Out-of-pocket payments by patients with chronic diseases can result in catastrophic expenditures. This study examines how chronic disease burden, measured by the presence of any chronic condition such as diabetes, cancer, chronic lung disease, heart attack, stroke and high blood pressure and the number of chronic conditions are associated with the likelihood of catastrophic out-of-pocket payments among older adults in 11 European Union (EU) countries.

The 2017 wave of the SHARE (Survey of Health, Ageing and Retirement in Europe) provides the most recent dataset suitable for our analysis. The sample size was 13,437. Probit regression models were estimated at 10%, 25% and 40% catastrophic health expenditure thresholds, controlling for demographic, socioeconomic and lifestyle characteristics, with standard errors clustered at the country level.

Our findings show that the number of chronic conditions was statistically significant association with catastrophic health expenditures across all thresholds, whereas the presence of any chronic condition was significant only at the 10% threshold and not at higher thresholds. Compared to older people in Spain, which country has the lowest level of catastrophic out-of-pocket health expenditures in the EU, older people in the Czech Republic, Greece, Italy and Poland more frequently experienced catastrophic health expenditure, whereas older people in Austria, Germany, Sweden, France, and Denmark exhibited lower risks.

Our findings demonstrate that multimorbidity, rather than the presence of a single chronic condition, drives catastrophic health expenditures among older adults. Older adults in the Czech Republic, Greece, Italy and Poland are more likely to experience catastrophic health expenditures compared to those in Spain, where out-of-pocket health expenditures are the lowest in the EU.

This study aimed to evaluate the diagnostic performance of [¹⁸F]AlF-NOTA-QHY-04 PET/CT, a novel CXCR4-targeted imaging agent, in detecting primary central nervous system lymphoma (PCNSL) at initial diagnosis and suspected recurrence, in comparison with contrast-enhanced magnetic resonance imaging (CE-MRI) and [¹⁸F]FDG PET/CT.

We prospectively enrolled patients with suspected PCNSL between September 2022 and December 2024. A total of 29 patients underwent both CE-MRI and [¹⁸F]AlF-NOTA-QHY-04 PET/CT, with 20 patients also receiving [¹⁸F]FDG PET/CT. Biopsy pathology served as the reference standard for newly diagnosed lesions. Recurrence was assessed using a composite reference standard based on CE-MRI, clinical follow-up, and cerebrospinal fluid (CSF) findings when available; an exploratory sensitivity analysis excluded MRI-dependent cases. Imaging parameters including the maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), and tumor-to-background ratios (TBR) were calculated. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis and compared.

Six treatment-naïve patients (14 lesions) and 16 patients with recurrence (16 lesions) were confirmed, along with 7 patients without recurrence. Both primary and recurrent lesions showed intense tracer uptake on [¹⁸F]AlF-NOTA-QHY-04 PET/CT, characterized by notably high TBR. In the 20-patient subgroup undergoing both PET scans, [¹⁸F]AlF-NOTA-QHY-04 demonstrated significantly lower absolute SUVmax compared to [¹⁸F]FDG (median: 2.42 vs. 11.73, P < 0.001) but a substantially higher TBR-SUVmax (median: 42.75 vs. 1.07, P < 0.001), leading to the identification of more positive lesions (14 vs. 7, P = 0.023). Relative to the composite reference standard, [¹⁸F]AlF-NOTA-QHY-04 PET/CT achieved sensitivity and accuracy (87.50% and 90.91%, respectively) comparable to CE-MRI (100% for both, P > 0.05) and significantly superior to [¹⁸F]FDG PET/CT (43.75% and 59.09%, P = 0.023). ROC analysis identified [¹⁸F]AlF-NOTA-QHY-04 SUVmax as the optimal diagnostic parameter (AUC = 0.979).

