METHODS: A cross-sectional observational study was conducted in the Emergency and Trauma Department, Hospital Kuala Lumpur (ETDHKL). The implementation of a binary triage system separates patients with risk of COVID-19 who present with fever and respiratory symptoms from other patients. Data on exposed HCWs to COVID-19 patients were captured pre-restructuring and post-restructuring of the emergency department and analysed using descriptive statistics.
RESULTS: A total of 846 HCWs were involved in this study. Pre-restructuring reported 542 HCWs exposed to COVID-19 patients while post-restructuring reported 122. Using the four categorical exposure risks for HCWs which are no identifiable risk, low risk, medium risk, and high risk, the number of HCWs exposed during pre-restructuring were 15(1.8%), 504 (59.6%), 15 (1.8%), and 8 (0.9%), respectively, while post-restructuring the numbers were 122 (14.4%), 8 (0.9%), 109 (12.9%), and 5 (0.1%), respectively. There was a 77.5% reduction in the number of exposed HCWs after our implementation of the new system (542 vs 122).
CONCLUSION: A binary triage system based on severity and infectivity and supported with structural reorganization can be effective in reducing HCWs COVID-19 exposure.
METHODS: Haematological cancer cases with ICD-10 coded C81-C96 and ICD-O coded /3 diagnosed from 1996 to 2015 were retrieved from Sarawak Cancer Registry. Adult was defined as those 15 years and above. Incidence rate (IR) was calculated based on yearly Sarawak citizen population stratified to age, gender, and ethnic groups. Age-standardised IR (ASR) was calculated using Segi World Standard Population.
RESULTS: A total of 3,947 cases were retrieved and analysed. ASR was 10 and male predominance (IR ratio 1.32, 95%CI 1.24,1.41). Haematological cancers generally had a U-shaped distribution with lowest IR at age 10-14 years and exponential increment from age 40 years onwards, except acute lymphoblastic leukaemia (ALL) with highest IR in paediatric 2.8 versus adult 0.5. There was a significant difference in ethnic and specific categories of haematological cancers, of which, in general, Bidayuh (IR ratio 1.13, 95%CI 1.00, 1.27) and Melanau (IR ratio 0.54, 95%CI 0.45, 0.65) had the highest and lowest ethnic-specific IR, respectively, in comparison to Malay. The ASR (non-Hodgkin lymphoma, acute myeloid leukaemia, ALL, chronic myeloid leukaemia, and plasma cell neoplasm) showed a decreasing trend over the 20 years, -2.09 in general, while Hodgkin lymphoma showed an increasing trend of + 2.80. There was crude rate difference between the 11 administrative divisions of Sarawak.
CONCLUSIONS: This study provided the IR and ASR of haematological cancers in Sarawak for comparison to other regions of the world. Ethnic diversity in Sarawak resulted in significant differences in IR and ASR.
METHOD: Data between 1996 to 2015 from a population-based cancer registry in Sarawak Malaysia was analyzed. Crude incidence rates and age-standardized rates (ASR) were calculated and compared between ethnic groups and locations (administrative division) and Joinpoint regression analysis was done to analyze trends.
RESULT: A total of 3643 cases of NPC were recorded with male to female ratio of 2.5:1. Annualised age-standardized incidence rates able 2) for men is 13.2 cases per 100,000 population (95% CI: 12.6, 13.7) and for women is 5.3 cases per 100,000 population (95% CI: 5.0, 5.6). The highest incidence rates were reported among the Bidayuh population and it ranks among the highest in the world. Trend analysis noted an overall reduction of cases, with a significant decrease between 1996 and 2003 (annual percentage reduction of incidence by 3.9%). Analysis of individual ethnic groups also shows a general reduction with exception of Iban males showing an average 5.48 per cent case increase between 2009 to 2015, though not statistically significant.
CONCLUSION: Comparing the incidences with other registries, the Bidayuh population in Sarawak remained among the highest in the world and warrants close attention for early screening and prevention strategies.
