Prevalence and impact of migraine among university students in Bangladesh: findings from a cross-sectional survey.

BACKGROUND: Migraine is one of the main causes of long-term morbidity, and it is one of the major contributors of all types of headaches in worldwide. Despite its disruptive effect, it is frequently underdiagnosed and undertreated in Bangladesh. The aim of the present study was to determine the prevalence of migraines and its impact on daily life of university students in Bangladesh. METHODS: This cross-sectional study was conducted among 2,352 students of Rajshahi University and Jahangirnagar University during March 2020 through a self-administered online survey. ID Migraine™ scale and HIT-6 scale were used to screen migraine and its impact respectively. Frequency distribution, Chi-square test and t-test along with multiple logistic regressions model were used to determine the prevalence and associated factors of migraine respectively. RESULTS: The overall prevalence of migraine among the participants was 21.4%. The prevalence was higher among females (29%) than males (12%). A multivariable logistic regression model provided the following eight risk factors of migraine: (i) gender (p < 0.01), (ii) family income (p < 0.01), (iii) marital status (p < 0.01), (iv) infrequent exercise (p < 0.01), (v) family history of headache (p < 0.01), (vi) high screen time (p < 0.05), (vii) depressive symptoms (p < 0.05) and (viii) anxiety disorder (p < 0.01). More than two-thirds of the people with migraines reported more than five attacks during the past month with moderate to severe intense headache. Stress was the most reported trigger of migraine among university students (71%) followed by irregular sleep (47%), academic pressure (33%), and external noise (28%). Almost 37% of the participants who had migraines reported that headache caused severe impact in their day to day life. CONCLUSIONS: The prevalence of migraine among university students of Bangladesh is alarmingly high. Frequent migraine attacks and severe intensity of headache cause a substantial level of impact among the sufferers. Cautious avoidance of the triggering factors through appropriate interventions and prophylactic medication can mitigate the negative impact of migraine as well as improve the quality of life.

Pre-hospital delay in patients with myocardial infarction: an observational study in a tertiary care hospital of northern Bangladesh.

BACKGROUND: Delayed hospital presentation is a hindrance to the optimum clinical outcome of modern therapies of Myocardial infarction (MI). This study aimed to investigate the significant factors associated with prolonged pre-hospital delay and the impact of this delay on in-hospital mortality among patients with MI in Northern Bangladesh. METHODS: This cross sectional study was conducted in December 2019 in cardiology ward of a 1000-bed tertiary care hospital of Bangladesh. Patients admitted in the ward with the diagnosis of myocardial infarction were included in the study. Socio demographic data, clinical features and patients' health seeking behavior was collected in a structured questionnaire from the patients. Median with interquartile range (IQR) of pre hospital delay were calculated and compared between different groups. Chi-square (χ2) test and binary logistic regression were used to estimate the determinants of pre-hospital delay and effect of pre-hospital delay on in-hospital mortality. RESULTS: Three hundred thirty-seven patients was enrolled in the study and their median (IQR) pre-hospital delay was 9.0 (13.0) hours. 39.5% patients admitted in the specialized hospital within 6 h. In logistic regression, determinants of pre-hospital delay were patients age (for < 40 years aOR 2.43, 95% CI 0.73-8.12; for 40 to 60 years aOR 0.44, 95% CI 0.21-0.93), family income (for lower income aOR 5.74, 95% CI 0.89-37.06; for middle income aOR 14.22, 95% CI 2.15-94.17), distance from primary care center ≤5 km (aOR 0.42, 95% CI 0.12-0.90), predominant chest pain (aOR 0.15, 95% CI 0.05-0.48), considering symptoms as non-significant (aOR 17.81, 95% CI 5.92-53.48), referral from primary care center (for government hospital aOR 4.45, 95% CI 2.03-9.74; for private hospital OR 98.67, 95% CI 11.87-820.34); and not having family history of MI (aOR 2.65, 95% CI 1.24-5.71) (R2 = 0.528). Risk of in-hospital mortality was almost four times higher who admitted after 6 h compared to their counterpart (aOR 0.28, 95% CI 0.12-0.66); (R2 = 0.303). CONCLUSION: Some modifiable factors contribute to higher pre-hospital delay of MI patients, resulting in increased in-hospital mortality. Patients' awareness about cardiovascular diseases and improved referral pathway of the existing health care system may reduce this unexpected delay.

