Burns, Travis C.

Update This article was updated on May 12, 2023, because of a previous error. In the Note on page 612, Byson P. Lesniak, MD, had not been listed as a member of the STaR Trial for Multiple Ligament Knee Injuries Network. The Note now reads “The STaR Trial for Multiple Ligament Knee Injuries Network includes Robert Arciero, MD; Brandee S. Black, MD; Catherine M. Coady, MD, FRSCS; Jonathan M. Cooper, DO; Katherine J. Coyner, MD; Cory M. Edgar, MD, PhD; Al M.J. Getgood, MD, FRCS(Tr&Orth); Joe M. Hart, PhD, ATC; Jonathan D. Hodax, MD, MS; Jonathan D. Hughes, MD; Cale A. Jacobs, PhD, ATC; Darren L. Johnson, MD; Ryan M. Khan, MSc, CCRP; Byson P. Lesniak, MD; Jeffrey A. Macalena, MD; Robert G. Marx, MD; Mark D. Miller, MD; Bradley Nelson, MD; Alicia Oostdyk, PhD; Charity G. Patterson, PhD, MSPH; Adam J. Popchak, PT, PhD; Anil S. Ranawat, MD; Michael J. Stuart, MD; Caroline E. Taber, AB; Ryan J. Warth, MD; Daniel B. Whelan, MD, MSc, FRCSC; and Isabel Wolfe, BS.” An erratum has been published: J Bone Joint Surg Am. 2023 Jun 21;105(12):e33. Background: Multiple ligament knee injuries (MLKIs) represent a spectrum of injury patterns that are often associated with concomitant musculoskeletal and neurovascular injuries, complex treatment, and postoperative complications. However, there has not been high-level evidence describing the presentation and treatment of MLKIs. The purpose of this multicenter retrospective study was to describe characteristics of MLKIs, their management, and related complications using a pathoanatomic MLKI classification system based on the Schenck Knee Dislocation classification system. Methods: This review identified and analyzed MLKIs that occurred between 2011 and 2015. Cases with an MLKI were included in this study if there was a complete tear of ≥2 ligaments and at least 1 ligament was repaired or reconstructed. Cases in which a ligament was deemed clinically incompetent due to a partial ligament tear and required surgical repair or reconstruction were considered equivalent to grade-III tears for inclusion and classification. Demographic information, the mechanism of injury, times from injury to presentation to an orthopaedic surgeon and to surgery, the ligament injury pattern, associated injuries, surgical procedures, and complications were captured. Data were analyzed descriptively. Results: A total of 773 individuals from 14 centers who underwent surgery for an MLKI were reviewed. The mean age of the individuals was 30.5 ± 12.7 years, and 74.2% were male. The most common mechanism involved sports (43.2%). The median time from injury to presentation to the orthopaedic surgeon was 11 days (interquartile range [IQR], 3 to 48 days), and the time to initial ligament surgery was 64 days (IQR, 23 to 190 days). While the most common injury patterns were an anterior cruciate ligament tear combined with either a medial-sided (MLK 1-AM, 20.7%) or lateral-sided (MLK 1-AL, 23.2%) injury, one-third (34.7%) were bicruciate injuries. Associated injuries most often involved menisci (55.6%), nerves (18.5%) and tendons (15.6%). The method of surgical intervention (repair versus reconstruction), external fixator use, and staging of procedures varied by MLKI classification. Loss of motion (11.4%) was the most common postoperative complication. Conclusions: A better understanding of the clinical characteristics and management of the various MLKI patterns can be used to support clinical decision-making and individualized treatment of these complex injuries, and may ultimately lead to enhanced outcomes and reduced associated risks. Level of Evidence: Therapeutic Level IV . See Instructions for Authors for a complete description of levels of evidence.

Background: Patient-reported outcomes (PROs) measure progression and quality of care. While legacy PROs such as the International Knee Documentation Committee (IKDC) survey are well-validated, a lengthy PRO creates a time burden on patients, decreasing adherence. In recent years, PROs such as the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function and Pain Interference surveys were developed as computer adaptive tests, reducing time to completion. Previous studies have examined correlation between legacy PROs and PROMIS; however, no studies have developed effective prediction models utilizing PROMIS to create an IKDC index. While the IKDC is the standard knee PRO, computer adaptive PROs offer numerous practical advantages. Purpose: To develop a nonlinear predictive model utilizing PROMIS Physical Function and Pain Interference to estimate IKDC survey scores and examine algorithm sensitivity and validity. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: The MOTION (Military Orthopaedics Tracking Injuries and Outcomes Network) database is a prospectively collected repository of PROs and intraoperative variables. Patients undergoing knee surgery completed the IKDC and PROMIS surveys at varying time points. Nonlinear multivariable predictive models using Gaussian and beta distributions were created to establish an IKDC index score, which was then validated using leave-one-out techniques and minimal clinically important difference analysis. Results: A total of 1011 patients completed the IKDC and PROMIS Physical Function and Pain Interference, providing 1618 complete observations. The algorithms for the Gaussian and beta distribution were validated to predict the IKDC (Pearson = 0.84-0.86; R 2 = 0.71-0.74; root mean square error = 9.3-10.0). Conclusion: The publicly available predictive models can approximate the IKDC score. The results can be used to compare PROMIS Physical Function and Pain Interference against historical IKDC scores by creating an IKDC index score. Serial use of the IKDC index allows for a lower minimal clinically important difference than the conventional IKDC. PROMIS can be substituted to reduce patient burden, increase completion rates, and produce orthopaedic-specific survey analogs.

Abstract Introduction Musculoskeletal injuries are an endemic amongst U.S. Military Service Members and significantly strain the Department of Defense’s Military Health System. The Military Health System aims to provide Service Members, military retirees, and their families the right care at the right time. The Military Orthopedics Tracking Injuries and Outcomes Network (MOTION) captures the data that can optimize musculoskeletal care within the Military Health System. This report provides MOTION structural framework and highlights how it can be used to optimize musculoskeletal care. Materials and Methods MOTION established an internet-based data capture system, the MOTION Musculoskeletal Data Portal. All adult Military Health System patients who undergo orthopedic surgery are eligible for entry into the database. All data are collected as routine standard of care, with patients and orthopedic surgeons inputting validated global and condition-specific patient reported outcomes and operative case data, respectively. Patients have the option to consent to allow their standard of care data to be utilized within an institutional review board approved observational research study. MOTION data can be merged with other existing data systems (e.g., electronic medical record) to develop a comprehensive dataset of relevant information. In pursuit of enhancing musculoskeletal injury patient outcomes MOTION aims to: (1) identify factors which predict favorable outcomes; (2) develop models which inform the surgeon and military commanders if patients are behind, on, or ahead of schedule for their targeted return-to-duty/activity; and (3) develop predictive models to better inform patients and surgeons of the likelihood of a positive outcome for various treatment options to enhance patient counseling and expectation management. Results This is a protocol article describing the intent and methodology for MOTION; thus, to date, there are no results to report. Conclusions MOTION was established to capture the data that are necessary to improve military medical readiness and optimize medical resource utilization through the systematic evaluation of short- and long-term musculoskeletal injury patient outcomes. The systematic enhancement of musculoskeletal injury care through data analyses aligns with the National Defense Authorization Act (2017) and Defense Health Agency’s Quadruple Aim, which emphasizes optimizing healthcare delivery and Service Member medical readiness. This transformative approach to musculoskeletal care can be applied across disciplines within the Military Health System.