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322 citation(s) found for "Edwin, Bjørn".

The Use of Computed Tomography Densitometry for the Assessment of Emphysema in Clinical Trials: A Position Paper from the Fleischner Society
Estépar, Raúl San Jośe , Barr, R. Graham, Fain, Sean B. , Hoffman, Eric A. , Humphries, Stephen M. , Obuchowski, Nancy A. , Ryerson, Christopher J. , Bankier, Alexander A. , Crapo, James D. , Han, Meilan, Kellermeyer, Liz , Newell, John D. , Miller, Bruce E. , Nordenmark, Lars H. , Rémy‐Jardin, Martine , Silverman, Edwin K. , Washko, George R. , Lynch, David A. , San Jose Estepar, Raul , Hoffman, Eric A , Humphries, Stephen M , Tal-Singer, Ruth , Ash, Samuel Y , Barr, R. Graham, Greniér, Philippe , Kirby, Miranda , Seo, Joon Beom , Tal‐Singer, Ruth , Han, MeiLan King , Goldin, Jonathan , McCollough, Cynthia H. , Prokop, Mathias , Ohno, Yoshiharu , Strange, Charlie

American Journal of Respiratory and Critical Care Medicine | March 24, 2025 | Volume: 211 | Issue: 5 | Pages: 709-728

10.1164/rccm.202410-2012so | PMID 40126404 Get It

Abstract Emphysema’s significant morbidity and mortality underscore the need for reliable outcome metrics in clinical trials. However, commonly accepted chronic obstructive pulmonary disease outcome measures do not adequately capture emphysema severity or progression. Computed tomography (CT) metrics have been validated as accurate indicators of pathological emphysema and predictors of chronic obstructive pulmonary disease progression, exacerbations, and mortality. This position paper reviews the evidence supporting CT densitometry as a biomarker for emphysema, establishes implementation standards, and highlights areas for future research. A systematic literature review addressed three key questions: whether CT densitometry can be used as a diagnostic biomarker of emphysema, whether CT densitometry can be used as a prognostic biomarker, and whether longitudinal change in densitometry can be used as a disease progression monitoring biomarker. Emphysema metrics, such as the percentage of low attenuation areas below −950 Hounsfield units, are validated, highly reproducible diagnostic and prognostic biomarkers. Volume-adjusted lung density is recommended for disease monitoring. Both metrics demonstrate a scan–rescan intraclass correlation coefficient of 0.99 with proper technique. The paper also discusses relevant CT physics, techniques, and sources of variation, including technical factors, physiological changes, and software analysis. Key recommendations for clinical trials include using standardized CT techniques, proper subject selection, and longitudinal evaluation with volume-adjusted lung density.
Assessing Mucosal Recovery During the First 15 Months of Adopting a Gluten-Free Diet in Children With Celiac Disease
Chang, Denis , Wong, Madison , Davidowitz, Cleo R., Absah, Imad , Badalyan, Vahe , Chaaban, Mohammad Karam, Fahey, Lisa M. , Isaac, Daniela Migliarese , Khanna, Maya, Lansing, Marihan, Liu, Edwin , Raber, Catherine , Singh, Arunjot , Stahl, Marisa G. , Walsh, Catharine M. , Silvester, Jocelyn A. , Leonard, Maureen M. , Chaaban, Mohammad K, Silvester, Jocelyn A , Walsh, Catharine M , Khanna, Maya

American Journal of Gastroenterology | March 14, 2025 | Volume: 120 | Issue: 7 | Pages: 1657-1661

