Search Results (1,214)

Background: Adolescent pregnancies represent a significant global health challenge, with increased risks of maternal and neonatal complications. Traditional obstetrical risk assessment tools have limited applicability in this population due to unique physiological and anatomical characteristics. This study aimed to develop and validate novel predictive scores specifically designed for obstetrical risk stratification in adolescent pregnancies. Methods: A retrospective study was conducted over seven years (2018–2024) in Brasov County, Romania, including 1322 adolescent pregnancies (ages 12–16 years). Two novel predictive scores were developed: the Cervical Ripening Ultrasound Index (CRUI) for predicting successful vaginal delivery and labor induction, and the ADOLESRISK score for comprehensive obstetrical risk stratification. Statistical analysis included logistic regression, ROC curve analysis, and validation testing using SPSS 26.0 and R Studio version 4.3.2. Results: The CRUI score demonstrated superior predictive performance (AUC = 0.87, 95% CI: 0.84–0.90) compared to traditional Bishop score (AUC = 0.62, 95% CI: 0.58–0.66) for successful labor induction in adolescents. The ADOLESRISK score achieved 84% sensitivity and 76% specificity for predicting major obstetrical complications, significantly outperforming conventional risk assessment tools. Key risk factors incorporated included maternal age, educational level, nutritional status, and specific ultrasound parameters. Internal validation using train–test split methodology (70–30%) confirmed robust performance in the independent validation cohort (n = 397), with maintained discriminative ability (CRUI: AUC = 0.85, 95% CI: 0.80–0.90; ADOLESRISK: AUC = 0.82, 95% CI: 0.77–0.87) across different demographic subgroups. Conclusions: The CRUI and ADOLESRISK scores represent significant advances in adolescent obstetrical care, providing clinicians with tools for personalized risk assessment and management. Implementation of these scores could potentially reduce maternal complications by 25–30% and improve neonatal outcomes by 20–25%, representing a major contribution to adolescent reproductive health globally. Full article

Objectives: Lung cancer remains as the most common cause of cancer-related death. The possible relationships between inflammatory markers and lung cancer prognosis have yet to be clarified. In this study, we aimed to assess and compare various inflammatory markers and prognostic tests for their role in predicting mortality in patients with lung cancer who were admitted to the intensive care unit. Methods: A total of 229 patients diagnosed with small cell or non-small cell lung cancer who attended follow-up after treatment were included. The predictive performance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), modified Glasgow prognostic score (mGPS), Prognostic nutritional index (PNI), APACHE II score, and MPM II-Admission (Mortality Probability Models II-0) were assessed in terms of mortality status. We also performed multivariable logistic regression to determine whether any of these parameters were independently associated with mortality. Results: We included 229 patients into our study; the mean age was 66.17 ± 11.89 years. Among these, 135 (58.95%) patients died and 94 (41.05%) patients were discharged. When we evaluated the performance of the prognostic scores in predicting mortality, we found mGPS, MPM II-Admission, and APACHE II scores had the highest sensitivity, and MPM II-Admission, PNI, and APACHE II scores had the highest specificity. Multivariable regression revealed that PNI was the only inflammation-related parameter that was independently associated with mortality. Conclusions: PNI, APACHE-II, and MPM II-Admission may be used as easily accessible tests for mortality estimation in lung cancer patients admitted to the ICU. Full article

Pediatric craniofacial fractures represent a significant diagnostic challenge due to age-dependent anatomical variability, subtle fracture lines, and the limited availability of specialists during emergency care. Computed tomography (CT) remains the gold standard for fracture assessment; however, small or non-displaced fractures may be easily overlooked. Advances in artificial intelligence offer opportunities for automated support in injury detection. In this study, we developed a 2.5D deep learning model that uses multiplanar CT reconstructions (axial, coronal, sagittal) as a three-channel input to a ResNet-18 network with transfer learning. A total of 63 high-quality CT examinations were included and split into a training set (n = 44) and a validation set (n = 19). The preprocessing pipeline included isotropic resampling, bone-window normalization, and the generation of 384 × 384 images. Model performance was evaluated using ${\mathrm{AUC}}_{ROC}$, ${\mathrm{AUC}}_{PR}$, sensitivity, specificity, precision, F1-score, and threshold optimization using Youden’s index. The proposed model achieved ${\mathrm{AUC}}_{ROC}$ = 0.822 and ${\mathrm{AUC}}_{PR}$ = 0.855. At the optimal decision threshold (t = 0.54), sensitivity reached 0.556, specificity 1.000, and F1-score 0.714. Grad-CAM visualizations correctly highlighted fracture-related structures, which was confirmed in an independent clinical assessment. The results demonstrate the potential of the proposed model as a decision-support tool for pediatric craniofacial trauma, providing a foundation for future extensions toward radiomics and hybrid deep-radiomic pipelines. Full article

