The growing use of quantified self-technologies (QST) in chronic disease management is linked to better self-monitoring and patient engagement. However, little is known about how patients in resource-constrained settings fund and sustain the use of QST in diabetes self-management. This study asked: "How do patients with diabetes perceive and experience the economic burden of using QST in Zimbabwe?" Using a qualitative design, 20 patients with diabetes participated in semi-structured interviews. The reflexive thematic analysis of Braun and Clarke generated three interrelated themes: technology investment costs, conventional healthcare costs, and socio-economic constraints. The findings show that the economic experience of QST adoption is context-dependent and is shaped by the financial realities of patients with diabetes and their access to technology. By focusing on patient-level cost experiences, the study adds qualitative evidence to public health debates on digital health affordability and highlights the need to assess perceived financial implications within a third-world socio-economic context. It is concluded that, although QST is available in third-world countries, sustained use depends on the financial capacity of patients with diabetes.

Hemoglobin A1c is a central biomarker for long-term glycemic control and a key predictor of diabetes-related complications. The COVID-19 pandemic disrupted routine healthcare delivery and introduced potential metabolic effects of SARS-CoV-2 infection, yet the long-term impact of COVID-19 on glycemic trajectories in individuals with diabetes remains unclear. In this retrospective study, we leveraged harmonized electronic health record data from the National Clinical Cohort Collaborative to evaluate changes in HbA1c before and after documented SARS-CoV-2 infection in adults with diabetes (n = 93,320). Patients were required to have repeated HbA1c measurements pre- and post-infection and stable exposure to key antihyperglycemic medications. A paired statistical analysis was used to identify individuals with statistically significant post-infection changes in HbA1c. We then developed and evaluated multiple supervised machine learning classifiers using an 80/20 train-test split and cross-validation to assess demographic, clinical, and structural factors associated with significant glycemic change. Most patients (71%) did not experience a statistically significant change in average HbA1c following COVID-19 infection, and among those who did, decreases were more common than increases. A random forest classifier achieved the best overall performance, and feature importance and SHAP analyses highlighted body mass index, insulin use, age, and socioeconomic proxies as key contributors. These findings suggest that while COVID-19 infection does not substantially alter long-term glycemic control for most patients with diabetes, individual-level clinical and structural factors influence post-infection glycemic variability.

This study explores experiences of spending time in immersive virtual reality with a natural environment among individuals with type 2 diabetes, aiming to enhance perceived wellbeing and reduce perceived stress. Seventeen participants with type 2 diabetes took part in a multimodal lifestyle education program and used immersive virtual reality with natural environment over a six-month period, selecting from a number of 30 min serene natural environments. Semi-structured interviews were conducted and analyzed using qualitative content analysis. Participants described immersive virtual reality with a natural environment experience as providing tranquility, inspiration, and a sense of transcending time and space (A). Feelings of calm and mental withdrawal from everyday demands were often reported (A2), and memories were evoked (A2). Some participants experienced these effects as extending beyond the immersive virtual reality with natural environment sessions themselves (A3-4). At the same time, several factors were identified that could disrupt the restorative experience (A5), including technical issues, individual preferences for specific environments, health- or situation-related constraints, and difficulties establishing a regular routine for headset use. Immersive virtual reality with natural environment was generally viewed as a valuable complement to real-world nature experiences, particularly for individuals with limited access to outdoor environments (B1-2). Overall, the findings suggest that immersive virtual reality with natural environment experiences may offer a supportive resource for enhancing emotional wellbeing and managing stress in people with type 2 diabetes, while not replacing the benefits of actual nature exposure.

The prevalence of chronic conditions such as hypertension, diabetes, and Human Immunodeficiency Virus (HIV) is rising globally, yet access to continuous care remains limited, particularly in rural low- and middle-income countries. This study evaluated the acceptability and psychosocial predictors of retention in a linkage-to-care (LTC) intervention for patients with chronic conditions in rural South Africa. We conducted a cross-sectional analytical study with a retrospective cohort component among 1673 patients diagnosed with hypertension, diabetes, and/or HIV in Limpopo Province, South Africa. Acceptability and psychosocial factors were assessed cross-sectionally using a theory-informed, interviewer-administered questionnaire between January and June 2024. Retention in care over the preceding six months (July-December 2023) was extracted from routine clinic records and classified as consistent (no gaps > 6 months between visits) or inconsistent (≥1 gap > 6 months. Logistic regression examined associations between psychosocial factors and retention outcomes, adjusting for age, gender, marital status, and diagnostic category. Overall, 25.1% of participants maintained consistent retention over six months, while 74.9% were retained inconsistently. Acceptability of the LTC intervention varied significantly by diagnosis (p < 0.001): 79.5% of participants with multimorbidity rated the intervention as acceptable compared to 54.9% with hypertension, 64.5% with diabetes, and 46.8% with HIV. However, only 12.8% of multimorbid participants agreed that intervention activities fit well with their daily lives. In adjusted analyses, participants who were not happy to participate had 85% lower odds of consistent retention (adjusted odds ratio [AOR] = 0.15, 95% CI: 0.09-0.22) and 7.2 times higher odds of inconsistent retention (AOR = 7.2, 95% CI: 4.8-10.9). Most participants supported de-identified data sharing, though privacy concerns were elevated among those with multimorbidity. Acceptability of LTC interventions differs by diagnosis, with multimorbid patients reporting poorer alignment with daily routines. Retention is strongly associated with emotional engagement and self-efficacy, suggesting that LTC interventions should integrate psychosocial support and be contextually adapted for multimorbid patients in rural settings.