10.14309/ajg.0000000000003400 | PMID 40084739 Get It

INTRODUCTION: Determine contemporary rates of early mucosal recovery in children with celiac disease (CeD). METHODS: Multicenter retrospective cohort study in Canada and the United States. Children diagnosed with CeD between 2016 and 2021 who underwent a follow-up biopsy within 15 months of diagnosis were included. RESULTS: Overall, 96 of 130 children (74%) had mucosal recovery, including 48% children (12/25) who were assessed within 3 months. Musculoskeletal symptoms at diagnosis were the only clinical characteristic associated with persistent enteropathy. DISCUSSION: While mucosal recovery can occur within months, more than a quarter of children with CeD had persistent enteropathy within 15 months of treatment.
Receipt of poly(ADP) ribose polymerase inhibitors (PARPi) in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) harboring BRCA1/2 alterations.
Ostrowski, Micah , Lin, Edwin , Srivastava, Ayana , Ji, Richard, Li, Haoran , Gupta, Sumati , Maughan, Benjamin L. , Roy, Soumyajit , Swami, Umang , Agarwal, Neeraj , Jo, Yeonjung , Chehade, Chadi Hage , Özay, Zeynep İrem , Gebrael, Georges , Sayegh, Nicolas , Thomas, Vinay Mathew , Riaz, Irbaz Bin , Agarwal, Neeraj

Journal of Clinical Oncology | February 18, 2025 | Volume: 43 | Issue: 5_suppl | Pages: 108-108

10.1200/jco.2025.43.5_suppl.108 Get It

108 Background: PARPi are approved for the treatment of pts with mCRPC either as single agents or as a combination with an androgen receptor pathway inhibitor (ARPI) [PMID: 37442702]. In a US Food and Drug Administration (FDA) pooled analysis, the benefit from PARPi appeared greatest for pts harboring BRCA1/2 alterations [PMID: 38484203]. However, real-world uptake of PARPi in pts with mCRPC with BRCA1/2 alterations is unknown. Herein, our objective was to assess the usage of PARPi in real-world pts with mCRPC harboring BRCA1/2 alterations. Methods: A de-identified nationwide Flatiron Health electronic health record (EHR)-derived database was used to extract pt-level data. Eligibility criteria: pts with mCRPC harboring alterations in BRCA1 or BRCA2 or both and alive after 8/15/2020 (i.e., 3 months following the approval of the first PARPi, rucaparib, in mCRPC) with available treatment information. The data cutoff date was 5/31/2024. Pts were categorized into two cohorts based on the receipt of any PARPi or not. Baseline characteristics at the time of mCRPC diagnosis, including age, race-ethnicity, and insurance plan, were collected in both cohorts. Results: Of the overall cohort of 24,105 pts with metastatic prostate cancer, 443 pts had mCRPC with BRCA1/2 alterations and were eligible and included in this analysis. 227 (51.2%) received a PARPi, while 216 did not (48.8%). Among the 227 pts who received a PARPi, 166 received it as a single agent (73.1%), 40 received it in combination with an ARPI (17.6%), and 21 received it in combination with other agents (9.3%). The median age was 72 in both cohorts (IQR 65 – 79 in patients receiving a PARPi and 66 – 78 in patients who did not). Other baseline characteristics in both groups are shown (Table). Conclusions: Despite PARPi demonstrating survival improvement in pts with mCRPC with BRCA1/2 alterations, a significant proportion of pts do not receive them. Our findings highlight the need to improve education among clinicians of level 1 evidence and improve access to life-prolonging therapies in pts with mCRPC. Baseline characteristics of pts with mCRPC who received vs. did not receive a PARPi. Characteristic Subgroup Pts who received a PARPiN = 227 Pts who did not receive a PARPiN = 216 Race-ethnicity, n (%) Asian 9 (4) 1 (0.5) Black 22 (9.7) 30 (13.9) Hispanic-Latino 10 (4.4) 10 (4.6) White 149 (65.6) 124 (57.4) Other and unknown 37 (16.3) 51 (23.6) Insurance, n (%) Commercial health plan 192 (84.5) 182 (84.3) Medicare-other government programs 31 (13.7) 18 (8.3) Medicaid 1 (0.4) 3 (1.4) Others and unknown 3 (1.3) 13 (6)
First next-generation sequencing (NGS) testing at the end of life in patients with metastatic prostate cancer.
Ostrowski, Micah , Lin, Edwin , Nordblad, Blake , Maughan, Benjamin L. , McKay, Rana R. , Swami, Umang , Özay, Zeynep İrem , Jo, Yeonjung , Chehade, Chadi Hage , Sayegh, Nicolas , Gebrael, Georges , Fortuna, Gliceida Galarza , Li, Haoran, Thomas, Vinay Mathew , Graf, Ryon P. , Riaz, Irbaz Bin , Guha, Avirup , Roy, Soumyajit, Antonarakis, Emmanuel S. , Agarwal, Neeraj

