Prediction of 30-Day Mortality Following Revision Total Hip and Knee Arthroplasty: Machine Learning Algorithms Outperform CARDE-B, 5-Item, and 6-Item Modified Frailty Index Risk Scores.

BACKGROUND: Although risk calculators are used to prognosticate postoperative outcomes following revision total hip and knee arthroplasty (total joint arthroplasty [TJA]), machine learning (ML) based predictive tools have emerged as a promising alternative for improved risk stratification. This study aimed to compare the predictive ability of ML models for 30-day mortality following revision TJA to that of traditional risk-assessment indices such as the CARDE-B score (congestive heart failure, albumin (< 3.5 mg/dL), renal failure on dialysis, dependence for daily living, elderly (> 65 years of age), and body mass index (BMI) of < 25 kg/m2), 5-item modified frailty index (5MFI), and 6MFI. METHODS: Adult patients undergoing revision TJA between 2013 and 2020 were selected from the American College of Surgeons National Surgical Quality Improvement Program database and randomly split 80:20 to compose the training and validation cohorts. There were 3 ML models - extreme gradient boosting, random forest, and elastic-net penalized logistic regression (NEPLR) - that were developed and evaluated using discrimination, calibration metrics, and accuracy. The discrimination of CARDE-B, 5MFI, and 6MFI scores was assessed individually and compared to that of ML models. RESULTS: All models were equally accurate (Brier score = 0.005) and demonstrated outstanding discrimination with similar areas under the receiver operating characteristic curve (AUCs, extreme gradient boosting = 0.94, random forest = NEPLR = 0.93). The NEPLR was the best-calibrated model overall (slope = 0.54, intercept = -0.004). The CARDE-B had the highest discrimination among the scores (AUC = 0.89), followed by 6MFI (AUC = 0.80), and 5MFI (AUC = 0.68). Albumin < 3.5 mg/dL and BMI (< 30.15) were the most important predictors of 30-day mortality following revision TJA. CONCLUSIONS: The ML models outperform traditional risk-assessment indices in predicting postoperative 30-day mortality after revision TJA. Our findings highlight the utility of ML for risk stratification in a clinical setting. The identification of hypoalbuminemia and BMI as prognostic markers may allow patient-specific perioperative optimization strategies to improve outcomes following revision TJA.

A concerted neuron-astrocyte program declines in ageing and schizophrenia.

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.

Concerted neuron-astrocyte gene expression declines in aging and schizophrenia.

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron-and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.

Do preoperative PROMIS scores independently predict 90-day readmission following primary total knee arthroplasty?

INTRODUCTION: The rising demand for total knee arthroplasty (TKA) is expected to increase the total number of TKA-related readmissions, presenting significant public health and economic burden. With the increasing use of Patient-Reported Outcomes Measurement Information System (PROMIS) scores to inform clinical decision-making, this study aimed to investigate whether preoperative PROMIS scores are predictive of 90-day readmissions following primary TKA. MATERIALS AND METHODS: We retrospectively reviewed a consecutive series of 10,196 patients with preoperative PROMIS scores who underwent primary TKA. Two comparison groups, readmissions (n = 79; 3.6%) and non-readmissions (n = 2091; 96.4%) were established. Univariate and multivariate logistic regression analyses were then performed with readmission as the outcome variable to determine whether preoperative PROMIS scores could predict 90-day readmission. RESULTS: The study cohort consisted of 2170 patients overall. Non-white patients (OR = 3.53, 95% CI [1.16, 10.71], p = 0.026) and patients with cardiovascular or cerebrovascular disease (CVD) (OR = 1.66, 95% CI [1.01, 2.71], p = 0.042) were found to have significantly higher odds of 90-day readmission after TKA. Preoperative PROMIS-PF10a (p = 0.25), PROMIS-GPH (p = 0.38), and PROMIS-GMH (p = 0.07) scores were not significantly associated with 90-day readmission. CONCLUSION: This study demonstrates that preoperative PROMIS scores may not be used to predict 90-day readmission following primary TKA. Non-white patients and patients with CVD are 3.53 and 1.66 times more likely to be readmitted, highlighting existing racial disparities and medical comorbidities contributing to readmission in patients undergoing TKA.