[¹⁸F]AlF-NOTA-QHY-04 PET/CT demonstrated high tumor-to-background contrast in PCNSL, consistent with its low background brain uptake. It shows diagnostic accuracy comparable to CE-MRI and significantly superior to [¹⁸F]FDG PET/CT, demonstrating high potential as a valuable imaging tool for the diagnosis and restaging of PCNSL.

Perinatal complications can occur in gestational diabetes mellitus (GDM) despite adequate metabolic control and standard diagnostics. Metabolic alterations can cause structural and functional changes in the fetus, especially in the cardiovascular system, by affecting the autonomic nervous system and the cardiac conduction system. Advanced fetal cardiac monitoring may provide detailed insights into these processes and their impact on perinatal outcomes.

In this exploratory, prospective, single-center cohort study, 172 women with singleton pregnancies between 33 + 0 and 40 + 0 weeks were recruited (56 GDM, 116 controls). Non-invasive fetal ECG (fECG) and computerized cardiotocography (cCTG) assessed the fetal heart rate variability (HRV) and heart time intervals (HTI). Adverse perinatal outcomes (APO) were defined as a composite of the clinically relevant endpoints of operative delivery or emergency cesarean for fetal distress, NICU admission, umbilical cord pH < 7.1, and/or 5-min APGAR < 7. Predictive potential was evaluated using univariate and multivariate regression models.

The median HbA1c in the GDM group was 5.32%, indicating overall good metabolic control. One hundred forty-five cCTGs and one hundred sixty-three fECGs provided data on HTI and fetal HRV parameters. HTI did not differ between GDM and controls. Although fetal HRV parameters differed, they did not add predictive value for APO. Only maternal metabolic status, as reflected by HbA1c, showed a measurable association with APO (OR 12.83, 95% CI 1.34-122.94).

In well-controlled GDM pregnancies, HRV and HTI derived from fECG and cCTG do not enhance risk prediction for APO. Maternal HbA1c remains predictive for the perinatal risk, underscoring the importance of strict metabolic control.

Develop and study a culturally tailored genomics education tool to better inform future consent processes for genomics research participation among a medically underserved population with diabetes.

A single-arm, cohort pre/postsurvey study to assess an educational intervention developed using a community engaged approach.

Federally Qualified Health Centers in San Diego.

Adults (18 years or older) self-identifying as Latino or Hispanic with type 2 diabetes or a history of gestational diabetes were invited to participate. A total of 111 enrolled and completed the preintervention survey; 60 completed the education session and postsurvey. Lay healthcare promotoras previously trained to offer bilingual diabetes education and support were also invited; 34 enrolled and completed the study.

Using community-engaged research approaches, we developed a genomics education programme to include required elements of informed consent for future diabetes genomics research. The 1-hour, face-to-face genomics education programme was delivered 14 times with a variety of day versus evening and weekday versus weekend options, across a 9-month period. Participants completed a 21-item survey, which included 12 items measuring genomics knowledge and 9 items assessing attitudes towards genomics in healthcare.

Primary outcome was the difference between pre and posteducation mean total genomics knowledge scores among the patients who completed the education session and postsurvey. Secondary outcomes included comparison of baseline survey scores between patient and promotora subgroups, difference between patient pre and posteducation mean total attitude scores, and prescore to postscore changes within each knowledge and attitude survey item. An exploratory analysis of associations between preintervention scores and sociodemographic characteristics was also completed.

Among 60 patients, mean genomics knowledge scores significantly increased from 7.3 (SD=1.9) preintervention to 9.4 (SD=1.5) postintervention (p<0.0001). Preintervention, promotoras (mean 8.1, SD=2.0) had significantly higher knowledge scores than patients (mean 6.9, SD 2.3) (p=0.01). Similarly, promotoras (mean 6.8, SD1.3) demonstrated a more positive attitude than patients (mean 6.0, SD=1.4) (p=0.0008). Patient attitudes towards genomic testing did not change significantly from preintervention to postintervention (6.2 (SD=1.4) vs 6.3 (SD=1.4), p=0.51).

