Maternal and Fetal Outcomes in Pulmonary Hypertension During Pregnancy: A Contemporary Nationwide Analysis.

Pulmonary hypertension (PH) disproportionately affects women, presenting challenges during pregnancy. Historically, patients with PH are advised to avoid pregnancy; however, recent reports have indicated that the incidence of adverse events in pregnant patients with PH may be lower than previously reported. We conducted a retrospective cohort study in pregnant patients with PH using the National Readmission Database from January 1, 2016, to December 31, 2020. PH was categorized according to the World Health Organization classification. Primary end points include maternal mortality and 30-day nonelective readmission rate. Other adverse short-term maternal (cardiovascular and obstetric) and fetal outcomes were also analyzed. Of 9,922,142 pregnant women, 3,532 (0.04%) had PH, with Group 1 PH noted in 1,833 (51.9%), Group 2 PH in 676 (19.1%), Group 3 PH in 604 (17.1%), Group 4 PH in 23 (0.7%), Group 5 PH in 98 (2.8%), and multifactorial PH in 298 (8.4%). PH patients exhibited higher rates of adverse cardiovascular events (15.7% vs 0.3% without PH, p <0.001) and mortality (0.9% vs 0.01% without PH, p <0.001). Mixed PH and Group 2 PH had the highest prevalence of adverse cardiovascular events in the World Health Organization PH groups. Patients with PH had a significantly higher nonelective 30-day readmission rate (10.4% vs 2.3%) and maternal adverse obstetric events (24.2% vs 9.1%) compared with those without PH (p <0.001) (Figure 1). In conclusion, pregnant women with PH had significantly higher adverse event rates, including in-hospital maternal mortality (85-fold), compared with those without PH.

A practical guide to the development and deployment of deep learning models for the orthopaedic surgeon: Part III, focus on registry creation, diagnosis, and data privacy.

Deep learning is a subset of artificial intelligence (AI) with enormous potential to transform orthopaedic surgery. As has already become evident with the deployment of Large Language Models (LLMs) like ChatGPT (OpenAI Inc.), deep learning can rapidly enter clinical and surgical practices. As such, it is imperative that orthopaedic surgeons acquire a deeper understanding of the technical terminology, capabilities and limitations associated with deep learning models. The focus of this series thus far has been providing surgeons with an overview of the steps needed to implement a deep learning-based pipeline, emphasizing some of the important technical details for surgeons to understand as they encounter, evaluate or lead deep learning projects. However, this series would be remiss without providing practical examples of how deep learning models have begun to be deployed and highlighting the areas where the authors feel deep learning may have the most profound potential. While computer vision applications of deep learning were the focus of Parts I and II, due to the enormous impact that natural language processing (NLP) has had in recent months, NLP-based deep learning models are also discussed in this final part of the series. In this review, three applications that the authors believe can be impacted the most by deep learning but with which many surgeons may not be familiar are discussed: (1) registry construction, (2) diagnostic AI and (3) data privacy. Deep learning-based registry construction will be essential for the development of more impactful clinical applications, with diagnostic AI being one of those applications likely to augment clinical decision-making in the near future. As the applications of deep learning continue to grow, the protection of patient information will become increasingly essential; as such, applications of deep learning to enhance data privacy are likely to become more important than ever before. Level of Evidence: Level IV.

Hip Arthroscopy Simulator Training With Immersive Virtual Reality Has Similar Effectiveness to Nonimmersive Virtual Reality.