Journal of Clinical Oncology | February 18, 2025 | Volume: 43 | Issue: 5_suppl | Pages: 90-90

10.1200/jco.2025.43.5_suppl.90 Get It

90 Background: Poly(ADP) ribose polymerase inhibitors and pembrolizumab are approved for patients with metastatic prostate cancer (mPC) with susceptible genomic alterations based on NGS testing. We recently reported that the rate of NGS testing in mPC remains low at 29.3% in the United States (1). Herein, we investigated the rates of NGS testing at the end of life in a real-world patient population. Methods: This study utilized the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database. Eligibility: diagnosis of mPC, with information on receipt of NGS testing (blood/tissue) and recorded date of death. The time between each patient’s first NGS testing result date and date of death was measured and categorized into 3 groups: NGS test results delivered more than 3 months (mo) before death, within 3 mo of death, and delivered after death. Frequencies and percentages of these 3 categories were reported, also by the year of death. Results: Out of 24,105 patients with mPC in the database, 3,397 had both a recorded date of death and underwent NGS testing and were eligible and included. The median age was 74 (IQR 67–80), 70% were White non-Hispanic, and 83% were treated in a community-based practice. In these patients, 2,901 (85.4%) NGS results were reported more than 3 mo before death, 457 (13.5%) within 3 mo of death, and 39 (1.1%) after death. From 2015 to 2024, the percentage of patients receiving their result more than 3 mo before death increased from 27% to 91%, while those receiving it within 3 mo before death decreased from 55% to 8.5%, and the percentage of NGS results reported after death declined from 18% to 0.6%. Baseline characteristics (including race-ethnicity, insurance plan, practice type [academic vs. community]) in these categories will be presented at the meeting. Conclusions: Despite the availability of life-prolonging targeted therapies based on NGS testing results for patients with mPC, in ∼14% of patients, the first NGS testing results were reported within 3 mo before death or after death. The lack of timely NGS testing limits patients' access to life-prolonging personalized treatments in earlier settings, resulting in missed opportunities for improved outcomes. 1. Hage Chehade, Swami, JAMA Network Open, 2024.
Characterization of Factors Associated With Death in Deceased Patients With Mitochondrial Disorders
Ivaniuk, Alina , Anselm, Irina , Bowen, Aaron B. , Cohen, Bruce H. , Eminoğlu, Fatma Tuba , Estrella, Jane , Gallagher, Renata C. , Gannon, Jennifer , Gorman, Gráinne S. , Greene, Carol L. , Haas, Richard , Kapoor, Seema , Karaa, Amel , Koenig, Mary Kay , Kornblum, Cornelia , Lichter‐Konecki, Uta , Lopriore, Piervito , McFarland, Robert , Moe, Aye , Ng, Yi Shiau , Saneto, Russell P. , Scaglia, Fernando , Tarnopolsky, Mark A. , Walker, Melissa , Group, as the Hong Kong Mitochondrial Diseases Interest, Fung, Cheuk Wing , Wong, Tsz-sum, Belaramani, Kiran , Chan, Chun-kong , Chan, Wing-ki, Chan, Wai-lun Larry, Cheung, H. M. E., Cheung, Ka-yin, Chang, Richard Shek‐kwan , Cheung, Sing-ngai, Cheung, Tsz-Fung, Cheung, Yuk-fai, Chong, Shuk-ching Josephine, Chow, Chi-kwan Jasmine , Fan, Florence , Fok, Wai-ming Joshua , Fung, Tsui-hang Sharon , Hui, Kwok-fai, Hui, Ting-hin, Ko, Chun Hung, Kwan, Min-chung, Kwok, Anne Mei Kwun , Kwok, Sung-shing Jeffrey, Lai, Moon-sing, Lam, Yau-on, Lam, Ching‐Wan , Lau, Ming-chung, Law, Hiu-Fung, Lee, Wing‐Cheong , Leung, Kin-hang, Leung, Kit-yan, Li, Siu-hung, Ling, Tsz-ki, Liu, Kam Tim , Lui, Colin H. T., Luk, Ching-on, Luk, Ho‐Ming , Ma, Che-Kwan, Ma, Karen , Ma, Kam-hung , Mew, Yuen-ni, Mo, Alex, Hg, Sui-Fun, Poon, Grace Wing-kit , Sheng, Bun , Szeto, Cheuk-ling Charing, Tai, Shuk‐Mui, Tang, Jing-Liang, Tse, Choi-ting Alan , Tsung, Li-yan Lilian, Wong, Ho-ming June, Wong, Wing-yin Winnie, Wong, Kwok-kui, Wong, Suet-na Sheila , Wong, Chun-nei Virginia, Wong, Wai-shan Sammy, Wong, Chi-kin Felix, Wu, Shun-Ping, Wu, Hiu-fung Jerome , Yau, Man-Mut, Yau, Eric Kin Cheong , Yeung, Wai Lan , Yeung, Hon‐Ming Jonas , Yip, Kin-keung Edwin, Young, Pui-hong Terence, Yuan, Gao , Yuen, Yuet‐Ping , Yuen, Chi-lap, Anselm, Irina A , Bowen, Aaron , Ganetzky, Rebecca D , Gannon, Jennifer , Gorman, Grainne S , Greene, Carol , Gropman, Andrea L , Haas, Richard H , Hirano, Michio , Kapoor, Seema , Karaa, Amel , Koenig, Mary Kay , Kornblum, Cornelia , Kose, Engin , Larson, Austin A , Lichter-Konecki, Uta , Lopriore, Piervito , Mancuso, Michelangelo , McFarland, Robert , Moe, Aye Myat , Ng, Yi Shiau , Saneto, Russell P , Scaglia, Fernando , Sue, Carolyn M , Tarnopolsky, Mark , Walker, Melissa A , Parikh, Sumit , Cheuk-Wing, Fung , Wong, Tsz-Sum , Belaramani, Kiran , Chan, Chun-Kong , Chan, Wing-Ki , Chan, Wai-Lun Larry , Cheung, Hon-Wing , Cheung, Ka-Yin , Chang, Shek-Kwan , Cheung, Sing-Ngai , Cheung, Tsz-Fung , Cheung, Yuk-Fai , Chow, Chi-Kwan Jasmine , Chung, Hon-Yin B , Fan, Sin-Ying Florence , Fok, Wai-Ming Joshua , Fung, Tsui-Hang Sharon , Hui, Kwok-Fai , Hui, Ting-Hin , Hui, Joannie , Ko, Chun Hung , Kwan, Min-Chung , Kwok, Mei-Kwan Anne , Kwok, Sung-Shing Jeffrey , Lai, Moon-Sing , Lam, Yau-On , Lam, Ching-Wan , Lau, Ming-Chung , Law, Chun-Yiu Eric , Law, Hiu-Fung , Lee, Wing-Cheong , Leung, Kin-Hang , Leung, Kit-Yan , Li, Siu-Hung , Liu, Kam-Tim Timothy , Lo, Fai-Man , Lui, Colin , Luk, Ho-Ming , Ma, Che-Kwan , Ma, Karen , Ma, Kam-Hung , Mo, Alex , Hg, Sui-Fun , Poon, Wing-Kit Grace , Sheng, Bun , Tse, Choi-Ting Alan , Wong, Ho-Ming June , Wong, Wing-Yin Winnie , Wong, Kwok-Kui , Wong, Suet-Na Sheila , Wong, Chun-Nei Virginia , Wong, Wai-Shan Sammy , Wu, Hiu-Fung Jerome , Yau, Kin-Cheong Eric , Yeung, Wai-Lan , Yeung, Hon-Ming Jonas , Yip, Kin-Keung Edwin , Young, Pui-Hong Terence , Yuan, Gao , Yuen, Yuet-Ping Liz , Ivaniuk, Alina , Cohen, Bruce H , Ganetzky, Rebecca , Larson, Austin , Morava, Éva , Sue, Carolyn M. , Parikh, Sumit , Group, as the Hong Kong Mitochondrial Diseases Interest, Fong, Ka-Wing, Lee, Han‐Chih Hencher , Tang, Jing-Liang, Wu, Hui-Jun

