Preoperative opioid use is associated with worse preoperative patient-reported outcomes in hip arthroscopy patients.

OBJECTIVES: The purpose of this study was to define the rate of preoperative opioid use among patients undergoing hip arthroscopy, ascertain which clinical factors are associated with opioid use, and assess the effect of preoperative opioid usage on preoperative patient-reported outcome (PRO) measures. METHODS: A single institution orthopedic registry was retrospectively analyzed for patients undergoing hip arthroscopy for femoroacetabular impingement (FAI) syndrome with or without labral tear between 2015 and 2022. Patients completed Patient-Reported Outcomes Measurement Information System (PROMIS) in six domains, Numeric Pain Scores (NPS), and Musculoskeletal Outcomes Data Evaluation and Management System expectations domain preoperatively. Patients' charts were reviewed to determine demographic factors and identify any active opioid prescription within 6 weeks before surgery. Bivariate analysis was used to determine associations between preoperative opioid use and baseline PROs. Statistically significant bivariate associations were further tested by multivariate analysis to determine independent predictors. RESULTS: A total of 123 patients were included (age 39.7 â€‹± â€‹12.0 years; 87 females; body mass index 27.4 â€‹± â€‹5.7 kg/m2). There were 21 patients (17%) using opioids preoperatively. Prior orthopedic or other surgery and lower education level were associated with preoperative opioid use. Patients with preoperative opioid use scored statistically significantly worse compared with those without preoperative opioid use on baseline PROMIS Physical Function (38.6 vs 40.5, p â€‹= â€‹0.01), Pain Interference (65.9 vs 60.2, p â€‹= â€‹0.001), Fatigue (60.7 vs 51.6, p â€‹= â€‹0.005), Social Satisfaction (38.2 vs 43.2, p â€‹= â€‹0.007), and Depression (54.2 vs 48.8, p â€‹= â€‹0.01). Preoperative opioid use was also associated with statistically significantly worse preoperative NPS for both the operative hip (6.3 vs 4.6, p â€‹= â€‹0.003) and whole body (3.0 vs 1.4, p â€‹= â€‹0.008). Preoperative opioid use was an independent predictor of worse baseline PROMIS Pain Interference, Fatigue, Social Satisfaction, and NPS for the operative hip. CONCLUSION: Patients using opioids preoperatively had worse baseline PROs for physical function, pain, social satisfaction, and depression than those not using opioids preoperatively. When controlling for confounding variables, preoperative opioid use was independently predictive of worse baseline pain, fatigue, and social satisfaction. LEVEL OF EVIDENCE: Level III, prognostic study.

Development of a patient specific cartilage graft using magnetic resonance imaging and 3D printing.

OBJECTIVES: The goal of this project was to develop and validate a patient-specific, anatomically correct graft for cartilage restoration using magnetic resonance imaging (MRI) data and 3-dimensional (3D) printing technology. The specific aim was to test the accuracy of a novel method for 3D printing and implanting individualized, anatomically shaped bio-scaffolds to treat cartilage defects in a human cadaveric model. We hypothesized that an individualized, anatomic 3D-printed scaffold designed from MRI data would provide a more optimal fill for a large cartilage defect compared to a generic flat scaffold. METHODS: Four focal cartilage defects (FCDs) were created in paired human cadaver knees, age <40 years, in the weight-bearing surfaces of the medial femoral condyle (MFC), lateral femoral condyle (LFC), patella, and trochlea of each knee. MRIs were obtained, anatomic grafts were designed and 3D printed for the left knee as an experimental group, and generic flat grafts for the right knee as a control group. Grafts were implanted into corresponding defects and fixed using tissue adhesive. Repeat post-implant MRIs were obtained. Graft step-off was measured as the distance in mm between the surface of the graft and the native cartilage surface in a direction perpendicular to the subchondral bone. Graft contour was measured as the gap between the undersurface of the graft and the subchondral bone in a direction perpendicular to the joint surface. RESULTS: Graft step-off was statistically significantly better for the anatomic grafts compared to the generic grafts in the MFC (0.0 â€‹± â€‹0.2 â€‹mm vs. 0.7 â€‹± â€‹0.5 â€‹mm, p â€‹< â€‹0.001), LFC (0.1 â€‹± â€‹0.3 â€‹mm vs. 1.0 â€‹± â€‹0.2 â€‹mm, p â€‹< â€‹0.001), patella (-0.2 â€‹± â€‹0.3 â€‹mm vs. -1.2 â€‹± â€‹0.4 â€‹mm, p â€‹< â€‹0.001), and trochlea (-0.4 â€‹± â€‹0.3 vs. 0.4 â€‹± â€‹0.7, p â€‹= â€‹0.003). Graft contour was statistically significantly better for the anatomic grafts in the LFC (0.0 â€‹± â€‹0.0 â€‹mm vs. 0.2 â€‹± â€‹0.4 â€‹mm, p â€‹= â€‹0.022) and trochlea (0.0 â€‹± â€‹0.0 â€‹mm vs. 1.4 â€‹± â€‹0.7 â€‹mm, p â€‹< â€‹0.001). The anatomic grafts had an observed maximum step-off of -0.9 â€‹mm and a maximum contour mismatch of 0.8 â€‹mm. CONCLUSION: This study validates a process designed to fabricate anatomically accurate cartilage grafts using MRI and 3D printing technology. Anatomic grafts demonstrated superior fit compared to generic flat grafts. LEVEL OF EVIDENCE: Level IV.