PURPOSE: To (1) compare the efficacy of immersive virtual reality (iVR) to nonimmersive virtual reality (non-iVR) training in hip arthroscopy on procedural and knowledge-based skills acquisition and (2) evaluate the relative cost of each platform. METHODS: Fourteen orthopaedic surgery residents were randomized to simulation training utilizing an iVR Hip Arthroscopy Simulator (n = 7; PrecisionOS) or non-iVR simulator (n = 7; ArthroS Hip VR; VirtaMed). After training, performance was assessed on a cadaver by 4 expert hip arthroscopists through arthroscopic video review of a diagnostic hip arthroscopy. Performance was assessed using the Objective Structured Assessment of Technical Skills (OSATS) and Arthroscopic Surgery Skill Evaluation Tool (ASSET) scores. A cost analysis was performed using the transfer effectiveness ratio (TER) and a direct cost comparison of iVR to non-iVR. RESULTS: Demographic characteristics did not differ between treatment arms or by training level, hip arthroscopy experience, or prior simulator use. No significant differences were observed in OSATS and ASSET scores between iVR and non-iVR cohorts (OSATS: iVR 19.6 ± 4.4, non-iVR 21.0 ± 4.1, P = .55; ASSET: iVR 23.7 ± 4.5, non-iVR 25.8 ± 4.8, P = .43). The absolute TER was 0.06 and there was a 132-fold cost difference of iVR to non-iVR. CONCLUSIONS: Hip arthroscopy simulator training with iVR had similar performance results to non-iVR for technical skill and procedural knowledge acquisition after expert arthroscopic video assessment. The iVR platform had similar effectiveness in transfer of skill compared to non-iVR with a 132 times cost differential. CLINICAL RELEVANCE: Due to the accessibility, effectiveness, and relative affordability, iVR training may be beneficial in the future of safe arthroscopic hip training.

Modern Hip Arthroscopy for FAIS May Delay the Natural History of Osteoarthritis in 25% of Patients: A 12-Year Follow-up Analysis.

BACKGROUND: Little is known about the effect of modern hip arthroscopy on the natural history of femoroacetabular impingement syndrome (FAIS) with respect to joint preservation. PURPOSE: To (1) characterize the natural history of FAIS and (2) understand the effect of modern hip arthroscopy by radiographically comparing the hips of patients who underwent only unilateral primary hip arthroscopy with a minimum follow-up of 10 years. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Between 2010 and 2012, 619 consecutive patients were reviewed from the practice of a single fellowship-trained hip arthroscopic surgeon. Inclusion criteria were FAIS, bilateral radiographic findings of femoroacetabular impingement, primary unilateral hip arthroscopy (labral repair, femoroplasty, or capsular closure), and minimum 10-year follow-up. The preoperative and minimum 10-year postoperative radiographs of patients were evaluated at each time point. Both operative and nonoperative hips were graded using the Tönnis classification or the presence of hip arthroplasty by 2 independent reviewers. Subgroup analyses were performed. RESULTS: A total of 200 hips from 100 patients were evaluated at a mean follow-up of 12.0 years. Preoperatively, 98% and 99% of operative and nonoperative hips were evaluated as Tönnis grades 0 and 1, respectively; 5% of nonoperative hips had worse Tönnis grades than operative hips. The nonoperative hip advanced to a worse Tönnis grade in 48% (48/100) of cases compared with 28% (28/100) among operative hips. At follow-up, Tönnis grades between hips were equal in 70% (70/100) of the cases, the operative hip had a better grade 25% (25/100) of the time, and the nonoperative hip had a better grade 5% (5/100) of the time. Modern hip arthroscopy was associated with a relative risk reduction of 42% in osteoarthritis progression. Impingement with borderline dysplasia, age, preoperative Tönnis grade, and alpha angle >65° were key risk factors in the radiographic progression of osteoarthritis. CONCLUSION: Although the majority of patients (70%) undergoing hip arthroscopy for FAIS did not experience differences between operative and nonoperative hips in terms of the radiographic progression of osteoarthritis, the natural history may be favorably altered for 25% of patients whose Tönnis grade was better after undergoing arthroscopic correction. Modern hip arthroscopy indications and techniques represent a valid joint-preservation procedure conferring a relative risk reduction of 42% in the progression of osteoarthritis. Arthroscopy for mixed patterns of impingement and instability were the fastest to degenerate.

Medical Imaging Applications Developed Using Artificial Intelligence Demonstrate High Internal Validity Yet Are Limited in Scope and Lack External Validation.

