Diseases (Basel, Switzerland)最新文献

Background/Objectives: Chronic kidney disease (CKD) poses a significant health burden for individuals with diabetes mellitus, increasing morbidity and mortality. Understanding CKD and its risk factors is essential for early detection, effective management, and prevention of complications. This study aimed to assess CKD awareness as the primary outcome and to explore self-reported CKD prevalence and associated factors as secondary outcomes among patients with diabetes in the Northern Border Region, Saudi Arabia. Methods: A cross-sectional survey was conducted among 389 adults with a self-reported physician diagnosis of diabetes in the specified region, using a validated, self-administered online questionnaire. Data were analyzed to evaluate CKD awareness and identify perceived risk factors and factors associated with self-reported CKD. Results: Of the participants, 182 (46.8%) demonstrated good awareness of CKD, while the self-reported prevalence of CKD was 83 (21.3%). Males and unmarried participants were more likely to have good CKD awareness (p = 0.008 and 0.009, respectively). Significant associations were observed between self-reported CKD prevalence and age, sex, type of diabetes, family history of kidney disease, and comorbidities (all p < 0.05). Multivariate logistic regression showed that hypertension was strongly associated with self-reported CKD [aOR = 5.77; 95% CI: 3.12-10.67; p < 0.001], as was heart disease [aOR = 4.21; 95% CI: 1.35-13.13; p = 0.013]. Conclusions: Patients with diabetes in this region exhibited moderate awareness of CKD, with higher awareness among males and unmarried individuals. Hypertension and cardiac disease were significantly associated with self-reported CKD. These findings underscore the importance of targeted education, routine evidence-based screening, and structured management strategies for CKD within diabetes care and provide a basis for a regional strategic plan to strengthen CKD monitoring among patients with diabetes.

Background: The COVID-19 pandemic has contributed to the increase in maternal mortality due to the direct effects of the viral infection and the indirect effects caused by the overload of health services, and the resulting economic and social crises. This study aims to analyze sociodemographic, gestational, and clinical factors associated with maternal deaths from COVID-19 in Pernambuco between 2020 and 2021.

Method: The study included 37 cases (deaths) and 112 controls (survivors). Crude and adjusted odds ratios were estimated using conditional and Firth's penalized logistic regression models, respectively, to evaluate sociodemographic, gestational, and clinical factors.

Results: In the bivariate analysis, the main factors associated with maternal death from COVID-19 were ≤8 years of schooling, the postpartum period, multiparity, oxygen saturation below 95%, obesity, and diabetes mellitus. The presence of fever and cough was associated with a lower probability of death. The independent factors that remained associated with maternal death were the postpartum period (aOR: 80.78; 95% CI: 16.54-394.37), parity ≥ 1 (aOR: 5.74; 95% CI: 1.16-28.22), and oxygen saturation below 95% (aOR: 7.16; 95% CI: 1.37-37.44), with fever acting as a possible protective factor (aOR: 0.08; 95% CI: 0.01-0.42). Factors such as obesity and diabetes were not independent predictors in the final multivariable model.

Conclusions: The findings reinforce that maternal death is a multifactorial phenomenon. The relevance of this investigation lies in identifying clinical and obstetric vulnerability profiles in a region heavily impacted by the health crisis. Knowledge gained from past crises contributes to the improvement of public health strategies and clinical management protocols, aiming to mitigate preventable maternal deaths in future public health emergencies.

Background: Sarcopenia is a progressive muscle disorder associated with metabolic syndrome (MS), in which early impairments in muscle strength and quality precede muscle mass loss. Simple, non-invasive measures such as handgrip strength, estimated appendicular skeletal muscle mass (eASM), and phase angle (PA) may aid early detection, while adipokines link muscle dysfunction to metabolic regulation. Objective: In the present study, we aimed to evaluate the association between sarcopenia markers and PA in patients with MS. Methods: A cross-sectional study was conducted in patients with MS, at a third-level hospital in Mexico City. Sarcopenia was assessed by handgrip strength and eASM; body composition and PA were measured using bioelectrical impedance; and plasma adipokines were quantified by ELISA. Results: Seventy-four (mean age, 57.7 years; 75% female; BMI, 32.5 kg/m²) participants with MS were included. Handgrip strength correlated with eASM (r = 0.64; p < 0.01) and PA (rho = 0.43; p < 0.01), and eASM also correlated with PA (rho = 0.40; p < 0.01) and predicted higher PA values (OR = 2.74; p = 0.042). The sarcopenic subgroup had lower brachial circumference and plasma adiponectin. Conclusions: Sarcopenia is frequent in MS and associated with lower adiponectin, suggesting a vulnerable condition. Functional/structural markers of sarcopenia showed significant correlation with PA, whereas combined methods may enhance the early detection and management of muscle deterioration in metabolic disease.