Patient-Reported Outcomes Measurement Information System Physical Function and Global Physical Health Subscale Strongly Correlate and Perform Similarly to the Knee Injury and Osteoarthritis Outcome Score-Physical Function Short Form.

BACKGROUND: Arthroplasty surgeons use a variety of patient-reported outcome measures (PROMs) to assess functional well-being, including the Knee Injury and Osteoarthritis Outcome Score (KOOS) Physical Function short form (KOOS-PS), Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function Short Form 10a (PROMIS PF SF 10a), and PROMIS Global-10 Physical Health subscale. However, there is a paucity of literature assessing their concurrent validity and performance. METHODS: Between June 2016 and December 2020, patient visits at an arthroplasty clinic for knee concerns were identified. Patients who completed KOOS-PS, PROMIS PF SF 10a, and PROMIS Global-10, including its physical and mental health subscales, at the same visit were identified. Spearman rho (ρ) correlations were calculated and ceiling and floor effects identified. Overall, 5,303 patient encounters were included. RESULTS: Among physical function domains, strong correlation existed between the KOOS-PS and PROMIS PF SF 10a (ρ = 0.76, P < .001), KOOS-PS and PROMIS Global Physical Health (ρ = 0.71, P < .001), and PROMIS PF SF 10a and PROMIS Global Physical Health (ρ = 0.78, P < .001). No physical function-focused PROM had an appreciable floor effect (ie, at or more than 1%). The KOOS-PS had a small but measurable ceiling effect (n = 105 [2.0%]). CONCLUSIONS: All of the examined PROMs are acceptable to measure the functional status of patients with knee pathology, with the PROMIS Global-10 also being able to capture elements of mental health too. The PROMIS Global-10 may be of most value of the PROMs assessed, as the United States Centers for Medicare and Medicaid Services already incorporate the mental health component into new alternative payment models.

Degree of articular injury as measured by CT cross sectional area is associated with physical function following the treatment of bicondylar tibial plateau fractures.

BACKGROUND: Bicondylar tibial plateau fractures are complex injuries that commonly require surgical repair. Long-term clinical outcome has been associated with discrepancies in leg alignment, instability and condylar width abnormalities. While intuitive, the degree of articular damage at time of injury has not been linked to outcomes in patients with bicondylar tibial plateau fractures. The aim of this study was to quantify percentage of articular surface cross sectional area disruption and assess for correlation between the degree of articular injury and patient reported physical function. METHODS: Retrospective cohort study at two level 1 trauma centers. 57 consecutive patients undergoing surgical repair for bicondylar tibial plateau fractures between 2013 and 2016. MAIN OUTCOME MEASURE: Preoperative CT scans were reviewed, and the percentage of articular surface disruption cross sectional area was calculated. PROMIS® scores were collected from patients at a minimum of 2 years. RESULTS: 57 patients with an average age of 58 ± 14.3 years were included. The average PROMIS® score was 45.5. There was a correlation between percentage of articular surface disruption and total PROMIS® scores (0.4, CI: 0.2-0.5, p = .007) and the physical function of the PROMIS® score (0.4, CI: 0.2-0.6, p < .001). CONCLUSION: Our method for calculating articular surface disruption on CT is a simple, reproducible and accurate method for assessing the degree of articular damage in patients with bicondylar tibial plateau fractures. We found that the percentage of cross-sectional articular surface disruption correlates with patient reported outcomes and physical function.

A global federated real-world data and analytics platform for research.