PURPOSE: To (1) review definitions and concepts necessary to interpret applications of deep learning (DL; a domain of artificial intelligence that leverages neural networks to make predictions on media inputs such as images) and (2) identify knowledge and translational gaps in the literature to provide insight into specific areas for improvement as adoption of this technology continues. METHODS: A comprehensive search of the literature was performed in December 2023 for articles regarding the use of DL in sports medicine. For each study, information regarding the joint of focus, specific anatomic structure/pathology to which DL was applied, imaging modality utilized, source of images used for model training and testing, data set size, model performance, and whether the DL model was externally validated was recorded. A numerical scale was used to rate each DL model's clinical impact, with 1 corresponding to proof-of-concept studies with little to no direct clinical impact and 5 corresponding to practice-changing clinical impact and ready for clinical deployment. RESULTS: Fifty-five studies were identified, all of which were published within the past 5 years, while 82% were published within the past 3 years. Of the DL models identified, 84% were developed for classification tasks, 9% for automated measurements, and 7% for segmentation. A total of 62% of studies utilized magnetic resonance imaging as the imaging modality, 25% radiographs, and 7% ultrasound, while 1 study each used computed tomography, arthroscopic images, or arthroscopic video. Sixty-five percent of studies focused on the detection of tears (anterior cruciate ligament [ACL], rotator cuff [RC], and meniscus). The diagnostic performance of ACL tears, as determined by the area under the receiver operator curve (AUROC), ranged from 0.81 to 0.99 for ACL tears (excellent to near perfect), 0.83 to 0.94 for RC tears (excellent), and from 0.75 to 0.96 for meniscus tears (acceptable to excellent). In addition, 3 studies focused on detection of cartilage lesions had AUROC ranging from 0.90 to 0.92 (excellent performance). However, only 4 (7%) studies externally validated their models, suggesting that they may not be generalizable or may not perform well when applied to populations other than that used to develop the model. Finally, the mean clinical impact score was 2 (range, 1-3) on scale of 1 to 5, corresponding to limited clinical applicability. CONCLUSIONS: DL models in orthopaedic sports medicine show generally excellent performance (high internal validity) but require external validation to facilitate clinical deployment. In addition, current models have low clinical applicability and fail to advance the field due to a focus on routine tasks and a narrow conceptual framework. LEVEL OF EVIDENCE: Level IV, scoping review of Level I to IV studies.

Provision of ambrisentan from a health-system specialty pharmacy affiliated with a pulmonary hypertension Center of Comprehensive Care.

PURPOSE: This descriptive report describes the process used to obtain access to providing ambrisentan from a health-system specialty pharmacy (HSSP) affiliated with a pulmonary hypertension Center of Comprehensive Care, develop a pulmonary arterial hypertension (PAH) care team at the HSSP, and characterize medication adherence and access metrics. SUMMARY: PAH is a rare disease treated with several specialty medications requiring intensive monitoring. Historically, specialty medications used to treat PAH have been provided by only select specialty pharmacies due to restricted drug distribution channels. It is recommended that patients with PAH receive their care at centers with expertise in the diagnosis and management of this disorder, but the HSSPs at these expert centers are unable to provide specialty PAH medications. The current care model for PAH leads to patients receiving their medical and pharmaceutical care from separate entities. This descriptive report describes a multidisciplinary team's approach to gaining access to providing ambrisentan and developing a disease state care team within an established HSSP. After implementing this service, specialty pharmacy metrics were assessed, including proportion of days covered (PDC), time to first fill, patient contact rate, Risk Evaluation and Mitigation Strategy (REMS) program compliance, time to prior authorization (PA) approval, rate of optimal adherence (PDC of >80%), and PA renewal rate, to demonstrate a proof-of-concept HSSP model for PAH. In this model, the HSSP was able to demonstrate high-quality specialty pharmacy metrics with regard to medication adherence, medication access, and REMS program compliance. CONCLUSION: The development of a PAH care team to provide ambrisentan at an existing HSSP was associated with high adherence rates, efficient and reliable medication access, and REMS program compliance.

