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BACKGROUND: After the medial open wedge high tibial osteotomy, the deformity of lower limb force line moving inward and knee varus can be corrected, which will inevitably lead to compensatory changes in the position of adjacent joints to adapt to the new force line. Up to now, there are relatively few studies to systematically and comprehensively measure the compensatory changes of hip joint, patellofemoral joint, ankle joint and other adjacent joints from the perspective of imaging. OBJECTIVE: To analyze the compensatory changes of hip joint, patellofemoral joint, and ankle joint caused by the changes of lower limb force line from the perspective of imaging after medial open wedge high tibial osteotomy. METHODS: The imaging data of 49 patients who underwent medial open wedge high tibial osteotomy in Affiliated Hospital of Qingdao University from June 2016 to December 2019 were retrospectively analyzed. To evaluate the efficacy of lower limb line correction after medial open wedge high tibial osteotomy, hip-knee-ankle angle, lateral distal femoral angle, medial proximal tibial angle, joint line convergence angle, weight bearing line ratio, and tibial posterior slope were measured in all patients with preoperatively and immediately postoperatively and at the end of the follow-up. To evaluate the compensatory changes of hip joint, patellofemoral joint, and ankle joint after medial open wedge high tibial osteotomy, the hip abduction angle, tibial plafond inclination angle, talar inclination angle, Caton-Deschamps index, lateral patellar shift, lateral patellar tilt, medial space of patellofemoral joint, and lateral space of patellofemoral joint were measured in all patients before treatment and after the last follow-up. RESULTS AND CONCLUSION: (1) After medial open wedge high tibial osteotomy, the lower extremity line correction of the patients was satisfactory, and there was statistical significance in the comparison of hip-knee-ankle angle, medial proximal tibial angle, joint line convergence angle, and weight bearing line ratio before and immediately after the operation, and in the last follow-up (P < 0.05). (2) There was no increase in tibial posterior slope after medial open wedge high tibial osteotomy, and there was no significant difference between tibial posterior slope before and after treatment (P > 0.05). (3) The hip adduction was aggravated after treatment, and the difference between preoperative and last follow-up of hip abduction angle was statistically significant (P < 0.05). An ankle varus was corrected after treatment, and the difference between tibial plafond inclination angle and talar inclination angle before surgery and the last follow-up was statistically significant (P < 0.05). (4) The position of patella decreased after treatment, and the difference of Caton-Deschamps index between preoperative and postoperative data was statistically significant (P < 0.05), but there was no anteroposterior and lateral displacement, or patella tilt (P > 0.05). [ABSTRACT FROM AUTHOR]

Agent-based modeling (ABM) has enriched the theory and methods of research in water resources management. Better understanding of the state-of-the-art of ABM and its potential in the field of water resources management can promote institutional development and reform in China􀆳s water resources management system. In this paper, while ABM of water resources management (WR-ABM) is defined, its key components—agent decision rules and agent interactions—are identified and their modeling approaches are summarized. Various WR-ABMs applied in basinscale optimal water allocation, urban household water use and agricultural water management published during the period of 2009—2018 are carefully reviewed. Future research on the use of WR-ABMs that should address the challenges and weakness in the water resources management are discussed and several research directions are recommended herein: ① further expanding the use of complex adaptive system theory in the field of water resources management; ② coupling ABM and water resources system models that include uncertainties; ③ exploring the use of machine learning algorithms in the decision-making modeling; ④ improving the methods used in the model parameter calibration, result verification and validation; ⑤ using standard documentation protocol, such as the ODD protocol, for the description of models; and ⑥ achieving comprehensive and optimal balance between completeness and simplification in model design. [ABSTRACT FROM AUTHOR]