Search Results (301)

Urinary stone disease is common, recurrent, and increasingly managed through imaging-driven pathways, yet standard-dose CT of the kidneys, ureters, and bladder (CT KUB) raises concerns about cumulative radiation exposure and the limited use of quantitative imaging information for risk stratification. This review synthesizes contemporary evidence on dose-optimized CT, advanced spectral technologies, and artificial intelligence (AI)-enabled analytics that are reshaping diagnosis, treatment selection, and triage. This review summarizes data supporting low-dose and ultra-low-dose CT protocols that preserve diagnostic accuracy while substantially reducing dose, and discusses how dual-energy CT, photon-counting CT, and radiomics facilitate noninvasive stone characterization and extraction of imaging biomarkers beyond size and location. It also reviews AI approaches for automated detection, segmentation, and volumetric quantification across CT, KUB, and ultrasounds, highlighting their potential to standardize stone-burden metrics. It further examines predictive models, including logistic regression, nomograms, and machine learning, for perioperative infectious complications, emergency department admission or intervention, procedure success, and long-term recurrence, and outlines reporting and validation frameworks and implementation considerations, including software as a medical device regulation and human oversight. In contrast to prior reviews that consider imaging and AI separately, this review integrates dose reduction, spectral characterization, and AI-driven analytics within real-world clinical pathways to distinguish established clinical applications from those that remain investigational. Integrating advanced CT and AI outputs into well-validated prediction models embedded in real-world workflows may enable safer imaging, more consistent triage, and more personalized follow-up for urinary stone disease. Full article

Background/Objectives: Vitamin B12 deficiency is a common but often underdiagnosed complication in patients with type 2 diabetes (T2D) undergoing long-term metformin therapy. Accurate early prediction could enable targeted screening and timely intervention. This study aimed to develop and interpret a machine learning model for predicting vitamin B12 deficiency in metformin-treated patients with T2D, using eXtreme Gradient Boosting (XGBoost). Methods: A retrospective cross-sectional study was conducted at a single endocrinology centre (La Rabta University Hospital, Tunis, Tunisia). Patients with T2D treated with metformin for at least three years were included (n = 257); those with conditions independently affecting vitamin B12 metabolism were excluded. Vitamin B12 deficiency was defined as a serum B12 level below 150 pmol/L or a borderline level (150–221 pmol/L) with concurrent hyperhomocysteinemia (>15 μmol/L). XGBoost was selected after comparison with Logistic Regression (L2), Random Forest, and Support Vector Machine on the same 5-fold stratified cross-validated pipeline. Hyperparameters were optimized via Bayesian search (100 iterations × 5-fold stratified cross-validation), with the Matthews correlation coefficient (MCC) as the primary optimization metric to account for class imbalance. Model interpretability was achieved using SHapley Additive exPlanations (SHAP). Discrimination and calibration were assessed on an independent test set using bootstrap 95% confidence intervals (2000 resamples). Results: Of 257 patients, 95 (37.0%) presented with vitamin B12 deficiency. On the independent test set (n = 52), the optimized XGBoost model achieved an ROC-AUC of 0.671 [95% CI: 0.514–0.818], sensitivity of 0.737 [95% CI: 0.533–0.938], specificity of 0.545 [95% CI: 0.375–0.710], MCC of 0.273 [95% CI: 0.018–0.517], and a Brier Score of 0.259. SHAP analysis identified HbA1c, microalbuminuria, autonomic neuropathy, BMI, DN4 score, and fasting glucose as the most influential predictors. Nonlinear SHAP interaction plots revealed an increased predicted risk in patients with low HbA1c combined with a high cumulative metformin dose. Conclusions: The XGBoost–SHAP framework provided interpretable predictions of vitamin B12 deficiency in patients with T2D on metformin, identifying key clinical profiles for targeted screening. External multi-centre validation is required before clinical deployment. Full article