Background: Globally, the incidence of prostate cancer is estimated to increase by approximately 80% by 2040 compared to 2018. Bone is the most common metastatic site in prostate cancer and accurate prediction of bone metastasis in prostate cancer is crucial for deciding treatment decisions. The aim of this study is to evaluate the potential of G6PD activity level as a biomarker for predicting bone metastasis in patients with prostate cancer. Methods: A total of 56 patients participated in this study and participants included in the study were prostate cancer patients aged 19 years or older who visited YCH Hospital. We compared G6PD activity levels according to presence of bone metastasis. Also, ROC analysis was conducted to evaluate the predictive performance of G6PD activity level for bone metastasis. Optimal cutoff value of G6PD activity level was determined using Youden’s index and corresponding sensitivity and specificity were calculated. Results: The median G6PD activity was significantly higher in the group with bone metastasis than in the group without bone metastasis. According to ROC curve analysis, the area under the curve (AUC) was 0.78 (95% CI, 0.66–0.90). The optimal cutoff value of G6PD activity level for predicting bone metastasis was determined to be 11.5 U/g Hb. At this cutoff value, sensitivity and specificity were 0.81 and 0.73, respectively. Conclusions: G6PD activity is a complementary non-invasive biomarker for predicting bone metastasis in patients with prostate cancer. Full article

Cardiovascular–kidney–metabolic syndrome (CKMS) represents the intricate interconnection of cardiovascular, kidney, and metabolic disorders, with systemic inflammation now recognized as a key driver of both pathogenesis and prognosis. This systematic review aimed to synthesize current evidence on the prognostic value of inflammatory biomarkers in individuals with CKMS. A systematic search of PubMed, Embase, CINAHL, Web of Science, and Scopus were conducted to identify studies published between 1 January 2024 and 30 June 2025, following the recognition of CKMS as a distinct syndrome in December 2023. Eligible studies included adults (aged ≥ 18 years) with CKMS, that assesses one or more inflammatory markers and reported prognostic outcomes such as mortality or disease progression. Data extracted included study characteristics, biomarker types, outcome measures, and key findings. In addition to longitudinal cohorts, we included a small number of cross-sectional studies and treated them as association (non-prognostic) evidence analyzed in a separate stream from prognostic cohorts. Risk of bias was evaluated using the Quality in Prognostic Studies (QUIPS) tool. Due to considerable variability in prognostic outcomes, follow-up durations, and inflammatory indices, a meta-analysis was not feasible. Instead, a narrative synthesis was undertaken to summarize the evidence, identify consistent associations, and emphasize the need for standardized approaches and biomarker validation in future CKMS research. Analysis was conducted in line with the SWiM guidelines. Thirteen studies (n = 13) comprising 282,016 participants (100,590 males; 97,295 females) were included from 1404 initial records. Five of the studies were cross-sectional, providing information on associations rather than prognostic outcomes. Most were large-scale cohort studies conducted in the USA and China. Frequently assessed biomarkers included systemic inflammatory response index (SIRI), systemic immune-inflammation index (SII), high-sensitivity C-reactive protein to high-density lipoprotein cholesterol ratio (hs-CRP/HDL-C), dietary inflammatory index (DII), and triglyceride–glucose (TyG) index. Elevated levels of these biomarkers were consistently associated with higher risk of all-cause and cardiovascular mortality, CKMS progression, and adverse metabolic outcomes. This review highlights systemic inflammation as a critical and associated marker of CKMS prognosis. Inflammatory biomarkers may assist in hypothesis generation, but clinical utility remains to be established pending standardized adjustment and external validation. Because CKMS has only recently been operationalized, we limited inclusion to studies published from 1 January 2024 onward, enhancing definitional comparability but narrowing the evidence base and potentially emphasizing early-adopter regions (predominantly the U.S. and China). Accordingly, these findings should be interpreted as early signals that require replication in diverse settings and confirmation through longitudinal and interventional studies to inform integrative CKMS management strategies. Across observational studies, the certainty of evidence is low to moderate due to indirectness and imprecision; findings should be treated as associational signals pending external validation. Full article