Fluid resuscitation and relation to respiratory support escalation in patients with and without pulmonary hypertension with sepsis.

STUDY OBJECTIVE: To compare guideline-based fluid resuscitation and need for respiratory support escalation in septic patients with pulmonary hypertension (PH) to those without PH. DESIGN: Single-center, retrospective cohort study. SETTING: Tertiary care academic medical center in Detroit, Michigan. PATIENTS: Adult patients with or without PH hospitalized and diagnosed with sepsis from November 1, 2013 through December 31, 2019. Patients with sepsis were assigned to one of two groups based on a previous PH diagnosis or no PH diagnosis. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was incidence of respiratory support escalation within 72 h from sepsis time zero. Respiratory support escalation included high-flow nasal cannula, bilevel positive airway pressure, or intubation. One-hundred and four patients were included with 52 patients in each study group. Patients with PH were more likely to require escalation of respiratory support compared to non-PH patients (32.7% vs. 11.5%; p = 0.009). Fewer patients with PH received 30 mL/kg of crystalloid within 6 h of time zero compared with non-PH patients (3.8% vs. 42.3%; p < 0.001). Vasopressor initiation was more common in patients with PH compared with the non-PH group (40.4% vs. 19.2%; p = 0.018). PH diagnosis was the only independent predictor of respiratory support escalation. CONCLUSIONS: During initial sepsis management when compared with patients without PH, patients with PH had increased instances of respiratory support escalation within 72 h of sepsis time zero despite lower fluid resuscitation volumes.

Long-term Outcomes After Arthroscopic Treatment of Femoroacetabular Impingement for Patients With Borderline Dysplasia.

BACKGROUND: Outcomes after isolated hip arthroscopic surgery for patients with dysplasia have been unfavorable. Results have included iatrogenic instability and conversion to total hip arthroplasty at a young age. However, patients with borderline dysplasia (BD) have shown more favorable results at short- and medium-term follow-up. PURPOSE: To assess long-term outcomes after hip arthroscopic surgery for femoroacetabular impingement in patients with BD (lateral center-edge angle [LCEA] = 18°-25°) compared with a control group of patients without dysplasia (LCEA = 26°-40°). STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: We identified a group of 33 patients (38 hips) with BD who were treated for FAI between March 2009 and July 2012. An age- and sex-matched control group of 83 patients (96 hips) was also identified. Patient-reported outcome scores were collected preoperatively and subsequently at a mean of 9.6 years postoperatively. RESULTS: The mean LCEA and Tönnis angle were 22.42°± 2.02° and 6.27°± 3.23° in the BD group, respectively, and 31.71°± 3.52° and 2.42°± 3.02° in the control group, respectively (P < .001). At a mean follow-up of 9.6 years (range, 8.2-11.6 years), there was a significant improvement in all patient-reported outcome scores in both groups (P < .001). There were no significant differences between preoperative and postoperative scores or rates of achieving the minimal clinically important difference between the BD and control groups. Bilateral surgery was noted to be a risk factor for any revision during the follow-up period (P < .001). There were 2 hips (5.3%) that underwent revision surgery in the BD group and 10 hips (10.4%) in the control group; of these, 1 patient in the BD group underwent total hip arthroplasty, and 1 patient who had undergone bilateral surgery in the control group underwent bilateral hip resurfacing. CONCLUSION: Durable outcomes (>9 years) with low revision rates can be expected after hip arthroscopic surgery with an approach that involves labral preservation where possible and careful attention to capsular closure in patients with BD. The observed outcomes were similar to those of a femoroacetabular impingement group with normal coverage. These results highlight the importance of classifying patients into impingement or instability categories and tailoring treatment appropriately with arthroscopic surgery or periacetabular osteotomy, respectively.

The Effects of Arthroscopic Labral Repair on Patient-Reported Outcomes in the Setting of Periacetabular Osteotomy.

