods: We identified patient entries indicating elective BTKA between 2006 and 2010 in a national database; subgrouped them by type of anesthesia: general (G), neuraxial (N), or combined neuraxial-general (NG); and analyzed differences in demographics and perioperative outcomes.

Results: Of 15,687 identified procedures, 6.8% (n = 1066) were performed under N, 80.1% (n = 12,567) under G, and 13.1% (n = 2054) under NG. Comparing N to G and NG, patients in group N were, on average, younger (63.9, 64.6, and 64.8 years; P = 0.030) but did not differ in overall comorbidity burden. Patients in group N required blood product transfusions significantly less frequently (28.5%, 44.7%, 38.0%; P < 0.0001). In-hospital mortality, 30-day mortality, and complication rates tended to be lower in group N, without reaching statistical significance. After adjusting for covariates, N and NG were associated with 16.0% and 6.0% reduction in major complications compared with G, but only the reduced odds for the requirement of blood transfusions associated with N reached statistical significance (N vs G: odds ratio, 0.52 [95% CI, 0.45-0.61], P < 0.0001; NG vs G: odds ratio, 0.77 [95% CI, 0.69-0.86], P < 0.0001).

Conclusions: Neuraxial anesthesia for BTKA is associated with significantly lower rates of blood transfusions and, by trend, decreased morbidity. Although by itself the effect may be limited, N might be used within a multimodal approach to reduce complications after BTKA.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIGURE 1

The flowchart depicts the study population and subgroup distribution.