Explore the vast range of titles available.

ObjectiveThis study aimed to determine the characteristics of acute poisoning patients.DesignThis was a prospective cohort study.SettingThe study was conducted for 1 year (1 July 2023 to 30 June 2024) at a tertiary care hospital in Sindh, Pakistan.ParticipantsFrom the patients who arrived at the emergency department due to poisoning, 1404 were registered and included in the study.Outcome measuresThe data were collected on demographics (gender, age, residential area, education, employment) and poisoning characteristics, prehospital care, treatment, and services at the hospital, and treatment outcomes (survived and died). A χ2 test was used to find the association between independent variables and treatment outcomes. A multivariate logistic regression model was used to determine the predictors of death at a 95% CI.ResultsThe majority of patients were male (57.1%) and aged ≤30 years (77.6%). The poisoning was primarily intentional (67.5%), and pesticides (56.1%) were commonly involved in the poisoning. The patients were managed mainly by symptomatic treatment (98.1%) and gastric lavage (65.1%). Multivariate logistic regression indicated that delayed reporting (adjusted OR (AOR)=2.00; 95% CI 1.20 to 3.36; p=0.008) and non-existence of antidote (AOR=1.81; 95% CI 1.08 to 3.03; p=0.025) increased the odds of death while unintentional poisoning (AOR=0.27; 95% CI 0.14 to 0.51; p<0.001) and prolonged stay at hospital had a protective effect (AOR=0.19; 95% CI 0.10 to 0.38; p<0.001).ConclusionThe study found that the intentional pesticide poisoning within uneducated, young populations in rural areas was significantly prevalent, and early identification and management of severe cases and extended hospital stays influenced survival.

This study aimed to explore knowledge, attitude, perceptions, and willingness regarding vaccination among university students in Pakistan. This cross-sectional study was carried out using an open online self-administered survey via Google Forms. The survey data were collected between the 15 to 30 of October 2022. A total of 946 respondents participated in the study, of which the majority were female (514, 54.3%). Most students belonged to a medical background, specifically pharmaceutical sciences. Most of the respondents did not know about monkeypox before 2022 (646, 68.3%). Regarding overall knowledge of monkeypox, most of the respondents had average knowledge (726, 76.7%), with very few having good knowledge (60, 6.3%). Regarding overall attitudes towards monkeypox, most of the respondents had neutral attitudes (648, 68.5%). There was a significant association between knowledge of Monkeypox with the type of academic degree (p < 0.001), type of discipline (p < 0.001), and region of respondents (p < 0.001). The willingness to vaccinate among the population was (67.7%). The current study pointed out that the overall knowledge of monkeypox was average in most respondents, with considerable knowledge gaps in most aspects. The overall attitude towards monkeypox was neutral. Further, the knowledge about monkeypox was strongly associated with academic degree, study discipline, and region of respondents. Our findings emphasize the need to raise public awareness by educating students on the monkeypox virus. This will improve adherence to preventative recommendations.

The COVID-19 pandemic has badly affected the world with its devastating effects, including Sindh, Pakistan. A massive vaccination campaign against COVID-19 is considered one of the effective ways to curtail the spread of the disease. However, the acceptability of the COVID-19 vaccine is based on the general population's knowledge, attitude, perception and willingness for vaccination. Therefore, a survey among the public in Sindh, Pakistan, was done to evaluate their knowledge, attitude, perception and willingness to accept COVID-19 vaccination. The online survey was conducted among the residents of Sindh, Pakistan, in July 2021 through a survey tool designed using Google Forms and sent to the population through various social media. Of 926 study participants, 59.0% were male, and 68.6% were aged between 18 and 31 years. Higher percentages of responses were recorded from the Hyderabad division (37.5%), and 60.0% of respondents were graduates, with 34.8% of them in the private sector. The results showed that 36.4% of respondents had good knowledge, and 30.3% had a positive attitude toward COVID-19 vaccination. Almost 77% of respondents perceived that everyone should get vaccinated in the country and those health care workers on priority. A majority (80.8%) of respondents were willing to accept COVID-19 vaccination. Despite having insufficient knowledge and a low percentage of positive attitude public in Sindh are willing to be vaccinated. Based on this finding, more effort has to be done to promote vaccination among the public, especially among the less educated population.