BACKGROUND: It is currently unknown whether the addition of arthroscopic labral repair in the setting of periacetabular osteotomy (PAO) provides any clinical benefit. PURPOSE/HYPOTHESIS: The purpose of this study was to compare outcomes of patients who underwent arthroscopic labral repair concomitantly with PAO versus patients who underwent PAO alone. We hypothesized that there would be no difference in patient-reported outcome measures (PROMs) between the cohorts. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: Patients undergoing PAO from a single-center prospective hip preservation registry were eligible for this study if they completed pre- and postoperative PROMs (minimum, 1 year). PROMs were collected at 1 year, 2 years, and latest follow-up at 6.05 years for PAO group and 4.2 years for scope/PAO group. The study group consisted of 53 patients who underwent arthroscopic labral repair at the time of their PAO, and the comparison group consisted of 170 patients who underwent PAO alone. A subset of the PAO group who had radiologic evidence of a detached labral tear (n = 33) was also compared with the rest of the PAO-alone group. PROMs were compared at every time point for both groups as well as the subset of patients who underwent PAO alone despite a labral tear. RESULTS: The mean follow-up of all patients was 2 years (range, 1-6 years). Overall, 85.2% of the PAO group and 85.7% of the scope/PAO group met the minimal clinically important difference for either the modified Harris Hip Score (mHHS) or the International Hip Outcome Tool (iHOT-33) at the most recent follow-up. There was no difference in improvement between groups (mHHS, P = .670; iHOT-33, P = .944). Patients who had a radiologically diagnosed detached labral tear and underwent PAO alone had no difference in outcomes when compared with the rest of the PAO cohort (mHHS, P = .981; iHOT-33, P = .909). CONCLUSION: There was no significant benefit measured by PROMs at follow-up for concomitant arthroscopic labral repair in the setting of PAO.

A practical guide to the development and deployment of deep learning models for the orthopedic surgeon: part II.

Deep learning has the potential to be one of the most transformative technologies to impact orthopedic surgery. Substantial innovation in this area has occurred over the past 5 years, but clinically meaningful advancements remain limited by a disconnect between clinical and technical experts. That is, it is likely that few orthopedic surgeons possess both the clinical knowledge necessary to identify orthopedic problems, and the technical knowledge needed to implement deep learning-based solutions. To maximize the utilization of rapidly advancing technologies derived from deep learning models, orthopedic surgeons should understand the steps needed to design, organize, implement, and evaluate a deep learning project and its workflow. Equipping surgeons with this knowledge is the objective of this three-part editorial review. Part I described the processes involved in defining the problem, team building, data acquisition, curation, labeling, and establishing the ground truth. Building on that, this review (Part II) provides guidance on pre-processing and augmenting the data, making use of open-source libraries/toolkits, and selecting the required hardware to implement the pipeline. Special considerations regarding model training and evaluation unique to deep learning models relative to "shallow" machine learning models are also reviewed. Finally, guidance pertaining to the clinical deployment of deep learning models in the real world is provided. As in Part I, the focus is on applications of deep learning for computer vision and imaging.

Majority of competitive soccer players return to soccer following hip arthroscopy for femoroacetabular impingement: female and older aged players are less likely to return to soccer.

