Background: Optimizing operating room (OR) scheduling accuracy is important for improving OR efficiency and maximizing value of total knee arthroplasty (TKA). However, data on factors that may impact TKA OR scheduling accuracy are limited.
Materials And Methods: A retrospective review of 7655 knee arthroplasties (6999 primary TKAs and 656 revision TKAs) performed between January 2020 and May 2023 was conducted. Patient baseline characteristics, surgeon experience (years in practice), as well as actual vs scheduled OR times were collected. Actual OR times that were at least 15% shorter or longer than scheduled OR times were considered to be clinically important. Logistic regression analyses were employed to assess the influence of specific patient and surgeon factors on OR scheduling inaccuracies.
Results: Using adjusted odds ratio, patients with primary TKA who had a lower body mass index (<.001) were independently associated with overestimation of scheduled surgical time. Conversely, younger age (<.001), afternoon procedure start time (<.001), surgeons with less than 10 years of experience (=.037), and higher patient body mass index (<.001) were associated with underestimation of scheduled surgical time. For revision TKA, female sex (=.021) and morning procedure start time (=.038) were associated with overestimation of scheduled surgical time, while surgeons with less than 10 years of experience (=.014) and patients who underwent spinal/epidural/block anesthesia (=.038) were associated with underestimation of scheduled surgical time.
Conclusion: This study highlights patient, surgeon, and intraoperative variables that impact the accuracy of scheduling for TKA procedures. Health systems should take these variables into consideration when creating OR schedules to fully optimize resources and available space. [. 2024;47(5):313-319.].
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http://dx.doi.org/10.3928/01477447-20240702-01 | DOI Listing |
Sci Rep
December 2024
School of Management Science and Engineering, Shandong Jianzhu University, Jinan, 250101, China.
This study seeks to improve urban supply chain management and collaborative governance in the context of public health emergencies (PHEs) by integrating fuzzy theory with the Back Propagation Neural Network (BPNN) algorithm. By combining these two approaches, an early warning mechanism for supply chain risks during PHEs is developed. The study employs Matlab software to simulate supply chain risks, incorporating fuzzy inference techniques with the adaptive data modeling capabilities of neural networks for both training and testing.
View Article and Find Full Text PDFSci Rep
December 2024
Key Laboratory of Exercise and Physical Fitness, Ministry of Education, Beijing Sport University, Beijing, China.
Chronic sedentary behavior can have a negative impact on the executive function (EF) of young people. While physical activity (PA) has been shown to improve this phenomenon, the effects of different types of PA on EF vary. In this study, we compared the effects of moderate-intensity continuous training (MICT) (60-70% HRmax, 30 min), body weight training (BWT) (2 sets tabata, 20 min), and mind-body exercise (MBE) (2 sets Yang style shadowboxing, 20 min) on EF in 59 sedentary youth (n = 59, age = 20.
View Article and Find Full Text PDFPLoS One
December 2024
CHU Clermont Ferrand, Plateforme d'Exploration de la Mobilité, Pôle MOBEX, Université Clermont Auvergne, Clermont-Ferrand, France.
Background: In osteoarthritis quadriceps strength is an important outcome to assess exercise capacity and recovery after arthroplasty. However, its measurement is limited due to lack of time and the need for trained personnel and equipment whose accuracy is verified.
Objectives: To find out the determinants of a reduced quadriceps strength and to establish a score to screen for it.
AJOG Glob Rep
February 2025
Mother and Child Welfare Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran (all authors).
Background: Episiotomy has specific indications that, if properly followed, can effectively prevent women from experiencing severe lacerations that may result in significant complications like anal incontinence. However, the risk factors related to episiotomy has been the center of much debate in the medical field in the past few years.
Objective: The present study used a machine learning model to predict the factors that put women at the risk of having episiotomy using intrapartum data.
Eur Urol Open Sci
January 2025
Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands.
Background And Objective: Urothelial bladder cancer (UCB) care requires frequent follow-up cystoscopy and surgery. Confocal laser endomicroscopy (CLE), a probe-based optical technique for real-time microscopic evaluation, has shown promising accuracy for grading of UCB. We investigated the diagnostic accuracy of CLE-based assessment of the surgical radicality of the bladder resection bed (RB).
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