The COVID-19 pandemic has had a profound impact on global health, especially among patients with cardiovascular disease (CVD) and the existence of additional conditions such as diabetes (DM), hypertension (HT), and chronic kidney disease (CKD) can have a significant impact on survival rates. The aim of this study was to determine the mortality rate in patients with CVD and the impact of other comorbidities on the death of patients with COVID-19. This systematic review was conducted using PubMed, EMBASE, and Google Scholar databases from August 2020 to June 2025. Inclusion criteria were patients with cardiovascular disease and associated comorbidities during the COVID-19 pandemic. Article selection was limited to articles published in English and Polish. Statistical analysis using a random-effects model was performed using STATA software. Heterogeneity between studies was examined, and a funnel plot for publication bias was generated. The higher mortality rates (OR = 3.00, 95% CI: 2.06-4.38) for patients with cardiovascular disease were observed. In the group of patients with comorbidities such as hypertension and diabetes mellitus the risk of death was also determined and for HT was OR = 1.94, 95% CI, 1.50-2.52 and for DM OR = 2.17, 95% CI: 1.64-2.86. The mortality in the chronic kidney disease group was higher than for HT and DM (OR = 3.91, 95% CI: 2.50-6.10). The risk of death is three times higher for patients with COVID-19 and CVD. High mortality risk is also linked to diabetes and hypertension but for chronic kidney disease patients increased up to four times.

Preeclampsia is a pregnancy-specific multisystem disorder and a major cause of maternal and perinatal morbidity and mortality worldwide. This narrative review summarizes current evidence on the principal risk factors and pathophysiological mechanisms involved in its development. The disease is best explained by the two-stage model: in stage 1, inadequate trophoblast invasion and incomplete spiral artery remodeling lead to placental hypoperfusion, hypoxia, and oxidative stress; in stage 2, the hypoxic placenta releases anti-angiogenic and pro-inflammatory factors, including soluble fms-like tyrosine kinase-1 (sFlt-1) and soluble endoglin (sEng), which trigger systemic endothelial dysfunction and the maternal clinical syndrome. The review highlights the central role of angiogenic imbalance, immune dysregulation, and chronic inflammation in disease progression. Particular emphasis is placed on maternal risk factors such as primiparity, advanced maternal age, obesity, diabetes mellitus, chronic hypertension, multiple pregnancy, prior preeclampsia, genetic susceptibility, and epigenetic regulation. We also emphasize the contribution of microRNAs in relation to placental hypoxia, trophoblast invasion, angiogenesis, endothelial injury and microchimerism to the development of preeclampsia. The review also examines the role of T helper 1 (Th1)/Th2/Th17/regulatory T cells (Treg) imbalance and uterine natural killer cell dysfunction at the maternal-fetal interface. Improved understanding of these interconnected mechanisms may support earlier diagnosis, better risk stratification, and the development of targeted preventive and therapeutic strategies.

This prospective study evaluated first-trimester markers in pregnancies with isolated and combined forms of fetal growth disorders and gestational diabetes mellitus (GDM). Among 1869 screened women, the analysis included 83 controls, 55 GDM, 22 isolated intrauterine growth restriction (iIUGR), and 33 isolated large-for-gestational-age (iLGA) cases, with GDM subgroups stratified by fetal growth (GDM with normal fetal weight, GDM + IUGR, and GDM + LGA). First-trimester clinical and routine biochemical parameters were recorded, and serum concentrations of 80 proteins were measured using targeted LC-MRM-MS proteomics. Different trajectories emerged: IUGR phenotypes showed low PAPP-A/PlGF and high TSH (p < 0.01), indicating early placental insufficiency, while macrosomia showed opposite trends. GDM + IUGR represented the most severe "double hit" phenotype (lowest PlGF, earliest delivery), whereas GDM + LGA showed increased umbilical artery resistance despite excessive growth, suggesting endothelial dysfunction. Targeted proteomics revealed characteristic signatures: iIUGR featured low complement (C4A|C4B) and IGF proteins (IGFALS, IGFBP3) versus GDM and iLGA (p < 0.001); GDM + IUGR showed elevated PZP and CD5L versus iIUGR (p < 0.05); GDM + LGA was marked by high C4BPA and low RBP4, SERPINA7 versus iLGA (p < 0.05). Complement and IGF pathways were consistently implicated. Machine learning achieved 77% sensitivity for IUGR prediction using clinical parameters and 88% sensitivity for LGA prediction using proteomic data. These findings demonstrate that fetal growth disorders represent pathophysiologically unique entities detectable in the first trimester, enabling early risk stratification and personalized management.