Snakebite envenoming remains a significant yet neglected public health problem in tropical countries, particularly in rural South Asia. This study aimed to identify demographic characteristics, management practices, and the determinants of poor treatment outcomes among snakebite patients in Sindh, Pakistan. A prospective cohort study was conducted at Peoples Medical College Hospital (PMCH), Shaheed Benazirabad, Sindh, Pakistan, from July 1, 2023, to June 30, 2024. A non-probability purposive sampling technique was used for data collection, and all consecutive patients presenting with confirmed or suspected snakebite were included. Data were collected through a validated study tool on demographics, pre-hospital management, hospital care, and treatment outcomes. Categorical variables were tested with the Chi-square test, and Kaplan-Meier survival analysis was used to test the effect of exposure-to-reporting time and hospital stay time on outcomes using IBM SPSS V29. A total of 320 patients were included; 74.7% were male, and 98.4% were from rural areas. Most victims were aged 20-29 years (31.9%) and engaged in farming or manual labor (67.2%). Nearly half (49.7%) of the bites occurred during summer. Delayed hospital presentation was common, with 22.8% arriving after six hours of the bite. The overall poor-outcome rate was 10.9%, and mortality was 1.9%. A significant association was found between exposure-to-reporting time ( = 0.040) and hospital stay duration ( < 0.001) with treatment outcomes. Delayed presentation to the hospital and prolonged hospitalization were major predictors of poor outcomes following snakebite. Strengthening emergency referral systems, ensuring timely antivenom availability, and promoting community awareness are essential to reduce morbidity and mortality in snakebite-endemic regions of Pakistan.

COVID-19 is the current topic of discussion globally as people are getting affected by it on a huge scale. This study is focused to determine the concerns and perceptions of healthcare workers (HCWs) due to the COVID-19 pandemic and its effect on their mental health, routine work, family and social life. Study was conducted at various health care facilities of Sindh, Pakistan, from October to December 2020 (three months). An online survey questionnaire consisting of fourteen closed-ended questions was designed in Google Forms and circulcalted among the HCWs through email and social media. The data collected was analyzed using SPSS 24 and descriptive statistical tools were used to measure the frequencies and the Chi-square test was applied among correlated variables. Among 412 respondents, majority of the participants were male (54.6%) and young with 18-28 years of age (47.3%). Two-third of HCWs were highly concerned about their family’s health versus own health (67.7% vs 44.7% respectively) and 157 (38.1%) were emotionally distressed. It was also found that HCWs with assigned duties in the isolation wards were more emotionally distressed (56.2% high to very high) compared to those not working in isolation units (45.3% high to very high). More than half of HCWs (51.9%) reported that their family life was also disturbed. Our findings indicate that COVID-19 pandemic has a significant psychological impact on frontline soldiers (HCWs) particularly they were worried about family’s health. The HCWs who were assigned duties in isolation units were more emotionally distressed than those who were not assigned duties in isolation wards.

Background and Objectives: Lipid-based self-nanoemulsifying drug delivery systems (SNEDDS) have resurged the eminence of nanoemulsions by modest adjustments and offer many valuable opportunities in drug delivery. Chlorpromazine, an antipsychotic agent with poor aqueous solubility—with extensive first-pass metabolism—can be a suitable candidate for the development of SNEDDS. The current study was designed to develop triglyceride-based SNEDDS of chlorpromazine to achieve improved solubility, stability, and oral bioavailability. Materials and Methods: Fifteen SNEDDS formulations of each short, medium, and long chain, triglycerides were synthesized and characterized to achieve optimized formulation. The optimized formulation was characterized for several in vitro and in vivo parameters. Results: Particle size, zeta potential, and drug loading of the optimized SNEDDS (LCT14) were found to be 178 ± 16, −21.4, and 85.5%, respectively. Long chain triglyceride (LCT14) showed a 1.5-fold increased elimination half-life (p < 0.01), up to 6-fold increased oral bioavailability, and 1.7-fold decreased plasma clearance rate (p < 0.01) compared to a drug suspension. Conclusion: The findings suggest that SNEDDS based on long-chain triglycerides (LCT14) formulations seem to be a promising alternative for improving the oral bioavailability of chlorpromazine.

