MATERIALS AND METHODS: This was a cross-sectional, observational study on empathy among doctors practicing in the private, public hospital sector and faculty at a medical university in Negeri Sembilan, Malaysia that utilised convenience sampling for data collection. The Toronto Empathy Questionnaire (TEQ) a validated tool was used to measure empathy.
RESULTS: The questionnaire was completed by 127 doctors, 52% (n= 66) were males and 48% (n=61) females. There was no significant difference in empathy between male (M=46.44; SD=6.01) and female (M=45.05, SD=5.69) doctors; t (123) = 1.326, p=0.187. Pearson correlation coefficient was computed to assess the linear relationship between age and empathy and revealed no correlation between the two variables: r (125) =0.15, p=0.099. Medical-based doctors (M= 47.47, SD=5.98) demonstrated more empathy than surgicalbased (M=44.32, SD=5.41); t (123) =-3.09, p=0.002. Those already specialised in their fields (M=47.38, SD=4.57) had more empathy than those who had not (M= 44.36, SD=6.52); t (123) =-2.96, p = 0.004. Doctors in the university (M=47.97, SD=4.31) tended to have more empathy than those in the public hospitals (M= 44.63, SD=6.27); t (117) =-2.91, p=0.004. Academicians had more empathy than non-academicians but there was no difference between those who were in clinical practice and not.
CONCLUSION: Our findings indicate that medical-based doctors demonstrate more empathy than surgical-based doctors, and there appeared to be no correlation between age and empathy. However, clinical experience and growth within the specialty seem to improve empathy. Doctors teaching in the university setting demonstrated more empathy than those practicing in the hospital setting. Inclusion of empathy-related sessions in the undergraduate and post-graduate curriculum could bridge the gap in empathy noted with age, discipline, and experience in practice. Further research on empathy among doctors using a wider population in Malaysia and a TEQ questionnaire validated to the Asian population would provide better insight regarding this area of medical practice. Future research on outcomes of inclusion of programmes targeted at improving empathy to create awareness during practice would support patient satisfaction and safety.
METHODS: Lead Investigators from countries formally involved in the EAS FHSC by mid-May 2018 were invited to provide a brief report on FH status in their countries, including available information, programmes, initiatives, and management.
RESULTS: 63 countries provided reports. Data on FH prevalence are lacking in most countries. Where available, data tend to align with recent estimates, suggesting a higher frequency than that traditionally considered. Low rates of FH detection are reported across all regions. National registries and education programmes to improve FH awareness/knowledge are a recognised priority, but funding is often lacking. In most countries, diagnosis primarily relies on the Dutch Lipid Clinics Network criteria. Although available in many countries, genetic testing is not widely implemented (frequent cost issues). There are only a few national official government programmes for FH. Under-treatment is an issue. FH therapy is not universally reimbursed. PCSK9-inhibitors are available in ∼2/3 countries. Lipoprotein-apheresis is offered in ∼60% countries, although access is limited.
CONCLUSIONS: FH is a recognised public health concern. Management varies widely across countries, with overall suboptimal identification and under-treatment. Efforts and initiatives to improve FH knowledge and management are underway, including development of national registries, but support, particularly from health authorities, and better funding are greatly needed.
METHODS: We identified children ≤ 12 years old hospitalized for COVID-19 across five hospitals in Negeri Sembilan, Malaysia, from 1 January 2021 to 31 December 2021 from the state's pediatric COVID-19 case registration system. The primary outcome was the development of moderate/severe COVID-19 during hospitalization. Multivariate logistic regression was performed to identify independent risk factors for moderate/severe COVID-19. A nomogram was constructed to predict moderate/severe disease. The model performance was evaluated using the area under the curve (AUC), sensitivity, specificity, and accuracy.
RESULTS: A total of 1,717 patients were included. After excluding the asymptomatic cases, 1,234 patients (1,023 mild cases and 211 moderate/severe cases) were used to develop the prediction model. Nine independent risk factors were identified, including the presence of at least one comorbidity, shortness of breath, vomiting, diarrhea, rash, seizures, temperature on arrival, chest recessions, and abnormal breath sounds. The nomogram's sensitivity, specificity, accuracy, and AUC for predicting moderate/severe COVID-19 were 58·1%, 80·5%, 76·8%, and 0·86 (95% CI, 0·79 - 0·92) respectively.
CONCLUSION: Our nomogram, which incorporated readily available clinical parameters, would be useful to facilitate individualized clinical decisions.