Objective: This article describes a scalable, performant, sustainable global network of electronic health record data for biomedical and clinical research. Materials and Methods: TriNetX has created a technology platform characterized by a conservative security and governance model that facilitates collaboration and cooperation between industry participants, such as pharmaceutical companies and contract research organizations, and academic and community-based healthcare organizations (HCOs). HCOs participate on the network in return for access to a suite of analytics capabilities, large networks of de-identified data, and more sponsored trial opportunities. Industry participants provide the financial resources to support, expand, and improve the technology platform in return for access to network data, which provides increased efficiencies in clinical trial design and deployment. Results: TriNetX is a growing global network, expanding from 55 HCOs and 7 countries in 2017 to over 220 HCOs and 30 countries in 2022. Over 19 000 sponsored clinical trial opportunities have been initiated through the TriNetX network. There have been over 350 peer-reviewed scientific publications based on the network's data. Conclusions: The continued growth of the TriNetX network and its yield of clinical trial collaborations and published studies indicates that this academic-industry structure is a safe, proven, sustainable path for building and maintaining research-centric data networks.

Validation and Generalizability of Machine Learning Models for the Prediction of Discharge Disposition Following Revision Total Knee Arthroplasty.

BACKGROUND: Postoperative discharge to facilities account for over 33% of the $ 2.7 billion revision total knee arthroplasty (TKA)-associated annual expenditures and are associated with increased complications when compared to home discharges. Prior studies predicting discharge disposition using advanced machine learning (ML) have been limited due to a lack of generalizability and validation. This study aimed to establish ML model generalizability by externally validating its prediction for nonhome discharge following revision TKA using national and institutional databases. METHODS: The national and institutional cohorts comprised 52,533 and 1,628 patients, respectively, with 20.6 and 19.4% nonhome discharge rates. Five ML models were trained and internally validated (five-fold cross-validation) on a large national dataset. Subsequently, external validation was performed on our institutional dataset. Model performance was assessed using discrimination, calibration, and clinical utility. Global predictor importance plots and local surrogate models were used for interpretation. RESULTS: The strongest predictors of nonhome discharge were patient age, body mass index, and surgical indication. The area under the receiver operating characteristic curve increased from internal to external validation and ranged between 0.77 and 0.79. Artificial neural network was the best predictive model for identifying patients at risk for nonhome discharge (area under the receiver operating characteristic curve = 0.78), and also the most accurate (calibration slope = 0.93, intercept = 0.02, and Brier score = 0.12). CONCLUSION: All five ML models demonstrated good-to-excellent discrimination, calibration, and clinical utility on external validation, with artificial neural network being the best model for predicting discharge disposition following revision TKA. Our findings establish the generalizability of ML models developed using data from a national database. The integration of these predictive models into clinical workflow may assist in optimizing discharge planning, bed management, and cost containment associated with revision TKA.

The Use of Artificial Neural Networks for the Prediction of Surgical Site Infection Following TKA.

This is a retrospective study. Surgical site infection (SSI) is associated with adverse postoperative outcomes following total knee arthroplasty (TKA). However, accurately predicting SSI remains a clinical challenge due to the multitude of patient and surgical factors associated with SSI. This study aimed to develop and validate machine learning models for the prediction of SSI following primary TKA. This is a retrospective study for patients who underwent primary TKA. Chart review was performed to identify patients with superficial or deep SSIs, defined in concordance with the criteria of the Musculoskeletal Infection Society. All patients had a minimum follow-up of 2 years (range: 2.1-4.7 years). Five machine learning algorithms were developed to predict this outcome, and model assessment was performed by discrimination, calibration, and decision curve analysis. A total of 10,021 consecutive primary TKA patients was included in this study. At an average follow-up of 2.8 ± 1.1 years, SSIs were reported in 404 (4.0%) TKA patients, including 223 superficial SSIs and 181 deep SSIs. The neural network model achieved the best performance across discrimination (area under the receiver operating characteristic curve = 0.84), calibration, and decision curve analysis. The strongest predictors of the occurrence of SSI following primary TKA, in order, were Charlson comorbidity index, obesity (BMI >30 kg/m2), and smoking. The neural network model presented in this study represents an accurate method to predict patient-specific superficial and deep SSIs following primary TKA, which may be employed to assist in clinical decision-making to optimize outcomes in at-risk patients.

The utility of machine learning algorithms for the prediction of patient-reported outcome measures following primary hip and knee total joint arthroplasty.