PROMIS cluster analysis predicts two-year outcomes in knee surgery patients.

Aims & objectives: Meaningful clinical interpretation of orthopaedic patient-reported outcome scores remains challenging. Grouping scores may be more meaningful than individual score analysis. The purpose of this study was to determine if grouping knee surgery patients into four preoperative Patient-Reported Outcomes Measurement Information System (PROMIS) clusters would have prognostic value for two-year postoperative outcomes. Materials & methods: 488 of 697 (70%) patients undergoing elective knee surgery at a single urban institution were enrolled in an orthopaedic registry and completed two-year follow up. Patients were administered questionnaires for PROMIS, International Knee Documentation Committee Score (IKDC), Marx Activity Rating Scale (MARS), and Surgical Satisfaction (SSQ-8). A k-means cluster analysis was performed to identify preoperative PROMIS clusters. Chi-square or Kruskal-Wallis tests were conducted for bivariate analyses. Least-squares multiple linear regression models were performed to identify if cluster group was an independent predictor. Results: Cluster analysis revealed four clusters of patients. Psychological distress was most significant in determining classification. More impaired clusters were associated with higher rates of arthroplasty, African American race, preoperative opioid use, lower income, higher comorbidity index, and other sociodemographic and operative factors. Worse preoperative cluster status was associated with higher chance of achieving minimally clinically important change (MCID) on all metrics except PROMIS Pain Interference (PI), IKDC, and MARS. Multivariable analysis confirmed better preoperative cluster as predictive of better PROMIS Physical Function (PF), PI, IKDC scores, and satisfaction. Worse preoperative cluster was predictive of greater improvement on PF and PI but not IKDC. Conclusion: Preoperative PROMIS clusters have prognostic value in predicting outcomes for knee surgery patients. Better preoperative cluster function predicts superior outcomes. While worse preoperative cluster predicts worse outcome, all clusters still significantly improve, so worse preoperative cluster is not a contraindication to surgery.

Does timing matter? The effect of preoperative smoking cessation on the risk of infection or revision following rotator cuff repair.