Sexual dysfunction in women with type 2 diabetes mellitus: A single-centre cross-sectional study from Bangladesh.

Objective: Sexual dysfunction among women with diabetes is a common but neglected health issue worldwide. The objective of the present study was to investigate the prevalence of sexual dysfunction and its associated factors among women with type 2 diabetes mellitus (T2DM). Subjects and methods: This cross-sectional comparative study comprises 150 women with diabetes and 100 healthy women without diabetes who visited the endocrinology outpatient department of Mymensingh Medical College Hospital (MMCH). The data were collected from July to December 2019. Sexual dysfunction was assessed by the 19-item Female Sexual Function Index (FSFI). Informed consent was obtained before participation. Collected data were analysed by SPSS 26. Results: More women with diabetes than control subjects reported sexual dysfunction (79% vs. 72%; p = 0.864). The global FSFI score was lower among the diabetes patients than among the healthy controls (20.8 ± 7.2 vs. 23.7 ± 4.8; p < 0.001). Patients with T2DM scored significantly lower in the domains of desire (p = 0.04), lubrication (p = 0.01), orgasm (p = 0.01), and satisfaction (p < 0.001), but not the domain of arousal (p = 0.09). A prolonged duration of diabetes was the primary contributor to orgasm problems (adjusted odds ratio, aOR 1.3, 95% CI 1.1-1.7) and painful intercourse (aOR 1.2, 95% CI 1.1- 1.5). Conclusion: Sexual problems are frequent in women with diabetes. Inclusion of sexual health in comprehensive diabetes management is crucial to address this problem as well as to improve the quality of life of female diabetes patients.

Forecasting COVID-19 cases: A comparative analysis between recurrent and convolutional neural networks.

Though many countries have already launched COVID-19 mass vaccination programs to control the disease outbreak quickly, numerous countries around worldwide are grappling with unprecedented surges of new COVID-19 cases due to a more contagious and deadly variant of coronavirus. As the number of new cases is skyrocketing, pandemic fatigue and public apathy towards different intervention strategies pose new challenges to government officials to combat the pandemic. Henceforth, it is indispensable for the government officials to understand the future dynamics of COVID-19 flawlessly to develop strategic preparedness and resilient response planning. In light of the above circumstances, probable future outbreak scenarios in Brazil, Russia, and the United kingdom have been sketched in this study with the help of four deep learning models: long short term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) and multivariate convolutional neural network (MCNN). In our analysis, the CNN algorithm has outperformed other deep learning models in terms of validation accuracy and forecasting consistency. It is unearthed in our study that CNN can provide robust long-term forecasting results in time-series analysis due to its capability of essential features learning, distortion invariance, and temporal dependence learning. However, the prediction accuracy of the LSTM algorithm has been found to be poor as it tries to discover seasonality and periodic intervals from any time-series dataset, which were absent in our studied countries. Our study has highlighted the promising validation of using convolutional neural networks instead of recurrent neural networks when forecasting with very few features and less amount of historical data.

Forecasting COVID-19 cases: A comparative analysis between Recurrent and Convolutional Neural Networks.

When the entire world is waiting restlessly for a safe and effective COVID-19 vaccine that could soon become a reality, numerous countries around the globe are grappling with unprecedented surges of new COVID-19 cases. As the number of new cases is skyrocketing, pandemic fatigue and public apathy towards different intervention strategies are posing new challenges to the government officials to combat the pandemic. Henceforth, it is indispensable for the government officials to understand the future dynamics of COVID-19 flawlessly in order to develop strategic preparedness and resilient response planning. In light of the above circumstances, probable future outbreak scenarios in Brazil, Russia and the United kingdom have been sketched in this study with the help of four deep learning models: long short term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) and multivariate convolutional neural network (MCNN). In our analysis, CNN algorithm has outperformed other deep learning models in terms of validation accuracy and forecasting consistency. It has been unearthed in our study that CNN can provide robust long term forecasting results in time series analysis due to its capability of essential features learning, distortion invariance and temporal dependence learning. However, the prediction accuracy of LSTM algorithm has been found to be poor as it tries to discover seasonality and periodic intervals from any time series dataset, which were absent in our studied countries. Our study has highlighted the promising validation of using convolutional neural networks instead of recurrent neural networks when it comes to forecasting with very few features and less amount of historical data.