Background/Objective: Central pathophysiological heterogeneity among Parkinson’s disease (PD) motor subtypes has been increasingly recognized, yet subtype-specific peripheral disturbances are limited. We aimed to characterize demographic, biochemical, and neurophysiological differences among PD motor subtypes, evaluate hematoinflammatory effects on peripheral and proximal motor conduction, and identify prognostic phenotypic biomarkers. Methods: A total of 110 participants (60 idiopathic PD patients (30 akinetic-rigid (AR), 30 tremor-predominant (TD), and 50 age- and sex-matched healthy controls (HCs)) were enrolled. Demographic data, nerve conduction studies (NCS) including detailed F-wave analysis, and hematoinflammatory markers were collected. Kruskal–Wallis, linear mixed models, multivariable regression, and ROC analyses were applied. Results: Hematoinflammatory indices were elevated in both subtypes compared with HCs, with more pronounced changes in AR (mean platelet volume (MPV) H = 4.367, p = 0.003; systemic inflammatory response index (SIRI) H = 3.929, p = 0.004). AR showed severe upper-limb–predominant motor involvement (median motor onset latency H = 55.30, p < 0.001; amplitude H = 50.52, p = 0.04; conduction velocity H = 49.15, p < 0.001), whereas TD showed milder, lower-limb–predominant changes (tibial motor onset latency H = 19.89, p < 0.001; amplitude H = 51.50, p = 0.02; velocity H = 15.39, p < 0.001). AR also demonstrated prolonged minimal (Fmin)/mean (Fmean) ulnar F-wave latencies versus TD (respectively, H = 10.51, p = 0.001; H = 8.79, p = 0.003), with both showing increased tibial Fmean/Fmax latencies. Platelet–eosinophil indices independently predicted ulnar F-latencies (B = 0.104–0.105; p = 0.001; model R² = 0.21–0.39). Select F-wave metrics yielded ROC AUCs ≈ 0.65–0.92 (ulnar Fmin AUC ≈ 0.92 vs. HCs); AR achieved sensitivity/specificity ≈ 70–74%. Conclusions: The AR subtype showed increased hematoinflammatory changes, specifically in MPV and SIRI, as well as a tendency toward more pronounced proximal motor and peripheral nerve conduction impairment compared with TD. Platelet–eosinophil indices and F-wave metrics may represent potential candidate markers for diagnostic or stratification purposes in PD subtyping and could possibly aid in prognostic estimation. Full article

Background and Objectives: Contrast-induced nephropathy (CIN) remains a significant complication following invasive coronary procedures. The HALP score—a composite index derived from hemoglobin, albumin, lymphocyte, and platelet counts—reflects nutritional and inflammatory status and may serve as a predictive biomarker for CIN. The aim of our study is to evaluate the relationship between the HALP score and the development of CIN in non-ST segment elevation myocardial infarction (NSTEMI) patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI). Materials and Methods: This retrospective study included 577 NSTEMI patients who underwent CAG or PCI between December 2022 and June 2025. Patients were divided into two groups based on CIN development. The HALP score was calculated and compared between groups. Results: Of the 577 NSTEMI patients included, 74 (12.8%) developed CIN. Patients who developed CIN were significantly older and had a higher prevalence of diabetes mellitus (DM), worse baseline renal function, and lower levels of hemoglobin, albumin, HDL cholesterol, and lymphocytes (p < 0.001). They also showed higher neutrophil counts, troponin-T levels, and received greater volumes of contrast media (CM). Oral antidiabetic drug (OAD) use was positively associated with CIN, while angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker use showed a negative association in univariate analysis. The HALP score was significantly lower in the CIN (+) group than CIN (−) group (15.88 ± 28.48 vs. 53.86 ± 28.48, p < 0.001). Multivariate analysis identified older age, DM, reduced left ventricular ejection fraction, elevated creatinine, increased neutrophils, lower hemoglobin, albumin, and lymphocytes, and higher CM volume as independent predictors of CIN. The HALP score remained a strong inverse predictor of CIN (OR: 0.895; 95% CI: 0.865–0.924; p < 0.001) and the Mehran score was positively associated with CIN risk (OR: 1.578; 95% CI: 1.154–2.087; p < 0.001). Covariate-adjusted receiver operating characteristic (AROC) analysis demonstrated that the HALP score showed good predictive accuracy (AUC: 0.780), with 74.3% sensitivity and 83.3% specificity at a cutoff of 24.1. Conclusions: The HALP score is a simple, accessible, and cost-effective biomarker with strong predictive value for CIN in NSTEMI patients undergoing invasive coronary procedures. Full article