BACKGROUND: Nicotine in tobacco products is known to impair bone and tendon healing, and smoking has been associated with an increased rate of retear and reoperation following rotator cuff repair (RCR). Although smoking is known to increase the risk of failure following RCR, former smoking status and the timing of preoperative smoking cessation have not previously been investigated. METHODS: A national all-payer database was queried for patients undergoing RCR between 2010 and 2020. Patients were stratified into 5 mutually exclusive groups according to smoking history: (1) never smokers (n = 50,000), (2) current smokers (n = 28,291), (3) former smokers with smoking cessation 3-6 months preoperatively (n = 34,513), (4) former smokers with smoking cessation 6-12 months preoperatively (n = 786), and (5) former smokers with smoking cessation >12 months preoperatively (n = 1399). The risks of postoperative infection and revision surgery were assessed at 90 days, 1 year, and 2 years following surgery. Multivariate logistic regressions were used to isolate and evaluate risk factors for postoperative complications. RESULTS: The 90-day rate of infection following RCR was 0.28% in never smokers compared with 0.51% in current smokers and 0.52% in former smokers who quit smoking 3-6 months prior to surgery (P < .001). Multivariate logistic regression identified smoking (odds ratio [OR], 1.49; P < .001) and smoking cessation 3-6 months prior to surgery (OR, 1.56; P < .001) as risk factors for 90-day infection. The elevated risk in these groups persisted at 1 and 2 years postoperatively. However, smoking cessation >6 months prior to surgery was not associated with a significant elevation in infection risk. In addition, smoking was associated with an elevated 90-day revision risk (OR, 1.22; P = .038), as was smoking cessation between 3 and 6 months prior to surgery (OR, 1.19; P = .048). The elevated risk in these groups persisted at 1 and 2 years postoperatively. Smoking cessation >6 months prior to surgery was not associated with a statistically significant elevation in revision risk. CONCLUSION: Current smokers and former smokers who quit smoking within 6 months of RCR are at an elevated risk of postoperative infection and revision surgery at 90 days, 1 year, and 2 years postoperatively compared with never smokers. Former smokers who quit >6 months prior to RCR are not at a detectably elevated risk of infection or revision surgery compared with those who have never smoked.

Depression and anxiety are associated with worse baseline function in hip arthroscopy patients.

PURPOSE: The purpose of this study was to analyze the correlation between baseline depression and anxiety and preoperative functional status in hip arthroscopy patients. METHODS: A prospective, institutional review board-approved orthopaedic registry was used to retrospectively study 104 patients undergoing hip arthroscopy. Enrolled patients were administered baseline questionnaires for Patient-Reported Outcomes Measurement Information System (PROMIS) domains, Musculoskeletal Outcomes Data Evaluation and Management System (MODEMS) preoperative expectations, and Numeric Pain Scale (NPS). RESULTS: The average baseline PROMIS Depression and Anxiety scores were 49.9 ± 9.8 and 55.5 ± 9.3, respectively. Bivariate analysis demonstrated that greater baseline PROMIS Anxiety correlated with worse preoperative PROMIS PI (p < 0.001), Fatigue (p < 0.001), Social Satisfaction (p < 0.001), and NPS score (p = 0.013). Bivariate analysis showed that greater PROMIS Depression correlated with worse preoperative PROMIS PF (p = 0.001), PI (p < 0.001), Fatigue (p < 0.001), SS (p < 0.001), and NPS score (p = 0.004). After controlling for confounders, multivariable analysis confirmed increased PROMIS Depression as an independent predictor of worse preoperative PROMIS PF (p = 0.009), MODEMS Expectations (p = 0.025), and NPS score (p = 0.002). Increased PROMIS Anxiety was predictive of worse baseline PROMIS PI (p < 0.001), Fatigue (p < 0.001), and Social Satisfaction (p < 0.001). A previous clinical diagnosis of depression or anxiety was only an independent predictor of worse baseline PROMIS Fatigue (p = 0.002) and was insignificant in all other models. CONCLUSION: Increasing severity of depression and anxiety correlated with and predicted worse functional status at baseline in hip arthroscopy patients. As compared to clinical diagnosis of anxiety and depression, PROMIS metrics have superior utility in recognizing potentially modifiable mental health concerns that predict worse preoperative status. Ultimately, the study identifies an at-risk population undergoing hip arthroscopy that requires particular attention and potential mental health intervention in the preoperative setting. LEVEL OF EVIDENCE: III.

Patient Perception of Being "Completely Better" After Anterior Cruciate Ligament Reconstruction.