Neurology | January 30, 2025 | Volume: 104 | Issue: 4 | Pages: No page available

10.1212/wnl.0000000000209779 | PMID 39883904 Get It

Polygenic Risk Score Added to Conventional Case Finding to Identify Undiagnosed Chronic Obstructive Pulmonary Disease
Zhang, Jingzhou , Hobbs, Brian D. , Silverman, Edwin K., Sparrow, David , Ortega, Victor E. , Xu, Hanfei , Zhang, Chengyue , Cho, Michael H., Hobbs, Brian D , Silverman, Edwin K. , Dupuis, Josée , Walkey, Allan J. , O’Connor, George T. , Cho, Michael H. , Moll, Matthew , Zhang, Chengyue

JAMA | January 22, 2025 | Volume: 333 | Issue: 9 | Pages: 784

10.1001/jama.2024.24212 | PMID 39841442 Get It

ImportanceChronic obstructive pulmonary disease (COPD) is often undiagnosed. Although genetic risk plays a significant role in COPD susceptibility, its utility in guiding spirometry testing and identifying undiagnosed cases is unclear.ObjectiveTo determine whether a COPD polygenic risk score (PRS) enhances the identification of undiagnosed COPD beyond a case-finding questionnaire (eg, the Lung Function Questionnaire) using conventional risk factors and respiratory symptoms.Design, Setting, and ParticipantsThis cross-sectional analysis of participants 35 years or older who reported no history of physician-diagnosed COPD was conducted using data from 2 observational studies: the community-based Framingham Heart Study (FHS) and the COPD-enriched Genetic Epidemiology of COPD (COPDGene) study.ExposuresModified Lung Function Questionnaire (mLFQ) scores and COPD PRS.Main Outcomes and MeasuresThe primary outcome was spirometry-defined moderate to severe COPD (forced expiratory volume in the first second of expiration/forced vital capacity [FEV1/FVC] <0.7 and FEV1 [percent predicted] <80%). The performance of logistic models was assessed using the PRS, mLFQ score, and PRS plus mLFQ score for predicting spirometry-defined COPD.ResultsAmong 3385 FHS participants (median age, 52.0 years; 45.9% male) and 4095 COPDGene participants (median age, 56.8 years; 55.5% male) who reported no history of COPD, 160 (4.7%) FHS and 775 (18.9%) COPDGene participants had spirometry-defined COPD. Adding the PRS to the mLFQ score significantly improved the area under the curve from 0.78 to 0.84 (P < .001) in FHS, 0.69 to 0.72 (P = .04) in COPDGene non-Hispanic African American, and 0.75 to 0.78 (P < .001) in COPDGene non-Hispanic White participants. At a risk threshold for spirometry referral of 10%, the addition of the PRS to the mLFQ score correctly reclassified 13.8% (95% CI, 6.6%-21.0%) of COPD cases in FHS, but not in COPDGene.Conclusions and RelevanceA COPD PRS enhances the identification of undiagnosed COPD beyond a conventional case-finding approach in the general population. Further research is needed to assess its impact on COPD diagnosis and outcomes.
Imaging and Nonsurgical Management of Renal Masses
Jorgenson, Laura C. , Navin, Patrick J. , Thompson, Scott M. , Takahashi, Edwin A. , Schmit, Grant D. , Potretzke, Theodora A. , Venkatesh, Sudhakar K. , Potretzke, Aaron M. , Stish, Bradley J. , Atwell, Thomas D. , Adamo, Daniel, Thompson, Scott , Takahashi, Edwin A , Schmit, Grant, Potretzke, Theodora , Venkatesh, Sudhakar K , Stish, Bradley, Atwell, Thomas D , Navin, Patrick , Adamo, Daniel A.