Ordinary linear regression is the most common approach for modeling relationships between continuous outcomes and explanatory variables in epidemiological research. However, this method relies on restrictive assumptions—normality, homoscedasticity, and linearity—that are often violated in real-world biomedical data. When these assumptions fail, mean-based estimates may obscure important heterogeneity across the outcome distribution. This study aims to illustrate the methodological and interpretive advantages of quantile regression over ordinary regression in the analysis of epidemiological data. Secondary data were derived from a cross-sectional study of 1415 healthy Greek adults aged 25–82 years. Body mass index (BMI) served as the outcome variable, while sex, age, physical activity, dieting status, and daily energy intake were considered predictors. Both ordinary and quantile regression models were applied to estimate associations between BMI and its determinants across the 25th, 50th, 75th, and 90th quantiles. Ordinary regression identified positive associations of BMI with age and energy intake and a negative association with physical activity. Quantile regression revealed that these relationships were not constant across the BMI distribution. The inverse association with physical activity intensified at higher quantiles, and the gender effect reversed direction at the upper tail, suggesting heterogeneity was not captured by mean-based models. Quantile regression provides a distribution-sensitive alternative to ordinary regression, offering insight into covariate effects across different points of the outcome distribution and serving as both a robust analytical tool and an educational framework for applied epidemiological research. Full article

Background: Acute coronary syndromes (ACSs) remain a leading cause of death and disability. Since the publication of the 2023 ESC ACS guidelines, multiple studies and an ESC/EAS dyslipidaemia update have refined how clinicians diagnose, revascularize, and treat ACS across the care continuum. Content: This state-of-the-art review synthesizes advances from 2023 to 2025 across five domains. Diagnosis: High-sensitivity troponin-based accelerated pathways remain foundational; GRACE 3.0 improves calibration for early vs. delayed angiography, while selective use of CCTA and routine use of intracoronary imaging/physiology help define the mechanism and optimize PCI. Revascularization: complete revascularization continues to underpin care in multivessel disease, with recent data favouring culprit-only PCI acutely and staged non-culprit treatment during the index stay in most STEMI presentations, particularly with heart-failure physiology. Antithrombotic therapy: Aspirin remains critical early after ACS-PCI; emerging evidence supports shorter DAPT and aspirin withdrawal after 1 month in carefully selected, low-ischaemic-risk patients, whereas day-0 aspirin-free strategies in unselected ACS are not non-inferior. Secondary prevention: A “strike early and strong” approach to LDL-cholesterol—often with combination therapy in hospital—is emphasized, alongside nuanced roles for SGLT2 inhibitors and GLP-1 receptor agonists. Special populations and implementation: Sex- and age-aware tailoring (including MINOCA/SCAD evaluation), pragmatic bleeding-risk mitigation, digitally enabled cardiac rehabilitation, and registry-driven quality improvement translate evidence into practice. Summary: Contemporary ACS care is moving from uniform protocols toward risk-stratified, mechanism-informed pathways. We offer practical algorithms and checklists to align interventional timing, antithrombotic intensity/duration, and secondary prevention with individual patient risk—bridging new evidence to bedside decisions. Full article

Background: Magnesium is essential for mitochondrial function and muscle regeneration, potentially protecting against low muscle mass (LMM). We examined the association of dietary magnesium intake with LMM risk and skeletal muscle index (SMI), and whether inflammatory indicators mediate this relationship. Methods: A total of 5793 participants aged 20–59 years were included in this study from the National Health and Nutrition Examination Survey (NHANES) conducted from 2011 to 2018. To investigate the association of dietary magnesium intake with LMM and SMI, we applied weighted logistic regression model, linear regression model, restricted cubic spline analysis, subgroup analysis and sensitivity analysis. Inflammatory indicators were assessed using mediation analysis, including the C-reactive protein–albumin–lymphocyte (CALLY) index, neutrophil–platelet score (NP), platelet-to-albumin ratio (PAR) and red blood cell distribution width-to-albumin ratio (RAR) mediation. Results: In the fully adjusted model, participants in the highest magnesium quartile had a reduced risk of LMM, with OR of 0.33 (95% CI: 0.18, 0.60), and increased levels of SMI, with β values of 0.05 (95% CI: 0.04, 0.07). Mediation analysis showed that NP, PAR, and RAR mediated 18%, 13%, and 21% of the association between magnesium and LMM, respectively, and also acted as mediators of the relationship between magnesium and SMI, with mediation ratios of 32%, 24%, and 25%, respectively. Conclusion: Higher dietary magnesium intake was associated with lower LMM risk and higher SMI, partly mediated through inflammatory indicators involving NP, PAR, and RAR. This finding may provide a new perspective on the prevention and management of LMM. Full article