A community-informed education intervention improved genomics knowledge in an under-represented population, providing a model to foster more adequately informed consent for advanced technology research participation.

Diabetes mellitus is characterized by impaired glucose regulation, predisposing patients to both hyperglycemia and hypoglycemia. Hypoglycemia, particularly frequent in insulin-treated individuals, remains a serious but underrecognized complication. Remote patient monitoring (RPM) technologies, such as continuous glucose monitors, smartphone apps, and hybrid closed-loop systems with remote monitoring capabilities, have emerged as promising tools to improve glycemic control and prevent hypoglycemia in nonclinical settings. Evidence examining the use of RPM technologies has expanded rapidly; however, the scope, characteristics, and reported outcomes of these interventions remain fragmented across modalities and settings.

This scoping review aims to systematically map and describe the extent, range, and characteristics of published evidence on RPM interventions for glycemic management among adults with type 1 and type 2 diabetes in nonclinical settings.

The review will follow the Joanna Briggs Institute scoping review methodology and adhere to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guidelines. The population, concept, and context framework defines the population as adults with type 1 or type 2 diabetes who experience or are at risk for hypoglycemia; the concept as RPM techniques (continuous glucose monitors, hybrid closed-loop systems with remote monitoring capabilities, telemedicine, and smartphone apps); and the context as nonclinical environments. The PubMed, Embase, and Scopus databases will be searched, supplemented by gray literature. Eligible studies will include clinical trials, observational studies, and cohort studies; reviews, case studies, and non-English articles will be excluded. Two independent reviewers will conduct screening, data extraction, and summarization. Findings will be synthesized descriptively in tabular and narrative formats.

At the time of submission, the protocol has been registered, and the formal search strategy is being finalized. As of March 2026, the formal database search has been completed, and screening of studies is scheduled to begin in April 2026.

This protocol outlines a structured approach to mapping the current landscape of RPM interventions for glycemic management in nonclinical settings. The completed review will synthesize reported intervention characteristics and outcomes to clarify existing evidence and identify areas for future investigation.

OSF Registries 10.17605/OSF.IO/XNBWF; https://osf.io/xnbwf/overview.

PRR1-10.2196/88197.

In randomized trials, the primary analysis often estimates the average treatment effect on a clinical endpoint. Some treatments also lead to early changes in a biomarker that is prognostic for the clinical endpoint, prompting investigators to explore how these acute biomarker changes might inform the treatment's effect on long-term clinical outcomes. A naive analysis that directly examines treatment-by-biomarker-change interactions may lead to biased estimates because it fails to account for the fact that biomarker changes are influenced by the treatment and post-randomization factors. A key statistical challenge is that we do not know whether the observed biomarker change in an individual patient truly reflects a treatment-induced effect or whether the change would have occurred under placebo as well. This uncertainty makes it difficult to disentangle the causal effect of the treatment from natural biomarker variability. We apply principal stratification with a normal copula governed by the correlation [Formula: see text] between the potential acute biomarker changes under treatment and placebo. A flexible model for the conditional distribution of the clinical endpoint given the biomarker change enables estimation of the conditional average treatment effect on the clinical endpoint, given the acute biomarker change under treatment, as a function of [Formula: see text]. We illustrate the method by determining how knowledge of acute change in estimated glomerular filtration rate modifies the expected effect of sodium-glucose cotransporter-2 inhibitors (SGLT-2i) on clinical endpoints in patients with chronic kidney disease.

