首页|Miguel Hernandez University Reports Findings in Machine Learning (A calculator f or musculoskeletal injuries prediction in surgeons: a machine learning approach)
Miguel Hernandez University Reports Findings in Machine Learning (A calculator f or musculoskeletal injuries prediction in surgeons: a machine learning approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in Alicante, Spai n, by NewsRx journalists, research stated, "Surgical specialists experience sign ificant musculoskeletal strain as a consequence of their profession, a domain wi thin the healthcare system often recognized for the pronounced impact of such is sues. The aim of this study is to calculate the risk of presenting musculoskelet al injuries in surgeons after surgical practice." The news reporters obtained a quote from the research from Miguel Hernandez Univ ersity, "Crosssectional study carried out using an online form (12/2021-03/2022 ) aimed at members of the Spanish Association of Surgeons. Demographic variables on physical and professional activity were recorded, as well as musculoskeletal pain (MSP) associated with surgical activity. Univariate and multivariate analy sis were conducted to identify risk factors associated with the development of M SP based on personalized surgical activity. To achieve this, a risk algorithm wa s computed and an online machine learning calculator was created to predict them . Physiotherapeutic recommendations were generated to address and Alleviate each MSP. A total of 651 surgeons (112 trainees, 539 specialists). 90.6% reported MSP related to surgical practice, 60% needed any therapeu tic measure and 11.7% required a medical leave. In the long term, MSP was most common in the cervical and lumbar regions (52.4, 58.5% , respectively). StatisticAlly significant risk factors (OR CI 95%) were for trunk pain, long interventions without breaks (3.02, 1.65-5.54). Obesi ty, indicated by BMI, to lumbar pain (4.36, 1.84-12.1), while an inappropriate l aparoscopic screen location was associated with cervical and trunk pain (1.95, 1 .28-2.98 and 2.16, 1.37-3.44, respectively). A predictive model and an online ca lculator were developed to assess MSP risk. Furthermore, a need for enhanced erg onomics training was identified by 89.6% of surgeons. The prevalen ce of MSP among surgeons is a prevalent but often overlooked health concern."
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