Search Results (3,943)

There are many controversies over the material sources of the Late Paleozoic strata in the Lower Yangtze region, and there is a lack of consensus on the basin source–sink system, which hinders the reconstruction of Late Paleozoic paleogeography and exploration of energy and mineral resources in the area. This study aimed to clarify the sedimentary provenance and tectonic background of the Upper Permian Longtan Formation in the Chizhou area of southern Anhui Province. The key objectives were to: (i) analyze the geochemical characteristics of sandstones using major, trace, and rare earth elements; (ii) determine the tectonic setting of the sediment source region based on discrimination diagrams; and (iii) integrate geochemical, sedimentological, and paleocurrent data to reconstruct the source-to-sink system. The geochemical data suggest that the sandstone samples exhibit relatively high SiO₂, Fe₂O₃, MgO, and Na₂O content and relatively low TiO₂, Al₂O₃, and K₂O content, consistent with average values of post-Archean Australian shale (PAAS) and the upper continental crust (UCC). The chondrite-normalized rare earth element patterns resemble PAAS, with enrichment in light REEs and depletion in heavy REEs. Tectonic discrimination diagrams indicate a provenance from active continental margins and continental island arcs, with minor input from passive continental margins. Combined with regional tectonic context and paleocurrent measurements, the results suggest that the Longtan Formation sediments primarily originated from the Neoproterozoic Jiangnan orogenic belt and the Cathaysia Block, notably the Wuyi terrane. These research results not only provide new geological data for further clarifying the provenance of Late Paleozoic sedimentary basins in the Lower Yangtze region but also establish the foundation for constructing the Late Paleozoic tectonic paleogeographic pattern in South China. Full article

Background/Objectives: Feigning spectrum behavior (FSB) is the exaggeration, fabrication, or false imputation of symptoms. It occurs in compensable injury with great cost to society by way of loss of productivity and excessive costs. The aim of this study is to identify feigning by developing cut scores on the long and short forms (SF) of the Orebro Musculoskeletal Pain Screening Questionnaire (OMPSQ and OMPSQ-SF) and the Perceived Stress Scale (PSS and PSS-4). Methods: As part of pre-screening for a support program, 40 injured workers who had been certified unfit for work for more than 2 weeks were screened once with the OMPSQ and PSS by telephone by a mental health professional. A control sample comprised of 40 non-injured community members were screened by a mental health professional on four occasions under different aliases, twice responding genuinely and twice simulating an injury. Results: Differences between the workplace injured people and the community sample were compared using ANCOVA with age and gender as covariates, and then receiver operator characteristics (ROCs) were calculated. The OMPSQ and OMPSQ-SF discriminated (ρ < 0.001) between all conditions. All measures discriminated between the simulation condition and workplace injured people (ρ < 0.001). Intraclass correlation demonstrated the PSS, PSS-4, OMPSQ, and OMPSQ-SF were reliable (ρ < 0.001). Area Under the Curve (AUC) was 0.750 for OMPSQ and 0.835 for OMPSQ-SF for work-injured versus simulators. Conclusions: The measures discriminated between injured and non-injured people and non-injured people instructed to simulate injury. Non-injured simulators produced similar scores when they had multiple exposures to the test materials, showing the uniformity of feigning spectrum behavior on these measures. The OMPSQ-SF has adequate discriminant validity and sensitivity to feigning spectrum behavior, making it optimal for telephone screening in clinical practice. Full article