This study presents an ultra-sensitive dual-core photonic crystal fiber-based surface plasmon resonance (PCF-SPR) sensor for the detection of waterborne pathogens through refractive index (RI) variation. The proposed sensor integrates a bimetallic coating of silver and titanium dioxide (Ag–TiO₂). Silver ensures sharp plasmonic resonance, and TiO₂ enhances chemical stability and coupling efficiency. This dual-core configuration allows for increased interaction between the core-guided modes and the plasmonic interface. As a result, the sensor’s sensitivity improves significantly. The sensor can accurately detect analytes with an RI value of 1.28 to 1.43. It demonstrates a maximum wavelength sensitivity (WS) of 107,000 nm/RIU, an amplitude sensitivity (AS) of 2209.21 RIU⁻¹, a wavelength resolution of 9.35 × 10⁻⁷ RIU, and a figure of merit (FOM) of about 520. These results support the sensor’s ability to identify the presence of different pathogenic contaminants, such as E. coli, Vibrio cholerae, and Bacillus anthracis, based on their unique RI properties. This optimized design, high resolution, and potential for real-time detection enable this sensor to be a promising solution for environmental monitoring applications. Full article

Objectives: This systematic review and meta-analysis investigated whether salivary cortisol and alpha-amylase levels differ between patients with anorexia nervosa (AN) and healthy controls. Methods: A systematic literature search was conducted in PubMed, ScienceDirect, SpringerLink, and Scopus for relevant studies published up to December 2024. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Statistical heterogeneity was assessed using Cochran’s Q and the I² statistic. Results: Data on salivary alpha-amylase were extracted from six studies including 218 patients with AN and 220 healthy controls. No significant group difference was observed (SMD = −0.48; 95% CI, −1.05 to 0.10; I² = 86%), though sensitivity analysis indicated significantly lower levels in AN (SMD = −1.12; 95% CI, −2.16 to −0.09; I² = 82%). Salivary cortisol was assessed in 24 reports from 17 studies (517 patients with AN, 672 controls), revealing significantly higher levels in AN (SMD = 0.69; 95% CI, 0.54–0.85; I² = 30%). Sensitivity analyses showed stable effect sizes. Meta-regression indicated that neither age nor body mass index significantly moderated the results. Conclusions: Salivary cortisol may serve as a reliable, noninvasive biomarker for AN, with potential utility in early identification and prevention of disease progression. Full article

Thanks to both endogenous and exogenous antioxidants (AOs), the antioxidant defense system ensures redox homeostasis, which is crucial for protecting the body from oxidative stress and maintaining overall health. The food industry also exploits the antioxidant properties to prevent or delay the oxidation of other molecules during processing and storage. There are many classical methods for assessing antioxidant capacity/activity, which are based on mechanisms such as hydrogen atom transfer (HAT), single electron transfer (SET), electron transfer with proton conjugation (HAT/SET mixed mode assays) or the chelation of selected transition metal ions (e.g., Fe²⁺ or Cu¹⁺). The antioxidant capacity (AOxC) index value can be expressed in terms of standard AOs (e.g., Trolox or ascorbic acid) equivalents, enabling different products to be compared. However, there is currently no standardized method for measuring AOxC. Nanoparticle sensors offer a new approach to assessing antioxidant status and can be used to analyze environmental samples, plant extracts, foodstuffs, dietary supplements and clinical samples. This review summarizes the available information on nanoparticle sensors as tools for assessing antioxidant status. Particular attention has been paid to nanoparticles (with a size of less than 100 nm), including silver (AgNPs), gold (AuNPs), cerium oxide (CeONPs) and other metal oxide nanoparticles, as well as nanozymes. Nanozymes belong to an advanced class of nanomaterials that mimic natural enzymes due to their catalytic properties and constitute a novel signal transduction strategy in colorimetric and absorption sensors based on the localized surface plasmon resonance (LSPR) band. Other potential AOxC sensors include quantum dots (QDs, <10 nm), which are particularly useful for the sensitive detection of specific antioxidants (e.g., GSH, AA and baicalein) and can achieve very good limits of detection (LOD). QDs and metallic nanoparticles (MNPs) operate on different principles to evaluate AOxC. MNPs rely on optical changes resulting from LSPR, which are monitored as changes in color or absorbance during synthesis, growth or aggregation. QDs, on the other hand, primarily utilize changes in fluorescence. This review aims to demonstrate that, thanks to its simplicity, speed, small sample volumes and relatively inexpensive instrumentation, nanoparticle-based AOxC assessment is a useful alternative to classical approaches and can be tailored to the desired aim and analytes. Full article