Background: Pulmonary inflammation is a widely recognized characteristic of active tuberculosis (TB). Although standard TB treatment is effective, a substantial proportion of mycobacteriologically cured TB patients experience persistent pulmonary inflammation, which can lead to long-term lung impairment, post-tuberculosis lung disease (PTLD) and potentially TB recurrence.

Methods: We conducted a case-control study to compare host serum biomarker profiles in individuals with minimal (TLG < 50 SUVbw*mL, n = 37) versus extensive (TLG ≥ 50 SUVbw*mL, n = 34) persistent lung inflammation following completion of standard drug-sensitive TB treatment. Lung inflammation was measured by 18F-FDG PET/CT scan using total lung glycolysis (TLG) as a surrogate marker. All participants had negative sputum cultures at four months of TB treatment, and blood samples were collected at treatment completion (month six). A Luminex^® multiplex assay performed on the Bio-Plex^® 200 platform was used to analyze 48 host serum biomarkers involved in cytokine/chemokine signaling.

Results: Following multiple t-test analysis, fifteen biomarkers were significantly elevated (p < 0.05) in participants with extensive persistent lung inflammation compared to those with minimal inflammation. Among these, 14 demonstrated potential as discriminatory markers, with area under the curve (AUC) values ranging from 0.707 to 0.806, sensitivities ranging from 47.06% to 73.53%, and specificities ranging from 70.27% to 83.78%. Notably, 13 of these 16 candidate biomarkers significantly correlated with TLG values, further supporting their potential clinical utility.

Conclusion: We report associations between serum inflammatory mediators and persistent pulmonary inflammation following mycobacterial clearance in TB patients, highlighting their potential as diagnostic biomarkers that could potentially meet the target product profile (TPP) criteria.

Background/Objectives: Delirium is frequent and serious in older adults attending the emergency department (ED), but evidence on its pharmacological management in this setting is limited. This study aimed to quantify the pharmacological treatment of delirium in older adults in the ED and examine its association with subsequent hospital admission. Methods: A cross-sectional study was conducted between November 2021 and June 2022 in a Spanish ED. The sample included 153 adults aged 65 years or older with clinician-diagnosed delirium. Clinical, triage, and medication data were obtained from electronic medical records, and associations with hospital admission were analysed using multivariable logistic regression. Results: Ninety-one participants (59.5%) were hospitalised. Antipsychotic, analgesic, and benzodiazepine use was associated with hospitalisation. Absence of an underlying cause was a protective factor. The logistic regression model was significant. Conclusions: By identifying the most frequently administered pharmacological treatments for delirium in older adults in the ED and describing their association with hospitalisation, this study provides key insights into real-world clinical practice patterns in this setting.

Background: Hepatitis B virus (HBV) infection remains highly endemic in sub-Saharan Africa, where hepatitis delta virus (HDV) co-infection substantially worsens liver disease outcomes. Mauritania has long been suspected to be a high-burden setting for HBV-HDV co-infection, yet contemporary data describing its clinical and virological impact remain limited.

Methods: We conducted a hospital-based cross-sectional study at the National Institute of Hepato-Virology (INHV) in Nouakchott, including 401 HBsAg-positive patients. Demographic, clinical, biological, and virological data were collected. HDV serology and RNA testing were performed when available. Liver disease severity, including cirrhosis and hepatocellular carcinoma (HCC), was assessed using clinical, biological, and imaging criteria.

Results: HDV antibodies were detected in 31.9% of HBsAg-positive patients, confirming Mauritania as a hyper-endemic area for HDV. HDV co-infection was strongly associated with advanced liver disease, with HDV antibodies present in 86.4% of cirrhotic patients and 82.4% of those with HCC. Patients with HDV infection frequently exhibited suppressed HBV DNA levels, reflecting viral interference. A substantial proportion of patients presented with decompensated cirrhosis or HCC at diagnosis, and nearly 70% were treatment-naïve. Overall, HDV co-infection emerged as the principal driver of severe liver disease in this cohort.

Conclusions: HBV/HDV co-infection is highly prevalent in Mauritania and is associated with a wide clinical spectrum ranging from asymptomatic infection to decompensated cirrhosis and hepatocellular carcinoma. HDV co-infection is the principal driver of severe liver disease, often occurring despite low or undetectable HBV DNA levels. Systematic HDV screening among all HBsAg-positive individuals is urgently needed to improve risk stratification, guide therapeutic decisions, and reduce liver-related morbidity and mortality.

Background/objectives: To determine whether left atrial (LA) strain by speckle-tracking echocardiography can identify supraventricular arrhythmia risk in patients with type 2 diabetes mellitus (T2DM) without overt structural heart disease.

Methods: Prospective, single-center observational cohort study including 107 adults: 57 with T2DM and 50 age-matched controls. Participants underwent clinical assessment and echocardiography at baseline and 12 months. LA reservoir, conduit, and contractile strain (LASr, LAScd, LASct) were measured; left atrial volume indexed (LAVI) and LA stiffness index (LASI) were calculated. The primary endpoint was clinically significant supraventricular arrhythmia at 12 months on 24 h Holter (atrial fibrillation (AF)/atrial flutter (AFL) ≥ 30 s and/or excessive supraventricular ectopy). Predictors were assessed using penalized logistic regression and discrimination by ROC analysis.