RadioGraphics | December 19, 2024 | Volume: 45 | Issue: 1 | Pages: No page available

10.1148/rg.240093 | PMID 39700039 Get It

Radiologists play a key role in the management of renal masses, and it is important to understand the nonsurgical treatment options for solid renal masses, typical imaging findings after treatment, common complications, and methods to avoid pitfalls.
Gastrointestinal Safety Assessment of GLP-1 Receptor Agonists in the US: A Real-World Adverse Events Analysis from the FAERS Database
Osei, Samuel Prince , Akomaning, Edwin , Florut, Teodora Francesca, Lacy, Brian E. , Bhagavathula, Akshaya Srikanth , Aldhaleei, Wafa A , Bhagavathula, Akshaya Srikanth , Sodhi, Mohit , Aldhaleei, Wafa Ali

Diagnostics | December 16, 2024 | Volume: 14 | Issue: 24 | Pages: 2829

10.3390/diagnostics14242829 | PMID 39767190 Get It

Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are commonly used to treat obesity and diabetes but are linked to a variety of gastrointestinal (GI) adverse events (AEs). Real-world data on GLP-1 RA-related GI AEs and outcomes are limited. This study assessed GI AEs and adverse outcomes using the US FDA Adverse Event Reporting System (FAERS). Methods: This retrospective pharmacovigilance study used the US FDA FAERS database (2007–2023). We searched GLP-1 RA medications, AEs, and adverse outcomes. Demographic, treatment indication, and AE data were collected. Descriptive analysis involved frequencies and percentages, while reporting odds ratio (ROR), proportional reporting ratio, Bayesian confidence propagation neural network, and multivariate logistic regression were used to analyze GLP-1 RA-related GI AEs and outcomes. Results: From 2007 to 2023, a total of 187,757 AEs were reported with GLP-1 RAs, and 16,568 were GLP-1 RA-associated GI AEs in the US. Semaglutide was linked to higher odds of nausea (IC025: 0.151, βCoeff: 0.314), vomiting (IC025: 0.334, βCoeff: 0.495), and delayed gastric emptying (IC025: 0.342, βCoeff: 0.453). Exenatide was associated with pancreatitis (IC025: 0.601, βCoeff: 0.851) and death (ROR: 4.50, IC025: 1.101). Overall, semaglutide had a broader range of notable adverse effects; by comparison, dulaglutide and liraglutide use was associated with fewer significant GI AEs. Conclusions: Analysis of the FAERS data reveals that GLP-1 RAs, particularly semaglutide and exenatide, are significantly associated with specific GI AEs, such as nausea, vomiting, delayed gastric emptying, and pancreatitis. Clinicians should be aware of these potential risks to ensure optimal monitoring and patient safety. This study demonstrated the utility of pharmacovigilance data in identifying safety signals, which can inform future pharmacoepidemiological investigations to confirm causal relationships. Clinicians should be aware of these potential risks to ensure optimal monitoring and patient safety.
A Novel Machine Learning Model to Predict Revision ACL Reconstruction Failure in the MARS Cohort
Group, MARS, Vasavada, Vrinda, Devana, Sai K. , Hame, Sharon L. , Jazrawi, Laith M. , Huston, Laura J. , Haas, Amanda K. , Cooper, Daniel E. , Amendola, Annunziato, Annunziata, Christopher C., Arciero, Robert A. , Bach, Bernard R. , Baker, Champ L., Bartolozzi, Arthur R. , Baumgarten, Keith M. , Berg, Jeffrey H., Bernas, Geoffrey A., Brockmeier, Stephen F. , Bush‐Joseph, Charles A., Butler, J. Brad, Carey, James L. , Carpenter, James E. , Cole, Brian J. , Cooper, Jonathan M., Creighton, R. Alexander , Dunn, Warren R. , Flanigan, David C. , Frederick, Robert W., Ganley, Theodore J. , Gatt, Charles J. , Gecha, Steven R., Hannafin, Jo A., Harris, Norman Lindsay, Hechtman, Keith S., Hershman, Elliott B., Hoellrich, Rudolf G., Johnson, David C. , Kaeding, Christopher C., Kamath, Ganesh V. , Klootwyk, Thomas E., Levy, Bruce A. , Benjamin, C. , Maiers, G. Peter, Marx, Robert G. , Matava, Matthew J. , Mathien, Gregory M., McCormack, Robert G. , Miller, Bruce S., Nissen, Carl W. , O’Neill, Daniel F., Parker, Richard D., Purnell, Mark L., Ramappa, Arun J. , Rauh, Michael A. , Rettig, Arthur C., Sekiya, Jon K., Shea, Kevin G. , Slauterbeck, James R., Smith, Matthew V. , Svoboda, Steven J. , Taft, Timothy N., Tenuta, Joachim J., Tingstad, Edwin M., Vidal, Armando F. , Viskontas, Darius G., White, Richard A., Wolcott, Michelle L., Wright, Rick W. , York, James J. , Group, MARS, Vasavada, Kinjal , Moran, Jay T. , Lee, Chang Hee , Sherman, Orrin H. , Allen, Christina R. , DeBerardino, Thomas M. , Spindler, Kurt P , Stuart, Michael J., Brophy, Robert H. , Cox, Charles L. , David, Tal S. , Giffin, J. Robert , Johnson, David C., Johnson, Timothy S. , Jones, Morgan H. , Kaeding, Christopher C. , McAllister, David R. , McCarty, Eric C. , Miller, Bruce S., Owens, Brett D. , Spang, Jeffrey T. , Vidal, Armando F. , Williams, James S. , Wolf, Brian R.