PURPOSE: To determine return to soccer rates and soccer performance in a large cohort of competitive soccer players after hip arthroscopic surgery for the treatment of femoroacetabular impingement (FAI) and to identify possible risk factors associated with not returning to soccer. METHODS: An institutional hip preservation registry was retrospectively reviewed for patients identified as competitive soccer players who underwent primary hip arthroscopy for FAI performed between 2010 and 2017. Patient demographics and injury characteristics as well as clinical and radiographic findings were recorded. All patients were contacted for return to soccer information using a soccer-specific return to play questionnaire. Multivariable logistic regression analysis was used to identify potential risk factors for not returning to soccer. RESULTS: Eighty-seven competitive soccer players (119 hips) were included. 32 players (37%) underwent simultaneous or staged bilateral hip arthroscopy. The mean age at surgery was 21.6 ± 7.0 years. Overall, 65 players (74.7%) returned to soccer, of which 43 players (49% of all included players) returned to pre-injury level of play or better. Most common reasons for not returning to soccer were pain or discomfort (50%) followed by fear of re-injury (31.8%). The mean time to return to soccer was 33.1 ± 26.3 weeks. Among 22 players who did not return to soccer, 14 (63.6%) reported satisfaction from surgery. Multivariable logistic regression analysis revealed female players (odds ratio [OR] = 0.27; confidence interval [CI] = 0.083 to 0.872; p = 0.029) and older aged players (OR = 0.895; 95% CI = 0.832 to 0.963; p = 0.003) were less likely to return to soccer. Bilateral surgery was not found to be a risk factor. CONCLUSION: Hip arthroscopic treatment for FAI in symptomatic competitive soccer players allowed three-quarters of them to return to soccer. Despite not returning to soccer, two-thirds of players who did not return to soccer were satisfied with their outcome. Female and older aged players were less likely to return to soccer. These data can better guide clinicians and soccer players with realistic expectations related to the arthroscopic management of symptomatic FAI. LEVEL OF EVIDENCE: III.

A practical guide to the development and deployment of deep learning models for the Orthopedic surgeon: part I.

Deep learning has a profound impact on daily life. As Orthopedics makes use of this rapid escalation in technology, Orthopedic surgeons will need to take leadership roles on deep learning projects. Moreover, surgeons must possess an understanding of what is necessary to design and implement deep learning-based project pipelines. This review provides a practical guide for the Orthopedic surgeon to understand the steps needed to design, develop, and deploy a deep learning pipeline for clinical applications. A detailed description of the processes involved in defining the problem, building the team, acquiring and curating the data, labeling the data, establishing the ground truth, pre-processing and augmenting the data, and selecting the required hardware is provided. In addition, an overview of unique considerations involved in the training and evaluation of deep learning models is provided. This review strives to provide surgeons with the groundwork needed to identify gaps in the clinical landscape that deep learning models may be able to fill and equips them with the knowledge needed to lead an interdisciplinary team through the process of creating novel deep-learning-based solutions to fill those gaps.

Hip Arthroscopy With Bone Marrow Aspirate Injection for Patients With Symptomatic Labral Tears and Early Degenerative Changes Shows Similar Improvement Compared With Patients Undergoing Hip Arthroscopy With Symptomatic Labral Tears Without Arthritis.

PURPOSE: To define the clinical effect of intra-articular injection of iliac crest-derived bone marrow aspirate concentrate (BMAC) at the time of hip arthroscopy in patients with symptomatic labral tears and early radiographic degenerative changes. METHODS: A retrospective review of a prospectively collected hip registry database was performed. Patients with symptomatic labral tears and Tönnis grade 1 or 2 degenerative changes who underwent labrum-preserving hip arthroscopy with BMAC injection were included and were matched with patients who underwent hip arthroscopy without BMAC injection. Patient-reported outcomes (PROs) collected preoperatively and up to 2 years postoperatively included the modified Harris Hip Score, Hip Outcome Score-Activities of Daily Living, Hip Outcome Score-Sport, and International Hip Outcome Tool 33 score. Clinical relevance was measured with the minimal clinically important difference, patient acceptable symptom state, and substantial clinical benefit for each outcome score. RESULTS: A total of 35 patients underwent labrum-preserving hip arthroscopy with BMAC injection and were matched with 35 control patients. There were no differences in demographic characteristics between the groups (P > .05). The BMAC group consisted of 22 patients (62.9%) with Tönnis grade 1 changes and 13 (37.1%) with Tönnis grade 2 changes, whereas all 35 control patients had Tönnis grade 0 hips. All PROs were significantly improved in both groups at 2 years, with no difference in improvement. The rate of failure requiring conversion to total hip arthroplasty was 14.3% (mean, 1.6 years postoperatively) in the BMAC group and 5.7% (mean, 7 years postoperatively) in the control group (P = .09). The difference in the frequency of patients achieving the minimal clinically important difference, patient acceptable symptom state, and substantial clinical benefit was not statistically significant between cohorts. CONCLUSIONS: In a challenging group of patients with symptomatic labral tears and early radiographic degenerative changes, hip arthroscopy with BMAC injection results in statistically and clinically significant improvement in PROs comparable to a group of patients with nonarthritic hips undergoing hip arthroscopy at short-term follow-up. LEVEL OF EVIDENCE: Level III, retrospective comparative therapeutic trial.

