將軍澳醫院

OBJECTIVE:This study aims to evaluate changes in the epidemiology of major osteoporotic fractures (MOF) stratified by diabetes status over 15 years in a population-based cohort. METHODS:Individuals aged ≥50 years who sustained MOF between 2009 and 2023 identified from territory-wide electronic health database, stratified by diabetes status. Records of HbA1c, hypoglycemic episodes, and osteoporosis screening and treatments were retrieved. Ratios of rates of MOF, osteoporosis screening and treatments between the diabetes and nondiabetes groups were calculated to reflect the disparity between 2 groups. Secular trends were reported in average annual percentage change (AAPC) using joinpoint regression. All rates were age-standardized to the 2021 Hong Kong Census mid-year population. RESULTS:86 263 hip fractures and 124 268 nonhip fractures were recorded during the study period. Although annual age-standardized incidence of hip fractures decreased, rate ratios between diabetes and nondiabetes remained static at 4.1 for women (AAPC: -0.16%, 95% CI: -0.65 to +0.35, P = .54) and 2.5 for men (AAPC: +0.07%, 95%CI: -0.58 to 0.71, P = .83), suggesting persistent gap of diabetes-specific excess fracture risk. This gap was similarly observed for nonhip fractures. Over the years, age-standardized mean HbA1c improved from 59 mmol/mol (7.5%) to 53 mmol/mol (7%), along with fewer severe hypoglycemic episodes. Prevalence of individuals with screening dual-energy x-ray absorptiometry performed increased, more so in women with diabetes. Anti-osteoporosis medication prescriptions increased in both diabetes and nondiabetes, but increased to a lesser extent in the diabetes population. CONCLUSION:Diabetes-specific excess fracture risk persisted despite improved glycemic control. Despite increasing efforts of osteoporosis screening in diabetes, this has not translated into more aggressive treatment of bone fragility in diabetes.

Background Differentiating heart failure (HF) with mildly reduced/reduced ejection fraction (HFmr/rEF) from HF with preserved ejection fraction (HFpEF) guides therapy but echocardiography may be delayed or unavailable. We developed and validated machine learning models using routine 12-lead ECG data to classify HF phenotypes.Methods In this retrospective cohort of hospitalised patients with HF, predictors available at or before the index ECG were used. HFmrEF was pooled with HFrEF (left ventricular ejection fraction <50%) for model development. Data were split 70/30 into training and held-out test sets. Random forest (RF), Extreme Gradient Boosting and support vector machine models were trained and tuned using fivefold cross-validation in the training set. Boruta was used to select key ECG features. Test-set performance was evaluated by area under the curve (AUC) and accuracy; AUCs were compared using DeLong’s test.Results Overall, 495 patients were included (254 HFmr/rEF; 241 HFpEF). RF consistently performed best. Using ECG features alone, RF achieved an AUC of 0.821 (95% CI 0.752 to 0.890) and accuracy of 75.7%. A parsimonious RF model using 12 Boruta-selected ECG variables achieved an AUC of 0.832 (95% CI 0.766 to 0.899) and accuracy of 76.4%, with no significant AUC difference versus a comprehensive RF model using clinical/laboratory/ECG predictors (AUC 0.804, 95% CI 0.734 to 0.875; p=0.288) or the model using all ECG features (p=0.092). Adding X-ray cardiomegaly did not improve performance.Conclusion A parsimonious RF model based on a small set of standard ECG measurements differentiates HFmr/rEF from HFpEF with good discrimination, supporting ECG as an adjunct for phenotyping when echocardiography is not immediately available.

