Search Results (1,524)

Hypochloremia has recently emerged as an independent prognostic marker in heart failure (HF), which is especially common in older adults, where it represents a main cause of death and hospitalization. This narrative review of the literature aims to summarize the main evidence about the clinical significance of hypochloremia in older adults with HF. Particularly, hypochloremia results from the interplay among neurohormonal activation, congestion, renal dysfunction, and diuretic therapy. In older adults, age-related decline in renal function, frailty, multimorbidity, and polypharmacy increase susceptibility to chloride disturbances. Overall, the prevalence of hypochloremia in HF in older people was estimated to be about 25–29%. Although studies specifically involving older adults with HF remain limited, available data support the prognostic relevance of hypochloremia in this population. Moreover, recent evidence has identified distinct hypochloremic phenotypes, namely dilutional and depletional forms, characterized by different pathophysiological mechanisms. Emerging chloride-centered therapeutic strategies may be particularly relevant in older patients. In conclusion, hypochloremia is confirmed as an important marker of disease severity and adverse prognosis in older patients with HF. Routine assessment of serum chloride may improve risk stratification and support a more individualized therapeutic approach. Further prospective studies are needed to clarify the role of chloride-guided management strategies and their impact on clinical outcomes in older patients with HF. Full article

Background/Objectives: Respiratory infections are a major cause of morbidity and mortality among older adults. However, vaccination coverage against respiratory pathogens remains suboptimal, particularly in rural and vulnerable populations. This study aimed to identify factors associated with respiratory vaccination uptake among older adults living in rural Amazonian communities in Peru. Methods: We conducted an observational, analytical, cross-sectional study using secondary data from the Amazon Frail Project. A total of 429 adults aged ≥60 years from rural and suburban communities in San Martín, Loreto, and Ucayali were included. Vaccination coverage for influenza, pneumococcal disease, pertussis, and COVID-19, as well as vaccine combinations, was assessed. Multiple linear and Poisson regression models with robust variance were used to identify associated factors. Results: Complete vaccination coverage was 42.89% for influenza, 23.08% for pneumococcal disease, 4.43% for pertussis, and 70.16% for COVID-19. Only 3.50% of participants had received all four respiratory vaccines. Higher educational attainment, multimorbidity, social frailty, greater muscle mass, better physical performance, and healthcare center attendance were associated with higher vaccination uptake. Depressive symptoms, cognitive impairment, functional dependency, physical frailty, dynapenia, and higher body mass index were associated with lower vaccination uptake. Conclusions: Respiratory vaccination coverage was suboptimal among older adults living in rural Amazonian communities. Educational, functional, physical, social, and healthcare access factors significantly influenced vaccine uptake, highlighting the need for targeted immunization strategies in vulnerable rural populations. Full article

Providing care for effective management of tuberculosis (TB) and diabetes mellitus (DM) is a challenge, particularly in resource-limited settings. This study assessed factors affecting the provision of care for patients with TB-DM in Addis Ababa, Ethiopia, using the six elements of the SELFIE—Sustainable intEgrated chronic care modeLs for FinancIng and performancE framework. A health facility-based cross-sectional study was conducted with randomly selected patients with TB-DM multi-morbidity. Data were analysed using the Statistical Package for Social Sciences (SPSS) version 27. Logistic regression was employed to identify factors influencing TB-DM care provision. A total of 357 respondents participated, with a response rate of 96.5%. The mean age of the respondents was 49.8 years. Only 13.4% of patients received good TB-DM services. Key factors influencing TB-DM care were (a) insufficient counseling on the proper use of medication (AOR = 2.6, CI: 1.1–6.6, p = 0.035) and the risk of TB for DM patients (AOR = 10, CI: 3.7–27, p < 0.001), (b) leadership and governance including supportive leadership for TB-DM care (77.1%), organized TB-DM care (62.5%), the presence of a care policy (77.1%), and continuity of care (58.3%), (c) workforce factors such as the presence of a multidisciplinary team (60.4%), TB-DM service coordinator (58.3%), HCWs with adequate knowledge (87.5%), (d) costs of health services are fair (75%) and (e) lack of technologies such as EMR (88%) and lack of medical products to treat TB-DM (64.7%) delays care for TB-DM. Most TB-DM patients in Addis Ababa had limited access to care. The continuous monitoring of services can facilitate the identification of care gaps, thereby guiding the implementation of improved interventions. Full article