The Burgers–Huxley equation is a nonlinear partial differential equation that incorporates convective, diffusive and reactive effects and arises in various reaction–diffusion and fluid flow models. In this paper, a numerical method based on the method of lines is proposed for its solution. The spatial derivatives are approximated using a third-order finite difference scheme, which converts the governing partial differential equation into a system of ordinary differential equations. The resulting semi-discrete system is solved in time using the classical fourth-order Runge–Kutta method. The stability and convergence properties of the proposed scheme are analyzed to establish its numerical reliability. Several numerical experiments are presented to illustrate the accuracy and efficiency of the method. The computed results confirm that the proposed approach provides accurate and stable solutions for the Burgers–Huxley equation.

A Pi-Sigma neural network (PSNN) is a kind of neural network architecture that blends the structure of conventional neural networks with the ideas of polynomial approximation. Training a PSNN requires modifying the weights and coefficients of the polynomial functions to reduce the error between the expected and actual outputs. It is a generalization of the conventional feedforward neural network and is especially helpful for function approximation applications. Eliminating superfluous connections from enormous networks is a well-liked and practical method of figuring out the right size for a neural network. We have acknowledged the benefit of L 2/3 regularization for sparse modeling. However, an oscillation phenomenon could result from L 2/3 regularization’s nonsmoothness. This study suggests a smoothing L 2/3 regularization method for a PSNN in order to make the models more sparse and help them learn more quickly. The new smoothing L 2/3 regularizer eliminates the oscillation. Additionally, it enables us to show the PSNN’s weak and strong convergence findings. In order to guarantee convergence, we also link the learning rate parameter and the penalty parameter. Results of the simulation are provided. We present the simulation results, which demonstrate that the smoothing L 2/3 regularization performs significantly better than the original L 2/3 regularization, thereby supporting the theoretical conclusions are offered as well.

This study presents an extended cubic B-spline Galerkin scheme for the numerical solution of multi-term time-fractional differential equations. The proposed formulation employs extended cubic B-splines together with the Caputo fractional derivative to model the time-fractional operators. Gauss quadrature is used to accurately evaluate the resulting integral. A stability analysis of the scheme is provided and its accuracy is assessed through L2 and L∞ error norms over different spatial nodes and mesh refinements. The numerical results demonstrate excellent agreement with the exact solutions, as illustrated in the tables and figures. These findings confirm the robustness, efficiency and reliability of the proposed method for solving multi-term time-fractional differential equations.

A Pi-Sigma neural network (PSNN) is a kind of neural network architecture that blends the structure of conventional neural networks with the ideas of polynomial approximation. Training a PSNN requires modifying the weights and coefficients of the polynomial functions to reduce the error between the expected and actual outputs. It is a generalization of the conventional feedforward neural network and is especially helpful for function approximation applications. Eliminating superfluous connections from enormous networks is a well-liked and practical method of figuring out the right size for a neural network. We have acknowledged the benefit of L regularization for sparse modeling. However, an oscillation phenomenon could result from L regularization's nonsmoothness. This study suggests a smoothing L regularization method for a PSNN in order to make the models more sparse and help them learn more quickly. The new smoothing L regularizer eliminates the oscillation. Additionally, it enables us to show the PSNN's weak and strong convergence findings. In order to guarantee convergence, we also link the learning rate parameter and the penalty parameter. Results of the simulation are provided. We present the simulation results, which demonstrate that the smoothing L regularization performs significantly better than the original L regularization, thereby supporting the theoretical conclusions are offered as well.