Background and Objectives: Red cell distribution width (RDW) has been associated with adverse cardiometabolic outcomes; however, whether RDW—particularly RDW standard deviation (RDW-SD)—represents an independent determinant of metabolic syndrome (MetS) or reflects cumulative metabolic burden remains unclear. This study evaluated the association between RDW-SD and MetS presence and examined its relationship with the quantitative accumulation of MetS components. Materials and Methods: In this single-center observational study, 222 adults undergoing evaluation for MetS were consecutively recruited. Participants with overt anemia, extreme mean corpuscular volume values, or acute inflammation were excluded. MetS was defined according to revised NCEP ATP-III criteria. Associations between RDW-SD and MetS were assessed using hierarchical multivariable logistic regression models. The relationship between RDW-SD and the number of MetS components was examined using multivariable linear regression. Discriminative performance was evaluated by receiver operating characteristic (ROC) curve analysis. Results: MetS was present in 68.0% of participants. RDW-SD levels were significantly higher in individuals with MetS and increased progressively across quartiles. RDW-SD was independently associated with the number of MetS components (standardized β = 0.226, p < 0.001). However, RDW-SD was not independently associated with MetS presence in fully adjusted logistic models (OR = 1.07, 95% CI: 0.97–1.18, p = 0.198). The addition of RDW-SD provided minimal incremental explanatory value (Nagelkerke R² increase from 0.348 to 0.356). ROC analysis demonstrated poor discriminatory ability (area under the curve [AUC] = 0.611, 95% CI: 0.535–0.687), supporting limited standalone diagnostic utility. Conclusions: RDW-SD was independently associated with cumulative metabolic burden but not with the independent presence of MetS after adjustment for established cardiometabolic factors. Given the cross-sectional design, these findings should be interpreted as associative rather than causal. Full article

Background: Gastrointestinal (GI) symptoms are common in endurance and ultra-endurance sports and may impair performance or lead to race withdrawal. While nutritional strategies are frequently emphasized, the respective roles of baseline digestive susceptibility and cumulative exercise exposure remain insufficiently characterized. Methods: Two complementary cross-sectional questionnaire-based studies were conducted in endurance athletes. Study 1 included 230 ultra-trail runners and examined determinants of systematic GI symptoms during competition using a composite digestive vulnerability (DV) score reflecting susceptibility indicators. Study 2 included 497 endurance and ultra-endurance athletes from multiple disciplines and investigated multivariable correlates of GI symptoms and GI-related race withdrawal, integrating training-related GI symptoms (proxy of digestive vulnerability), habitual competition duration (≥6 h), sport category and specific digestive symptoms. Logistic regression models were adjusted for age and sex. Results: In Study 1, the DV score was independently associated with systematic GI symptoms during competition (adjusted OR per point = 1.93, 95% CI 1.33–2.80). In Study 2, athletes reporting GI symptoms during training had markedly higher odds of experiencing GI symptoms during competition (adjusted OR = 3.96, 95% CI 2.67–5.87). Habitual exposure to events lasting ≥6 h was independently associated with increased odds of GI-related race withdrawal (adjusted OR = 2.25, 95% CI 1.35–3.78). GI symptoms during competition represented the strongest proximal correlate of withdrawal (adjusted OR = 7.04, 95% CI 4.00–12.30), indicating a sequential relationship between baseline digestive vulnerability, symptom expression during competition and race termination. After adjustment for digestive vulnerability and exercise exposure, no individual nutritional category remained independently associated with GI outcomes. Conclusions: Gastrointestinal symptoms and race withdrawal in endurance athletes were more consistently associated with digestive vulnerability expressed during training and cumulative exercise exposure than with isolated nutritional items. These findings support a vulnerability–exposure framework in which individual digestive susceptibility interacts with prolonged physiological stress during endurance exercise. Identifying athletes with elevated digestive vulnerability during training may represent a practical strategy to improve individualized nutritional preparation and reduce GI-related race interruption. Full article