BACKGROUND: Patient-reported outcome measures (PROMs) are increasingly used as quality benchmark in total hip and knee arthroplasty (THA; TKA) due to bundled payment systems that aim to provide a patient-centered, value-based treatment approach. However, there is a paucity of predictive tools for postoperative PROMs. Therefore, this study aimed to develop and validate machine learning models for the prediction of numerous patient-reported outcome measures following primary hip and knee total joint arthroplasty. METHODS: A total of 4526 consecutive patients (2137 THA; 2389 TKA) who underwent primary hip and knee total joint arthroplasty and completed both pre- and postoperative PROM scores was evaluated in this study. The following PROM scores were included for analysis: HOOS-PS, KOOS-PS, Physical Function SF10A, PROMIS SF Physical and PROMIS SF Mental. Patient charts were manually reviewed to identify patient demographics and surgical variables associated with postoperative PROM scores. Four machine learning algorithms were developed to predict postoperative PROMs following hip and knee total joint arthroplasty. Model assessment was performed through discrimination, calibration and decision curve analysis. RESULTS: The factors most significantly associated with the prediction of postoperative PROMs include preoperative PROM scores, Charlson Comorbidity Index, American Society of Anaesthesiology score, insurance status, age, length of hospital stay, body mass index and ethnicity. The four machine learning models all achieved excellent performance across discrimination (AUC > 0.83), calibration and decision curve analysis. CONCLUSION: This study developed machine learning models for the prediction of patient-reported outcome measures at 1-year following primary hip and knee total joint arthroplasty. The study findings show excellent performance on discrimination, calibration and decision curve analysis for all four machine learning models, highlighting the potential of these models in clinical practice to inform patients prior to surgery regarding their expectations of postoperative functional outcomes following primary hip and knee total joint arthroplasty. LEVEL OF EVIDENCE: Level III, case control retrospective analysis.

Elevated ESR and CRP Prior to Second-Stage Reimplantation Knee Revision Surgery for Periprosthetic Joint Infection Are Associated with Increased Reinfection Rates.

Although two-stage revision surgery is considered as the most effective treatment for managing chronic periprosthetic joint infection (PJI), there is no current consensus on the predictors of optimal timing to second-stage reimplantation. This study aimed to compare clinical outcomes between patients with elevated erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) prior to second-stage reimplantation and those with normalized ESR and CRP prior to second-stage reimplantation. We retrospectively reviewed 198 patients treated with two-stage revision total knee arthroplasty for chronic PJI. Cohorts included patients with: (1) normal level of serum ESR and CRP (n = 96) and (2) elevated level of serum ESR and CRP prior to second-stage reimplantation (n = 102). Outcomes including reinfection rates and readmission rates were compared between both cohorts. At a mean follow-up of 4.4 years (2.8-6.5 years), the elevated ESR and CRP cohort demonstrated significantly higher reinfection rates compared with patients with normalized ESR and CRP prior to second-stage reimplantation (33.3% vs. 14.5%, p < 0.01). Patients with both elevated ESR and CRP demonstrated significantly higher reinfection rates, when compared with patients with elevated ESR and normalized CRP (33.3% vs. 27.6%, p = 0.02) as well as normalized ESR and elevated CRP (33.3% vs. 26.3%, p < 0.01). This study demonstrates that elevated serum ESR and/or CRP levels prior to reimplantation in two-stage knee revision surgery for chronic PJI are associated with increased reinfection rate after surgery. Elevation of both ESR and CRP were associated with a higher risk of reinfection compared with elevation of either ESR or CRP, suggesting the potential benefits of normalizing ESR and CRP prior to reimplantation in treatment of chronic PJI.

Insurance Payer Type Affects Outcomes after Revision Total Joint Arthroplasty: A Matched Cohort Analysis.

