Introduction: Excessive opioid use after orthopaedic surgery procedures remains a concern because it may result in increased morbidity and imposes a financial burden on the healthcare system. The purpose of this study was to develop machine learning algorithms to predict prolonged opioid use after hip arthroscopy in opioid-naïve patients. Methods: A registry of consecutive hip arthroscopy patients treated by a single fellowship-trained surgeon at one large academic and three community hospitals between January 2012 and January 2017 was queried. All patients were opioid-naïve and therefore had no history of opioid use before surgery. The primary outcome was prolonged postoperative opioid use, defined as patients who requested one or more opioid prescription refills postoperatively. Recursive feature elimination was used to identify the combination of variables that optimized model performance from an initial pool of 17 preoperative features. Five machine learning algorithms (stochastic gradient boosting, random forest, support vector machine, neural network, and elastic-net penalized logistic regression) were trained using 10-fold cross-validation five times and applied to an independent testing set of patients. These algorithms were assessed by calibration, discrimination, Brier score, and decision curve analysis. Results: A total of 775 patients were included, with 141 (18.2%) requesting and using one or more opioid refills after primary hip arthroscopy. The stochastic gradient boosting model achieved the best performance (c-statistic: 0.75, calibration intercept: −0.02, calibration slope: 0.88, and Brier score: 0.13). The five most important variables in predicting prolonged opioid use were the preoperative modified ones: Harris hip score, age, BMI, preoperative pain level, and worker's compensation status. The final algorithm was incorporated into an open-access web application available here: https://orthoapps.shinyapps.io/HPRG_OpioidUse/. Conclusions: Machine learning algorithms demonstrated good performance for predicting prolonged opioid use after hip arthroscopy in opioid-naïve patients. External validation of this algorithm is necessary to confirm the predictive ability and performance before use in clinical settings.
The purpose of this in vitro study was to quantify the bone resected from the proximal femur during hip arthroscopy using metrics generated from magnetic resonance imaging (MRI) and computed tomography (CT) reconstructed threedimensional (3D) bone models. Seven cadaveric hemipelvises underwent both a 1.5 T MRI and CT scan before and following an arthroscopic proximal femoral osteochondroplasty. The images from MRI and CT were segmented to generate 3D proximal femoral surface models. A validated 3D-3D registration method was used to compare surface-to-surface distances between the 3D models before and following surgery. The new metrics of maximum height, mean height, surface area and volume, were computed to quantify bone resected during osteochondroplasty.Stability of the metrics across imaging modalities was established through paired sample t-tests and bivariate correlation. Bivariate correlation analyses indicated strong correlations between all metrics (r = 0.728-0.878) computed from MRI and CT derived models. There were no differences in the MRI-and CT-based metrics used to quantify bone resected during femoral osteochondroplasty. Preoperative and postoperative MRI and CT derived 3D bone models can be used to quantify bone resected during femoral osteochondroplasty, without significant differences between the imaging modalities.
Purpose: To (1) investigate trends in kinesiophobia and pain catastrophizing after hip arthroscopy for femoroacetabular impingement syndrome (FAIS), and (2) determine whether kinesiophobia and pain catastrophizing scores are associated with achieving minimal clinically important difference (MCID) for any of the hip-specific patient-reported outcome questionnaires. Methods: Patients undergoing primary hip arthroscopy for treatment of FAIS between December 2016 and March 2017 were prospectively enrolled. Patients received the Tampa Scale of Kinesiophoibia-11 (TSK-11) and Pain Catastrophizing Scale (PCS) questionnaires preoperatively, 6 months, and 1 year postoperatively. They also received the hip-specific patient-reported outcome questionnaires (Hip Outcome Score Activities of Daily Living and Sport-Specific subscales, modified Harris Hip Score, and International Hip Outcome Tool-12), as well as visual analog scale for satisfaction and pain preoperatively and 1-year postoperatively. The threshold for achieving MCID was determined for each hip outcome tool, and patients achieving MCID were compared with those who did not. Results: A total of 85 (80.2%) patients (mean age: 33.7 AE 12.4 years; female: 75.3%) were included in the final analysis. At 1-year follow-up, there was a significant reduction in TSK-11 scores (26.22 AE 5.99 to 18.70 AE 6.49; P < .001) and PCS scores (17.81 AE 10.13 to 4.77 AE 7.57; P < .001) when compared with preoperative scores. 1-year PCS scores were significantly lower in patients achieving MCID compared with patients failing to achieve MCID (3.2 AE 4.4 vs 10.8 AE 15.2; P ¼ .006). There were no significant differences in TSK-11 scores between those achieving and not achieving MCID. Conclusions: Patient kinesiophobia and pain catastrophizing both show significant improvements 1 year after undergoing hip arthroscopy for FAIS. However, pain catastrophizing scores at 1 year are significantly greater in patients not achieving MCID, whereas no association was identified between kinesiophobia and likelihood for MCID achievement. This suggests PCS may be a more useful tool than TSK-11 during postoperative rehabilitation for identifying patients at risk for not achieving MCID.
To analyze time to completion of preoperative legacy patient-reported outcomes (PROs) and more recent computer adaptive Patient-Reported Outcomes Measurement Information System (PROMIS) questionnaires in patients with symptomatic femoroacetabular impingement syndrome undergoing primary hip arthroscopy. Methods: A retrospective analysis was conducted on patients undergoing hip arthroscopy by a single fellowship-trained hip arthroscopist. Inclusion criteria were patients undergoing primary arthroscopic hip surgery and completion of at least 1 legacy PRO or PROMIS questionnaire at the preoperative time point. Exclusion criteria were history of contralateral or ipsilateral hip surgery, noneEnglish-speaking patients, patients who completed PROs by phone or by paper form, and patients who did not complete preoperative PROs. Legacy PROs included modified Harris Hip Score (mHHS), Hip Outcome Score (HOS), International Hip Outcome Tool (iHOT-12), and Hip Pain Visual Analog Scale (VAS-Pain). PROMIS PROs included Physical Function (PROMIS-PF), Pain Interference (PROMIS-PI), and Depression (PROMIS-D). Only preoperative PROs were included in the analysis. Completion time was calculated using the questionnaire start and stop time reported by the survey collecting software. The median and interquartile range of each PRO were reported for analysis of central tendency and statistical dispersion, respectively. Results: A total of 1,901 patients and 269 patients were included in the legacy and PROMIS groups, respectively.
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