Patients with multiple myeloma (MM) exhibit profound immune dysregulation, predisposing them to severe outcomes following SARS-CoV-2 infection. Current evidence highlights shared immunopathological mechanisms linking MM and COVID-19, with particular emphasis on the interleukin-6 (IL-6) axis as a shared amplifier of inflammation rather than the sole driver of disease. MM is characterized by a baseline pro-inflammatory milieu, in part mediated by IL-6, which is further amplified during SARS-CoV-2 infection, resulting in cytokine escalation, complement activation, coagulopathy, and multi-organ injury. This amplification operates within a broader, redundant network that also includes T-cell exhaustion, NK-cell dysfunction, checkpoint signaling, complement and endothelial injury, and treatment-induced immune defects. This overlap provides a mechanistic basis for the disproportionately high morbidity and mortality observed in this population. Even with advancements in vaccination, antiviral therapy, and clinical practice, patients with MM who exhibit impaired vaccine responses, active disease, or treatment-related immune dysfunction continue to experience considerable vulnerability to COVID-19. In addition, MM patients demonstrate suboptimal vaccine-induced immune responses, contributing to persistent vulnerability to severe and breakthrough infections. Modern MM therapies, including anti-CD38 antibodies, BCMA-directed agents, and bispecific T-cell redirecting antibodies, further reshape antiviral immunity by reducing NK cells, inducing plasma cell aplasia, causing hypogammaglobulinemia, and impairing T-cell function. Emerging treatment approaches targeting this shared pathway have been explored, with a focus on mesenchymal stem cell (MSC)-derived extracellular vesicles (EVs). EVs exhibit multimodal properties, including suppression of pro-inflammatory cytokines, restoration of immune homeostasis, inhibition of viral entry, and promotion of tissue repair and regeneration. Early clinical experience in severe COVID-19 populations suggests a favorable short-term safety profile; reported efficacy, however, derives from small, largely uncontrolled or early-phase studies, and the single randomized trial reporting a mortality benefit did so only in an exploratory post hoc subgroup, with its pre-specified primary endpoint not met. Overall, EVs constitute a biologically plausible but as yet unproven adjunctive strategy that warrants further investigation. Critically, no MM patient has ever been enrolled in an EV trial; current rationale for EV use in MM is therefore extrapolated entirely from non-MM populations, and no MM-specific data exist. Difficulties such as EV heterogeneity, manufacturing variability, uncertain pharmacokinetics, limited targeting efficiency, and potential prothrombotic effects must be resolved before their application in MM-specific clinical settings. Full article

Background: Cervical cancer remains one of the leading causes of cancer-related morbidity among women worldwide. The Papanicolaou (Pap) smear is widely used for early detection; however, its manual interpretation is time-consuming, requires substantial expertise, and is often affected by inter-observer variability, particularly in cases with dense and overlapping cells. Methods: This study developed an optimized deep learning framework for cervical cell instance segmentation, specifically targeting the separation of overlapping cells in Pap smear images. The proposed framework was based on Mask R-CNN with a ResNet-50 backbone and Feature Pyramid Network. A public development dataset of 460 cervical smear images was used for model development and internal evaluation, while an independent 210-image dataset collected from King Abdullah University Hospital was reserved as an external held-out clinical assessment set. To improve small-cell detection and mask refinement, the Region Proposal Network was adapted using biologically informed anchor scales (16, 32, 64, 128, 256), followed by soft calibration-based post-processing. Results: The proposed framework achieved an AP50 of 89.90% and a Mask IoU of 90.44%. Small-cell performance, measured using APs under the COCO small-object convention, reached 22.80%, while APm and APl reached 68.45% and 81.42%, respectively. Clinical cell-count evaluation on the independent KAUH held-out set was performed using the mean count of five physicians as the reference standard and achieved an overall clinical detection accuracy of 93.00%. Conclusions: The optimized Mask R-CNN framework improved the detection and separation of overlapping cervical cells in Pap smear images and may serve as a supportive tool for cytopathology workflows. The results suggest that biologically informed anchor optimization and soft calibration can improve cell-level instance segmentation, particularly for small and overlapping cells. Further validation on larger multi-center datasets remains necessary before routine clinical deployment. Full article