Background: The aim of this study is to evaluate the potential effects of insurance payer type on the postoperative outcomes following revision TJA. Methods: A single-institution database was utilized to identify 4,302 consecutive revision THA and TKA. Patient demographics and indications for revision were collected and compared based on patient insurance payer type: (1) Medicaid, (2) Medicare, and (3) private. Propensity score matching and, subsequent, multivariate regression analyses were applied to control for baseline differences between payer groups. Outcomes of interest were rates of complications occurring perioperatively and 90 days post-discharge. Results: After propensity-score-based matching, a total of 2,328 patients remained for further multivariate regression analyses (300 [12.9%] Medicaid, 1022 [43.9%] Medicare, 1006 [43.2%] private). Compared to privately insured patients, Medicaid and Medicare patients had 71% (P<0.01) and 53% (P=0.03) increased odds, respectively, for developing an in-hospital complication. At 90 days post-discharge, compared to privately insured patients, Medicaid and Medicare patients had 88% and 43% odds, respectively, for developing overall major complications. Conclusion: Our propensity-score-matched cohort study found that, compared to privately insured patients, patients with government-sponsored insurance were at an increased risk for developing both major or minor complications perioperatively and at 90-days post-discharge for revision TJA. This suggests that insurance payer type is an independent risk factor for poor outcomes following revision TJA.

Machine learning algorithms predict extended postoperative opioid use in primary total knee arthroplasty.

PURPOSE: Adequate postoperative pain control following total knee arthroplasty (TKA) is required to achieve optimal patient recovery. However, the postoperative recovery may lead to an unnaturally extended opioid use, which has been associated with adverse outcomes. This study hypothesizes that machine learning models can accurately predict extended opioid use following primary TKA. METHODS: A total of 8873 consecutive patients that underwent primary TKA were evaluated, including 643 patients (7.2%) with extended postoperative opioid use (> 90 days). Electronic patient records were manually reviewed to identify patient demographics and surgical variables associated with prolonged postoperative opioid use. Five machine learning algorithms were developed, encompassing the breadth of state-of-the-art machine learning algorithms available in the literature, to predict extended opioid use following primary TKA, and these models were assessed by discrimination, calibration, and decision curve analysis. RESULTS: The strongest predictors for prolonged opioid prescription following primary TKA were preoperative opioid duration (100% importance; p < 0.01), drug abuse (54% importance; p < 0.01), and depression (47% importance; p < 0.01). The five machine learning models all achieved excellent performance across discrimination (AUC > 0.83), calibration, and decision curve analysis. Higher net benefits for all machine learning models were demonstrated, when compared to the default strategies of changing management for all patients or no patients. CONCLUSION: The study findings show excellent model performance for the prediction of extended postoperative opioid use following primary total knee arthroplasty, highlighting the potential of these models to assist in preoperatively identifying at risk patients, and allowing the implementation of individualized peri-operative counselling and pain management strategies to mitigate complications associated with prolonged opioid use. LEVEL OF EVIDENCE: IV.

A bidirectional competitive interaction between circHomer1 and Homer1b within the orbitofrontal cortex regulates reversal learning.

Although circular RNAs (circRNAs) are enriched in the brain, their relevance for brain function and psychiatric disorders is poorly understood. Here, we show that circHomer1 is inversely associated with relative HOMER1B mRNA isoform levels in both the orbitofrontal cortex (OFC) and stem-cell-derived neuronal cultures of subjects with psychiatric disorders. We further demonstrate that in vivo circHomer1 knockdown (KD) within the OFC can inhibit the synaptic expression of Homer1b mRNA. Furthermore, we show that circHomer1 directly binds to Homer1b mRNA and that Homer1b-specific KD increases synaptic circHomer1 levels and improves OFC-mediated behavioral flexibility. Importantly, double circHomer1 and Homer1b in vivo co-KD results in a complete rescue in circHomer1-associated alterations in both chance reversal learning and synaptic gene expression. Lastly, we uncover an RNA-binding protein that can directly bind to circHomer1 and promote its biogenesis. Taken together, our data provide mechanistic insights into the importance of circRNAs in brain function and disease.

Knee Arthroscopy Prior to Revision TKA Is Associated with Increased Re-Revision for Stiffness.