Atrial fibrillation (AF) frequently coexists with chronic coronary syndrome (CCS), reflecting shared cardiovascular risk factors and structural remodeling pathways. Identifying CCS patients at increased likelihood of AF remains clinically relevant, particularly when arrhythmia is silent or paroxysmal. Background: We hypothesized that established clinical and angiographic risk scores used in CCS may capture cumulative cardiovascular burden and could therefore assist in AF risk stratification. The biomarker-based ABC-stroke score was incorporated as a biological reference framework reflecting myocardial stress and injury. Methods: This prospective, single-center proof-of-concept study included 131 consecutive patients undergoing invasive coronary angiography for suspected myocardial ischemia. Patients were classified according to rhythm status, irrespective of AF subtype. Coronary artery disease severity was quantified using the Gensini and SYNTAX (PCI and CABG) scores. Global cardiovascular risk was assessed using Framingham, ASCVD, SCORE2, and SCORE2-OP. Correlation analyses, ROC curves, and multivariable logistic regression were performed to evaluate associations between risk scores, coronary complexity, and AF. Results: Clinical and angiographic risk scores differed significantly according to rhythm status and AF phenotype. Patients with AF exhibited higher global cardiovascular risk and greater coronary anatomical complexity compared with those in sinus rhythm. SYNTAX PCI and SYNTAX CABG demonstrated moderate discriminative performance for AF detection (AUC 0.745 and 0.760, respectively), with SYNTAX CABG remaining independently associated with AF in multivariable analysis. Significant correlations were observed between traditional cardiovascular risk scores and SYNTAX-derived measures of coronary complexity, whereas correlations with the Gensini score were weaker. The ABC-stroke reference model showed a strong discriminative signal, consistent with its biological proximity to AF-related myocardial stress. Conclusions: Established clinical and angiographic risk scores used in CCS are associated with the presence and phenotype of AF. These findings suggest that routinely available coronary risk assessment tools may serve as practical instruments for identifying CCS patients at increased likelihood of AF, potentially facilitating targeted rhythm screening and earlier risk stratification. Full article

Background: Acute kidney injury (AKI) is a common and high-risk complication of hospitalization that frequently occurs in patients with chronic cardiometabolic disease. Although heart failure (HF) and diabetes mellitus (DM) are prevalent among hospitalized adults and may differentially modify AKI-associated outcomes, their joint impact on in-hospital risk profiles and cumulative burden remains incompletely characterized. Methods: We conducted a retrospective analysis of adult hospitalizations complicated by AKI using a nationally representative inpatient database. Hospitalizations were classified into four cardiorenal metabolic phenotypes: AKI alone, AKI with HF, AKI with DM, and AKI with both HF and DM. Primary outcomes included in-hospital mortality, dialysis initiation, and mechanical ventilation. Survey-weighted multivariable logistic regression models incorporating HF, DM, and their interaction were used to estimate adjusted associations and model-based predicted probabilities. Adjusted risks were visualized across outcomes, and a composite burden metric was constructed to summarize cumulative in-hospital adverse events. Results: AKI outcomes varied substantially across cardiorenal metabolic phenotypes. HF was consistently associated with higher adjusted mortality and mechanical ventilation risk, whereas DM alone was associated with lower adjusted mortality. A significant interaction between HF and DM was observed regarding dialysis initiation, with a disproportionately higher adjusted risk when both conditions coexisted. Integrated visualization across outcomes demonstrated distinct risk profiles by phenotype, with the combined HF and DM group exhibiting the highest cumulative burden of adverse in-hospital events. Conclusions: Among hospitalizations complicated by AKI, the underlying cardiorenal metabolic status is associated with marked heterogeneity in in-hospital outcomes. HF appears to be a dominant modifier of AKI-associated risk, while DM exerts outcome-specific effects and synergistically increases the risk of dialysis initiation when combined with HF. These findings highlight the importance of incorporating cardiometabolic context into AKI risk stratification approaches and underscore the value of multidimensional in-hospital assessments. Full article

