Singapore medical journal最新文献

Introduction: Hand tumours are frequently encountered in clinical practice. However, large-scale epidemiological data of soft tissue tumours in the hand are infrequently published. Epidemiological data provide diagnostic cues to guide the workup and management of hand tumours. Assessing significant independent demographic factors and tumour characteristics associated with hand tumours is essential in health care.

Methods: A retrospective review of patients who underwent excision of hand tumours in Singapore General Hospital between 2004 and 2015 was conducted. The data collected included age, gender, ethnicity, histological diagnosis, malignancy and location of tumour. Generalised linear latent and mixed models (GLLAMM) analyses were performed.

Results: A total of 4476 tumours were identified from 4226 patients with a mean age of 51.3 (range 8-101) years and male to female ratio of 1 to 1.15. Most patients were Chinese (75%), followed by Malay (9%), Indian (8%) and others (8%). The most common hand tumours excised were ganglions (43%) (majority in the wrist), followed by giant cell tumours (9%) (commonly in the digits). Most soft tissue tumours were benign (97%), with only 3% of malignant cases. The GLLAMM analyses revealed further potential factors on the status of malignancy, tumour origin and tumour location.

Conclusion: Most soft tissue tumours in the hand and wrist are benign. This can guide workup and counselling of patients before the operation. While malignant tumours are uncommon, they have the potential for significant morbidity and mortality if not appropriately evaluated or treated. The application of GLLAMM analyses showed that age, ethnicity and gender were significant predictors of malignancy.

Introduction: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations may miss diagnoses, which later require the callback of patients for further management. Artificial intelligence (AI) has been viewed as a potential solution to augment the shortage of radiologists after hours. We explored the efficacy of an AI solution in the detection of appendicular and pelvic fractures for adult radiographs performed after hours at a general hospital ED in Singapore, and estimated the potential monetary and non-monetary benefits.

Methods: One hundred and fifty anonymised abnormal radiographs were retrospectively collected and fed through an AI fracture detection solution. The radiographs were re-read by two radiologist reviewers and their consensus was established as the reference standard. Cases were stratified based on the concordance between the AI solution and the reviewers' findings. Discordant cases were further analysed based on the nature of the discrepancy into overcall and undercall subgroups. Statistical analysis was performed to evaluate the accuracy, sensitivity and inter-rater reliability of the AI solution.

Results: Ninety-two examinations were included in the final study radiograph set. The AI solution had a sensitivity of 98.9%, an accuracy of 85.9% and an almost perfect agreement with the reference standard.

Conclusion: An AI fracture detection solution has similar sensitivity to human radiologists in the detection of fractures on ED appendicular and pelvic radiographs. Its implementation offers significant potential measurable cost, manpower and time savings.

Introduction: This study aimed to compare the pregnancy and perinatal outcomes of women with and without severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during pregnancy.

Methods: Women who delivered in an obstetric unit from March 2022 to October 2022 were recruited. The history of vaccination and SARS-CoV-2 infection during pregnancy was recorded. The pregnancy and perinatal outcomes of women with and without SARS-CoV-2 infection were compared.

Results: A total of 1015 women were recruited - 41.5% had SARS-CoV-2 infection during pregnancy and 25.2% were unvaccinated. The incidences of preeclampsia, gestational diabetes mellitus and caesarean section were similar between the two groups. There were more preterm deliveries (9.0% vs 5.1%, P = 0.01) and more late preterm deliveries of between 33 and 36 + 6 weeks (6.2% vs. 3.7%, P = 0.03) in the SARS-CoV-2 infection group. There were no statistically significant differences between the two groups in perinatal outcomes, including birthweight, incidence of small for gestational age, low Apgar scores, and neonatal intensive care or special care baby unit admissions. There were no differences in pregnancy and perinatal outcomes between women infected in the first/second trimester and those infected in the third trimester, except for lower mean birthweight (3180 g vs. 3292 g, P = 0.04). There were no major differences in pregnancy outcome between vaccinated and unvaccinated women.

Conclusion: The pregnancy and perinatal outcomes of women who were infected with SARS-CoV-2 during gestation appear favourable.

Introduction: Early in the coronavirus disease 2019 (COVID-19) pandemic, a low incidence of cardiovascular complications was reported in Singapore. Little was known about the trend of cardiovascular complications as the pandemic progressed. In this study, we examined the evolving trends in electrocardiographic and cardiovascular manifestations in patients hospitalised with COVID-19.

Methods: We examined the first 1781 consecutive hospitalised patients with polymerase chain reaction-confirmed COVID-19. We divided the population based on whether they had abnormal heart rate (HR) or electrocardiography (ECG) or normal HR and ECG, comparing the baseline characteristics and outcomes. Cardiovascular complications were defined as acute myocardial infarction, stroke, pulmonary embolism, myocarditis and mortality.

Results: The 253 (14.2%) patients who had abnormal HR/ECG at presentation were more likely to be symptomatic. Sinus tachycardia was commonly observed. Troponin I levels (97.0 ± 482.9 vs. 19.7 ± 68.4 ng/L, P = 0.047) and C-reactive protein levels (20.1 ± 50.7 vs. 13.9 ± 24.1 μmol/L, P = 0.003) were significantly higher among those with abnormal HR/ECGs, with a higher prevalence of myocarditis (2.0% vs. 0.5%, P = 0.019), pulmonary embolism (2.0% vs. 0.3%, P = 0.008) and acute myocardial infarction (1.2% vs. 0.1%, P = 0.023). After adjusting for age and comorbidities, abnormal HR/ECG (adjusted odds ratio 4.41, 95% confidence interval 2.21-8.77; P < 0.001) remained independently associated with adverse cardiovascular complications. Over time, there was a trend towards a higher proportion of hospitalised patients with cardiovascular complications.

Conclusion: Cardiovascular complications appear to be increasing in proportion over time among hospitalised patients with COVID-19. A baseline ECG and HR measurement may be helpful for predicting these complications.