Results: At baseline and 12 months, T2DM showed impaired LA mechanics versus controls (baseline: LASr 20.1 ± 5.7 vs. 25.8 ± 6.3%, LAScd -11.6 ± 4.2 vs. -15.6 ± 4.9%, LASct -9.9 ± 3.2 vs. -13.1 ± 3.7%; all p < 0.001) and higher LASI (0.4 ± 0.2 vs. 0.3 ± 0.1, p < 0.001). LAVI was higher in T2DM at 12 months (34.0 ± 7.0 vs. 29.9 ± 6.5 mL/m², p = 0.003). Supraventricular arrhythmias occurred in 20/57 patients (35.1%) of the T2DM vs. 1/50 patients (2.0%) of the control group (p < 0.001). Arrhythmias were assessed by 24 h Holter monitoring at the 12-month follow-up. In T2DM, LAScd provided the best single-parameter discrimination (AUC 0.692), with an optimal cut-off around -8% (sensitivity 55.6%, specificity 81.8%); a LAScd+left ventricular ejection fraction (LVEF) model improved AUC to 0.772.

Conclusions: In this prospective observational cohort, T2DM was associated with subclinical LA dysfunction and a higher burden of supraventricular arrhythmias. LAScd emerged as the most clinically informative LA deformation marker for arrhythmic risk stratification and may support targeted rhythm surveillance in diabetic patients. These findings require external validation in larger, independent multicenter cohorts.

Background/Objectives: Perinatal depression and anxiety are significant mental health concerns, and pharmacological treatments often pose considerable challenges. Therefore, this study aimed to evaluate the mental health status of pregnant and postpartum women and identify the factors affecting perinatal depression and anxiety. Methods: This cross-sectional study included 286 pregnant and postpartum women who completed questionnaires, including the Patient Health Questionnaire-9 (PHQ-9), Korean Version of the Edinburgh Postnatal Depression Scale (K-EPDS), and Generalized Anxiety Disorder-7 (GAD-7). Results: Symptoms of depression and anxiety were prevalent among participants. PHQ-9-positive cases were significantly less frequent in women from nuclear families, and their Pregnancy Stress Scale scores were significantly higher. K-EPDS-positive women had significantly lower rates of wanted pregnancies and marital satisfaction. GAD-7-positive cases showed significantly lower rates of wanted pregnancies, lower levels of social support, and higher Pregnancy Stress Scale scores. Conclusions: These findings highlight key psychosocial factors associated with perinatal depression and anxiety among pregnant and postpartum women, underscoring the importance of comprehensive mental health assessment during the perinatal period.

Background/objectives: Latent tuberculosis infection (LTBI) represents a critical reservoir for subsequent development of active tuberculosis (ATB) and poses significant challenges for early diagnosis and disease prevention. Traditional immunological assays, such as interferon-gamma release assays (IGRAs), are limited in their ability to reliably distinguish LTBI from ATB. Recent advances in high-throughput omics technologies and machine learning (ML) approaches offer new opportunities for precise, biomarker-based differential diagnostics.

Methods: Transcriptomic and proteomic profiling of host immune responses has revealed reproducible gene and protein signatures associated with LTBI and ATB. The integration of ML techniques-including feature selection, dimensionality reduction, multimodal learning, and explainable AI-facilitates the construction of robust diagnostic models. Single-modality signatures, derived from RNA-seq, microarrays, or proteomic assays, are complemented by multimodal approaches that incorporate soluble mediators, immunological readouts, and imaging-derived features. Deep learning frameworks, such as convolutional neural networks and transformer-based architectures, enhance the extraction of complex molecular and structural patterns from high-dimensional datasets.

Results: ML-driven analyses of transcriptomic and proteomic data consistently outperform conventional immunological tests in terms of sensitivity, specificity, and clinical applicability. Multimodal integration further improves diagnostic accuracy and robustness. These advances support the translational development of concise, quantitative reverse transcription PCR (qRT-PCR)-based biomarker panels suitable for routine clinical application, enabling early and reliable differentiation between LTBI and ATB. Overall, the combination of high-throughput omics and AI-based analytical frameworks provides a promising pathway for enhancing global tuberculosis diagnostics.

Conclusions: This review provides a structured and critical synthesis of transcriptomic and proteomic biomarker research for LTBI and ATB discrimination, with a particular emphasis on machine learning-based analytical frameworks. Unlike previous narrative reviews, we systematically compare data-generating platforms, modelling strategies, validation approaches, and sources of heterogeneity across studies. We further identify key translational barriers, including cohort homogeneity, platform dependency, and limited external validation, and propose directions for future research aimed at improving clinical applicability.