This is an experimental study. As knee arthroscopy may be used as a suitable temporizing alternative prior to revision surgery, knee arthroscopy potentially may be a risk factor for subsequent adverse outcomes after revision total knee arthroplasty (TKA). This study aimed to evaluate the impact of prior knee arthroscopy on outcomes of subsequent TKA revision surgery. We identified 1,689 consecutive patients who underwent revision TKA: (1) patients with no prior knee arthroscopy (n = 1,549) and (2) patients with knee arthroscopy prior to revision TKA (n = 140). A control group of matched revision TKA patients who did not undergo prior knee arthroscopy was identified (700 patients), using one-to-five matching. Matched patients with prior knee arthroscopy demonstrated an increased likelihood of requiring re-revision (odds ratio [OR], 2.06, p < 0.001), particularly for stiffness (OR, 2.72, p < 0.02) compared with patients who underwent revision TKA without prior knee arthroscopy. Knee arthroscopy demonstrated a time-dependent impact on revision TKA outcomes, with an increased likelihood of requiring re-revision for patients who underwent knee arthroscopy within 6 months prior to revision TKA compared with patients who underwent knee arthroscopy within 6 to 12 months prior to revision TKA (OR, 3.16, p < 0.04). This cohort matched study shows that patients who had prior knee arthroscopy demonstrated a significantly higher likelihood of requiring re-revision compared with patients who underwent revision TKA without prior knee arthroscopy. Additionally, there was a significant increased likelihood in requiring re-revision for patients who had prior knee arthroscopy within 6 months. This provides clinically useful information for counseling of patients who are considering temporizing their symptoms with knee arthroscopy prior to revision TKA.

A Live Video Program to Prevent Chronic Pain and Disability in At-Risk Adults With Acute Orthopedic Injuries (Toolkit for Optimal Recovery): Protocol for a Multisite Feasibility Study.

BACKGROUND: Despite the pivotal role of psychosocial factors in pain and disability after orthopedic injury, there are no evidence-based preventive interventions targeting psychosocial factors in patients with acute orthopedic injuries. We developed the first mind-body intervention focused on optimizing recovery and improving pain and disability in patients with acute orthopedic injuries who exhibit high levels of catastrophic thinking about pain and/or pain anxiety (Toolkit for Optimal Recovery [TOR] after orthopedic injury). In a pilot single-site randomized controlled trial (RCT), the TOR met a priori set benchmarks for feasibility, acceptability, and satisfaction. The next step in developing TOR is to conduct a multisite feasibility RCT to set the stage for a scientifically rigorous hybrid efficacy-effectiveness trial. OBJECTIVE: The objective of this study is to conduct a rigorous multisite feasibility RCT of TOR to determine whether the intervention and study methodology meet a priori set benchmarks necessary for the successful implementation of a future multisite hybrid efficacy-effectiveness trial. In this paper, we describe the study design, manualized treatments, and specific strategies used to conduct this multisite feasibility RCT investigation. METHODS: This study will be conducted at 3 geographically diverse level 1 trauma centers, anonymized as sites A, B, and C. We will conduct a multisite feasibility RCT of TOR versus the minimally enhanced usual care (MEUC) control (60 patients per site; 30 per arm) targeting a priori set feasibility benchmarks. Adult patients with acute orthopedic injuries who endorse high pain catastrophizing or pain anxiety will be recruited approximately 1-2 months after injury or surgery (baseline). Participants randomized to the TOR will receive a 4-session mind-body treatment delivered via a secure live video by trained clinical psychologists. Participants randomized to the MEUC will receive an educational booklet. Primary outcomes include feasibility of recruitment, appropriateness, feasibility of data collection, acceptability of TOR (adherence to sessions), and treatment satisfaction across all sites. We will also collect data on secondary implementation outcomes, as well as pain severity, physical and emotional function, coping skills, and adverse events. Outcomes will be assessed at baseline, posttreatment, and at the 3-month follow-up. RESULTS: Enrollment for the RCT is estimated to begin in June 2021. The target date of completion of the feasibility RCT is April 2024. The institutional review board approval has been obtained (January 2020). CONCLUSIONS: This investigation examines the multisite feasibility of TOR administered via live videoconferencing in adult patients with acute orthopedic injuries. If feasible, the next step is a multisite, hybrid efficacy-effectiveness trial of TOR versus MEUC. Preventive psychosocial interventions can provide a new way to improve patient and provider satisfaction and decrease suffering and health care costs among patients with orthopedic injuries who are at risk for chronic pain and disability. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28155.