Importance Screening for diabetic retinopathy using fundus photographs is the global standard of care but results in high false-positive referrals to evaluate diabetic macular edema (DME), placing a substantial burden on specialist eye clinics. Integrating an AI-based optical coherence tomography (AI-OCT) system into screening pathways may reduce potentially unnecessary referrals. Objective To evaluate the diagnostic and referral performance of an AI-OCT system for DME detection within a diabetic retinopathy screening pathway in clinical settings. Design, Setting, and Participants Stepwise evaluation conducted in Hong Kong Special Administrative Region: a prospective silent-mode validation (February 2020 to July 2023) recruiting 603 patients with diabetes at a tertiary hospital triage unit, followed by a multicenter noninferiority RCT (September 2023 to April 2025), with follow-up completed in May 2025, recruiting 276 patients with suspected DME referred from a territory-wide diabetic retinopathy screening program. Interventions RCT participants were randomized to intervention (referral for DME evaluation based on both fundus photograph–based screening reports and AI-OCT reports [n = 137]) or control (automatic referral based solely on fundus photograph–based screening reports [n = 139]) groups. The AI-OCT system incorporated image-quality assessment, DME detection, and uncertainty flagging. Study outcomes focused on referral rates under the 2 pathways; for ethical reasons, all participants ultimately underwent specialist evaluation. Main Outcomes and Measures The primary outcome was false-positive DME referral rate, with a prespecified noninferiority margin of 20%. The secondary outcomes included sensitivity and specificity for DME detection and DME referral. Results In prospective silent-mode validation (mean age, 64.7 [SD, 9.4] years; 56.2% male), 86 of 1200 scans (7.2%) were identified as ungradable and 49 of 1114 gradable scans (4.4%) were classified as uncertain. The system achieved 98.8% (95% CI, 94.5%-100.0%) sensitivity and 90.7% (95% CI, 88.7%-92.4%) specificity for DME detection. In the RCT (mean age, 63.9 [SD, 10.9] years; 54.7% male), DME prevalence was similar in the intervention and control groups (30.9% vs 29.9%). The false-positive DME referral rate was 24.1% (95% CI, 14.6%-37.0%) and 69.1% (95% CI, 61.0%-76.1%), respectively (absolute difference, −45% [95% CI, −58.2% to −31.9%; P < .001 for noninferiority]; upper bound of the CI below the prespecified noninferiority margin of 20%). Sensitivity for DME referral was 100.0% (95% CI, 100.0%-100.0%) in both groups. Specificity for DME referral was 86.5% (95% CI, 79.3%-92.9%) in the intervention group and 0.0% (95% CI, 0.0%-0.0%) in the control group. No cases of DME occurred among nonreferred participants in the intervention group. Conclusions and Relevance Compared with standard practice, incorporation of the AI-OCT system as a secondary screening tool was noninferior with respect to false-positive referral rates and was associated with a substantial reduction in potentially unnecessary DME referrals without compromising sensitivity. Trial Registration Chinese Clinical Trial Registry: ChiCTR2300075087

Screening for BK polyomavirus (BKPyV) with quantitative polymerase chain reaction (qPCR) or a 2-stage approach with urine cytology followed by qPCR are acceptable strategies. However, the magnitude of the health benefits and incremental cost of adopting these 2 screening strategies are largely unknown. Probabilistic Markov models were constructed to evaluate the incremental costs and benefits of (1) screening with qPCR, (2) 2-stage screening, and (3) no routine viral screening. One-way and probabilistic sensitivity analyses were conducted to define the most influential variables in the model. Screening with either qPCR or 2-stage approaches produce incremental benefit (0.29 and 0.287 quality adjusted life years (QALYs) respectively) and save cost (USD 9,940 and USD11,610), compared with no screening. 2-stage screening associates with cost reduction (USD 1,670) at the expenses of loss in QALY (0.003 QALYs) than screening with qPCR. The incremental cost-effectiveness ratio of the models was sensitive to the graft survival rate and patient survival rate, incidence of BKPyV-DNAaemia, probability of transplantation, sensitivity and cost of urine cytology and qPCR. Screening with 2-stage screening was the best strategy in terms of net monetary benefit across a range of ‘willingness-to-pay’. From the healthcare provider’s perspective, routine BKPyV screening with either qPCR or 2-stage approach (urine cytology followed by qPCR test) is cost-saving and improves QALYs. We demonstrated various factors would affect cost efficiency of 2-stage screening vs screening with qPCR. The transplant centre should consider local factors and the willingness to pay to devise the best screening strategy. Not applicable.

Background/Objectives: Nasopharyngeal cancer (NPC) is prevalent in Southeast Asia, Southern China and North Africa. Up to 46% of NPC patients undergoing cisplatin chemoradiation treatment experience irreversible hearing loss. Prestin is a motor protein in the outer hair cells of the cochlea, and animal studies have shown that blood prestin levels are elevated following cisplatin induced hearing loss. We investigated whether rising serum prestin levels can predict sensorineural hearing loss (SHNL) in NPC patients undergoing induction cisplatin chemotherapy (icCRT). Methods: Serum prestin levels were measured at ten time points during cisplatin chemotherapy. Pure tone audiogram and tinnitus handicap inventory (THI) were measured at baseline and at one and nine months after cisplatin administration. These outcomes were obtained to investigate whether rising prestin levels predict SNHL or worsening THI. Results: Of the 11 patients accrued, there was no association between prestin level and SNHL. An increase in THI was associated with higher prestin levels. There was significant hearing loss at 8 kHz at one (right ear, p = 0.012, left ear, p = 0.043) and nine months (right ear, p = 0.011) after treatment. After completing cisplatin, patients also had increased THI. Conclusions: Prestin was not identified as a biomarker of cisplatin-induced hearing loss in our cohort of NPC patients undergoing icCRT. NPC patients experience worsening of tinnitus with cumulative cisplatin, and hearing loss can persist at nine months post treatment. Future studies should focus on improved novel methods for measuring prestin or other cochlear proteins to better identify potential markers before permanent cisplatin induced hearing loss.