Background: Claustrophobia is defined as the fear of enclosed spaces, and it is a rather common specific phobia. Although the Claustrophobia Questionnaire (CLQ) is a valid questionnaire to measure claustrophobia, there have been no studies validating this tool in Greek. Thus, our aim was to translate and validate the CLQ in Greek. Methods: We applied the forward–backward translation method to translate the English CLQ into Greek. We conducted confirmatory factor analysis (CFA) to examine the two-factor model of the CLQ. We examined the convergent and divergent validity of the Greek CLQ by using the Fear Survey Schedule-III (FSS-III-CL), the NEO Five-Factor Inventory (NEO-FFI-NL-N), and the Spielberger’s State-Trait Anxiety Inventory (STAI). We examined the convergent validity of the Greek CLQ by calculating Pearson’s correlation coefficient between the CLQ scores and scores on FSS-III-CL, NEO-FFI-NL-N, STAI-S (state anxiety), and STAI-T (trait anxiety). We examined the divergent validity of the Greek CLQ using the Fisher r-to-z transformation. To further evaluate the discriminant validity of the CLQ, we calculated the average variance extracted (AVE) score and the Composite Reliability (CR) score. We calculated the intraclass correlation coefficient (ICC) and Cronbach’s alpha to assess the reliability of the Greek CLQ. Results: Our CFA confirmed the two-factor model of the CLQ since all the model fit indices were very good. Standardized regression weights between the 26 items of the CLQ and the two factors ranged from 0.559 to 0.854. The convergent validity of the Greek CLQ was very good since it correlated strongly with the FSS-III-CL and moderately with the NEO-FFI-NL-N and the STAI. Additionally, the Greek CLQ correlated more highly with the FSS-III-CL than with the NEO-FFI-NL-N and the STAI, indicating very good divergent validity. The AVE for the suffocation factor was 0.573, while for the restriction factor, it was 0.543, which are both higher than the acceptable value of 0.50. Moreover, the CR score for the suffocation factor was 0.949, while for the restriction factor, it was 0.954. The reliability of the Greek CLQ was excellent since the ICC in test–retest study was 0.986 and the Cronbach’s alpha was 0.956. Conclusions: The Greek version of the CLQ is a reliable and valid tool to measure levels of claustrophobia among individuals. Full article

Background and Objectives: Risk stratification in acute heart failure (AHF) remains challenging, particularly in settings where biomarker availability is limited. Echocardiography offers valuable hemodynamic insights, but no single parameter fully captures the complexity of biventricular dysfunction and pressure overload. This study aimed to evaluate a novel echocardiographic index (ViRTUE Index–VTI-RVRA-TAPSE Unified Evaluation) integrating a peak systolic gradient between the right ventricle and right atrium (RV-RA gradient), tricuspid annular plane systolic excursion (TAPSE), the velocity–time integral in the left ventricular outflow tract (VTI LVOT), NT-proBNP (N-terminal pro–B-type Natriuretic Peptide) levels, and in-hospital mortality among patients with AHF. Materials and Methods: We retrospectively analyzed 123 patients admitted with AHF. Echocardiographic evaluation at admission included TAPSE, VTI LVOT, and the RV-RA gradient. An index was calculated as ${\displaystyle \frac{RV-RA gradient }{TAPSE x VTI LVOT}}$. NT-proBNP levels and in-hospital outcomes were recorded. Statistical analysis included correlation, logistic regression, and ROC curve evaluation. Results: The proposed index showed a significant positive correlation with NT-proBNP values (r = 0.543, p < 0.0001) and good discriminative ability for elevated NT-proBNP (AUC = 0.79). It also correlated with in-hospital mortality (r = 0.193, p = 0.032) and showed moderate prognostic performance (AUC = 0.68). Higher index values were associated with greater mortality risk. Conclusions: This novel index, based on standard echocardiographic measurements, reflects both systolic dysfunction and pressure overload in AHF. Its correlation with NT-proBNP and in-hospital mortality highlights its potential as a practical, accessible bedside tool for early risk stratification, particularly when biomarker testing is unavailable or delayed. Full article

