Hong Kong Medical Journal最新文献

Introduction: Peripartum cardiomyopathy (PPCM) is an uncommon but serious form of heart failure affecting women during late pregnancy or early postpartum. This territory-wide multicentre retrospective study aimed to evaluate the local incidence, risk factors, and clinical outcomes, including subsequent pregnancies, in Hong Kong.

Methods: Medical records were retrospectively reviewed for women who delivered at all public hospitals between 1 January 2013 and 31 December 2022 and met the 2010 European Society of Cardiology Working Group criteria for PPCM. Regression analysis was performed to investigate maternal risk factors.

Results: Thirty Asian women were diagnosed with PPCM, corresponding to an incidence of 1 in 11 179 live births. Eleven (36.7%) had antepartum onset of symptoms, and 25 (83.3%) were diagnosed after childbirth, most presenting with severe symptoms (90%). The median left ventricular ejection fraction was 30% (range, 10%-44%). Notable complications included cardiogenic shock (10%), respiratory failure (23.3%), acute renal failure (23.3%), and thromboembolism (23.3%). Most women received guideline-directed heart failure therapy. At 12 months, all-cause mortality was 6.7%, and cardiac recovery occurred in 60%. Eleven women had 13 subsequent pregnancies (three miscarriages, five terminations, and five live births). There were no maternal deaths or cases of recurrent PPCM. Genetic testing identified potentially pathogenic variants in at least 10% of women. Antenatal anaemia (adjusted odds ratio [OR]=13.04; 95% confidence interval [95% CI]=3.72-45.70) and hypertensive disorders of pregnancy (adjusted OR=38.00; 95% CI=9.66-149.52) were associated with higher odds of PPCM.

Conclusion: This study highlights the substantial morbidity and mortality associated with PPCM. Genetic testing may aid in risk stratification and prognostication.

Introduction: ¹⁸F-fluorodeoxyglucose positron emission tomography coupled with computed tomography (PET/CT) has been incorporated into breast cancer management. In Hong Kong, PET/CT use is increasing. This study aimed to establish consensus-based recommendations on the use of PET/CT in the management of early breast cancer.

Methods: A literature search was conducted in September 2023 using the keywords "breast cancer" and "PET/CT" within PubMed to identify research articles related to the use of PET/CT in early breast cancer. Guidelines from major international cancer agencies were also reviewed. Ten recommendation statements were drafted. A two-round modified Delphi consensus process was conducted over a 3-month period (19 December 2023 to 29 February 2024).

Results: A total of 76 experts consented to participate in the first round, of whom 71 completed the second round and were included as members of the expert panel, yielding a second-round response rate of 93.4%. The panel comprised oncologists (n=30, 42.3%), surgeons (n=35, 49.3%), and radiologists (including nuclear medicine radiologists) [n=6, 8.5%]. Experts from the Hospital Authority (n=37, 52.1%) and the private sector (n=32, 45.1%) were well represented. Two experts (2.8%) were from one of the two local university medical faculties. Over 75% of expert panel members had at least 15 years of clinical experience. Of the ten statements, consensus was achieved on seven in the first round and one additional statement in the second round.

Conclusion: Through the consensus process, the proposed recommendations are expected to gain wider acceptance and recognition among local healthcare professionals as guidance for the use of PET/CT in early breast cancer management.

Introduction: Case-mix systems aim to optimise acute care resource allocation, yet patients within the same groups often exhibit substantial variability in utilisation. This study aimed to examine how incorporating measures of clinical complexity and post-acute care utilisation-both critical to rehospitalisation risk and accurate resource planning-into case-mix stratification could improve the precision of acute care resource allocation.

Methods: Through iterative applications of unsupervised and supervised machine learning models, we extracted typical patient profiles from the study populations, analysed post-acute care utilisation patterns, and assessed the 28-day rehospitalisation rates resulting from different pairings between clinical profiles and post-acute care service utilisation patterns.

Results: Across various disease systems and age-groups, patients discharged without receiving algorithm-selected post-acute care (ie, No Service groups [NS groups]) showed significantly higher 28-day rehospitalisation rates relative to their corresponding segments in the same medoid case-mix groups (CMGs; pooled odds ratio [OR]=19.27; P<0.001). The NS groups also demonstrated higher rates of having two or more chronic diseases (pooled OR=1.84; P<0.001) and-for the 50-64-year-old population-resource-intensifying co-morbidities (pooled OR=1.23; P=0.05). Patients displaying higher rates of resource-intensifying co-morbidities compared with their ≥65-year-old counterparts (such as when the medoid CMG was renal failure or chronic obstructive pulmonary disease) also exhibited significantly higher 28-day rehospitalisation rates than the ≥65-year-old NS groups sharing the same medoid CMGs.

Conclusion: These findings support a precision-driven approach to designing rehospitalisation prevention programmes that target individuals aged 50 to 64 years discharged with specific clinical profiles, and developing and allocating human capital for these targeted prevention programmes.