Hong Kong Medical Journal最新文献

Introduction: This study aimed to construct consolidated and updated ultrasonographic fetal biometry and estimated fetal weight (EFW) references for the Hong Kong Chinese population and evaluate the extent of under- and overdiagnosis of small-for-gestational-age (SGA) and large-for-gestational-age (LGA) using these new references.

Methods: Fetal biometry and EFW references were constructed using the Generalised Additive Model for Location, Scale, and Shape, based on data from 1679 singleton pregnancies in non-smoking Chinese women. Ultrasound scans were performed at 12 to 40 weeks of gestation to measure biparietal diameter, head circumference, abdominal circumference (AC), and femur length, following standardised protocols. The rates of SGA and LGA diagnoses using the existing and updated Hong Kong fetal biometry references were compared in an independent cohort of 10 229 pregnancies.

Results: The median number of scans per gestational week between 20 and 39 weeks was 75 (interquartile range=67-83). Compared with existing references, the new AC reference would significantly (P<0.001) increase the proportions of SGA fetuses with AC measurements at <3rd and <10th percentiles from 1.7% and 6.1% to 3.4% and 10.0%, respectively. Conversely, it would significantly decrease (P<0.001) the proportions of LGA fetuses with AC at >90th and >97th percentiles from 15.0% and 4.9% to 11.5% and 3.5%, respectively.

Conclusion: Adoption of the new references, particularly for AC, may lead to increased identification of SGA cases and decreased identification of LGA cases. The proportions of these cases will be more consistent with their intended diagnostic thresholds. Further studies are needed to determine how these references impact pregnancy outcomes.

Introduction: Research concerning artificial intelligence in breast cancer detection has primarily focused on population screening. However, Hong Kong lacks a population-based screening programme. This study aimed to evaluate the potential of artificial intelligence-based computer-assisted diagnosis (AI-CAD) program in symptomatic clinics in Hong Kong and analyse the impact of radio-pathological breast cancer phenotype on AI-CAD performance.

Methods: In total, 398 consecutive patients with 414 breast cancers were retrospectively identified from a local, prospectively maintained database managed by two tertiary referral centres between January 2020 and September 2022. The full-field digital mammography images were processed using a commercial AI-CAD algorithm. An abnormality score <30 was considered a false negative, whereas a score of ≥90 indicated a high-score tumour. Abnormality scores were analysed with respect to the clinical and radio-pathological characteristics of breast cancer, tumour-to-breast area ratio (TBAR), and tumour distance from the chest wall for cancers presenting as a mass.

Results: The median abnormality score across the 414 breast cancers was 95.6; sensitivity was 91.5% and specificity was 96.3%. High-score cancers were more often palpable, invasive, and presented as masses or architectural distortion (P<0.001). False-negative cancers were smaller, more common in dense breast tissue, and presented as asymmetrical densities (P<0.001). Large tumours with extreme TBARs and locations near the chest wall were associated with lower abnormality scores (P<0.001). Several strengths and limitations of AI-CAD were observed and discussed in detail.

Conclusion: Artificial intelligence-based computer-assisted diagnosis shows potential value as a tool for breast cancer detection in symptomatic setting, which could provide substantial benefits to patients.

Chronic kidney disease (CKD) imposes a significant burden on healthcare systems worldwide, and diabetes is a major risk factor for CKD. There is currently no consensus in Hong Kong regarding the prioritisation of early identification and intervention for CKD. A comprehensive and Hong Kong-specific diabetes and CKD treatment guideline is also lacking. A multidisciplinary group of experts discussed issues surrounding the current management of CKD and reviewed evidence in the context of local experience to support recommendations. The experts used a modified Delphi approach to finalise recommendations. Consensus was regarded as ≥75% acceptability among all expert panel members. The panel members finalised 14 CKD-focused consensus statements addressing disease definition, screening, disease monitoring, lifestyle management, and treatment strategies. The recommendations provided are relevant to the Hong Kong healthcare setting and can be used as a guide by physicians across various specialties to facilitate the appropriate management of CKD.

Introduction: Total knee arthroplasty (TKA) is one of the most commonly performed orthopaedic procedures worldwide, due to the increased prevalence of osteoarthritis associated with an ageing global population. Although many studies have focused on the causes of readmission among TKA patients within 30 days post-surgery, none have been conducted in Hong Kong. This study investigated the 30-day readmission rate, causes, and risk factors among TKA patients in Hong Kong.

Methods: This retrospective review included patients who underwent TKA at a local university-affiliated hospital between 2001 and 2020. Eligible patients were identified using the Clinical Data Analysis and Reporting System and electronic patient records. Their data were analysed to determine the 30-day readmission rate, risk factors, and underlying causes.

Results: Among the 3827 TKA patients included, the male-to-female ratio was 1:2.78 (1012:2815) and the mean age (±standard deviation) was 71.11±8.82 years. Of these patients, 3.4% underwent unplanned readmission to hospitals through the Accident and Emergency Department within 30 days of TKA. The most common causes of readmission were knee pain (33.1%), knee swelling (26.2%), and gastrointestinal-related conditions (8.5%). Age ≥80 years (odds ratio [OR]=1.63; P=0.01) and hypertension (OR=2.08; P<0.001) were risk factors for readmission. Bilateral simultaneous TKA (OR=0.42; P=0.005) was associated with lower risk of readmission.

Conclusion: The readmission rate in this study was 3.4%, comparable to rates in previous reports. Enhanced patient education and optimised perioperative pain management are needed to minimise hospital readmissions. Fall prevention, cautious painkiller prescribing, and improved nursing care are recommended to prevent readmission.