Background and Objectives: Peripheral neuropathy (PNP) is a frequent and debilitating complication among patients with diabetes mellitus (DM) and other metabolic conditions, substantially affecting morbidity, functional status, and quality of life. Identifying predictors of PNP is essential for optimizing early diagnostic strategies and improving long-term management outcomes. The aim of this study was to determine the predictive factors of PNP in a cohort of patients with DM. Materials and Methods: A cross-sectional study including 117 patients diagnosed with DM assessed for PNP was conducted. All patients were evaluated clinically and biologically. PNP was clinically assessed using the Toronto Clinical Scoring System (TCSS) score and sudomotor function by Sudoscan. Results: The patients included were mostly males with type 2 DM and metabolic syndrome phenotypes. Moreover, the patients with PNP were much older than those without PNP (65 [57–69] vs. 59.50 [46–68] years, p = 0.008), with a longer duration of DM (10 [6–15.50] vs. 5.5 (2–14] years, p = 0.019), and associated autonomic diabetic neuropathy (χ² = 24.382, p < 0.001). Furthermore, TCSS and Sudoscan were correlated with a history of PNP, especially Sudoscan, which showed a very good discriminative ability for diabetic neuropathy diagnosis (AUC = 0.816). In a multivariable logistic regression including age, DM duration, and HbA1c, age was independently associated with PNP, with each additional year increasing the odds of neuropathy by approximately 6% (OR = 1.06, 95% CI 0.02–1.09, p = 0.002). When age was excluded, DM duration showed a borderline association with PNP (OR = 1.055, CI95% 0.997–1.117), suggesting potential overlap between these variables. Adding sudomotor assessment to the initial model improved the model performance (AUC 0.70–0.72). Conclusions: Age emerged as the main independent predictor of diabetic neuropathy, highlighting the role of cumulative metabolic exposure in the development of neural damage. Moreover, sudomotor assessment may have a complementary role in PNP assessment. Full article

Background: Intraoperative high-volume diuresis is a common but under-recognized phenomenon during off-pump coronary artery bypass grafting (OPCABG). Its clinical correlates and implications for perioperative management remain incompletely characterized. Methods: This single-center retrospective cohort study included 1274 adults undergoing elective OPCABG between January and August 2025. High-volume diuresis was defined as urine output ≥ 5 mL·kg⁻¹·h⁻¹. Multivariable logistic regression was used to identify factors independently associated with intraoperative high-volume diuresis. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC). Results: High-volume diuresis occurred in 39.6% of patients. Older age, hypertension and greater intraoperative fluid infusion were independently associated with high-volume diuresis, whereas preoperative diuretic and greater cumulative exposure to systolic blood pressure < 100 mmHg were inversely associated with diuresis. The multivariable model demonstrated acceptable discrimination (AUC = 0.756). Postoperative outcomes, including acute kidney injury, duration of mechanical ventilation, intensive care unit stay, and hospital length of stay, did not differ between groups. Conclusions: Intraoperative high-volume diuresis during OPCABG reflects complex physiological and hemodynamic responses and can be anticipated based on preoperative and intraoperative factors. These findings support a more individualized interpretation of urine output and perioperative management strategies in OPCABG. Full article

