The World Health Organization has defined osteoporosis as a metabolic bone disease characterized by low bone mass and microarchitectural deterioration of bone tissue leading to enhanced bone fragility and a consequent increase in frac ture risk. 1) It has been estimated that more than 200 million people are suffering from osteoporosis. 2) In 2008, about 40% of women in Korea were reported to have osteoporosis. 3) On the other hand, sarcopenia is defined as the loss of muscle mass and muscle strength and functional impairment of muscles with aging, which compromises physical performance. It is closely associated with fractures and has been investigated as a new independent risk factor for fragility fractures, leading to a condition known as osteosarcopenia. 4,5) Osteoporosis and sarcopenia are predominantly common in older individuals, resulting in increased morbidity, mortality, and healthcare costs. 6,7) Distal radius fractures (DRFs) are the most common upper extremity fracture in middle-aged and elderly people with an overall higher incidence in women. 8) The incidence of DRFs is rising in recent decades. A study from the USA found a 17% increase in the incidence of this injury over a 40-year period, and in Sweden the incidence almost doubled for the older population over a 30-year time span. 9,10) The proportion of DRFs treated by surgery tended to increase over time, from 32.6% in 2011 to 38.3% in 2015 in Korea. 11) Osteoporosis is an independent risk factor for lowenergy DRFs in the elderly population and hence should not be missed in managing DRFs. Studies have shown that patients with DRFs have a high incidence of osteoporosis and an increased risk of subsequent fractures, subtle early physical performance changes, and a high prevalence of sarcopenia. 12,13) Since DRFs typically occur 15 years earlier than hip fractures, they reflect early changes of the bone and muscle frailty and provide physicians with an opportunity to prevent progression of frailty and secondary fractures. 13,14) Since our last review on the evaluation of bone

Objectives The aim of this study was to determine the incidence of periprosthetic joint infection (PJI) following primary total joint arthroplasty (TJA) and to investigate risk factors in a large cohort utilizing common data model (CDM). Patients and methods The entire cohort of primary and revision hip or knee TJA between January 2003 and December 2017 was retrospectively analyzed utilizing the CDM database. We detected patients who had revision TJA as a consequence of PJI. We determined the incidence of PJI and examined risk factors, including demographic features, comorbidities, prior corticosteroid usage, and preoperative laboratory values. Results There were 34 revision TJAs as a consequence of PJI (hip, 16; knee, 18) among 12,320 primary TJAs (hip, 4,758; knee 7,562), representing 0.27% incidence of PJI (hip, 0.33%; knee 0.23%). Of the patients, 15 were males and 19 were females. The mean age at the time of primary TJA was 59.8±17.5 (range, 31 to 85) years in hip PJI patients and 71.4±7.2 (range, 56 to 80) years in knee PJI patients. Hypertension and urinary tract infection were both associated with PJI following primary hip TJA. Age between 70 and 79 years, male sex, urinary tract infection, anemia, and prior corticosteroid usage were all associated with PJI following primary knee TJA. Conclusion This study indicates the viability of employing CDM to undertake research on PJI and serves as a reference for future CDM-based risk factor analysis. Preoperative screening and mitigating identified risk factors can aid in the reduction of PJI following TJA.

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Wrist arthrodesis has been used successfully for the management of severe wrist flexion deformity when soft tissue procedures would not provide adequate correction. However, in athetoid type cerebral palsy which has a component of involuntary movement, the outcome of wrist arthrodesis has not been discussed much. We present our experience in 2 athetoid type cerebral palsy patients who underwent wrist arthrodesis due to severe involuntary movement of the wrist. One patient had a nonunion and both patients had unexpected aggravation of involuntary movement in the adjacent joints. Secure fixation using a pre-contoured plate is necessary and preparation for iliac bone grafting should be considered as proximal row carpectomy is usually not necessary in these patients. In addition, although single-event, multi-level surgery is advocated for patients with cerebral palsy, potential additional procedures for the adjacent joints should be discussed preoperatively because unexpected aggravation of involuntary movement of adjacent joints can occur after stabilization of the wrist.

Background: Common data model (CDM) is a standardized data structure defined to efficiently use different sources in hospitals. A study using the CDM is scarce for orthopedic outcome researches due to the complexity of variables. We aimed to test the feasibility of applying CDM in the orthopedic field and analyzed risk factors for periprosthetic joint infection (PJI) after total joint arthroplasty (TJA) using CDM.Methods: We undertook a retrospective cohort study of all primary and revision hip and knee TJAs at our institution from January 2003 to October 2017. We identified potential risk factors for PJI after TJAs in the literatures, which included preoperative demographic/social factors, previous medical history, intraoperative factors, laboratory results and others. The data sourced from EMR was extracted, transformed, and loaded into CDM.Results: Variables such as demographic/social factors, medical history and laboratory results could be converted into CDM, but the other known risk factors could not. In total, 12,320 primary hip and knee TJAs and 120 revision arthroplasties were identified. Among them, 34 revisions were done because of PJI. Risk factors of PJI were hypertension and urinary tract infection after total hip arthroplasty, and age (70-79 years), male sex, anemia, steroid use, and urinary tract infection after total knee arthroplasty. Conclusions: This study demonstrates that orthopedic outcome researches using CDM is feasible although data converting to CDM was possible for limited factors. Further data transforming technologies need to be developed to analyze more factors relevant to orthopedic area, such as intraoperative factors and imaging findings.