Dementia has been associated with an increased risk of hip fracture. However, little research has been conducted on the impact of dementia on wrist or vertebral fracture development. The aim of this study was to investigate whether dementia is a risk factor for different types of fracture in Taiwan. The study sample was drawn from Taiwan's National Health Insurance Research Database of reimbursement claims, and comprised 1408 patients who visited ambulatory care centers or were hospitalized with a diagnosis of dementia. The comparison group consisted of 7040 randomly selected individuals. Cox proportional hazard regression model was used to examine associations between dementia and the risk of different types of fracture. During a 3-year follow-up period, 264 patients with dementia (18.75%) and 1098 patients without dementia (15.60%) developed fractures. Dementia was independently associated with increased risk of hip fracture [adjusted hazard ratio (HR) 1.92, 95% CI 1.48-2.49]. Patients with dementia and osteoporosis had the highest risk of developing hip fracture (adjusted HR 2.27, 95% CI 1.28-4.01). Dementia did not increase wrist fracture or vertebral fracture risk when compared to the control group, even in patients with osteoporosis. Individuals with dementia are at greater risk of developing hip fracture, particularly if they also have osteoporosis. Early mental screening programs and health education should be initiated to decrease disability and dependence in patients with dementia.

To determine the association of prior traumatic brain injury (TBI) with subsequent diagnosis of neurodegeneration disease. All studies from 1980 to 2016 reporting TBI as a risk factor for diagnoses of interest were identified by searching PubMed, Embase, study references, and review articles. The data and study design were assessed by 2 investigators independently. A meta-analysis was performed by RevMan 5.3. There were 18 studies comprising 3,263,207 patients. Meta-analysis revealed a significant association of prior TBI with subsequent dementia. The pooled odds ratio (OR) for TBI on development of dementia, FTD and TDP-43 associated disease were 1.93 (95% CI 1.47–2.55, p < 0.001), 4.44 (95% CI 3.86–5.10, p < 0.001), and 2.97 (95% CI 1.35–6.53, p < 0.001). However, analyses of individual diagnoses found no evidence that the risk of Alzheimer’s disease, and Parkinson’s disease in individuals with previous TBI compared to those without TBI. History of TBI is not associated with the development of subsequent neurodegeneration disease. Care must be taken in extrapolating from these results because no suitable criteria define post TBI neurodegenerative processes. Therefore, further research in this area is needed to confirm these questions and uncover the link between TBI and neurodegeneration disease.

Estrogen deficiency is one of the main causes of postmenopausal osteoporosis in elderly women. Hormone replacement therapy has been employed to manage postmenopausal osteoporosis; however, it has raised concerns related to heart attacks and breast cancer. Sesame oil has been reported to affect sex hormone status. The aim of the present study is to evaluate the effect of sesame oil supplement on postmenopausal osteoporosis in rats. We used female Sprague Dawley rats that underwent bilaterally ovariectomy (OVX) as an experimental postmenopausal osteoporosis animal model. These rats were orally administrated sesame oil (0.25 or 0.5 mL/kg/day) for four months as the therapeutic group. We assessed bone mineral density (BMD) and the levels of osteocalcin, procollagen-I C-terminal propeptide (PICP), collagen cross-linked N-telopeptide (NTx), estradiol, and aromatase in the sera. The daily supplementation of sesame oil significantly increased BMD, serum osteocalcin levels, and trabecular areas in the OVX-treated rats. Sesame oil also elevated serum PICP levels and decreased NTx levels in these rats. Furthermore, sesame oil effectively maintained serum estradiol and aromatase levels in the OVX-induced osteoporosis rats. In conclusion, daily supplementation of sesame oil prevents postmenopausal osteoporosis by maintaining serum estrogen and aromatase levels, while also modulating the imbalance between bone formation and resorption in osteoporosis rats.

Patients with end-stage renal disease (ESRD) are at a higher mortality risk compared with the general population. Previous studies have described a relationship between mortality and patients with ESRD, but the data on standardized mortality ratio (SMR) corresponding to different causes of death in patients undergoing hemodialysis (HD) and peritoneal dialysis (PD) are limited. This study was designed as a nationwide population-based retrospective cohort study. Incident dialysis patients between January 2000 and December 2015 in Taiwan were included. Using data acquired from the Taiwan Death Registry, SMR values were calculated and compared with the overall survival. The results showed there were a total of 128,966 patients enrolled, including 117,376 incident HD patients and 11,590 incident PD patients. It was found that 75,297 patients (58.4%) died during the period of 2000–2017. The overall SMR was 5.21. The neoplasms SMR was 2.11; the endocrine, nutritional, metabolic, and immunity disorders SMR was 13.53; the circulatory system SMR was 4.31; the respiratory system SMR was 2.59; the digestive system SMR was 6.1; and the genitourinary system SMR was 27.22. Therefore, more attention should be paid to these diseases in clinical care.

Workers in high-temperature workplaces with inadequate water supply may exhibit symptoms of chronic dehydration and have increased risk of nephrolithiasis. The aim of this study was to investigate the risk of radiolucent stone formation among workers in a high-temperature workplace and the related risk factors associated with the condition. We collected data from 1681 workers in a steel factory in Southern Taiwan who underwent regular health examinations. Radiolucent stones were defined as positive findings on ultrasound with negative radiographic images. The prevalences of nephrolithiasis and radiolucent stones in this study were 12.0% and 5.1%, respectively. Heat exposure and age were two major risk factors influencing the probability of radiolucent stones. We combined the age and heat exposure into four groups (over and under 35 years of age with and without heat exposure) in a logistic regression. For workers younger than 35 years, the odds ratio of radiolucent stones was 2.695 (95% confidence interval: 1.201–6.049) in workers with heat exposure compared to workers without. Our investigation further demonstrated that heat exposure was a main risk factor for radiolucent stone formation. In conclusion, our identification of heat exposure as an independent factor for radiolucent stone development in steel workers highlights the need for attention to be paid to those working in similar environments.

This study aims to establish advanced sampling methods in free-text data for efficiently building semantic text mining models using deep learning, such as identifying vertebral compression fracture (VCF) in radiology reports. We enrolled a total of 27,401 radiology free-text reports of X-ray examinations of the spine. The predictive effects were compared between text mining models built using supervised long short-term memory networks, independently derived by four sampling methods: vector sum minimization, vector sum maximization, stratified, and simple random sampling, using four fixed percentages. The drawn samples were applied to the training set, and the remaining samples were used to validate each group using different sampling methods and ratios. The predictive accuracy was measured using the area under the receiver operating characteristics (AUROC) to identify VCF. At the sampling ratios of 1/10, 1/20, 1/30, and 1/40, the highest AUROC was revealed in the sampling methods of vector sum minimization as confidence intervals of 0.981 (95%CIs: 0.980–0.983)/0.963 (95%CIs: 0.961–0.965)/0.907 (95%CIs: 0.904–0.911)/0.895 (95%CIs: 0.891–0.899), respectively. The lowest AUROC was demonstrated in the vector sum maximization. This study proposes an advanced sampling method, vector sum minimization, in free-text data that can be efficiently applied to build the text mining models by smartly drawing a small amount of critical representative samples.