Background and Objectives: The susceptibility of burn patients to infections with multidrug-resistant organisms (MDROs) is high. The aim of this study is to describe the local patterns of antimicrobial resistance in a Romanian burn unit and to identify risk factors associated with the acquisition of extensively drug-resistant (XDR) pathogens. Materials and Methods: We conducted a one-year, observational, retrospective single-centre cohort study including all burn patients with at least one positive culture admitted to our unit during 2024. In order to identify the pathogens and perform antibiograms, we used routine microbiological diagnostic tests. A multivariable logistic regression model was used to identify XDR risk factors. We also compiled a cumulative antibiogram using the first non-duplicate isolate per patient, following the CLSI M39 guidelines. Results: Among the 180 total admissions, 128 (71.1%) had at least one positive microbiological culture, resulting in 643 bacterial isolates out of 559 samples. The most frequently identified species were A. baumannii, P. aeruginosa, S. aureus, and K. pneumoniae. We isolated MDROs in 59.37% of patients, and 26.56% had at least one XDR pathogen isolated during hospitalisation. We identified three independent predictors for the isolation of XDR pathogens: a higher Abbreviated Burn Severity Index (ABSI) score (aOR 6.12; p = 0.001), hospital length of stay (LOS) (aOR 1.02; p = 0.030), and the number of bacterial species identified per sample, representing polymicrobial growth (aOR 5.91; p = 0.001). Conclusions: Our findings highlight a significant percentage of MDR and XDR pathogens and provide the foundation for antimicrobial stewardship measures, using the local cumulative antibiogram for empirical therapy. Full article

Background: Glycated hemoglobin (HbA1c) is widely used for the diagnosis and monitoring of diabetes mellitus; however, its interpretation is largely based on fixed diagnostic thresholds. This study moves beyond describing a glycemic continuum by translating the non-linear HbA1c–microvascular relationship into an individualized risk estimation framework. Methods: In this cross-sectional observational study, adult subjects from a real-world clinical cohort were analyzed using HbA1c as a continuous variable. Associations between HbA1c and metabolic parameters were assessed using correlation analysis. Linear regression was applied to evaluate the relationship between HbA1c and cumulative diabetes-related complication burden. Non-linear associations between HbA1c and the risk of presenting at least one complication were explored using restricted cubic spline logistic regression models. Additional risk estimation analyses focused on the HbA1c gray zone (5.5–6.4%). Results: HbA1c showed a strong continuous association with fasting plasma glucose (ρ = 0.73, p < 0.001) and was positively associated with cumulative complication burden (β = 0.016 per 1% increase in HbA1c, p = 0.009). Non-linear modeling revealed a progressive increase in complication risk beginning below the diagnostic threshold for diabetes, with an inflection of the risk curve within the HbA1c gray zone. Individuals within this interval exhibited a higher prevalence and increased odds of presenting at least one complication compared with lower HbA1c values, although some estimates did not reach statistical significance. Conclusions: HbA1c acts as a continuous and non-linear marker of metabolic stress, with potentially biologically meaningful increases in complication risk emerging below traditional diagnostic thresholds. We demonstrate a non-linear acceleration of microvascular risk within the 5.5–6.4% interval, rather than a simple linear gradient. These findings support the concept of a glycemic risk continuum and highlight the clinical relevance of the HbA1c sub-diagnostic interval for early risk stratification and preventive strategies. Full article

Background: Diabetic kidney disease is a major complication of type 2 diabetes mellitus (T2DM) and a leading cause of chronic kidney disease (CKD) worldwide. While diabetes duration is often considered a marker of cumulative metabolic exposure, its independent contribution to renal decline beyond aging and hypertension remains incompletely defined. Methods: We conducted a cross-sectional study including 250 adults with T2DM. Diabetes duration was analyzed both as a continuous variable and across four predefined strata (0–4, 5–9, 10–14, and ≥15 years). The primary endpoint was estimated glomerular filtration rate (eGFR), analyzed as a continuous outcome. Functional CKD was defined as eGFR < 60 mL/min/1.73 m². Linear and logistic regression models were constructed in unadjusted and adjusted forms (age, sex, BMI, hypertension, HbA1c). A sensitivity analysis modeling duration per 5-year increase was performed. Results: Mean eGFR declined significantly across duration strata (82.45, 84.27, 78.72, and 61.57 mL/min/1.73 m², respectively; p < 0.001). The prevalence of functional CKD increased markedly in patients with ≥15 years of diabetes (54.2%) compared with shorter-duration groups (~15–18%; p < 0.001). In linear regression, each additional year of diabetes was associated with a 1.32 mL/min/1.73 m² decline in eGFR (p < 0.001), remaining significant after adjustment (β = −0.85; p < 0.001). In logistic regression, each additional year was associated with a 10.7% increase in adjusted odds of CKD (OR = 1.11; 95% CI 1.04–1.17; p < 0.001). Each 5-year increment conferred a 66% increase in adjusted CKD risk (OR = 1.66; 95% CI 1.25–2.21; p < 0.001). Patients with ≥15 years of diabetes had nearly fourfold higher adjusted odds of CKD compared with those with 0–4 years (OR = 3.90; 95% CI 1.42–10.75; p = 0.008). Conclusions: Diabetes duration is strongly and independently associated with declining kidney function. Prolonged disease exposure confers a substantial increase in CKD risk, even after adjustment for age, hypertension, and metabolic factors. These findings highlight the progressive nephrotoxic impact of cumulative hyperglycemic exposure and underscore the need for early and sustained nephroprotective strategies in T2DM. Full article