Background and Objectives: Xerostomia is common among institutionalized older adults, but the relative contributions of comorbidity burden and medication-class burden remain incompletely clarified. This study evaluated their associations with Xerostomia Inventory (XI) severity and explored related salivary dysfunction and clinical oral health findings. Materials and Methods: We conducted a cross-sectional study of 90 institutionalized older adults in Bucharest, Romania. Xerostomia Inventory (XI) scores, a binary dry-mouth question, chairside salivary assessments, comorbidity categories, medication classes, oral mucosal findings, and complete denture retention and stability were recorded. Primary analyses used hierarchical regression and bootstrap statistical decomposition; secondary and exploratory analyses evaluated salivary concordance, medication classes, denture-related findings, and oral mucosal conditions. Results: Medication-class count remained associated with XI severity after adjustment for comorbidity burden (partial r = 0.445, p < 0.001), whereas the association between comorbidity burden and XI was no longer significant after adjustment for medication-class count (partial r = −0.063, p = 0.557). Inclusion of medication-class count increased the explained variance in XI scores (ΔR² = 0.253, p < 0.001). Bootstrap decomposition yielded similar findings, with a significant indirect estimate and a non-significant direct estimate. Among complete denture wearers, XI severity was associated with maxillary denture instability (ρ = −0.687, n = 44). Conclusions: In this cohort, medication-class burden showed the strongest association with xerostomia severity, whereas comorbidity burden was not independently associated after adjustment. Given the cross-sectional design, these findings should be interpreted as exploratory associations and support future prospective studies integrating medication review with geriatric-prosthodontic assessment. Full article

Necrotising enterocolitis is a highly challenging condition in neonatal surgery, with a substantial proportion of affected infants requiring operative intervention with a significant associated morbidity and mortality. Radiological evidence of perforation represents a clear indication for surgery; however, in many other cases, the disease presentation and progression are heterogenous, with significant diagnostic and prognostic uncertainty. The surgical assessment and decision making in these cases relies on integrated judgement of the clinical trajectory, examination, and biochemical and radiological findings, as well as consideration of the comorbidities and gestational age. Although many have been proposed in the literature, there remains to be any universal validated thresholds or criteria for reliably identifying those infants who may be ‘failing medical management’ and are likely to develop intestinal necrosis. Similarly, comparisons of different surgical approaches (stoma, primary anastomosis, and damage-control strategies) and outcome reporting are often confounded by the disease severity index and patient selection, as well as the generally observational nature of studies within the field. Improved standardisation of disease and severity definitions, and the development of validated prognostic tools, will facilitate the earlier identification of infants most likely to benefit from surgery, which in turn could reduce delays to theatre and improve the outcomes. Multi-centre collaborative datasets provide important evidence in the path to achieving this aim, by providing valuable cohort and outcome data, which also contribute to informed shared decision making with parents and families. Full article