BACKGROUND: Contextualizing patient-reported outcomes (PROs) by defining clinically relevant differences is important. Considering that anterior cruciate ligament reconstruction (ACLR) ideally results in the restoration of normal knee function, an assessment of patients' perception of being "completely better" (CB) may be of particular value. PURPOSE: The purpose of this study was to assess the prevalence and characteristics of patients who self-report a CB status after ACLR. Additionally, we aimed to determine whether PROs were associated with a CB status after ACLR as well as to determine CB status thresholds for 2-year and change in values. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: We retrospectively analyzed data from an orthopaedic registry at a single institution. Patients were administered the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF), PROMIS Pain Interference (PI), and International Knee Documentation Committee (IKDC) Subjective Knee Form preoperatively and at 2 years after ACLR. Additionally, patients completed a CB anchor question at 2 years after ACLR. Thresholds for 2-year and change in PRO scores associated with achieving a CB status were identified with 90% specificity. RESULTS: Overall, 95 of the 136 patients (69.9%) considered their condition to be CB at 2 years after surgery. The 2-year and change in PROMIS PF, PROMIS PI, and IKDC scores were significantly better in the CB group than in the non-CB group. Thresholds associated with a CB status for 2-year PROMIS PF, PROMIS PI, and IKDC scores were more reliable than those for changes in scores and were ≥63, ≤44, and ≥80, respectively. Thresholds for the change in PROMIS PF, PROMIS PI, and IKDC scores were ≥19, ≤-16, and ≥44, respectively. CONCLUSION: The majority of patients reported that they were CB at 2 years after ACLR. This study may serve as a reference for orthopaedic surgeons and researchers when considering outcomes after ACLR.

Are deep infections that present before and after 90 days from orthopaedic trauma different? An analysis of the validity of the recent change in CDC criteria for infections.

BACKGROUND: In 2016, the Centers for Disease Control and Prevention (CDC) changed the time frame for their definition of deep surgical site infection (SSI) from within 1 year to within 90 days of surgery. We hypothesized that a substantial number of infections in patients who have undergone fracture fixation present beyond 90 days and that there are patient or injury factors that can predict who is more likely to present with SSI after 90 days. METHODS: A retrospective review yielded 452 deep SSI after fracture fixation. These patients were divided into two groups-those infected within 90 days of surgery and those infected beyond 90 days . Data were collected on risk factors for infection. Univariate and multiple logistic regression analyses were performed to compare the two groups. A randomly selected control group was used to build infection prediction models for both outcomes. The two outcomes were then modelled against each other to determine whether differences in predictors for early versus late infection exist. RESULTS: Of the 452 infections, 144 occurred beyond 90 days (32% [95% CI, 28%-36%]). No statistically significant patient factors were found in multivariable analysis between the early and late infection groups. The need for flap coverage was the only injury characteristic that differed significantly between groups, with patients in the late infection group more likely to have needed a flap. When modelled against the control group and directly comparing the two models, predictors for early infection include male sex and fractures of the pelvis, acetabulum, or hip, whereas predictors of late infection include hepatitis C and/or human immunodeficiency virus (HIV) and admission to the intensive care unit (ICU). CONCLUSION: Use of the recent CDC definition will underestimate the rate of actual postoperative infections when applied to orthopaedic trauma patients. Hepatitis C and/or HIV and ICU admission are predictors of late infection, whereas male sex and pelvis, acetabulum, or hip fractures are predictors of early infection. Patients who receive flap coverage may be more likely to present with late infection.

A Predictive Score for Determining Risk of Surgical Site Infection After Orthopaedic Trauma Surgery.

OBJECTIVES: To determine factors predictive of postoperative surgical site infection (SSI) after fracture fixation and create a prediction score for risk of infection at time of initial treatment. DESIGN: Retrospective cohort study. SETTING: Level I trauma center. PATIENTS/PARTICIPANTS: Study group, 311 patients with deep SSI; control group, 608 patients. INTERVENTION: We evaluated 27 factors theorized to be associated with postoperative infection. Bivariate and multiple logistic regression analyses were used to build a prediction model. A composite score reflecting risk of SSI was then created. MAIN OUTCOME MEASURES: Risk of postoperative infection. RESULTS: The final model consisted of 8 independent predictors: (1) male sex, (2) obesity (body mass index ≥ 30) (3) diabetes, (4) alcohol abuse, (5) fracture region, (6) Gustilo-Anderson type III open fracture, (7) methicillin-resistant Staphylococcus aureus nasal swab testing (not tested or positive result), and (8) American Society of Anesthesiologists classification. Risk strata were well correlated with observed proportion of SSI and resulted in a percent risk of infection of 1% for ≤3 points, 6% for 4-5 points, 11% for 6 to 8-9 points, and 41% for ≥10 points. CONCLUSION: The proposed postoperative infection prediction model might be able to determine which patients have fractures at higher risk of infection and provides an estimate of the percent risk of infection before fixation. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.