Neurodevelopmental disorders (NDDs) significantly impact children’s health and development. They pose a substantial burden to families and the healthcare system. Challenges in early identification, accurate and timely diagnosis, and effective treatment persist due to overlapping symptoms, lack of appropriate diagnostic biomarkers, significant stigma and discrimination, and systemic barriers. Generative Artificial Intelligence (GenAI) offers promising solutions to these challenges by enhancing screening, diagnosis, personalized treatment, and research. Although GenAI is already in use in some aspects of NDD management, effective and strategic leveraging of evolving AI tools and resources will enhance early identification and screening, reduce diagnostic processing by up to 90%, and improve clinical decision support. Proper use of GenAI will ensure individualized therapy regimens with demonstrated 36% improvement in at least one objective attention measure compared to baseline and 81–84% accuracy relative to clinician-generated plans, customize learning materials, and deliver better treatment monitoring. GenAI will also accelerate NDD-specific research and innovation with significant time savings, as well as provide tailored family support systems. Finally, it will significantly reduce the mortality and morbidity associated with NDDs. This article explores the potential of GenAI in transforming NDD management and calls for policy initiatives to integrate GenAI into NDD management systems. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

The transition to efficient production requires innovative water control techniques to maximize irrigation efficiency and minimize waste. Analyzing and optimizing irrigation practices is essential to improve water use and reduce environmental impact. The aim of the research was to identify a discrimination method to analyze the different hydration levels in baby-leaf products. The species being researched was spinach, harvested at the baby leaf stage. Utilizing a large dataset of 261 wavelengths from the hyperspectral imaging system, the feature selection minimum redundancy maximum relevance (FS-MRMR) algorithm was applied, leading to the development of a neural network-based prediction model. Finally, a mathematical classification model K-NN (k-nearest neighbors type) was developed in order to identify a transfer function capable of discriminating the hyperspectral data based on a threshold value of absolute leaf humidity. Five significant wavelengths were identified for estimating the moisture content of baby leaves. The resulting model demonstrated a high generalization capability and excellent correlation between predicted and measured data, further confirmed by the successful training, validation, and testing of a K-NN-based statistical classifier. The construction phase of the statistical classifier involved the use of the experimental dataset and the critical humidity threshold value of 0.83 (83% of leaf humidity) was considered, below which the baby-leaf crop requires the irrigation intervention. High percentages of correct classification were achieved for data within two humidity classes. Specifically, the statistical classifier demonstrated excellent performance, with 81.3% correct classification for samples below the threshold and 99.4% for those above it. The application of advanced spectral analysis and artificial intelligence methods has led to significant progress in leaf moisture analysis and prediction, yielding substantial implications for both agriculture and biological research. Full article

Mozambique soils are known for having an unbalanced agronomic and environmental composition that results in poor agricultural production yields. However, agriculture is the main economic activity of Mozambique, and soils must be characterised for their elemental deficiencies and/or excesses. This paper sampled nine farms from the Manica and Sussundenga districts (Manica province) in three campaigns in 2021/2022, 2022/2023, and 2023/2024 (before and after the rainy seasons). They were subjected to a physical–chemical analysis to assess their quality from the fertility and environmental contamination point of view. Attending to the physical–chemical properties analysed, and for all the soils and sampling campaigns, a low concentration below the limit of detection for B of <0.2 mg/Kg for the majority of soils and a low concentration of Al < 0.025 mg/Kg for all the soils were obtained. Also, higher concentrations for the majority of soils for the Ca between 270 and 1634 mg/Kg, for the Mg between 41 and 601 mg/Kg, for the K between 17 and 406 mg/Kg, for the Mn between 13.6 and 522 mg/Kg, for the Fe between 66.3 and 243 mg/Kg, and for the P between <20 and 132 mg/Kg were estimated. In terms of texture and for the sand, a high percentage between 6.1 and 79% was found. In terms of metal concentrations and for all the soils of the Sussundenga district and sampling campaigns, a concentration above the reference value concentration for the Cr (76–1400 mg/Kg) and a concentration below the reference value concentration for the Pb (5–19 mg/Kg), Ba (13–120 mg/Kg) and for the Zn (10–61 mg/Kg) were evaluated. A multivariate data analysis methodology was used based on cluster and discriminant analysis. The analysis of twenty-three physical–chemical variables of the soils suggested four clusters of soils characterised by deficiencies and excess elements that must be corrected to improve the yield and quality of agricultural production. Moreover, the multivariate analysis of the metal composition of soil samples from the second and third campaigns, before and after the rainy season, suggested five clusters with a pristine composition and different metal pollutant compositions and concentrations. The information obtained in this study allows for the scientific comprehension of agricultural soil quality, which is crucial for designing agronomic and environmental corrective measures to improve food quality and quantity in the Manica and Sussundenga districts and ensure environmental, social, and economic sustainability. Full article