Complications and Soft-Tissue Coverage After Complete Articular, Open Tibial Plafond Fractures.

OBJECTIVES: To evaluate the incidence of nonunion and wound complications after open, complete articular pilon fractures. Second, to study the effect that both timing of fixation and timing of flap coverage have on deep infection rates. DESIGN: Retrospective case series. SETTING: Three Academic Level 1 Trauma Centers. PATIENTS: One hundred sixty-one patients with open OTA/AO type 43C distal tibia fractures treated with open reduction internal fixation (ORIF) between 2002 and 2018. The mean (SD) age was 46 (14) years, 70% male, with median (interquartile range) follow-up of 2.1 (1.3-5.0) years (minimum 1 year). There were 133 (83%) type 3A and 28 (17%) type 3B open fractures. INTERVENTION: Fracture fixation: acute, primary (<24 hours) versus delayed, staged ORIF (>24 hours). Soft-tissue coverage: rotational or free flap. MAIN OUTCOME MEASUREMENT: Primary outcomes included deep infection and nonunion. Secondary outcomes included rates of soft-tissue coverage and reoperation. RESULTS: Acute fixation (<24 hours) was performed in 36 (22%) patients; 125 (78%) underwent delayed, staged fixation. Deep infection occurred in 27% patients and was associated with men (33% vs. 16%, P = 0.029), smoking (38% vs. 23%, P = 0.047), and type 3B fractures (39% vs. 25%, P = 0.046). Acute fixation of type 3A fractures demonstrated a higher rate of infection (38% vs. 20% P = 0.036) than delayed, staged fixation. In type 3B fractures, early flap coverage (<1 week) demonstrated a lower rate of infection (18% vs. 53%, P = 0.066) and 20% (vs. 43%) with a single-staged "fix and flap" procedure (P = 0.408). Nonunion occurred in 36 (22%) and was associated with deep infection (43% vs. 15%, P < 0.001). Fifteen (42%) were septic nonunions. Twenty-nine of the 36 (81%) nonunions achieved radiographic union after median (interquartile range) 27 (20-41) weeks and median (range) 1 (1-3) revision ORIF procedures. There was no difference in the rate of secondary union between septic and aseptic nonunions (85% vs. 86%, P = 1.00). There was a high rate of secondary procedures (47%): revision ORIF (17%), irrigation and debridement (15%), and removal of implants (11%). CONCLUSIONS: Complete articular, open pilon fractures are associated with a high rate of complications after ORIF. Early fixation carries a high risk of deep infection; however, early flap coverage for 3B fractures seems to play a protective role. We advocate for aggressive management including urgent surgical debridement and very early soft-tissue cover combined with definitive fixation during single procedure if possible. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Judicious Use of Early Fixation of Closed, Complete Articular Pilon Fractures Is Not Associated With an Increased Risk of Deep Infection or Wound Complications.