Diabetes mellitus is a chronic and increasingly prevalent metabolic disorder characterized by persistent hyperglycemia, resulting from defects in insulin secretion, insulin action, or both. Despite the availability of pharmacological agents that effectively manage blood glucose levels, many are associated with adverse effects, limited efficacy over time, and high costs. Consequently, there is growing interest in alternative therapies, especially those derived from traditional medicinal plants, that have long been employed in various cultures for managing diabetes. Recent advances in phytochemistry have identified bioactive plant secondary metabolites with promising antidiabetic properties. This review aims to provide a comprehensive overview of plant-derived compounds that exhibit inhibitory activity against key diabetes-related enzymes, including α-glucosidase, α-amylase, protein tyrosine phosphatase 1B (PTP1B) and dipeptidyl peptidase-4 (DPP-4). These enzymes play critical roles in glucose metabolism and insulin signaling pathways. The review highlights the structural diversity of these natural inhibitors, their mechanisms of action, and their effectiveness in preclinical models. Understanding the molecular interactions and pharmacological profiles of these metabolites may facilitate the development of safer and more effective antidiabetic agents.

Background and Objectives: There is limited evidence supporting the incorporation of dietary patterns into heart failure (HF) management. The Dietary Approaches to Stop Hypertension (DASH) diet is linked to cardiovascular disease prevention, but evidence correlating DASH adherence to HF risk is sparse. This study is the first prospective investigation into the relationship between the DASH diet, incident HF and its associated risk factors-hypertension and diabetes mellitus (DM)-in Australian women. Materials and Methods: Survey data (2001-2022) from the Australian Longitudinal Study on Women's Health (ALSWH) was analysed, where DASH diet scores were calculated from food frequency questionnaire (FFQ) responses and categorised into quintiles. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between DASH adherence and incident HF. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% CIs for secondary endpoints, hypertension and DM, and dietary exposure was modelled as a time-varying covariate. Results: 10 594 women (mean age 52.5 ± 1.45 years) participated and, at 21-year follow-up, there were 136 (1.3%) cases of HF, 2182 (20.6%) and 994 (5.7%) cases of hypertension and DM, respectively. After adjustment for covariates (including age and socioeconomic factors), no association was found between the highest DASH quintile and incident HF [OR 0.73, 95% CI: 0.37-1.43; p = 0.20]. However, adjusted HRs for hypertension and DM-0.73 (95% CI: 0.63-0.84; p < 0.001) and 0.65 (95% CI: 0.53-0.81; p < 0.001), respectively-indicated significant associations. Conclusions: In Australian women, DASH diet adherence was associated with a significantly lower risk of hypertension and DM, both of which are HF risk factors. The finding of no direct statistically significant association between the DASH diet and incident HF might reflect the small incidence of HF in our cohort.

Background and Objectives: This study aimed to evaluate the impact of body mass index (BMI) on post- operative outcomes in patients undergoing aortic arch repair with the frozen elephant trunk technique (FET). Materials and Methods: A total of 387 patients who underwent an FET procedure between 04/2014 and 11/2024 were retrospectively analyzed. Patients were divided into four groups according to BMI: underweight (BMI < 18.5, n = 12) normal weight (BMI: 18.5 to <25, n = 150), overweight (BMI: 25 to <30, n = 154), and obese (BMI: ≥30, n = 71). Patient characteristics and clinical outcomes were compared across groups. Multivariable Cox regression, interaction analysis, and restricted cubic spline modelling were performed using R (Version 4.4.3). Results: Interaction analysis revealed BMI-dependent effect modification for several predictors. Insulin-dependent diabetes mellitus was associated with increased mortality only in patients with BMI < 25 kg/m² (interaction p = 0.003). Transfusion of packed red blood cells (PRBCs) also showed a significant interaction with BMI (p = 0.016), with a stronger effect in patients with BMI < 25 kg/m², although significant in both strata. Moreover, cross-clamp time demonstrated a BMI-dependent interaction (p = 0.047), with numerically higher mortality hazards in overweight patients (BMI > 25 kg/m²), but without statistically significant subgroup effects. Spline analysis indicated a non-linear, threshold-based association between overall mortality and BMI but does not reach statistical significance. Kaplan-Meier analysis showed no significant difference in 5-year survival among BMI categories. Conclusions: BMI should not be used as a primary risk stratification tool for survival after an FET procedure. Rather, attention should be paid to comorbid conditions and intraoperative factors that interact with BMI. For patients with lower BMI (<25 kg/m²), optimizing glycemic control and minimizing transfusion may improve outcomes. Data suggests that a reduction in cross-clamp time may be particularly beneficial in patients with higher BMI (>25 kg/m²). Future studies should aim to clarify the impact of BMI on outcomes after FET, particularly in the context of patient selection and perioperative optimization strategies.