Objectives: Febrile neutropenia is a common oncologic emergency with significant morbidity and mortality. Although the MASCC (Multinational Association for Supportive Care in Cancer) score is widely used for risk stratification, its limited sensitivity and lack of laboratory parameters reduce its prognostic utility. This study aimed to evaluate whether incorporating serum lactate and CRP measurements into the MASCC score enhances its predictive performance for hospital admission and the 30-day mortality. Methods: This retrospective diagnostic accuracy study included adult patients diagnosed with febrile neutropenia in the emergency department of a tertiary care hospital between January 2021 and December 2024. The original MASCC score was calculated, and three modified models were derived: the MASCC-L (lactate/MASCC), MASCC-C (CRP/MASCC) and MASCC-LC models (CRP × lactate/MASCC). The predictive accuracy for hospital admission and the 30-day all-cause mortality was assessed using ROC analysis. Results: A total of 269 patients (mean age: 67.6 ± 12.4 years) were included; the 30-day mortality was 3.0%. The MASCC-LC model demonstrated the highest discriminative ability for mortality prediction (area under the curve (AUC): 0.995; sensitivity: 100%; specificity: 98%). For hospital admission prediction, the MASCC-C model had the highest specificity (81%), while the MASCC-LC model showed the best balance of sensitivity and specificity (both 73%). All the modified models outperformed the original MASCC score regarding both endpoints. Conclusions: Integrating lactate and CRP measurements into the MASCC score significantly improves its prognostic accuracy for both mortality and hospital admission in febrile neutropenic patients. The MASCC-LC model, relying on only three objective parameters, may serve as a practical and efficient tool for early risk stratification in emergency settings. Full article

Background: Pigmented superficial skin lesions pose a persistent diagnostic challenge due to overlapping clinical and dermoscopic appearances between benign and malignant entities. While histopathology remains the gold standard, there is growing interest in non-invasive imaging models that can preoperatively stratify malignancy risk. This methodological pilot study was designed to explore the feasibility and initial diagnostic performance of a novel radiology-adapted logistic regression approach. To develop and preliminarily evaluate a new logistic model integrating both structural (lesion size, depth) and vascular (Doppler patterns) ultrasonographic features for non-invasive risk stratification of pigmented superficial skin lesions. Material and Methods: In this prospective single-center pilot investigation, 44 patients underwent standardized high-frequency grayscale and Doppler ultrasound prior to excisional biopsy. Lesion size, depth, and vascularity patterns were systematically recorded. Three logistic regression models were constructed: (1) based on lesion size and depth, (2) based on vascularity patterns alone, and (3) combining all parameters. Model performance was assessed via ROC curve analysis. Intra-observer reliability was determined by repeated measurements on a random subset. Results: The lesion size and depth model yielded an AUC of 0.79, underscoring the role of structural features. The vascularity-only model showed an AUC of 0.76. The combined model demonstrated superior discriminative ability, with an AUC of approximately 0.85. Intra-observer analysis confirmed excellent repeatability (κ > 0.80; ICC > 0.85). Conclusions: This pilot study introduces a novel logistic framework that combines grayscale and Doppler ultrasound parameters to enhance non-invasive malignancy risk assessment in pigmented superficial skin lesions. These encouraging initial results warrant larger multicenter studies to validate and refine this promising approach. Full article

