ABSTRACT: Background: Cardiovascular disease remains a leading cause of global morbidity and mortality, and long-term secondary prevention is often limited by poor adherence, pill burden, treatment costs, and health system barriers. Fixed-dose combination polypills may simplify treatment by combining multiple cardiovascular medicines into a single formulation, thereby improving adherence and reducing recurrent cardiovascular events.
Objective: This systematic review evaluated the cost-effectiveness of fixed-dose combination polypills compared with usual care, standard therapy, or separate monocomponents for secondary cardiovascular disease prevention across different healthcare and income settings.
Methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. PubMed, Dimensions AI, ScienceDirect, and the Tufts Cost-Effectiveness Analysis Registry were searched for studies published between January 2015 and December 2025. Eligible studies included economic evaluations involving adults with established cardiovascular disease and reporting incremental cost-effectiveness ratios, cost per quality-adjusted life year, cost per disability-adjusted life year, cost savings, or related economic outcomes. Reporting quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards checklist.
Results: Fourteen records were included, comprising 13 full or partial economic evaluations and one Delphi consensus study with policy-relevant contextual interpretation. Most studies were conducted in high-income countries, particularly Spain, while evidence from low- and middle-income countries was limited. Fixed-dose combination polypills were generally reported as cost-effective or cost-saving, mainly driven by improved medication adherence, reduced pill burden, and prevention of recurrent cardiovascular events. Findings were also influenced by methodological factors such as analytic perspective and time horizon adopted across studies.
Conclusion: Fixed-dose combination polypills may offer economic value for secondary cardiovascular disease prevention, but broader implementation should be guided by local cost-effectiveness, affordability, budget impact, and real-world evidence, especially in low- and middle-income countries.

ABSTRACT: Introduction: Heart failure is a chronic condition that can negatively affect patients’ self-efficacy and lead to disease-related complications. Limited health literacy may hinder patients’ ability to effectively manage their condition and maintain self-efficacy. This study aimed to investigate the association between health literacy and self-efficacy among patients with heart failure.
Methods: This cross-sectional study was conducted among 193 patients with heart failure who were referred to two hospitals in Fars Province, Iran, in 2023. Participants were selected using convenience sampling. Data were collected using the Cardiac Self-Efficacy Questionnaire developed by Sullivan et al. (1998) and a heart failure-specific health literacy scale. Descriptive statistics, Pearson’s correlation coefficient, and multiple linear regression analyses were performed using SPSS version 21.
Results: Overall, 63.7% of participants demonstrated high levels of self-efficacy. Among the dimensions of health literacy, functional health literacy had the highest mean score (8.33 ± 3.67), whereas critical health literacy had the lowest mean score (4.21 ± 3.91). Health literacy was positively associated with self-efficacy (r = 0.27, p < 0.001). Multiple linear regression analysis indicated that age was a significant negative predictor of self-efficacy (β = -0.134, p = 0.001).
Conclusions: Health literacy was significantly associated with self-efficacy among patients with heart failure. Interventions aimed at improving health literacy, particularly critical health literacy skills, may enhance patients’ self-efficacy and support better disease self-management.

ABSTRACT: Congenital malformations of the gastrointestinal tract are a leading cause of neonatal surgical mortality and long-term disability, and outcomes remain markedly worse in low- and middle-income settings than in high-income countries, in part because of fragmented postoperative follow-up. We conducted a combined retrospective-prospective cohort study in the Samarkand region of Uzbekistan (2021–2024) to characterize the epidemiology and risk-factor profile of congenital gastrointestinal malformations and to evaluate a purpose-built, multistage, multidisciplinary rehabilitation program for infants after corrective surgery. Of 283 surgically treated neonates, 163 received the structured rehabilitation program (surgical, nutritional, physiotherapeutic, psychosocial and telemedicine components) and 120 received standard postoperative care. The rehabilitation program was associated with a shorter hospital stay (20.8 ± 3.2 vs 28.1 ± 3.5 days, p<0.001), a lower rate of postoperative complications (9.8% vs 25.7%, p<0.01), fewer unplanned readmissions at 6 months (11.0% vs 31.5%, p<0.01), and greater weight gain and serum protein/albumin recovery at 6 months (all p<0.01). Composite gastrointestinal functional recovery at 6 months was achieved in 90.2% of the program group versus 64.1% of the comparison group (p<0.001). Parental anxiety (State-Trait Anxiety Inventory) fell further in the program group (48.2±6.1 to 34.5±4.8) than in controls (47.8±6.3 to 42.9±5.2, p<0.001), and confidence in caregiving (visual analogue scale) improved correspondingly. A multivariable model incorporating birth weight, number of malformations and timing of nutritional rehabilitation predicted adverse outcome with 87.4% accuracy. These findings support multistage, family-centered, telemedicine-enabled rehabilitation as an effective and scalable strategy for improving postoperative outcomes after neonatal gastrointestinal surgery, particularly in resource-constrained regional health systems.