Background/Objectives: Chronic non-communicable diseases remain one of the main public health problems. Increasing multimorbidity and the importance of health literacy (HL) emphasize the need for a comprehensive assessment of health indicators. The aim of this study was to assess the main health indicators of the Lithuanian population and trends in the use of healthcare services and to discuss the relevance of these indicators in the context of HL, based on the links between HL and these indicators described in the scientific literature. Methods: A retrospective longitudinal descriptive study was performed using publicly available Lithuanian population health statistics of 2005–2024. Mortality, morbidity, avoidable hospitalizations, subjective health assessment, and utilization of healthcare services and preventive programs were analyzed using descriptive statistical analysis. HL was not directly measured but was used as a conceptual framework for interpreting the findings. Results: In Lithuania, the highest mortality rate is due to cardiovascular diseases (CVDs) (~50.8%). CVD and infectious diseases also dominate the structure of avoidable hospitalizations, and their rates vary greatly across municipalities, being higher in less urbanized areas. The assessment of the population’s health is improving over time, but gender differences remain in the use of healthcare services and preventive programs. Conclusions: The findings demonstrate a high burden of chronic diseases and regional disparities in healthcare utilization in Lithuania. HL may provide a useful context for interpreting these findings, although it was not directly assessed. Future studies should directly evaluate HL and its association with health indicators in the Lithuanian population. Full article

Background: Endobronchial tumors represent a heterogeneous spectrum of benign and malignant histopathological types. Selecting the optimal surgical strategy remains a multidisciplinary challenge. This study evaluates how the integration of spirometry, DLCO, and CPET can objectively stratify cardiorespiratory risk and guide surgical decision-making regarding resection type, postoperative complications, and perioperative mortality. Methods: A single-center, retrospective study was conducted between 2020 and 2025, evaluating an initial screening cohort of 93 patients with endobronchial masses. Following multidisciplinary tumor board review based on functional and anatomical criteria, 36 patients were excluded from major resection due to extensive disease or prohibitive functional risk, while 57 underwent tailored surgical interventions, including sleeve resections, lobectomies, bilobectomies, and pneumonectomies. Preoperative evaluation included spirometry, DLCO, cardiological assessment, CT, and autofluorescence bronchoscopy (AFB). Results: Spearman correlation analysis demonstrated that advanced age and higher ASA scores significantly correlated with reduced preoperative DLCO (p < 0.0001). The overall postoperative morbidity rate was 36.84% (n = 21) and perioperative mortality was 5.26% (n = 3). Stratified analysis by surgical magnitude demonstrated a significant escalation in overall complication rates from parenchymal-sparing sleeve resections (17.6%, 95% CI: 3.8% to 43.4%) to standard lobectomies (40.7%, 95% CI: 22.4% to 61.2%), bilobectomies (50.0%, 95% CI: 15.7% to 84.3%), and radical pneumonectomies (60.0%, 95% CI: 14.7% to 94.7%; p = 0.042). Severe morbidity (Clavien–Dindo Grade III–IV) was significantly lower in the sleeve resection subgroup (5.8%) compared to pneumonectomies (40.0%, p = 0.015). Fatal outcomes occurred exclusively following major resections and were attributable to ARDS and acute cardiovascular events. Conclusions: A multi-parametric preoperative protocol provides an informative framework for risk stratification in endobronchial tumor surgery, helping to describe baseline reserves and explore post-resection trends. However, the anatomical and hemodynamic magnitude of radical pneumonectomy constitutes an independent risk modifier that cannot be fully captured by preoperative functional testing alone, highlighting the exploratory nature of these single-center retrospective observations rather than a definitive algorithmic validation. Full article

Background: With the increasing prevalence of multimorbidity, the demand for palliative and end-of-life care is expected to rise substantially in the coming decades. Digital health technologies may enable automated detection of clinically relevant distress, including symptoms such as pain, breathlessness (dyspnea), anxiety/panic, nausea, and agitation. Remote detection of such distress in cognitively impaired patients who are unable to reliably call for help could enable timely intervention when patients are unattended. Methods: This observational feasibility study will collect multimodal data from a non-invasive sensor system consisting of 3D radar, a photoplethysmographic sensor (wearable), and a microphone. Sensor data will be linked to distress events identified by nurses or physicians during routine clinical care using structured proxy assessments. Adults (≥18 years) admitted to the Palliative Care Center Basel who are unable to reliably call for help due to cognitive impairment will be included based on written informed consent provided by a legal proxy. Aim: The aim of this study is to evaluate the feasibility of multimodal sensor-based monitoring for detecting clinician-identified distress events and to explore associations between sensor-derived variables and distress, informing future validation studies and the development of automated detection approaches in palliative care. Full article

