This study aimed to determine the prevalence and predictors of depression and anxiety among emergency medical services personnel at the Liaquat University of Medical & Health Sciences (LUMHS). The study was conducted over the course of one year, from December 2021 to December 2022, and involved a sample size of 120 participants. The study used a cross-sectional design, and data was collected using a self-administered questionnaire that assessed depression and anxiety symptoms, as well as demographic and job-related factors. The questionnaire was distributed to all emergency medical services personnel working in LUMHS, and participation in the study was voluntary. Data collected was analyzed using descriptive statistics to determine the prevalence of depression and anxiety among emergency medical services personnel in LUMHS. Logistic regression analysis was used to identify predictors of depression and anxiety, including demographic and job-related factors such as age, gender, years of service, and job stressors. The results showed that the prevalence of depression and anxiety among emergency medical services personnel in LUMHS was 45% and 50%, respectively. Logistic regression analysis revealed that older age, female gender, long years of service, and higher job stressors were significant predictors of depression and anxiety. These findings provided valuable information about the mental health status of emergency medical services personnel in LUMHS, highlighting the need for interventions and support services to address the high prevalence of depression and anxiety in this population. The study contributed to the growing body of research on mental health in the workplace, particularly in high-stress occupations such as emergency medical services and underscored the importance of addressing the mental health needs of this vulnerable population.

This retrospective cohort study aimed to investigate the impact of maternal cardiac diseases on fetal outcomes at the Liaquat University of Medical & Health Sciences (LUMHS). The study was conducted over one year, from December 2018 to December 2019, and involved a sample size of 120 participants. The study utilized medical records of pregnant women with cardiac diseases who delivered at LUMHS over the past 5 years. The data collected included maternal demographic and medical history, fetal and neonatal outcomes, and other relevant medical information. Descriptive statistics were used to analyze the data and determine the prevalence of maternal cardiac diseases and their impact on fetal outcomes. Logistic regression analysis was used to identify risk factors associated with adverse fetal outcomes, such as preterm birth, low birth weight, stillbirth, and congenital anomalies. The results showed that 20% of pregnant women had cardiac disease, with rheumatic heart disease being the most common. Women with cardiac diseases were found to be at higher risk for adverse fetal outcomes, including preterm birth, low birth weight, stillbirth, and congenital anomalies. Logistic regression analysis revealed that maternal age, parity, and type of cardiac disease were significant predictors of adverse fetal outcomes. These findings emphasize the importance of early identification and managing maternal cardiac diseases to prevent adverse fetal outcomes. The study contributes to growing maternal and fetal health research, particularly in high-risk populations such as pregnant women with cardiac diseases. It underscores the need for multidisciplinary management involving obstetricians, cardiologists, and neonatologists to optimize maternal and fetal outcomes in this population.

No abstract

No abstract

No abstract