Background Several risk assessments have been developed to evaluate fall risk in older adults, but it has not been conclusively established which of these tools is most effective for assessing fall risk in this vulnerable population. Recently, the U.S. Centers for Disease Control and Prevention (CDC) developed the self-rated Fall Risk Questionnaire (self-rated FRQ), a 12-item questionnaire designed to screen older adults who are at risk of falling and has been widely used in many centers. This study aimed to determine the validity and reliability of the self-rated FRQ in older adults with osteoporosis. Methods This prospective study was conducted at the Department of Orthopedic Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand from December 2019 to March 2020. Sixty-eight men or postmenopausal women aged > 65 years who were diagnosed with osteoporosis either by bone mineral density T-score or by occurrence of fragility fracture were evaluated with the self-rated FRQ, the Thai falls risk assessment test (Thai-FRAT), the timed get-up-and-go test (TUG test), the Berg Balance Scale (BBS), and the 5 times sit-to-stand test (5TSTS test). Validity of the self-rated FRQ was assessed by evaluating the correlations (r) between the self-rated FRQ score and the scores from the other four assessments. Reliability of the self-rated FRQ was evaluated by measuring test-retest reliability and internal consistency. Results The self-rated FRQ was moderately strongly correlated with the BBS, TUG test, and 5TSTS test (r = 0.535 to 0.690; p < 0.001), and fairly correlated with the Thai-FRAT (r = 0.487; p < 0.001). Test-retest reliability of the self-rated FRQ was high, with a Kappa of 1. Internal consistency of the self-rated FRQ was excellent (Cronbach’s alpha: 0.936). Conclusions The self-rated FRQ was found to be a valid and reliable tool for evaluating fall risk in older adults with osteoporosis. Since assessment of fall risk requires a multifaceted measurement tool, the self-rated FRQ is an appropriate tool that can be integrated into the fall risk assessment algorithm in older adults with osteoporosis.
Background Fragility hip fracture increases morbidity and mortality in older adult patients, especially within the first year. Identification of patients at high risk of death facilitates modification of associated perioperative factors that can reduce mortality. Various machine learning algorithms have been developed and are widely used in healthcare research, particularly for mortality prediction. This study aimed to develop and internally validate 7 machine learning models to predict 1-year mortality after fragility hip fracture. Methods This retrospective study included patients with fragility hip fractures from a single center (Siriraj Hospital, Bangkok, Thailand) from July 2016 to October 2018. A total of 492 patients were enrolled. They were randomly categorized into a training group (344 cases, 70%) or a testing group (148 cases, 30%). Various machine learning techniques were used: the Gradient Boosting Classifier (GB), Random Forests Classifier (RF), Artificial Neural Network Classifier (ANN), Logistic Regression Classifier (LR), Naive Bayes Classifier (NB), Support Vector Machine Classifier (SVM), and K-Nearest Neighbors Classifier (KNN). All models were internally validated by evaluating their performance and the area under a receiver operating characteristic curve (AUC). Results For the testing dataset, the accuracies were GB model = 0.93, RF model = 0.95, ANN model = 0.94, LR model = 0.91, NB model = 0.89, SVM model = 0.90, and KNN model = 0.90. All models achieved high AUCs that ranged between 0.81 and 0.99. The RF model also provided a negative predictive value of 0.96, a positive predictive value of 0.93, a specificity of 0.99, and a sensitivity of 0.68. Conclusions Our machine learning approach facilitated the successful development of an accurate model to predict 1-year mortality after fragility hip fracture. Several machine learning algorithms (eg, Gradient Boosting and Random Forest) had the potential to provide high predictive performance based on the clinical parameters of each patient. The web application is available at www.hipprediction.com. External validation in a larger group of patients or in different hospital settings is warranted to evaluate the clinical utility of this tool. Trial registration Thai Clinical Trials Registry (22 February 2021; reg. no. TCTR20210222003).
Background Osteitis fibrosa cystica is the classic manifestation of primary hyperparathyroidism (PHPT), occurs after prolonged exposure of bone to high serum parathyroid hormone (PTH) level. It has become increasingly rare due to early detection of PHPT. Case presentation A 37-year-old woman was referred to our institution for fixation of multiple fractures of upper and lower extremities that had been reoccurring in the past 5 years. Her medical history showed right-shoulder, left-elbow, and right-femur fractures after a fall 5 years previously. One month ago, she sustained fractures of the right distal humerus, left tibia, and left femur without history of trauma. Upon arrival to our hospital, a thorough review of her plain radiographs demonstrated brown tumors at multiple sites, along with a salt-and-pepper appearance of the skull and a rugger-jersey spine, compatible with osteitis fibrosa cystica. Patient was diagnosed with PHPT, confirmed by high-corrected serum calcium (13.6 [8.6–10.0] mg/dl), low serum phosphate (2.2 [2.5–4.5] mg/dL), high serum alkaline phosphatase (1482 [35–105] U/L), and significantly elevated parathyroid hormone (PTH 3850 [15–65] pg/mL). A histologically confirmed, 2.5-cm parathyroid adenoma was removed by parathyroidectomy. Ten days later, closed reduction and internal fixation of the left proximal femoral shaft was performed. Pain and ambulation were significantly improved 6 months postoperatively. At the 1.5-year follow-up, fracture unions and complete mineralization of brown tumors were noted; the patient could ambulate with neither pain nor an assistive device. Conclusions PHPT has become more asymptomatic in countries where routine calcium screening is performed. Nevertheless, the classic skeletal involvement, osteitis fibrosa cystica, should not be overlooked, particularly in young patients who present with a low-energy fracture.
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