Vascular cognitive impairment (VCI) is among the most prevalent neurological disorders. VCI typically results from small vessel disease (microangiopathy) associated with arterial hypertension, diabetes mellitus, and related conditions. A distinguishing characteristic of VCI due to small vessel disease is the subcortical-frontal pattern of cognitive impairment, primarily affecting attention and executive functions. Qualitative assessment of cognitive impairment profiles facilitates the differential diagnosis of VCI and other chronic, progressive cerebral disorders. Effective management of VCI requires rigorous control of vascular risk factors (ethiotropic therapy) and, during the pre-dementia stage, the implementation of pharmacological neuroprotection to prevent further cognitive decline. Neuroprotective therapy may include agents with multimodal mechanisms of action. This article presents findings from the MEMO randomised clinical trial, which demonstrated the efficacy of the neuroprotector Mexidol in improving cognitive, psychoemotional, and motor symptoms in patients with chronic cerebral ischemia (CBI) and moderate neurocognitive impairment syndrome.

To assess the efficacy and safety of alpha-lipoic acid (ALA) and pregabalin, both as mono and combination therapy, for treating painful diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus, with the hypothesis that pregabalin monotherapy is non-inferior to combination therapy.

A phase 4 randomized, active-controlled, open-label, multicentre trial was conducted over 12 weeks to investigate changes in visual analogue scale (VAS) pain scores from baseline as a primary efficacy endpoint. A total of 151 eligible subjects were randomly assigned to ALA (480 mg/day), pregabalin (150 mg/day), and combination groups in a 1:1:1 ratio.

The pregabalin monotherapy group showed a VAS change of -19.73 ± 18.94 mm, while the combination group showed -23.28 ± 18.15 mm at Week 12. The least square mean (LSM) difference between the two groups was 3.46 mm (95% CI: [-4.94, 11.87]), demonstrating that pregabalin monotherapy is non-inferior to combination therapy. Safety analysis revealed no significant differences across treatment groups. Cluster analysis revealed statistically significant differences in VAS scores between the pregabalin monotherapy and combination therapy groups at 12 weeks in cluster 1, characterized by a relatively shorter duration of DPN, and the LSM difference between both groups was 14.79 mm [4.59, 24.99] (p = 0.0055).

The pregabalin monotherapy demonstrated non-inferiority compared to the combination therapy in alleviating DPN pain. Cluster analysis supported the identification of patient groups where combination therapy could be more effective, but future comprehensive studies are required for further verification.

ClinicalTrials.gov, NCT04846673.

Diabetes mellitus is widely regarded as a risk factor for cancers. There is considerable controversy over whether maternal diabetes can cause cancer. This study aims to comprehensively assess and quantify the association between maternal diabetes and the risk of cancers in mother-offspring.

The PubMed, Embase, and Web of Science databases were searched up to September 30, 2025, to explore the impact of maternal diabetes on cancer in mothers and their offspring. The primary outcome was the risk of cancers in the mother or offspring, presented as risk ratios (RRs) with 95% confidence intervals (CI). The I² statistic is used to assess heterogeneity among studies, thereby guiding the selection of random-effects or common-effects models.

The 81 studies involving 44 917 447 mother-offspring. Maternal diabetes was associated with increased risks of any cancers in mothers and offspring. In studies adjusted for multiple confounders, the risk of offspring suffering from haematological malignancies (RR, 1.37; 95% CI, 1.23-1.52; I² = 1.0%) has significantly increased, especially leukaemia (1.34; 1.22-1.47; 0.0%). However, the risk of solid tumours (1.17; 1.09-1.24; 70.1%) in mothers increases significantly, especially, head and neck (1.34; 1.23-1.47; 35.1%), respiratory system (1.33; 1.05-1.67; 0.0%), gastrointestinal (1.30; 1.16-1.45; 45.5%), and gynecologic (1.16; 1.04-1.29; 64.1%). Maternal pre-gestational diabetes was more strongly associated with the risk of most cancers in offspring than gestational diabetes (1.60 [1.14-2.14] vs. 1.10 [1.02-1.18]; subgroup difference p = 0.0046).

Maternal diabetes is associated with an increased risk of cancers in mothers and offspring. Further high-quality large-sample studies are needed to clarify and consolidate potential causal relationships.