Regional Anesthesia Associated With Decreased Inpatient and Outpatient Opioid Demand in Tibial Plateau Fracture Surgery

Daniel J. Cunningham, MD, MHSc; Micaela LaRose, BA; Gloria Zhang, BS; Preet Patel, BS; Ariana Paniagua, BA; Jeffrey Gadsden, MD; Mark J. Gage, MD

Disclosures

Anesth Analg. 2022;134(5):1072-1081. 

In This Article

Methods

Study Design

This is a retrospective, observational study of inpatient opioid consumption and outpatient opioid demand in all patients ≥18 years of age undergoing tibial plateau fracture surgery at a single institution from July 1, 2013, to July 1, 2018. This study is designed and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement on reporting observational studies.[18] The study was approved by the appropriate institutional review board (IRB), and the requirement for written informed consent was waived by the IRB.

Variables and Data Sources

Patients ≥18 years of age who underwent tibial plateau fracture fixation (Current Procedural Terminology codes 27535 and 27536) at a single, level I trauma center between July 2013 and July 2018 were identified. In general, patients with tibial plateau fracture fixation are treated in a staged fashion (knee-spanning external fixator or knee immobilizer until definitive internal fixation) unless the soft tissues are particularly amenable to immediate fixation. Inpatient opioid consumption between 0 to 24, 24 to 48, and 48 to 72 hours postoperatively and outpatient opioid prescribing from 1 month preoperatively to 2 weeks, 6 weeks, and 90 days postoperatively were recorded. The 1-month preoperative time period was included in the analyses since opioids at the time of fracture before surgery and prescribed in anticipation of surgery contribute to the cumulative opioid supply that patients have postoperatively. This is particularly important in patients undergoing tibial plateau fracture surgery, which is often delayed by 1 to 3 weeks from initial injury until swelling improves. We recorded additional variables, including RA usage, age, sex, race, body mass index (BMI), smoking status, American Society of Anesthesiologists (ASA) score, injury mechanism, additional injuries, and open fracture. Additional surgery within 7 days postoperatively was included as a supplemental measure of injury severity since there were no standardized measures of injury severity such as Injury Severity Score. Opioid usage within the 6-month to 1-month preoperative timeframe was also recorded, which is consistent with the definition for preoperative opioid usage recommended by the Centers for Disease Control and Prevention (CDC).[19] Opioids intended for cough suppression were identified by the presence of alpha-agonists and/or antihistamines and were excluded from calculations. Opioids were converted to oxycodone 5-mg equivalents for ease of interpretation based on conversion factors from the CDC.[20] General 90-day postoperative complications were also recorded through chart review, including mortality, surgical site infection (SSI), acute compartment syndrome (ACS), loss of fixation, deep vein thrombosis (DVT), pulmonary embolism (PE), falls, delirium, and ileus.

Pain Protocol

Patients were considered for RA by their treating anesthesiologist and surgeon, and the decision for treatment with this modality was performed on a case-by-case basis. Postoperative pain medication protocol includes scheduled acetaminophen and oral and intravenous opioids provided according to a pain scale such as 5 to 15 mg oral oxycodone and 0.5 to 1 mg hydromorphone. Nonsteroidal anti-inflammatory pain medications are not routinely used in patients undergoing tibial plateau fracture surgery at our institution due to a theoretical reduction in bone healing rates. The treating team provides discharge pain medications, which often include as-needed oral opioids. Out of 264 patients, 245 (92.8%) patients in this series received a discharge opioid prescription.

Statistical Analysis

Proportions and percentages and medians with quartiles were calculated as appropriate for patients with and without RA. Fisher exact test and Wilcoxon rank-sum test were used to compare unadjusted differences in opioid demand between patients with and without RA.

Since this was a retrospective evaluation rather than a randomized controlled trial, patients did not receive RA at random. To diminish the impact of nonrandom treatment assignment on study outcomes, propensity to have received the treatment was evaluated using logistic regression to obtain propensity score weights for incorporation into multivariable modeling. Specifically, a main effects logistic regression model was constructed evaluating RA (binarized to the presence or absence of RA) with age, sex, race, BMI, smoking, preoperative opioid usage, ASA score (binarized to 1 to 2 versus 3 or more), injury energy (binarized to high versus low energy), the presence of additional injuries, and open injury as model covariates. Covariate balance was next assessed with bivariate logistic regression (RA and each covariate above) with and without propensity score weighting, and there were no remaining significant imbalances after incorporating these propensity weights into analyses. These propensity score weights were then used in the outcome models. This analysis was intended to minimize the impact of nonrandom treatment assignment according to the listed factors.[21,22]

Since there are multiple factors that may be associated with opioid demand in addition to RA, multivariable main effects generalized linear models were constructed utilizing the negative binomial distribution and log link function for continuous outcomes (inpatient opioid consumption and outpatient opioid demand) and logistic regression for categorical outcomes (odds of fill/refill). This type of modeling was chosen because of the positive skew in the data, which was expected since the data were essentially count data. The outcomes models included age, sex, race, BMI, smoking, preoperative opioid usage, ASA score, and measures of injury severity such as injury energy, the presence of additional injuries, open injury, and additional surgery within 7-day postfracture surgery as model covariates. Of note, additional surgery within 7-day postfracture surgery was included as an additional measure of polytrauma or injury severity since we did not have access to a standardized measure of injury severity. Incident rate ratios (IRRs) from generalized linear models were displayed. To provide a more interpretable result, point estimates and Q1 and Q3 with and without RA were predicted in the dataset using the model output. Histograms of these predictions were also included.

This was a convenience sample of all patients undergoing tibial plateau fracture surgery at our institution during the study timeframe. While there was no a priori sample size calculation, we have included the width of the confidence interval (CI) of the 2 main study outcomes: 0- to 24-hour opioid consumption (0.63–0.86 IRR) and 1 month preoperatively to 90 days postoperative opioid demand (0.71–0.96). R and R Studio (R: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, 2020) were used for statistical calculations. P values <.05 were considered statistically significant.

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