Dengue epidemic in a non-endemic zone of Bangladesh: Clinical and laboratory profiles of patients.

BACKGROUNDS: Approximately, half of the population in the world including tropical and sub-tropical climates region is at risk of dengue. Being an endemic country, Bangladesh has experienced the largest dengue epidemic in 2019. The present study aimed at evaluating the clinical and laboratory profile of dengue patients in northern Bangladesh during the epidemic. METHODS: This cross-sectional study included 319 serologically confirmed dengue patients admitted in Shaheed Ziaur Rahman Medical College Hospital in Bogra district. It is one of the main tertiary care hospitals in northern Bangladesh. Data were collected from July to September 2019. Patients' clinical and laboratory data were extracted from clinical records. Patients were classified into two classes according to the WHO 2009 dengue classification such as (i) non-severe dengue and (ii) severe dengue. Chi-square test and independent t-test were used in this study. RESULTS: Of the 319 patients, 94.1% had non-severe dengue and the remaining 5.9% had severe dengue (severe plasma leakage 68.4%, severe organ involvement 68.4%, and severe clinical bleeding 10.5%). Most of the patients were suffering from primary dengue infection. The most common clinical presentation was fever followed by headache and myalgia. Vomiting and abdominal pain were the most prevalent warning signs. The common hematological findings on admission were leukopenia (63.3%), thrombocytopenia (30.4%) and increased hematocrit (26.6%). Raised serum ALT or AST was observed in 14.1% cases whereas raised serum creatinine was observed in 6.6% cases. Signs of plasma leakage (pleural effusion, respiratory distress, and ascites, rise of hematocrit >20% during hospital stay) and hepatic or renal involvement (serum ALT >42UI/L or serum creatinine >1.2 mg/dL) on admission were mostly associated with severe dengue. CONCLUSION: The study provides clinical evidence on presentation as well as hematological and biochemical profile of dengue patients in northern Bangladesh that should be implicated in effective patient management.

Sexual dysfunction in women with type 2 diabetes mellitus: A single-centre cross-sectional study from Bangladesh

ABSTRACT Objective: Sexual dysfunction among women with diabetes is a common but neglected health issue worldwide. The objective of the present study was to investigate the prevalence of sexual dysfunction and its associated factors among women with type 2 diabetes mellitus (T2DM). Subjects and methods: This cross-sectional comparative study comprises 150 women with diabetes and 100 healthy women without diabetes who visited the endocrinology outpatient department of Mymensingh Medical College Hospital (MMCH). The data were collected from July to December 2019. Sexual dysfunction was assessed by the 19-item Female Sexual Function Index (FSFI). Informed consent was obtained before participation. Collected data were analysed by SPSS 26. Results: More women with diabetes than control subjects reported sexual dysfunction (79% vs. 72%; p = 0.864). The global FSFI score was lower among the diabetes patients than among the healthy controls (20.8 ± 7.2 vs. 23.7 ± 4.8; p < 0.001). Patients with T2DM scored significantly lower in the domains of desire (p = 0.04), lubrication (p = 0.01), orgasm (p = 0.01), and satisfaction (p < 0.001), but not the domain of arousal (p = 0.09). A prolonged duration of diabetes was the primary contributor to orgasm problems (adjusted odds ratio, aOR 1.3, 95% CI 1.1-1.7) and painful intercourse (aOR 1.2, 95% CI 1.1-1.5). Conclusion: Sexual problems are frequent in women with diabetes. Inclusion of sexual health in comprehensive diabetes management is crucial to address this problem as well as to improve the quality of life of female diabetes patients.