Orthopaedic Journal of Sports Medicine | November 14, 2024 | Volume: 12 | Issue: 11 | Pages: No page available

10.1177/23259671241291920 | PMID 39555321 Get It

Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights. Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure. Study Design: Cohort study; Level of evidence, 3. Methods: The authors prospectively recruited patients undergoing rACLR from the MARS cohort and obtained preoperative radiographs, surgeon-reported intraoperative findings, and 2- and 6-year follow-up data on patient-reported outcomes, additional surgeries, and graft failure. Machine learning models including logistic regression (LR), XGBoost, gradient boosting (GB), random forest (RF), and a validated ensemble algorithm (AutoPrognosis) were built to predict graft failure by 6 years postoperatively. Validated performance metrics and feature importance measures were used to evaluate model performance. Results: The cohort included 960 patients who completed 6-year follow-up, with 5.7% (n = 55) experiencing graft failure. AutoPrognosis demonstrated the highest discriminative power (model area under the receiver operating characteristic curve: AutoPrognosis, 0.703; RF, 0.618; GB, 0.660; XGBoost, 0.680; LR, 0.592), with well-calibrated scores (model Brier score: AutoPrognosis, 0.053; RF, 0.054; GB, 0.057; XGBoost, 0.058; LR, 0.111). The most important features for AutoPrognosis model performance were prior compromised femoral and tibial tunnels (placement and size) and allograft graft type used in current rACLR. Conclusion: The present study demonstrated the ability of the novel AutoPrognosis machine learning model to best predict the risk of graft failure in patients undergoing rACLR at 6 years postoperatively with moderate predictive ability. Femoral and tibial tunnel size and position in prior ACLR and allograft use in current rACLR were all risk factors for rACLR failure in the context of the AutoPrognosis model. This study describes a unique model that can be externally validated with larger data sets and contribute toward the creation of a robust rACLR bedside risk calculator in future studies. Registration: NCT00625885 (ClinicalTrials.gov identifier).
Surgical Predictors of Clinical Outcome 6 Years After Revision ACL Reconstruction
Group, The MARS, Wright, Rick W. , Huston, Laura J. , Haas, Amanda K. , Cooper, Daniel E. , Dunn, Warren R. , Lantz, Brett A., Amendola, Annunziato , Annunziata, Christopher C., Arciero, Robert A. , Bach, Bernard R. , Baker, Champ L., Bartolozzi, Arthur R. , Baumgarten, Keith M. , Berg, Jeffrey H., Bernas, Geoffrey A., Brockmeier, Stephen F. , Bush‐Joseph, Charles A., Butler, J. Brad, Carey, James L. , Carpenter, James E. , Cole, Brian J. , Cooper, Jonathan M., Creighton, R. Alexander , Flanigan, David C. , Frederick, Robert W., Ganley, Theodore J. , Gatt, Charles J. , Gecha, Steven R., Hame, Sharon L. , Hannafin, Jo A., Harner, Christopher D. , Harris, Norman Lindsay, Hechtman, Keith S., Hershman, Elliott B., Hoellrich, Rudolf G., Johnson, David C. , Kaeding, Christopher C., Kamath, Ganesh V. , Klootwyk, Thomas E., Levy, Bruce A. , Benjamin, C. , Maiers, G. Peter, Marx, Robert G. , Matava, Matthew J. , Mathien, Gregory M., McCormack, Robert G. , Miller, Bruce S., Nissen, Carl W. , O’Neill, Daniel F., Parker, Richard D., Purnell, Mark L., Ramappa, Arun J. , Rauh, Michael A. , Rettig, Arthur C., Sekiya, Jon K., Shea, Kevin G. , Slauterbeck, James R., Smith, Matthew V. , Svoboda, Steven J. , Taft, Timothy N., Tenuta, Joachim J., Tingstad, Edwin M., Vidal, Armando F. , Viskontas, Darius G., White, Richard A., Wolcott, Michelle L., York, James J. , Group, The MARS, Pennings, Jacquelyn S. , Allen, Christina R. , DeBerardino, Thomas M. , Spindler, Kurt P , Stuart, Michael J. , Brophy, Robert H. , Cox, Charles L. , David, Tal S. , Giffin, J. Robert , Johnson, David C., Johnson, Timothy S. , Jones, Morgan H. , Kaeding, Christopher C. , McAllister, David R. , McCarty, Eric C. , Miller, Bruce S., Owens, Brett D. , Sherman, Orrin H. , Spang, Jeffrey T. , Vidal, Armando F. , Williams, James S. , Wolf, Brian R.