Natural language processing: using artificial intelligence to understand human language in orthopedics.

Natural language processing (NLP) describes the broad field of artificial intelligence by which computers are trained to understand and generate human language. Within healthcare research, NLP is commonly used for variable extraction and classification/cohort identification tasks. While these tools are becoming increasingly popular and available as both open-source and commercial products, there is a paucity of the literature within the orthopedic space describing the key tasks within these powerful pipelines. Curation and navigation of the electronic medical record are becoming increasingly onerous, and it is important for physicians and other healthcare professionals to understand potential methods of harnessing this large data resource. The purpose of this study is to provide an overview of the tasks required to develop an NLP pipeline for orthopedic research and present recent examples of successful implementations.

External Validation of a Machine Learning Algorithm for Predicting Clinically Meaningful Functional Improvement After Arthroscopic Hip Preservation Surgery.

BACKGROUND: Individualized risk prediction has become possible with machine learning (ML), which may have important implications in enhancing clinical decision making. We previously developed an ML algorithm to predict propensity for clinically meaningful outcome improvement after hip arthroscopy for femoroacetabular impingement syndrome. External validity of prognostic models is critical to determine generalizability, although it is rarely performed. PURPOSE: To assess the external validity of an ML algorithm for predicting clinically meaningful improvement after hip arthroscopy. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: An independent hip preservation registry at a tertiary academic medical center was queried for consecutive patients/athletes who underwent hip arthroscopy for femoroacetabular impingement syndrome between 2015 and 2017. By assuming a minimal clinically important difference (MCID) outcome/event proportion of 75% based on the original study, a minimum sample of 132 patients was required. In total, 154 patients were included. Age, body mass index, alpha angle on anteroposterior pelvic radiographs, Tönnis grade and angle, and preoperative Hip Outcome Score-Sports Subscale were used as model inputs to predict the MCID for the Hip Outcome Score-Sports Subscale 2 years postoperatively. Performance was assessed using identical metrics to the internal validation study and included discrimination, calibration, Brier score, and decision curve analysis. RESULTS: The concordance statistic in the validation cohort was 0.80 (95% CI, 0.71 to 0.87), suggesting good to excellent discrimination. The calibration slope was 1.16 (95% CI, 0.74 to 1.61) and the calibration intercept 0.13 (95% CI, -0.26 to 0.53). The Brier score was 0.15 (95% CI, 0.12 to 0.18). The null model Brier score was 0.20. Decision curve analysis revealed favorable net treatment benefit for patients with use of the algorithm as compared with interventional changes made for all and no patients. CONCLUSION: The performance of this algorithm in an independent patient population in the northeast region of the United States demonstrated superior discrimination and comparable calibration to that of the derivation cohort. The external validation of this algorithm suggests that it is a reliable method to predict propensity for clinically meaningful improvement after hip arthroscopy and is an essential step forward toward introducing initial use in clinical practice. Potential uses include integration into electronic medical records for automated prediction, enhanced shared decision making, and more informed allocation of resources to optimize patient outcomes.

Ultrasound-assisted catheter-directed thrombolysis versus anticoagulation alone for management of submassive pulmonary embolism.