METHODOLOGY: This is a multi-centre, cross-sectional study involving the University of Malaya Medical Centre (UMMC), Queen Elizabeth II Hospital (QEH), and Tengku Ampuan Rahimah Hospital (TARH). Patients diagnosed with invasive breast cancer from January 2014 to December 2015 were included, excluding stromal cancers and lymphomas. Univariate and multivariate analyses identified factors influencing BCS.
RESULTS: A total of 1005 patients were diagnosed with breast cancer in the allocated time frame. Excluding incomplete records and those who did not have surgery, 730 patients were analysed. Overall BCS rate was 32.9%. The BCS rate was highest at QEH (54.1%), followed by UMMC (29.5%), and TARH (17.4%). 16.9% had BCS after neoadjuvant therapy. Factors influencing BCS uptake included age, ethnic group, breast-surgeon led services, AJCC Stage, tumour size, HER-2 expression, and tumour grade.
CONCLUSIONS: The rate of BCS in Malaysia is low. A wide variation of rate exists among the studied hospitals. Younger age, earlier AJCC stage, and the presence of a Breast sub-specialist surgeon, would make it more likely that the patient has her breast conserved.
METHODS: Information regarding incident site and hospital management response were analysed. Data on demography, triaging, injuries and hospital management of patients were collected according to a designed protocol. Challenges, difficulties and their solutions were reported.
RESULTS: The train's emergency response team (ERT) has shut down train movements towards the incident site. Red zone (in the tunnel), yellow zone (the station platform) and green zone (outside the station entrance) were established. The fire and rescue team arrived and assisted the ERT in the red zone. Incident command system was established at the site. Medical base station was established at the yellow zone. Two hundred and fourteen passengers were in the trains. Sixty-four of them were injured. They had a median (range) ISS of 2 (1-43), and all were sent to Hospital Kuala Lumpur (HKL). Six (9.4%) patients were clinically triaged as red (critical), 19 (29.7%) as yellow (semi-critical) and 39 (60.9%) as green (non-critical). HKL's disaster plan was activated. All patients underwent temperature and epidemiology link assessment. Seven (10.9%) patients were admitted to the hospital (3 to the ICU, 3 to the ward and 1 to a private hospital as requested by the patient), while the rest 56 (87.5%) were discharged home. Six (9.4%) needed surgery. The COVID-19 tests were conducted on seven patients (10.9%) and were negative. There were no deaths.
CONCLUSIONS: The mass casualty incident was handled properly because of a clear standard operating procedure, smooth coordination between multi-agencies and the hospitals, presence of a 'binary' system for 'COVID-risk' and 'non-COVID-risk' areas, and the modifications of the existing disaster plan. Preparedness for MCIs is essential during pandemics.
METHODS: The study was conducted among COVID-19 subjects at an out-of-hospital setting whereby lung ultrasound was done and subsequently chest x-rays were taken after being admitted to the health care facilities. Lung ultrasound findings were reviewed by emergency physicians, while the chest x-rays were reviewed by radiologists. Radiologists were blinded by the patients' lung ultrasound findings and clinical conditions. The analysis of the agreement between the lung ultrasound findings and chest x-rays was conducted.
RESULTS: A total of 261 subjects were recruited. LUS detected pulmonary infiltrative changes in more stage 3 COVID-19 subjects in comparison to chest x-rays. Multiple B-lines were the predominant findings at the right lower anterior, posterior and lateral zones. Interstitial consolidations and ground glass opacities were the predominant descriptive findings in chest x-rays. However, there was no agreement between lung ultrasound and chest x-ray findings in detecting COVID-19 pneumonia as the Cohen's Kappa coefficient was 0.08 (95% CI 0.06-0.22, p = 0.16).
CONCLUSION: The diagnostic imaging and staging of COVID-19 patients using lung ultrasound in out-of-hospital settings showed LUS detected lung pleural disease more often than CXR for stage 3 COVID-19 patients.