OBJECTIVES: To compare the deep infection rates after immediate versus staged open reduction internal fixation (ORIF) for pilon fractures. DESIGN: Retrospective cohort study. SETTING: Three academic Level I trauma centers. PATIENTS: Four hundred one patients with closed OTA/AO type 43C distal tibia fractures treated with ORIF. Sixty-six percent were men, and the mean age was 45.6 years. The median (interquartile range) follow-up was 1.7 (1.0-3.7) years. INTERVENTION: Acute, primary (<24 hours) versus delayed, staged ORIF (>24 hours). MAIN OUTCOME MEASUREMENT: Deep infection or wound complication as defined by return to operating room for surgical irrigation and debridement. RESULTS: Patients were grouped by time from presentation to surgery: acute ORIF (n = 99) and delayed ORIF (n = 302). Acute ORIF was more frequent in patients with OTA/AO type 43C1 fractures, low-energy mechanisms (ie, fall from standing), younger and female patients. Patients who demonstrated severe swelling (242, 80%), swelling and fracture blisters (26, 9%), swelling and ecchymosis precluding planned surgical approach (4, 1%), polytrauma requiring resuscitation (20, 6%), who were transferred from an outside facility with external fixator in place (6, 2%), who had evolving compartment syndrome (2, 1%), and who required medical clearance (2, 1%) underwent staged, delayed fixation. There were significantly more 43C1 fractures in the acute fixation group (31% vs. 7%, P < 0.001) and significantly more 43C3 fractures in the delayed group (63% vs. 37%, P < 0.001). The overall deep infection rate was 17%. Early surgery was not associated with an increased risk of postoperative wound complication (early 12% vs. delayed 18%, P = 0.235). Multivariate analysis adjusted for timing of surgery found high-energy trauma [odds ratio (OR) 4.0, 95% confidence interval (CI) 1.1-13.8], smoking (OR 2.4, CI 1.3-4.6), male sex (OR 2.1, CI 1.0-4.1), and increasing age (OR 1.02, CI 1.00-1.04, P = 0.040) to be independent predictors of deep infection. Diabetes demonstrated a nonstatistically significant increased risk (OR 2.6, 95% CI 0.9-7.3, P = 0.063). CONCLUSIONS: This study confirms the high risk of infection after the fixation of tibial plafond fractures. If early definitive fixation is considered, extreme care should be taken to carefully evaluate the soft tissue envelope and assess for other risk factors (such as age, male sex, smokers, diabetics, and those with higher-energy fracture patterns) that may predispose the patient to a postoperative soft tissue infection. Our study has shown that the judicious use of early definitive fixation in closed pilon fractures, in the appropriate patient, and with careful evaluation of the soft tissue envelope, is likely safe and does not seem to increase the risk of wound complications and deep infection in the hands of experienced fracture surgeons. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

On evidence for a dozen new basic emotions: A methodological critique.

Much theory, research, and application regarding emotion is based on a set of basic emotions. But the question remains: which emotions are in that set? One proposal is to expand the classic set of six with 12 new ones, each indicated by a facial expression purported to convey that one specific emotion universally. A series of studies offered as support for this proposal relied on presenting participants with the emotion label embedded in a story and then asking them to choose among four facial expressions or none. Here we critique that response procedure (used in various studies) as confounding emotion with story. Our Study 1 (N = 1,230 residents of the United States) found that the same response procedure could "show" that the facial expressions used in that previous research convey emotions other than the ones that had been proposed. Our Study 2 (N = 64 in India and N = 56 in China) found similar results with participants who speak non-Indo-European languages (Malayalam and Mandarin). Altogether, our results question whether the proposed set of new basic emotions is warranted, given problems in the response procedure in which an emotion is embedded in a story. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Does Surgical Approach Influence the Risk of Postoperative Infection After Surgical Treatment of Tibial Pilon Fractures?

OBJECTIVES: To determine whether a particular surgical approach or combination of approaches is a risk factor for infection. DESIGN: Retrospective review. SETTING: Two Level-1 trauma centers. PATIENTS/PARTICIPANTS: Five hundred ninety pilon fractures in 581 patients (66% male) with a median age of 45 years were identified. INTERVENTION: Open reduction internal fixation of pilon fractures. MAIN OUTCOME MEASURES: Postoperative deep surgical site infection and risk factors for postoperative deep infection. RESULTS: The most common primary surgical approach was medial (54%), followed by anterolateral (25%), anteromedial (11%), posterolateral (8%), and posteromedial (2%). A dual approach to the distal tibia was used in 18% of the cases. The overall deep infection rate was 19%. There was no association between primary surgical approach and development of infection (P = 0.19-0.78). Independent risk factors for infection were smoking (hazard ratio, 2.1; P < 0.001) and need for soft tissue coverage (hazard ratio, 6.9; P < 0.001). CONCLUSIONS: Surgical approach does not appear to be a significant risk factor for postoperative infection after open reduction internal fixation of distal tibial pilon fractures. When treating tibial plafond fractures, surgeons should select the approach they feel best addresses the specific fracture pattern. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.