Background and Objectives: Galectin-3 (Gal-3), a pro-inflammatory cytokine, has been implicated in atherosclerosis and adverse cardiovascular outcomes. While its role in coronary artery disease (CAD) is increasingly recognized, its association with systemic atherosclerosis remains underexplored. Objective: To investigate serum Gal-3 levels in patients with CAD and evaluate correlations between CAD severity and extra-coronary atherosclerotic involvement (carotid, femoral, and radial territories). Materials and Methods: We prospectively enrolled 56 patients with CAD undergoing coronary angiography (42.8% with acute-ACS; 57.2% with chronic coronary syndromes-CCS). Gal-3 levels were measured within 24 h of admission. Atherosclerosis severity was assessed angiographically and through vascular ultrasound of the carotid, femoral, and radial arteries. Patients were stratified by median Gal-3 levels, and clinical follow-up was performed at 1 and 3 months. Results: Gal-3 levels were significantly higher in CAD vs. controls (20.7 vs. 10.1 ng/mL; p < 0.00001) and in ACS vs. CCS (22.18. vs. 17.93 ng/mL; p = 0.019). Gal-3 correlated positively with culprit lesion diameter stenosis (DS) (R = 0.30; p = 0.023) and maximum severity of additional treated lesions (R = 0.62; p = 0.006). Gal-3 also correlated positively with carotid plaque thickness (R = 0.32; p = 0.016), while patients with Gal-3 levels above the median showed increased median values for femoral plaque thickness (32.4 vs. 26.45 mm, p = 0.046). No correlation was found with radial artery calcification. Gal-3 showed moderate discrimination for ACS (AUC = 0.685; cut-off 20.18 ng/mL). On multivariate analysis age, DS, and ACS presentation were independent predictors of Gal-3 above 19.07 ng/mL. Conclusions: Gal-3 levels are elevated in ACS and correlate with atherosclerotic burden, particularly in coronary, carotid, and femoral territories. These findings support Gal-3 as a potential marker of lesion severity and systemic vascular involvement, highlighting its possible role in risk stratification and the monitoring of atherosclerotic disease progression. This study provides integrated insights into the impact of Gal-3 across multiple vascular beds by assessing them concurrently within the same patient cohort. Full article

Research concerning green marketing has predominantly focused on consumer behavior. However, aspects such as the extent to which Small and Medium Enterprises (SMEs) embrace green marketing values, their ability to implement the green marketing mix, and the integration of green marketing into their business culture are critically important. This research aims to provide the 4P (product, price, place, and promotion)-focused green marketing literature with a measurement tool to assess how SMEs implement green marketing practices. The study employed a descriptive design and possesses an exploratory nature. Scale development involved two stages: First, analyses were conducted on a pre-test sample of 159 individuals, revealing the initial scale structure. Second, these analyses were repeated on a larger group of 387 participants. The scale was finalized by confirming the consistency of results across both analyses. Statistical Package for the Social Sciences (SPSS) version 24 and Analysis of Moment Structures (AMOS) version 24 were utilized for descriptive statistics and the scale development process. The final validated 12-item scale demonstrates a robust three-factor structure (“Environmental Promotion”, ”Green Packaging”, and ”Green Distribution”), explaining 62.6% of the total variance. The scale exhibits excellent psychometric properties, including high internal consistency (Cronbach’s α = 0.912), strong model fit from Confirmatory Factor Analysis (CFA), and both convergent and discriminant validity, as indicated by an Average Variance Extracted (AVE) value of 0.605. The scale is deemed applicable to larger populations. Full article

Background/Objectives: Malnutrition is a common problem in children with cerebral palsy (CP). The aim of this study was to investigate the suitability and diagnostic performance of mid-upper arm circumference (MUAC) z-score in diagnosing wasting in children with CP, and its impact on diagnostic accuracy when evaluated concomitantly with additional clinical factors (birth weight, history of phototherapy). Methods: This single-center, cross-sectional study included 83 children with CP, aged 6 months–17 years, followed-up in our clinic. Anthropometric measurements (MUAC, Body Mass Index (BMI)) and clinical data (birth weight, history of phototherapy, Gross Motor Function Classification System (GMFCS)) were prospectively collected. Wasting was defined according to the BMI z-score ≤ −2 criteria. The diagnostic performance of MUAC z-score was evaluated by Receiver Operating Characteristic (ROC) analysis. The contribution of additional covariates was examined using logistic regression analysis and the backward elimination method. Results: MUAC z-score alone demonstrated good discrimination in diagnosing wasting with an Area Under the Curve (AUC) value between 0.805 and 0.821, but its sensitivity was limited (67.0%). No statistically significant difference was found in diagnostic performance between MUAC measurements of the right arm, left arm, and the unaffected arm (p > 0.050). In logistic regression analysis, MUAC z-score (p = 0.001), birth weight (p = 0.014), and a history of phototherapy (p = 0.046) were found to be significantly associated with wasting malnutrition. The simplified model including these variables yielded an AUC value of 0.876. Conclusions: MUAC z-score is a usable tool for wasting malnutrition screening in children with CP. Although its sensitivity is limited when used alone, its diagnostic accuracy increases when evaluated concomitantly with additional clinical factors such as birth weight and a history of phototherapy. This combined approach may offer clinicians a more robust tool for the early diagnosis and management of wasting malnutrition in children with CP. Full article