BACKGROUND: Patients with submassive pulmonary embolism (PE) are vulnerable to sudden deterioration, recurrent PE, and progression to pulmonary hypertension and chronic right ventricular (RV) dysfunction. Previous studies have suggested a clinical benefit of using ultrasound-assisted catheter-directed thrombolysis (USCDT) to invasively manage patients with submassive PE. However, there is sparse data comparing the clinical outcomes of these patients when treated with USCDT versus anticoagulation (AC) alone. We sought to compare the outcomes of USCDT versus AC alone in the management of submassive PE. METHODS: 192 consecutive patients who underwent USCDT for submassive PE between January 2013 and February 2019 were identified. ICD9/ICD10 codes were used to detect 2554 patients diagnosed with PE who did not undergo thrombolysis. Propensity matching identified 192 patients with acute PE treated with AC alone. Clinical outcomes were compared between the two groups. Baseline demographics, laboratory values, and pulmonary embolism severity index scores were similar between the two cohorts. RESULTS: There was a significant reduction in mean systolic pulmonary artery pressure (sPAP) in the USCDT group compared to the AC group (∆11 vs ∆3.9 mmHg, p < 0.001). There was significant improvement in proportion of RV dysfunction in all patients, but the difference was larger in the USCDT group (∆43.3% vs ∆17.3%, p < 0.001). Patients who underwent USCDT had lower 30-day (4.3% vs 10.5%, p = 0.03), 90-day (5.5% vs 12.4%, p = 0.03), and 1-year mortality (6.2% vs 14.2%, p = 0.03). CONCLUSIONS: In patients with acute submassive PE, USCDT was associated with improved 30-day, 90-day, and 1 year mortality as compared to AC alone. USCDT also improved RV function and reduced sPAP to a greater degree than AC alone. Further studies are needed to verify these results in both short- and long-term outcomes.

Patient-Reported Outcomes Measurement Information System Mobility Computerized Adaptive Testing Maintains High Correlation and Low Test Burden Compared With Legacy Hip-Specific Instruments in Patients Undergoing Hip Arthroscopy for Femoroacetabular Impingement.

PURPOSE: To evaluate the reliability, construct validity, and responsiveness of the lower extremity-specific Patient-Reported Outcomes Measurement Information System (PROMIS) Mobility (MO) bank in patients who underwent hip arthroscopic surgery for femoroacetabular impingement. METHODS: Patients who underwent primary hip arthroscopic surgery at a large academic musculoskeletal specialty center between November 2019 and November 2020 completed the following baseline and 6-month measures: PROMIS MO, PROMIS Pain Interference (PI), PROMIS Physical Function (PF), modified Harris Hip Score, International Hip Outcome Tool 33, visual analog scale, and Single Assessment Numeric Evaluation. Construct validity was evaluated using Spearman correlation coefficients. The number of questions until completion was recorded as a marker of test burden. The percentage of patients scoring at the extreme high (ceiling) or low (floor) for each measure was recorded to measure inclusivity. Responsiveness was tested by comparing differences between baseline and 6-month measures, controlling for age and sex, using generalized estimating equations. Magnitudes of responsiveness were assessed through the effect size (Cohen d). RESULTS: In this study, 660 patients (50% female patients) aged 32 ± 14 years were evaluated. PROMIS MO showed a strong correlation with PROMIS PF (r = 0.84, P < .001), the International Hip Outcome Tool 33 (r = 0.73, P < .001), PROMIS PI (r = -0.76, P < .001), and the modified Harris Hip Score (r = 0.73, P < .001). Neither PROMIS MO, PROMIS PI, nor PROMIS PF met the conventional criteria for floor or ceiling effects (≥15%). The mean number of questions answered (± standard deviation) was 4.7 ± 2.1 for PROMIS MO, 4.1 ± 0.6 for PROMIS PI, and 4.1 ± 0.6 for PROMIS PF. From baseline to 6 months, the PROMIS and legacy measures exhibited significant responsiveness (P < .05), with similar effect sizes between the patient-reported outcome measures. CONCLUSIONS: This longitudinal study reveals that in patients undergoing hip arthroscopy, PROMIS MO computerized adaptive testing maintains high correlation with legacy hip-specific instruments, significant responsiveness to change, and low test burden compared with legacy measures, with no ceiling or floor effects at 6-month postoperative follow-up. LEVEL OF EVIDENCE: Level IV, retrospective case series.