Coronary heart disease (CHD) is a global cardiovascular disease with high morbidity and mortality, and its complex pathological mechanism poses great challenges to clinical prevention and treatment. Paeoniflorin (PA), a monoterpene glycoside active ingredient from Ranunculaceae plants, has shown potential in cardiovascular protection, but its specific anti-CHD molecular targets and systematic regulatory networks remain unclear. In this study, a mouse model of CHD was established, and a multi-omics strategy combining label-free quantitative proteomics and metabolomics was adopted to explore the mechanism of PA in treating CHD. The results showed that PA significantly improved cardiac function, alleviated myocardial pathological injury and fibrosis, and regulated lipid metabolism in CHD model mice, with the high-dose group showing the optimal effect. Proteomic analysis identified 51 key differentially expressed proteins (DEPs) reversed by PA, which were mainly enriched in complement and coagulation cascades, and neutrophil extracellular trap formation pathways, with the C3-Cfd-C3aR signaling axis as the core hub. Further verification confirmed that PA could downregulate the expression of C3, Cfd, C3aR, and their downstream molecule BTK, thereby inhibiting myocardial inflammatory response and cardiomyocyte apoptosis. In addition, PA downregulated the expression of platelet activation markers ITGA2B/ITGB3. Metabolomic analysis revealed that PA reversed 57 abnormal metabolites in CHD mice, which were enriched in GABAergic synapse, retrograde endocannabinoid signaling and other pathways. Molecular docking confirmed that PA could stably bind to C3, Cfd, C3aR, BTK, and ITGA2B/ITGB3 with strong binding activity. In conclusion, PA exerts anti-CHD effects through a multi-target and multi-pathway synergism, mainly by targeting the C3-Cfd-C3aR axis to inhibit inflammation, apoptosis and platelet activation, and regulating metabolic disorders. This study provides experimental evidence and theoretical support for the clinical application of PA as a multi-target therapeutic drug for CHD. Full article

Background/Objectives: Traditional community oral health programs (COHPs) often remain reactive, clinic-based, and insufficiently integrated with medical, social, and aged-care systems. As a result, they may be poorly positioned to address the needs of older adults experiencing multimorbidity, mobility limitations, cognitive impairment, care dependency, and financial or geographic barriers. This paper proposes SPACES, an implementation-oriented conceptual framework for designing, delivering, and evaluating community oral health programs for older adults. Methods: SPACES was developed through a targeted interpretive synthesis of peer-reviewed literature, policy guidance, and implementation-oriented sources related to oral health, healthy aging, integrated care, access barriers, workforce development, and sustainable service delivery. Results: The framework comprises six interconnected domains: Scalable Prevention and Education, Partnerships Across Sectors, Adaptive Care Coordination, Community Access Solutions, Empowered Workforce Development, and Sustainable Service Models. It is intended primarily for adults aged 60 years and older, while allowing adaptation in jurisdictions that use 65 years and older as the eligibility threshold. The framework applies across community, home care, assisted living, and long-term care settings. SPACES organizes evidence-informed components for older-adult oral health, including routine screening, caregiver-supported daily mouth care, risk-stratified prevention, referral pathways, proximity-based service delivery, geriatric workforce competencies, task sharing, sustainable financing, governance, and quality improvement. Conclusions: SPACES is presented not as a tested intervention but as a conceptual and program-planning tool to help planners clarify responsibilities, identify equity gaps, align cross-sector resources, and select measurable implementation indicators. Future stakeholder refinement and empirical evaluation are needed through co-design, pragmatic implementation studies, and real-world assessment of feasibility, acceptability, cost, equity impact, and oral health outcomes. Full article