ABSTRACT: Background: Social media use among young people has risen sharply, and concern about its relationship to mental health is widespread. The evidence base remains heterogeneous in effect size, measurement, and design.
Objective: To estimate the association between social media use and depressive and anxiety symptoms among adolescents and young adults, and to test whether the two differ.
Methods: Four databases were searched from January 2010 to April 2021. Eligible studies reported a quantitative association between a social media exposure and a validated depression or anxiety measure. Stress subscales were not treated as anxiety outcomes. Effect sizes were pooled as Pearson correlations using random-effects models.
Results: The pooled association with depressive symptoms was r = 0.263 (95% CI: 0.200-0.324; k = 10; N = 5,774; I² = 83.9%), prediction interval 0.031-0.468. For anxiety it was r = 0.363 (95% CI: 0.265-0.453; k = 7; N = 5,286; I² = 93.3%), prediction interval −0.009-0.646. A paired comparison across the five samples contributing to both outcomes found no difference (p = .77). Mean sample age predicted the depression association (b = 0.045 per year; p = .023) and accounted for almost all heterogeneity. Restricting to samples with mean age below 19 reduced the depression estimate to r = 0.196.
Conclusions: Social media use is positively associated with depressive and anxiety symptoms, at a small-to-moderate magnitude and with no detectable difference between outcomes. The anxiety prediction interval includes zero, and the association is weaker in adolescent samples. The cross-sectional evidence precludes causal inference.
Keywords: Social Media; Depression; Anxiety; Adolescents; Young Adults; Meta-Analysis; Internalizing Symptoms

ABSTRACT: Background: Preimplantation genetic testing (PGT) enables genetic assessment of embryos generated through in vitro fertilization before embryo transfer. Its applications include testing for chromosomal aneuploidy and monogenic disorders, with potential utility in reducing transmission of serious inherited conditions. Experience with PGT remains relatively underreported in sub-Saharan Africa.
Objective: To describe three successful applications of PGT for differing reproductive indications at a Nigerian fertility centre.
Methods: This descriptive case series reports three couples who underwent in vitro fertilization with PGT at a Kingswill Specialist Hospital, Lagos. Clinical and reproductive information was obtained from medical records. The indications comprised family balancing, a family history of oculocutaneous albinism, and prevention of sickle cell disease. Relevant PGT approaches were incorporated into assisted conception treatment before embryo transfer. Pregnancy and neonatal outcomes were documented.
Results: The first case involved a 39-year-old para 4 woman with four daughters who sought assisted conception with PGT and subsequently delivered twin boys following embryo transfer. The second couple had significant family histories of oculocutaneous albinism and underwent PGT for a monogenic disorder, resulting in the birth of a phenotypically unaffected female infant. In the third case, both partners had HbAS genotypes and had previously had two children with sickle cell disease (HbSS). Following PGT for a monogenic disorder, an unaffected embryo was transferred, resulting in the birth of a male infant with an HbAA genotype.
Conclusion: These cases illustrate the diverse potential applications of PGT in an African assisted-reproduction setting.

ABSTRACT: Background: Antimicrobial resistance (AMR) surveillance is essential for estimating resistance burden and guiding public-health responses, yet coverage remains uneven across geographic regions, populations, healthcare settings, and One Health domains. Low observed resistance may therefore reflect limited detection and reporting rather than genuinely low resistance.
Objectives: To map the nature and determinants of AMR under-surveillance, examine computational approaches for identifying surveillance blind spots, and develop an evidence-informed framework for AI-enabled detection of hidden AMR surveillance gaps.
Methods: PubMed and Dimensions were systematically searched for literature published from 2015–2026. Eligible studies addressed AMR surveillance coverage, capacity, representativeness, completeness, or computational approaches relevant to surveillance gaps. Study selection and synthesis followed JBI scoping-review methodology and PRISMA-ScR guidance.
Results: Twenty-two studies were included. Under-surveillance encompassed geographic and population underrepresentation, diagnostic and laboratory limitations, fragmented information systems, delayed reporting, weak genomic coverage, and incomplete One Health integration. Computational approaches included spatial and statistical modelling, machine learning, geographic information systems, genomic analytics, digital laboratory systems, and environmental surveillance. These approaches could identify or partially address surveillance incompleteness but remained constrained by data quality and representativeness. The synthesis informed a framework for detecting discordance between expected AMR risk and observed surveillance intensity.
Conclusions: AMR under-surveillance is a systems-level problem that can distort the apparent distribution of resistance. AI should complement microbiological surveillance by identifying uncertainty and prioritizing settings requiring strengthened surveillance.