Co-infection with human T-cell lymphotropic virus types 1 and 2 (HTLV-1/2) and HIV is not routinely screened for, yet it may significantly influence clinical progression, mortality, and quality of life in affected individuals. This study aimed to estimate the prevalence of HTLV-1/2 co-infection among adults living with HIV and to identify associated epidemiological factors in the Peruvian Amazon. A cross-sectional study was conducted including patients receiving antiretroviral therapy through the multidisciplinary TARGA program in Iquitos, Peru, during the second quarter of 2013. Screening for HTLV-1/2 antibodies was performed using enzyme-linked immunosorbent assay, with reactive samples confirmed by Line Immunoassay. Demographic and behavioral variables were collected, and prevalence odds ratios with 95% confidence intervals were estimated using logistic regression models. Among the 284 patients included, 28 were co-infected with HIV and HTLV-1/2, resulting in a prevalence of 10% with a 95% confidence interval of 6.5 to 14.1. In multivariable analysis, age over 35 years and having more than 10 lifetime sexual partners were independently associated with co-infection, with prevalence odds ratios of 12.4 and 3.6, respectively. HTLV-1/2 co-infection was highly prevalent among people living with HIV in the Peruvian Amazon, and the main risk factors identified suggest that cumulative exposure and sexual behavior play a significant role in the joint transmission of both retroviruses, supporting the need to consider systematic HTLV screening in endemic settings. Full article

Ischemic stroke remains a major cause of mortality and long-term disability worldwide, and improved strategies for identifying individuals at elevated vascular risk are needed. Serum autoantibodies have emerged as potential biomarkers reflecting vascular injury and immune activation; however, their integrative biological significance and incremental predictive value beyond established clinical risk factors remain unclear. We analyzed 833 participants, including patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA) and healthy controls. Serum levels of anti-PDCD11 antibody (Ab), anti-DNAJC2 antibody, and anti-PAI-1 (SERPINE1) antibody were quantified, and multivariable logistic regression and machine-learning (ML) models (logistic regression and random forest) were constructed using clinical variables with and without antibody markers. Model performance was evaluated using cross-validation, bootstrap-derived confidence intervals, calibration metrics, and reclassification indices. Model interpretability analyses, principal component analysis (PCA), unsupervised clustering, and propensity score matching were performed to explore latent biological structures. Clinical-only models demonstrated excellent discrimination (bootstrap Area Under the Curve (AUC) 0.917 for random forest and 0.919 for logistic regression). The addition of antibody markers yielded similar performance (AUC 0.913 and 0.923, respectively) without evidence of meaningful improvement in reclassification. However, SHapley Additive exPlanations (SHAP) analysis identified antibody markers as influential contributors following major clinical risk factors. PCA revealed a dominant antibody component explaining approximately 79% of the variance, which remained independently associated with stroke after age adjustment. Unsupervised clustering further identified a high-risk subgroup characterized by consistently elevated antibody levels. These findings support the presence of a latent antibody axis associated with vascular vulnerability. Although antibody markers did not substantially enhance global predictive performance, they captured integrated biological signals reflecting cumulative vascular and immunological stress. Autoantibody profiling may complement conventional risk assessment by improving biological characterization of stroke susceptibility. Prospective validation in independent cohorts is required prior to clinical implementation. Full article

