Arguello, Alexandra M.

Background: Synovial sarcoma is rare and may present as a small, slow-growing mass. These tumors are often mistaken as benign and are therefore prone to unplanned and/or non-oncologic excision. We sought to identify the rate of unplanned excision of synovial sarcoma and risk factors for recurrence and survival among this cohort. Methods: The medical records of 246 patients evaluated at a single institution for synovial sarcoma between 1997 and 2022 were retrospectively reviewed. Of these, 87 (35%) underwent unplanned, non-oncologic excision. The mean age of the cohort was 49 years. Primary tumors were located in the extremity (n = 63), abdomen (n = 6), thorax (n = 7), head/neck (n = 8), and paraspinal region (n = 3). The median maximum pre-treatment dimension of the primary tumor was 4.8 cm (IQR 7–2.4). Seventy-seven (86%) patients underwent re-excision of the tumor bed, 39 (45%) received chemotherapy, and 63 (72%) received radiation therapy. Results: Among patients who underwent unplanned excision, local recurrence-free survival (LRFS) was 98% at 1 year and 82% at 5 years. Metastasis-free survival (MFS) was 91% at 1 year and 72% at 5 years. Disease-specific survival (DSS) was 98% at 1 year and 72% at 5 years. When adjusting for tumor size, tumors which underwent unplanned excision did not have worse recurrence or survival compared to those which had planned excision (p > 0.10). Size > 5 cm, monophasic subtype, and axial location were associated with increased risk of disease recurrence. Forty-six patients had residual tumor following re-excision, which was associated with worse MFS (HR 8.17, 95% CI [1.89, 35.2], p < 0.01) and DSS (HR 7.66, 95% CI [1.76, 33.4], p < 0.01). Patients who received radiotherapy had improved MFS (HR 6.4, 95% CI [1.42, 29.0], p = 0.02) and DSS (HR 5.86, 95% CI [1.27, 26.9], p = 0.02). Conclusions: One-third of patients presenting with synovial sarcoma were diagnosed after unplanned, non-oncologic excision. Patients with large, axial tumors had worse survival. Approximately half of patients who underwent unplanned excision had no residual tumor after pre-operative radiation. The use of radiation was associated with decreased rates of recurrence and improved disease-specific survival. Our results suggest that margin-negative re-resection and radiotherapy should be considered when feasible following unplanned excision of synovial sarcoma.

Abstract Background Endoprostheses (EPC) are often utilized for reconstruction of the proximal humerus with either hemiarthroplasty (HA) or reverse arthroplasty (RA) constructs. RA constructs have improved outcomes in patients with primary lesions, but no studies have compared techniques in metastatic disease. The aim of this study is to compare functional outcomes and complications between HA and RA constructs in patients undergoing endoprosthetic reconstruction for proximal humerus metastases. Methods We retrospectively reviewed our institutional arthroplasty database to identify 66 (56% male; 38 HA and 28 RA) patients with a proximal humerus reconstruction for a non‐primary malignancy. The majority (88%) presented with pathologic fracture, and the most common diagnosis was renal cell carcinoma (48%). Resultss Patients with RA reconstructions had better postoperative forward elevation (74° vs. 32°, p < 0.01) and higher functional outcome scores. HA patients had more complications (odds ratio 13, p < 0.01), with instability being the most common complication. Conclusions Patients with nonprimary malignancies of the proximal humerus had improved functional outcomes and fewer complications after undergoing reconstruction with a reverse EPC compared to a HA EPC. Preference for reverse EPC should be given in patients with good prognosis and ability to complete postoperative rehabilitation.

AbstractPurposeIdentifying predictive factors for all‐cause reoperation after anterior cruciate ligament reconstruction could inform clinical decision making and improve risk mitigation. The primary purposes of this study are to (1) determine the incidence of all‐cause reoperation after anterior cruciate ligament reconstruction, (2) identify predictors of reoperation after anterior cruciate ligament reconstruction using machine learning methodology, and (3) compare the predictive capacity of the machine learning methods to that of traditional logistic regression.MethodsA longitudinal geographical database was utilized to identify patients with a diagnosis of new anterior cruciate ligament injury. Eight machine learning models were appraised on their ability to predict all‐cause reoperation after anterior cruciate ligament reconstruction. Model performance was evaluated via area under the receiver operating characteristics curve. To explore modeling interpretability and radiomic feature influence on the predictions, we utilized a game‐theory‐based method through SHapley Additive exPlanations.ResultsA total of 1400 patients underwent anterior cruciate ligament reconstruction with a mean postoperative follow‐up of 9 years. Two‐hundred and eighteen (16%) patients experienced a reoperation after anterior cruciate ligament reconstruction, of which 6% of these were revision ACL reconstruction. SHapley Additive exPlanations plots identified the following risk factors as predictive for all‐cause reoperation: diagnosis of systemic inflammatory disease, distal tear location, concomitant medial collateral ligament repair, higher visual analog scale pain score prior to surgery, hamstring autograft, tibial fixation via radial expansion device, younger age at initial injury, and concomitant meniscal repair. Pertinent negatives, when compared to previous studies, included sex and timing of surgery. XGBoost was the best‐performing model (area under the receiver operating characteristics curve of 0.77) and outperformed logistic regression in this regard.ConclusionsAll‐cause reoperation after anterior cruciate ligament reconstruction occurred at a rate of 16%. Machine learning models outperformed traditional statistics and identified diagnosis of systemic inflammatory disease, distal tear location, concomitant medial collateral ligament repair, higher visual analog scale pain score prior to surgery, hamstring autograft, tibial fixation via radial expansion device, younger age at initial injury, and concomitant meniscal repair as predictive risk factors for reoperation. Pertinent negatives, when compared to previous studies, included sex and timing of surgery. These models will allow surgeons to tabulate individualized risk for future reoperation for patients undergoing anterior cruciate ligament reconstruction.Level of evidenceIII.

