Good validity in the Norwegian Knee Ligament Register: assessment of data quality for key variables in primary and revision cruciate ligament reconstructions from 2004 to 2013

Autor: Espen Midttun, Morten Torheim Andersen, Lars Engebretsen, Håvard Visnes, Anne Marie Fenstad, Jan-Erik Gjertsen, Andreas Persson

Publikováno v: BMC Musculoskeletal Disorders, Vol 23, Iss 1, Pp 1-7 (2022)

Abstract Background The Norwegian Knee Ligament Register was founded in 2004 to provide representative and reliable data on cruciate ligament surgery. The aim of this study was to evaluate the validity of key variables in the Norwegian Knee Ligament

Externí odkaz: https://doaj.org/article/16d4ca0073184c2a873cfbd3e5bd6c6f

Low annual hospital volume of anterior cruciate ligament reconstruction is not associated with higher revision rates

Autor: Gilbert Moatshe, Andreas Persson, Jon Olav Drogset, R. Kyle Martin, Lars Engebretsen, Håvard Visnes, Anne Marie Fenstad

Publikováno v: Knee Surgery, Sports Traumatology, Arthroscopy. 30:1575-1583

Surgery performed in low-volume centres has been associated with longer operating time, longer hospital stays, lower functional outcomes, and higher rates of revision surgery, complications and mortality. This has been reported consistently in the ar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::530fcb8ca96bd3e05a280fc8f51d115f
https://doi.org/10.1007/s00167-021-06655-z

Machine learning algorithm to predict anterior cruciate ligament revision demonstrates external validity

Autor: R. Kyle Martin, Solvejg Wastvedt, Ayoosh Pareek, Andreas Persson, Håvard Visnes, Anne Marie Fenstad, Gilbert Moatshe, Julian Wolfson, Martin Lind, Lars Engebretsen

Publikováno v: Martin, R K, Wastvedt, S, Pareek, A, Persson, A, Visnes, H, Fenstad, A M, Moatshe, G, Wolfson, J, Lind, M & Engebretsen, L 2022, ' Machine learning algorithm to predict anterior cruciate ligament revision demonstrates external validity ', Knee Surgery, Sports Traumatology, Arthroscopy, vol. 30, no. 2, pp. 368-375 . https://doi.org/10.1007/s00167-021-06828-w

Purpose External validation of machine learning predictive models is achieved through evaluation of model performance on different groups of patients than were used for algorithm development. This important step is uncommonly performed, inhibiting cl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6dac46e870c490dec0e8536843454ac1
https://pure.au.dk/ws/files/330068798/Machine_learning_algorithm_to_predict_anterior_cruciate_ligament_revision_demonstrates_external_validity.pdf

Predicting Anterior Cruciate Ligament Reconstruction Revision: A Machine Learning Analysis Utilizing the Norwegian Knee Ligament Register

Autor: Ayoosh Pareek, Gilbert Moatshe, Lars Engebretsen, Anne Marie Fenstad, Håvard Visnes, Julian Wolfson, Solvejg Wastvedt, Andreas Persson, R. Kyle Martin

Publikováno v: The Journal of bone and joint surgery. American volume. 104(2)

Background Several factors are associated with an increased risk of anterior cruciate ligament (ACL) reconstruction revision. However, the ability to accurately translate these factors into a quantifiable risk of revision at a patient-specific level

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::098b73e6933c7e7f79621679c70d933c
https://pubmed.ncbi.nlm.nih.gov/34662318

Chronic hyperglycemia, hypercholesterolemia, and metabolic syndrome are associated with risk of tendon injury

Autor: Christine Winther Bang, Soren Bering Klausen, Michael Kjaer, Volkert Siersma, Peter Bager, D. Skovgaard, Christian Couppé, Inger Haukenes, Karin Grävare Silbernagel, Jamie Gaida, Stig Peter Magnusson, Håvard Visnes

Publikováno v: Scandinavian journal of medicinescience in sportsREFERENCES. 31(9)

Tendon injury is a considerable problem affecting both physically active and sedentary people. The aim of this study was to examine the relationship between markers for metabolic disorders (hyperglycemia, hypercholesterolemia, and metabolic syndrome)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::551343cfa6674d70e2b391eaa2f77bb5
https://pubmed.ncbi.nlm.nih.gov/33963621