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Objective: To compare the efficacy of romosozumab (ROMO) and denosumab (DEN) in prevalent long‐term glucocorticoid (GC) users. Methods: Adult patients receiving oral prednisolone (≥5 mg/day) with high risk of fracture were randomized to receive subcutaneous ROMO (210 mg monthly) or DEN (60 mg 6‐monthly) for 12 months, followed by DEN for two more doses. The primary end point was the change in spine bone mineral density (BMD) from Months 0 to 12. Secondary end points included changes in BMD of the spine/hip/femoral neck and bone turnover markers at various time points and adverse events. Results: Seventy patients (age 62.6 ± 9.1 years; 96% women; median prednisolone dose 5.0 mg/day; duration of therapy 10.7 ± 7.4 years) were enrolled, and 63 completed the study. At Month 12, the spine BMD increased significantly in both ROMO (+7.3% ± 4.5%; p < 0.001) and DEN (+2.3% ± 3.1%; p < 0.001) groups. The absolute spine BMD gain from Months 0 to 12 was significantly greater in ROMO‐treated patients (p < 0.001). Although the total hip BMD at Month 12 also increased significantly in the ROMO (+1.6% ± 3.3%; p = 0.01) and DEN groups (+1.6% ± 2.6%; p = 0.003), the absolute BMD gain was not significantly different between the groups. At Month 24, the spine BMD continued to increase in both the ROMO (+9.7% ± 4.8%; p < 0.001) and DEN group (+3.0% ± 3.0%; p < 0.001) compared to baseline, and the absolute BMD gain remained significantly greater in ROMO‐treated patients. The total hip BMD continued to increase in both groups (ROMO +2.9% ± 3.7%; p < 0.001; DEN +2.2% ± 3.4%; p = 0.001), but the changes from baseline were similar. Injection site reaction was more frequently reported in ROMO‐treated patients. Conclusion: ROMO was superior to DEN in raising the spine BMD at Month 12 in chronic GC users. After switching to DEN, ROMO‐treated patients continued to gain spine BMD to a greater extent than DEN until Month 24. [ABSTRACT FROM AUTHOR]

Background/Objectives: There has been limited evidence on the long-term impacts of coffee intake on health. We aimed to investigate the association between coffee intake and the incidence of diseases and mortality risk over 20 years among community-dwelling Chinese adults. Methods: Participants were from the Hong Kong Osteoporosis Study who attended baseline assessments during 1995–2010. Coffee intake was self-reported through a food frequency questionnaire and was previously validated. Disease diagnoses, which were mapped into 1795 distinct phecodes, and mortality data were obtained from linkage with territory-wide electronic health records. Cox models were used to estimate the association between coffee intake and the incidence of each disease outcome and mortality among individuals without a history of the respective medical condition at baseline. All models were adjusted for age, sex, body mass index, smoking, alcohol drinking, and education. Results: Among the 7420 included participants (mean age 53.2 years, 72.2% women), 54.0% were non-coffee drinkers, and only 2.7% consumed more than one cup of coffee per day. Over a median follow-up of 20.0 years, any coffee intake was associated with a reduced risk of dementia, atrial fibrillation, painful respirations, infections, atopic dermatitis, and dizziness at a false discovery rate (FDR) of <0.05. Furthermore, any coffee intake was associated with an 18% reduced risk of all-cause mortality (95% confidence interval = 0.73–0.93). Conclusion: In a population with relatively low coffee consumption, any coffee intake is linked to a lower risk of several neurological, circulatory, and respiratory diseases and symptoms, as well as mortality. [ABSTRACT FROM AUTHOR]

Aim: To develop 10‐year cardiovascular disease (CVD) risk prediction models in Chinese patients with type 2 diabetes mellitus (T2DM) managed in primary care using machine learning (ML) methods. Methods: In this 10‐year population‐based retrospective cohort study, 141 516 Chinese T2DM patients aged 18 years or above, without history of CVD or end‐stage renal disease and managed in public primary care clinics in 2008, were included and followed up until December 2017. Two‐thirds of the patients were randomly selected to develop sex‐specific CVD risk prediction models. The remaining one‐third of patients were used as the validation sample to evaluate the discrimination and calibration of the models. ML‐based methods were applied to missing data imputation, predictor selection, risk prediction modelling, model interpretation, and model evaluation. Cox regression was used to develop the statistical models in parallel for comparison. Results: During a median follow‐up of 9.75 years, 32 445 patients (22.9%) developed CVD. Age, T2DM duration, urine albumin‐to‐creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), systolic blood pressure variability and glycated haemoglobin (HbA1c) variability were the most important predictors. ML models also identified nonlinear effects of several predictors, particularly the U‐shaped effects of eGFR and body mass index. The ML models showed a Harrell's C statistic of >0.80 and good calibration. The ML models performed significantly better than the Cox regression models in CVD risk prediction and achieved better risk stratification for individual patients. Conclusion: Using routinely available predictors and ML‐based algorithms, this study established 10‐year CVD risk prediction models for Chinese T2DM patients in primary care. The findings highlight the importance of renal function indicators, and variability in both blood pressure and HbA1c as CVD predictors, which deserve more clinical attention. The derived risk prediction tools have the potential to support clinical decision making and encourage patients towards self‐care, subject to further research confirming the models' feasibility, acceptability and applicability at the point of care. [ABSTRACT FROM AUTHOR]