(1) Background: Resection of soft-tissue sarcomas (STS) of the upper extremity can result in substantial functional impairment with limited options for functional reconstruction. Free functional latissimus flaps have been utilized to restore function of the thigh; however, there is limited data on the use of latissimus flaps for functional reconstruction in the upper extremity. As such, we sought to evaluate our institutional experience with these flaps. (2) Methods: We reviewed ten (seven male; three female; and a mean age of 63 years) patients undergoing soft-tissue sarcoma resection involving the triceps (n = 4), biceps (n = 4), and deltoid (n = 2) reconstructed with a pedicled functional latissimus flap. All surviving patients had at least 1 year of follow-up, with a mean follow-up of 5 years. (3) Results: The mean elbow range of motion and shoulder elevation were 105° and 150°. The mean Musculoskeletal Tumor Society score was 88%, and the muscle strength was four. Four patients had a recipient site wound complication. There were no flap losses. One patient sustained a radiation-associated humerus fracture 5 years postoperatively, treated nonoperatively. (4) Conclusions: Although early complications are high, pedicled functional latissimus flaps allow for wound coverage, potential space obliteration, and restoration of function in the upper extremity following resection of large soft tissue sarcomas.

Objectives: The primary objective of this study was to analyze the relationship of percentage of surgical overlap with patient outcomes to determine if a detrimental level of overlap exists. Background: Overlapping surgery is defined as 1 attending physician supervising 2 or more operative cases simultaneously, without the critical portions of the cases occurring concurrently. To date, no study has examined the relationship of percent overlap, or the percentage of 1 case that is spent overlapping with another, to outcomes, efficiency, safety, and complications. Methods: This study is a retrospective cohort study conducted at a large tertiary referral center. The primary outcomes of interest included operative duration, in-hospital mortality, 30-day readmission, and patient safety indicators (PSIs). The Cochran-Armitage test for trend was used to evaluate the outcomes of interest. P values of ≤0.05 were considered statistically significant. Results: A total of 87,426 cases were included in this study. There were 62,332 cases without overlap (Group 0), 10,514 cases with 1% to 25% overlap (Group 1), 5303 cases with 26% to 50% overlap (Group 2), 4296 cases with 51% to 75% overlap (Group 3), and 4981 cases with >75% overlap (Group 4). In-hospital mortality decreased as overlap increased (P trend<0.0001). Operative time increased with increasing overlap (P trend<0.0001) while readmission rates showed no statistical significance between groups (P trend=0.5078). Rates of PSIs were lower for Groups 1, 2, and 3 (1.69%, 2.01%, and 2.08%) when compared to Group 0 (2.24%). Group 4 had the highest rate of PSIs at 2.35% (P=0.0086). Conclusion: Overlapping surgery was shown to have reduced in-hospital mortality and similar PSI and readmission rates when compared to nonoverlapping cases. Operative time was shown to increase in overlapping surgeries when compared to nonoverlapping surgeries. The results from this study indicate that the percentage of surgical overlap does not detrimentally affect most patient outcomes, especially with overlap of <75%.

AbstractPurposeThis study sought to develop and internally validate a machine learning model to identify risk factors and quantify overall risk of secondary meniscus injury in a longitudinal cohort after primary ACL reconstruction (ACLR).MethodsPatients with new ACL injury between 1990 and 2016 with minimum 2‐year follow‐up were identified. Records were extensively reviewed to extract demographic, treatment, and diagnosis of new meniscus injury following ACLR. Four candidate machine learning algorithms were evaluated to predict secondary meniscus tears. Performance was assessed through discrimination using area under the receiver operating characteristics curve (AUROC), calibration, and decision curve analysis; interpretability was enhanced utilizing global variable importance plots and partial dependence curves.ResultsA total of 1187 patients underwent ACLR; 139 (11.7%) experienced a secondary meniscus tear at a mean time of 65 months post‐op. The best performing model for predicting secondary meniscus tear was the random forest (AUROC = 0.790, 95% CI: 0.785–0.795; calibration intercept = 0.006, 95% CI: 0.005–0.007, calibration slope = 0.961 95% CI: 0.956–0.965, Brier’s score = 0.10 95% CI: 0.09–0.12), and all four machine learning algorithms outperformed traditional logistic regression. The following risk factors were identified: shorter time to return to sport (RTS), lower VAS at injury, increased time from injury to surgery, older age at injury, and proximal ACL tear.ConclusionMachine learning models outperformed traditional prediction models and identified multiple risk factors for secondary meniscus tears after ACLR. Following careful external validation, these models can be deployed to provide real‐time quantifiable risk for counseling and timely intervention to help guide patient expectations and possibly improve clinical outcomes.Level of evidenceIII.