The American Journal of Sports Medicine | November 6, 2024 | Volume: 52 | Issue: 13 | Pages: 3286-3294

10.1177/03635465241288227 | PMID 39503722 Get It

Background: Revision anterior cruciate ligament (ACL) reconstruction has been documented to have inferior outcomes compared with primary ACL reconstruction. The reasons why remain unknown. Purpose: To determine whether surgical factors performed at the time of revision ACL reconstruction can influence a patient’s outcome at 6-year follow-up. Study Design: Cohort study; Level of evidence, 2. Methods: Patients who underwent revision ACL reconstruction were identified and prospectively enrolled between 2006 and 2011. Data collected included baseline patient characteristics, surgical technique and pathology, and a series of validated patient-reported outcome instruments: Knee injury and Osteoarthritis Outcome Score (KOOS), International Knee Documentation Committee (IKDC) subjective form, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Marx activity rating score. Patients were followed up for 6 years and asked to complete the identical set of outcome instruments. Regression analysis was used to control for baseline patient characteristics and surgical variables to assess the surgical risk factors for clinical outcomes 6 years after surgery. Results: A total of 1234 patients were enrolled (716 men, 58%; median age, 26 years), and 6-year follow-up was obtained on 79% of patients (980/1234). Using an interference screw for femoral fixation compared with a cross-pin resulted in significantly better outcomes in 6-year IKDC scores (odds ratio [OR], 2.2; 95% CI, 1.2-3.9; P = .008) and KOOS sports/recreation and quality of life subscale scores (OR range, 2.2-2.7; 95% CI, 1.2-4.8; P < .01). Use of an interference screw compared with a cross-pin resulted in a 2.6 times less likely chance of having a subsequent surgery within 6 years. Use of an interference screw for tibial fixation compared with any combination of tibial fixation techniques resulted in significantly improved scores for IKDC (OR, 1.96; 95% CI, 1.3-2.9; P = .001); KOOS pain, activities of daily living, and sports/recreation subscales (OR range, 1.5-1.6; 95% CI, 1.0-2.4; P < .05); and WOMAC pain and activities of daily living subscales (OR range, 1.5-1.8; 95% CI, 1.0-2.7; P < .05). Use of a transtibial surgical approach compared with an anteromedial portal approach resulted in significantly improved KOOS pain and quality of life subscale scores at 6 years (OR, 1.5; 95% CI, 1.02-2.2; P≤ .04). Conclusion: There are surgical variables at the time of ACL revision that can modify clinical outcomes at 6 years. Opting for a transtibial surgical approach and choosing an interference screw for femoral and tibial fixation improved patients’ odds of having a significantly better 6-year clinical outcome in this cohort.