Explore the vast range of titles available.

AimsIndividuals with epilepsy are at risk of developing pre-ictal, ictal, postictal or interictal psychoses. Antipsychotic drugs (APDs) are the main class of drugs used to treat psychosis and schizophrenia. The efficacy and safety of APDs as a treatment for epileptic psychosis is not well understood. Hence, we aimed to conduct a systematic review assessing the effectiveness and adverse effects of antipsychotic drugs to treat psychosis in people with epilepsy.MethodsWe adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched MEDLINE, Embase, PsycInfo and AMED from database inception to 20/06/2023. We contacted experts in the field and performed citation searches to identify additional records. Title, abstract, full-text review, and data analysis were conducted in duplicate, with conflicts resolved by discussion among authors. Given the heterogeneity of study designs, meta-analysis was not deemed appropriate; instead, the results were tabulated in a narrative synthesis. The Joanna Briggs Institute Risk of Bias tool was used to assess study quality.ResultsWe identified 13 studies, with a total of 1,180 participants. In the 9 case series included, the psychotic symptoms of all but 3 out of 28 patients treated with APDs partially improved or fully resolved. 3 of the cohort studies reported an association between antipsychotic use and longer duration of psychotic episodes, 2 found similar results in both APD and non-APD groups, and 2 did not report control psychosis outcomes. When reported, seizure frequency was observed to remain unchanged or decrease following APD treatment.ConclusionAvailable evidence does not suggest that antipsychotics increase seizure risk in individuals with epilepsy. However, further data from randomised controlled trials and well-controlled cohort studies are urgently needed to draw more definitive conclusions.

Adherence to antihypertensives is crucial for control of blood pressure. This study analyzed factors and interventions that could affect adherence to antihypertensives in the US. PubMed, Scopus, Web of Science, and Embase were searched on January 21, 2022 and December 25, 2023 for studies on the adherence to antihypertensives in the US. Nineteen studies and 23 545 747 patients were included in the analysis, which showed that adherence to antihypertensives was the highest among Whites (OR: 1.47, 95% CI 1.34–1.61 compared to African Americans). Employment status and sex were associated with insignificant differences in adherence rates. In contrast, marital status yielded a significant difference where unmarried patients demonstrated low adherence rates compared to married ones (OR: 0.8, 95% CI 0.67–0.95). On analysis of comorbidities, diabetic patients reported lower adherence to antihypertensives (OR: 0.95, 95% CI 0.92–0.97); furthermore, patients who did not have Alzheimer showed higher adherence rates. Different BMIs did not significantly affect the adherence rates. Patients without insurance reported significantly lower adherence rates than insured patients (OR: 3.93, 95% CI 3.43–4.51). Polypill users had higher adherence rates compared with the free‐dose combination (OR: 1.21, 95% CI 1.2–1.21), while telepharmacy did not prove to be as effective. Lower adherence rates were seen among African Americans, uninsured, or younger patients. Accordingly, interventions such as fixed‐dose combinations should be targeted at susceptible groups. Obesity and overweight did not affect the adherence to antihypertensives.

Background and AimLow serum Vitamin D levels have been associated with diabetic nephropathy (DN). Our study aimed to analyse the serum levels of vitamin D in patients suffering from DN and the subsequent changes in serum vitamin D levels as the disease progresses.MethodsPubMed, Embase, SCOPUS and Web of Science were searched using keywords such as ‘25 hydroxyvitamin D’ and ‘diabetic nephropathy’. We included observational studies that reported the association between the serum 25 hydroxy vitamin D levels and diabetic nephropathy without restriction to age, gender, and location. R Version 4.1.2 was used to perform the meta-analysis. The continuous outcomes were represented as mean difference (MD) and standard deviation (SD) and dichotomous outcomes as risk ratios (RR) with their 95% confidence interval (CI).ResultsTwenty-three studies were included in our analysis with 7722 patients. Our analysis revealed that vitamin D was significantly lower in diabetic patients with nephropathy than those without nephropathy (MD: −4.32, 95% CI: 7.91–0.74, p-value = .0228). On comparing diabetic patients suffering from normoalbuminuria, microalbuminuria, or macroalbuminuria, we found a significant difference in serum vitamin D levels across different groups. Normoalbuminuria versus microalbuminuria showed a MD of −1.69 (95% CI: −2.28 to −1.10, p-value = .0002), while microalbuminuria versus macroalbuminuria showed a MD of (3.75, 95% CI: 1.43–6.06, p-value = .0058), proving that serum vitamin D levels keep declining as the disease progresses. Notwithstanding, we detected an insignificant association between Grade 4 and Grade 5 DN (MD: 2.29, 95% CI: −2.69–7.28, p-value = .1862).ConclusionSerum Vitamin D levels are lower among DN patients and keep declining as the disease progresses, suggesting its potential benefit as a prognostic marker. However, on reaching the macroalbuminuria stage (Grades 4 and 5), vitamin D is no longer a discriminating factor.

Non-adherence is a barrier to the control of hypertension. This study aimed to analyze the factors and interventions affecting adherence rates in the US. PubMed, Scopus, Web of Science, and Embase were searched on January 21 st, 2022 for studies on the adherence to anti-hypertensives in the US. R software (4.2.1) and RevMan (5.4) were used for the analysis. Our analysis showed that non-adherence to antihypertensives was higher in Hispanics compared with Blacks (OR= 1.25, p-value= 0.0335) with further analysis showing lower non-adherence rates among Whites compared with Blacks (OR= 0.63, p-value= 0.0049). Younger individuals had higher non-adherence rates (53%) compared with individuals older than 60 (46%), however, no statistically significant difference was detected between both groups. Unemployment was associated with decreased adherence (OR= 0.40, p-value< 0.00001), while gender and marital status yielded insignificant associations. Patients who suffered from multiple comorbidities (OR= 0.43, p-value= 0.004), depression (OR= 0.65, p-value <0.00001), and poor mental health (OR= 0.38, p-value< 0.00001) had lower adherence rates. Heavy alcohol consumption was associated with a decline in adherence, conversely, obesity didn't significantly affect the adherence rates. Regarding interventions, Fixed-dose combination had lower non-adherence rates compared with the control group (OR= 0.83, p-value= 0.0029), while telepharmacy didn't prove to be as effective. Lastly, exercise was associated with higher adherence (OR= 3.08, p-value< 0.00001). Race and unemployment play a role in adherence to anti-hypertensives. Patients who suffer from depression, multiple comorbidities, and heavy alcohol intake had lower adherence rates. Accordingly, interventions such as fixed-dose combinations and exercise should be targeted at susceptible groups.

This study examines the use of large language models (LLMs) by undergraduate and graduate students for programming assignments in advanced computing classes. Unlike existing research, which primarily focuses on introductory classes and lacks in-depth analysis of actual student-LLM interactions, our work fills this gap. We conducted a comprehensive analysis involving 411 students from a Distributed Systems class at an Indian university, where they completed three programming assignments and shared their experiences through Google Form surveys. Our findings reveal that students leveraged LLMs for a variety of tasks, including code generation, debugging, conceptual inquiries, and test case creation. They employed a spectrum of prompting strategies, ranging from basic contextual prompts to advanced techniques like chain-of-thought prompting and iterative refinement. While students generally viewed LLMs as beneficial for enhancing productivity and learning, we noted a concerning trend of over-reliance, with many students submitting entire assignment descriptions to obtain complete solutions. Given the increasing use of LLMs in the software industry, our study highlights the need to update undergraduate curricula to include training on effective prompting strategies and to raise awareness about the benefits and potential drawbacks of LLM usage in academic settings.