Background: Tuberculosis (TB) remains a major public health concern globally, despite sustained declines in incidence in many countries. Kazakhstan has implemented long-term national TB control strategies; however, comprehensive nationwide analyses integrating temporal trends, demographic patterns, and treatment outcomes over the past decade remain limited. Methods: A nationwide retrospective registry-based analysis of programmatic TB treatment episodes was conducted using anonymized data from the national tuberculosis registry of the Ministry of Health of Kazakhstan. All registered TB cases from 1 January 2014 to 31 December 2023 were included. Treatment outcome was analyzed as the final end-of-episode programmatic status (favorable vs. unfavorable). Because the anonymized extract did not contain complete patient-level dates required to derive person-time (treatment initiation and event dates), time-to-event models were not applied; instead, factors associated with unfavorable end-of-treatment outcomes were assessed using multivariable logistic regression and reported as adjusted odds ratios (aORs) with 95% CIs. Unfavorable treatment outcomes were defined as death, treatment failure, loss to follow-up, and not evaluated or not recorded outcome, according to the national TB program outcome definitions. Results: A total of 93,985 TB cases were analyzed. The number of registered cases declined from 16,391 in 2014 to 6548 in 2023, corresponding to a cumulative reduction of 60.1% and an AAPC of −9.7% per year. TB incidence decreased in both sexes, although rates remained consistently higher among men. Over time, the peak incidence shifted toward older age groups, particularly among men. The proportion of new cases increased to 80.1% by 2023, while relapses and treatment failures declined. In multivariable analysis, unfavorable treatment outcomes were independently associated with male sex (aOR 1.25), older age, relapse, treatment after interruption, prior treatment failure, smear-positive disease (aOR 1.60), combined pulmonary and extrapulmonary involvement, and disseminated TB (ICD-10 A19). The risk of unfavorable outcomes increased during 2020–2021 and declined in 2022–2023. Conclusions: Kazakhstan has achieved a substantial and sustained reduction in TB incidence over the past decade. Nevertheless, marked demographic and clinical disparities persist, particularly among men, older patients, smear-positive cases, and individuals with prior or interrupted treatment. Targeted interventions focused on these high-risk groups may further improve treatment outcomes and support continued progress toward TB control. Full article

Psoriasis is a chronic inflammatory disease associated with an increased cardiovascular risk (CVR). The mechanisms linking psoriasis to coronary atherosclerosis have not yet been fully elucidated. A dynamic interplay between metabolic disturbances, immune mechanisms, and elevated atherogenic lipoprotein particles may contribute to the accelerated development of atherosclerosis. Patients with psoriasis (n = 104) without known coronary artery disease underwent coronary computed tomography angiography (CCTA) to detect subclinical coronary atherosclerosis. Clinical data, metabolic parameters and indices, lipid fractions including remnant cholesterol, and immunological markers (immunoglobulin A- IgA) were analyzed. Associations with CT-confirmed coronary stenosis were assessed using univariate and multivariate logistic regression models. Patients with coronary atherosclerosis exhibited a more adverse metabolic and lipid profile. Remnant cholesterol emerged as a strong independent predictor of coronary stenosis. Elevated IgA levels were associated with the presence of coronary atherosclerosis, suggesting a potential role of immune activation that extends beyond general systemic inflammation. Longer duration of psoriasis correlated with the presence of coronary atherosclerosis, highlighting the importance of cumulative inflammatory burden. Our findings indicate that subclinical coronary atherosclerosis in patients with psoriasis is closely associated with an immuno-metabolic risk profile encompassing atherogenic lipoprotein fractions and immune activation. These results underscore the need for a broader approach to cardiovascular risk assessment in this population, extending beyond the evaluation of traditional cardiovascular risk factors alone. Full article