Background: Optimizing nutritional care for people with multimorbidity requires effective and feasible tools for early risk identification. This study aimed to investigate the associations of conicity index (C-index) and body roundness index (BRI) with multimorbidity among adults in Guangzhou, and to explore their potential utility in identifying individuals who may benefit from prioritized nutritional assessment. Methods: Based on the Fourth Adult Chronic Disease and Risk Factor Surveillance Program in Guangzhou, a total of 15,532 adults were recruited in this cross-sectional study. Multiple logistic regression analysis, restricted cubic spline (RCS) analysis and receiver operating characteristic curve (ROC) analysis with DeLong’s test were performed. Results: The prevalence of multimorbidity was 38.95%. Higher C-index and BRI quartiles were significantly associated with increased multimorbidity risk. Compared with the lowest quartile, the adjusted OR for the highest C-index quartile was 1.98 (95% CI: 1.78–2.21), and for the highest BRI quartile it was 3.05 (95% CI: 2.74–3.41). A dose–response relationship was observed (p < 0.001). BRI showed statistically significantly higher discriminative ability relative to traditional anthropometric indices, though its overall discriminative performance was modest (AUC = 0.678). Conclusions: C-index and BRI are strongly and positively associated with multimorbidity. These simple, non-invasive indices may support community-based risk stratification and help identify individuals who warrant further clinical and nutritional assessment. Full article

Chronic obstructive pulmonary disease (COPD) remains a major cause of respiratory morbidity and healthcare utilization, creating challenges for healthcare planning, resource allocation, and early intervention. This study aimed to develop a forecasting framework for quarterly age- adjusted COPD outpatient visit rates across 762 regions in Pennsylvania from 2019 to 2023, using multi-source data including PHC4 outpatient records, satellite-derived environmental pollutant variables, and meteorological variables. To compare models that capture nonlinear relationships with those that explicitly model temporal dependencies, several machine learning models and a deep learning long short-term memory (LSTM) model, designed to learn sequential patterns and lagged temporal effects, were evaluated. The seasonal naïve baseline achieved $R^2=0.570$, classical machine learning models achieved $R^2=0.58$–$0.62$, and the LSTM model achieved $R^2=0.705$ with lower prediction error. Lagged COPD activity was the strongest predictor, while environmental, meteorological, and geographic variables provided additional predictive information. These findings highlight the value of integrating multi-source environmental data with sequence-based modeling for forecasting regional COPD activity and suggest that environmental and meteorological variables can provide additional predictive information beyond historical COPD activity alone. Full article

Age-associated metabolic dysfunction is commonly defined by abnormalities in adiposity, glucose regulation, lipid metabolism, and blood pressure. Although clinically useful, these criteria do not fully capture the biological heterogeneity that explains why older adults with similar metabolic profiles may follow divergent trajectories toward type 2 diabetes, cardiovascular disease, metabolic dysfunction-associated steatotic liver disease, frailty or multimorbidity. This narrative Review summarizes clinical, translational, and mechanistic evidence on the biological processes that shape metabolic aging, with particular emphasis on inflammaging, immunosenescence, cellular senescence, oxidative stress, mitochondrial dysfunction, adipose tissue dysfunction, endothelial injury, and inflammation-related microRNAs. We first discuss how chronic low-grade inflammation and immune remodeling alter the interpretation of conventional metabolic syndrome components in older adults. We then review redox imbalance and mitochondrial stress as amplifiers of insulin resistance, lipid injury, vascular dysfunction, and tissue remodeling. The review also examines inflammation-related microRNAs, including circulating and extracellular-vesicle-associated miRNAs, as post-transcriptional regulators that may connect inflammatory, metabolic, and redox pathways. Finally, we discuss how conventional metabolic markers may be integrated with inflammatory mediators, oxidative-stress indicators, adipokines, endothelial and senescence-related markers, and miRNA profiles to improve biological interpretation of metabolic risk. Within this context, we present the Inflammaging–Redox–InflammamiR Axis as a conceptual framework for organizing these overlapping mechanisms rather than as an established diagnostic or causal model. The proposed biomarker tiers and candidate risk phenotypes are author-derived, hypothesis-generating constructs intended to guide future longitudinal and interventional research. Clinical translation will require standardized assays, longitudinal validation, external replication, and intervention studies. Full article