Background/Objectives: Despite the importance of parent mental health for child health, there are no global prevalence data on parental mental health symptoms when children are hospitalized. We aimed to describe depression and anxiety symptom prevalence and associated factors among parents of hospitalized children. Methods: We conducted this 14-country prospective cohort survey with parents/primary caregivers staying at a nearby Ronald McDonald House^® during their child’s hospital treatment. We used the Hospital Anxiety and Depression Scale to measure depression and anxiety symptoms and validated scales and theory-based questions to measure parent, family, and child covariates. We calculated the prevalence of clinically significant or concerning symptoms of depression and anxiety, and used multivariable regression analyses to examine associations between covariates and outcomes. Results: Among 3350 participants, 1789 (49.7%) reported depression symptoms and 2286 (69.0%) reported anxiety symptoms. Worry about housing and poorer ratings of their child’s health were associated with increased risk of depression symptoms. Poorer rating of the child’s health, living with a partner, and discrimination in daily life were associated with increased risk of anxiety symptoms. Higher levels of self-care, hospital family-centered care, and social support were associated with reduced risk of depression symptoms. Higher levels of self-care and social support were associated with reduced risk of anxiety symptoms. Conclusions: Clinically significant or concerning depression and anxiety symptoms are common among parents of hospitalized children globally. Hospitals should consider offering routine mental health symptom screening and preventative mental health and support services to all parents. Full article

Background and Aims: Sepsis-associated acute kidney injury (S-AKI) is common and is associated with poor outcomes. This prospective observational study aimed to assess the predictive value of four novel biomarkers—syndecan-1 (SDC1), neutrophil gelatinase-associated lipocalin (NGAL), proenkephalin (PENK), and presepsin (PSPN)—for renal outcomes and mortality in septic ICU patients. Methods: Serum biomarker levels were measured in serum samples collected at the time of sepsis diagnosis on the basis of the Sepsis-3 criteria. Acute kidney injury (AKI) was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, and patients were grouped by the presence of AKI, renal replacement therapy requirement (RRT), and intensive care unit (ICU) survival. Demographic, clinical, laboratory, and severity score data were compared between groups to evaluate the predictive performance of biomarkers and clinical parameters. Results: Of the 140 septic patients included, 55.0% developed AKI, 17.2% required RRT, and the ICU mortality rate was 50.0%. SDC1 was independently associated with both AKI (OR: 1.201; p = 0.024) and RRT initiation (OR: 1.260; p = 0.004). It also demonstrated the highest predictive performance for RRT (AUC: 0.715; p = 0.001) and a significant AUC for AKI evaluation (AUC: 0.659; p = 0.002). NGAL levels were significantly elevated in patients with AKI and higher SOFA scores but were not independently predictive. PENK and PSPN were not significantly associated with any renal outcome or mortality. The combined SOFA–SDC1 model improved discrimination for both AKI (AUC: 0.770) and RRT (AUC: 0.737), surpassing individual predictors. Conclusions: SDC1 emerged as the most reliable biomarker for assessing AKI and predicting the need for RRT, highlighting its potential role in early renal risk stratification among critically ill patients. Full article