Background: Hypertriglyceridemia is a lipid disorder characterized by elevated plasma triglyceride levels, and its prevalence increases with aging. This condition contributes substantially to morbidity and mortality in older adults. In settings with limited access to laboratory testing, especially in developing countries such as Brazil, identifying low-cost and easily applicable screening tools is essential. Objective: To investigate the discriminatory capacity of anthropometric indicators of obesity for screening hypertriglyceridemia in older adults. Methods: A population-based cross-sectional study was conducted with 223 community-dwelling older adults (57% women). Independent variables included body mass index (BMI), waist circumference (WC), abdominal circumference (AC), triceps skinfold thickness (TSF), body adiposity index (BAI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and conicity index (CI). Hypertriglyceridemia was defined as triglyceride levels ≥ 150 mg/dL. Discriminatory performance was assessed using receiver operating characteristic (ROC) curves, and associations were examined using Poisson regression with robust variance. Results: The prevalence of hypertriglyceridemia was 35%. Among older men, AC and CI showed the highest sensitivities (88.90% and 77.40%), while WHR and BMI demonstrated the highest specificities (83.10% and 76.90%). In older women, AC and BMI had the highest sensitivities (95.70% and 87.20%), whereas CI and WHtR exhibited the highest specificities (72.50% and 68.80%). All anthropometric indicators were positively associated with hypertriglyceridemia after adjustment for confounders. Conclusions: AC and CI demonstrated the strongest discriminatory capacity for screening older men with a higher probability of presenting hypertriglyceridemia, while AC and BMI showed the greatest discriminatory capacity among older women. In contrast, WHR and BMI had the highest ability to rule out the condition in older men, whereas CI and WHtR performed this role more effectively in older women. These findings show that low-cost anthropometric indicators can be used in a complementary manner, combining the most sensitive and the most specific measures to support an optimized triage process for hypertriglyceridemia in older adults, particularly in resource-limited settings. Full article

Introduction: Rheumatoid arthritis (RA) is associated with increased cardiovascular morbidity and mortality. Left ventricular diastolic dysfunction (LVDD) represents an early sign of cardiac involvement in RA. Objectives: This study aimed to evaluate the incidence of LVDD and the association of the neutrophil-to-lymphocyte ratio (NLR) and circulating FGF21 levels with chosen LVDD echocardiographic parameters, as well as to assess their diagnostic utility for LVDD in a cohort of patients with RA. Patients and Methods: A total of 51 RA patients (46 females, 5 males; average age 48.8 ± 8.2 years; median disease duration of 12 years) were enrolled. NLR and serum FGF21 levels were analysed for association with echocardiographic parameters of LVDD using univariate regression models. The diagnostic performance of these markers was evaluated by receiver operating characteristic (ROC) analysis. Results: LVDD was diagnosed in 10 patients (19.6%). The NLR was associated negatively with E velocity (β = −4.99, p = 0.02), E/A ratio (β = −0.16, p = 0.004), lateral and medial e′ velocities (β = −1.05, p = 0.038 and β = −0.97, p = 0.013, respectively), and positively with left atrial diameter (β = 2.08, p = 0.006). Serum FGF21 levels were negatively associated with the E/A ratio (β = −0.0005, p = 0.009) and lateral e′ velocity (β = −0.003, p = 0.04). ROC analysis demonstrated a greater diagnostic value for NLR (Youden index 0.30, cut-off point 2.26, sensitivity 50%, specificity 80%, and area under curve [AUC] 0.58) compared to FGF21 (Youden index 0.30, cut-off value 852.85 pg/mL, 100% specificity, 30% sensitivity, and AUC 0.48). Conclusions: NLR and FGF21 are associated with the echocardiographic parameters of the left ventricular diastolic dysfunction prior to the fulfilment of LVDD diagnostic criteria. RA patients with elevated NLR and FGF21 serum levels should be considered for LVDD screening. Full article