Articles: linear-models.
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Comparative Study
Comparison between linear regression and four different machine learning methods in selecting risk factors for osteoporosis in a Chinese female aged cohort.
Population aging is emerging as an increasingly acute challenge for countries around the world. One particular manifestation of this phenomenon is the impact of osteoporosis on individuals and national health systems. Previous studies of risk factors for osteoporosis were conducted using traditional statistical methods, but more recent efforts have turned to machine learning approaches. Most such efforts, however, treat the target variable (bone mineral density [BMD] or fracture rate) as a categorical one, which provides no quantitative information. The present study uses five different machine learning methods to analyze the risk factors for T-score of BMD, seeking to (1) compare the prediction accuracy between different machine learning methods and traditional multiple linear regression (MLR) and (2) rank the importance of 25 different risk factors. ⋯ In a group of women older than 55 years, we demonstrated that machine learning methods provide superior performance in estimating T-Score, with age being the most important impact factor, followed by eGFR, BMI, UA, and education level.
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Detecting the correlation of conflict rate within provinces over time provides a better understanding for health policymakers in identifying potential causes. The purpose of this study was to assess the trend of conflict rate in 31 provinces of Iran using the growth mixture model (GMM). ⋯ Our study showed the increasing growth of conflict in the last years in most provinces of Iran. Necessary interventions are important to prevent the rising conflict rate due to the various effects of conflict on psychological, social, and health factors.
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To examine the association of prior investment on the effectiveness of organizations delivering large-scale external support to improve primary care. ⋯ Long-term investment that establishes regionwide organizations with infrastructure and experience to support primary care practices in QI is associated with more consistent delivery of facilitation support, and greater improvement in practice capacity and some clinical outcomes.
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Many patients delayed health care during COVID-19. We assessed the extent to which patients managing multiple chronic conditions (MCC) delayed care in the first months of the pandemic, reasons for delay, and impact of delay on patient-reported physical and behavioral health (BH) outcomes. ⋯ Delay of care was substantial. Patients who delayed care multiple times were in poorer health and thus in need of more care. Effective strategies for reengaging patients in deferred care should be identified and implemented on multiple levels.
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Arch Orthop Trauma Surg · Dec 2022
Learning curve of the Krackow suture technique for the repair of Achilles tendon rupture.
Knowledge on the learning curve for the repair of Achilles tendon rupture is limited. The aim of this study was to quantify the learning curve for the Krackow suture technique for the repair of Achilles tendon rupture and to identify the correlation between the cumulative volume of cases and clinical outcome measures. ⋯ The learning rate for the Krackow suture technique for the repair of Achilles tendon rupture was approximately 89%, indicating that the required operative time can decrease by up to 11% when the cumulative volume of cases doubles. Therefore, it is important to rapidly accumulate surgical experience during the early phase of training.