Objective: Baseline circulating thrombospondin‐2 (TSP2) level was identified as a potential novel hepatic fibrosis biomarker that associates with development and progression of hepatic fibrosis in patients with nonalcoholic fatty liver disease and type 2 diabetes. Here, we investigated whether circulating TSP2 levels changed with improvement in liver stiffness (LS), which reflects liver fibrosis on transient elastography. Design: Serum TSP2 levels were measured in participants from a randomized, open‐label intervention study, at baseline and after 24‐weeks treatment of either dapagliflozin 10 mg (N = 30) or sitagliptin 100 mg daily (N = 30). Vibration‐controlled transient elastography was performed to evaluate the severity of hepatic fibrosis and steatosis using LS and controlled attenuation parameter (CAP), respectively. Patients and Measurements: Among all 60 participants with similar clinical characteristics at baseline (mean HbA1c 8.9%, CAP 289 dB/m and LS 5.8 kPa), despite similar HbA1c lowering, treatment with dapagliflozin, but not sitagliptin, led to significant improvements in body weight (BW) (p =.012), CAP (p =.015) and LS (p =.011) after 24 weeks. Results: Serum TSP2 level decreased significantly from baseline in dapagliflozin‐treated participants (p =.035), whereas no significant change was observed with sitagliptin. In correlation analysis, change in serum TSP2 levels only positively correlated with change in LS (r =.487, p =.006), but not with changes in BW, CAP or HbA1c after dapagliflozin treatment. Conclusions: Serum TSP2 level decreased with LS after dapagliflozin treatment, and was independent of improvements in BW, glycemic control and hepatic steatosis, further supporting the potential of serum TSP2 level as a novel hepatic fibrosis biomarker in type 2 diabetes. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the long‐term associations between coronavirus disease 2019 (COVID‐19) and diabetes complications and mortality, in patients with diabetes. Materials and Methods: People with diabetes diagnosed with COVID‐19 infection (exposed group), from 16 March 2020 to 31 May 2021 from the UK Biobank (UKB cohort; n = 2456), and from 1 April 2020 to 31 May 2022 from the electronic health records in Hong Kong (HK cohort; n = 80 546), were recruited. Each patient was randomly matched with participants with diabetes but without COVID‐19 (unexposed group), based on age and sex (UKB, n = 41 801; HK, n = 391 849). Patients were followed for up to 18 months until 31 August 2021 for UKB, and up to 28 months until 15 August 2022 for HK. Characteristics between cohorts were further adjusted with Inverse Probability Treatment Weighting. Long‐term association of COVID‐19 with multi‐organ disease complications and all‐cause mortality after 21 days of diagnosis was evaluated by Cox regression. Results: Compared with uninfected participants, patients with COVID‐19 infection with diabetes were consistently associated with higher risks of cardiovascular diseases (coronary heart disease [CHD]: hazard ratio [HR] [UKB]: 1.6 [95% confidence interval {CI}: 1.0, 2.4], HR [HK]: 1.2 [95% CI: 1.0, 1.5]; and stroke: HR [UKB]: 2.0 [95% CI: 1.1, 3.6], HR [HK]: 1.5 [95% CI: 1.3, 1.8]), microvascular disease (end stage renal disease: HR [UKB]: 2.1 [95% CI: 1.1, 4.0], HR [HK]: 1.2 [95% CI: 1.1, 1.4]) and all‐cause mortality (HR [UKB]: 4.6 [95% CI: 3.8, 5.5], HR [HK]: 2.6 [95% CI: 2.5, 2.8]), in both cohorts. Conclusions: COVID‐19 infection is associated with long‐term increased risks of diabetes complications (especially cardiovascular complications, and mortality) in people with diabetes. Monitoring for signs/symptoms of developing these long‐term complications post‐COVID‐19 infection in the infected patient population of people with diabetes may be beneficial in minimizing their morbidity and mortality. [ABSTRACT FROM AUTHOR]