Curve Analysis Research Articles

Comprehensive analysis of risk factors associated with submucosal invasion in patients with early-stage gastric cancer

BACKGROUND Submucosal invasion in early-stage gastric cancer (GC) is a critical determinant of prognosis and treatment strategy, significantly influencing the risk of lymph node metastasis and recurrence. Identifying risk factors associated with submucosal invasion is essential for optimizing patient management and improving outcomes. AIM To comprehensively analyze clinical, imaging, and endoscopic characteristics to identify predictors of submucosal invasion in patients with early-stage differentiated GC. METHODS A retrospective study was conducted at our institution from January 2019 to January 2023, including 268 patients diagnosed with early-stage differentiated GC who underwent surgical resection or endoscopic submucosal dissection. Data were collected on demographic, clinical, imaging, and endoscopic characteristics, with endoscopic images reviewed independently by two gastroenterologists. Statistical analysis included univariate and multivariate logistic regression to identify significant predictors of submucosal invasion, and receiver operating characteristic (ROC) curve analysis to evaluate the predictive value of continuous variables. RESULTS A total of 268 patients were included, with 178 males and 90 females, and a mean age of 61.5 ± 9.8 years. Univariate analysis showed that male gender, history of alcohol consumption, smoking, and computed tomography-detected gastric wall thickening were more prevalent in patients with submucosal invasion. Significant endoscopic predictors included tumor location in the upper two-thirds of the stomach, depressed morphology, marginal elevation, and high color differences on white-light endoscopy (WLE) and linked color imaging (LCI). Multivariate analysis identified upper stomach location [odds ratio (OR): 5.268], depressed type (OR: 5.841), marginal elevation (OR: 4.132), and LCI color difference ≥ 18.1 (OR: 4.479) as significant predictors. ROC analysis showed moderate predictive value for lesion diameter, WLE, and LCI color differences (area under the curve: 0.630, 0.799, and 0.760, respectively). CONCLUSION Depressed-type lesions, marginal elevation, location in the upper two-thirds of the stomach, and significant color differences on LCI are high-risk indicators for submucosal invasion. These findings suggest that such lesions warrant more aggressive intervention to prevent disease progression and improve patient outcomes.

Role of serum procalcitonin in differentiating disease flare and systemic bacterial infection among febrile children with known chronic rheumatic diseases: a cross-sectional study

Objectives. To evaluate the role of serum procalcitonin (PCT) as a diagnostic tool to differentiate bacterial sepsis from flare-ups during febrile episodes in children with known rheumatic disorders compared to other inflammatory markers like C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). Methods. Previously diagnosed patients with known rheumatic disorders presenting in emergency or outpatient departments with febrile episodes were included in the study. Blood samples were collected upon admission to test for signs of infection, including serum PCT levels with routine laboratory and radiological tests. Patients with juvenile idiopathic arthritis (JIA) and systemic lupus erythematosus (SLE) were stratified using the Juvenile Arthritis Disease Activity Score (JADAS-27) and SLE Disease Activity Index (SLEDAI) respectively. Patients without bacterial focus with high disease activity were included in the flare-up group and the rest in the sepsis cohort. The diagnostic value of PCT was calculated using receiver operating characteristic (ROC) curve analysis. Results. In the study (N=73), 41 (56.2%) patients were previously diagnosed with JIA and 28 (38.3%) had SLE. 38 patients had definite evidence of sepsis and 35 had disease flare-ups as per respective disease activity scores. There was a significant difference in PCT and CRP among the flare-up and sepsis groups. For detecting sepsis, the area under curve (0.959), sensitivity (94.7%), and specificity (74.3%) of PCT at a cut-off of 0.275 ng/mL were significantly better than those of CRP. Conclusion. PCT is a better diagnostic test than CRP or ESR during febrile episodes in differentiating flare-ups from infection and PCT >0.275 ng/mL indicates bacterial infection with good specificity and sensitivity in children with low disease activity.

Development of a novel diagnostic model to monitor the progression of metabolic dysfunction-associated steatotic liver disease to hepatocellular carcinoma in females.

The onset of metabolic dysfunction-associated steatotic liver disease-associated hepatocellular carcinoma (MASLD-HCC) is insidious and exhibits sex-specific variations. Effective methods for monitoring MASLD-HCC progression in females have not yet been developed. Transcriptomic data of female liver tissue samples were obtained from multiple public databases. Differentially expressed genes (DEGs) in MASLD-HCC were identified using differential expression and robust rank aggregation analyses. Diagnostic prediction models for MASLD (DP.MASLD) and HCC (DP.HCC) were developed and validated using elastic net analysis, and diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Bioinformatics was used to assess the pathogenesis of MASLD-HCC. Seven overlapping DEGs were identified in female patients with MASLD and HCC: AKR1B10, CLEC1B, CYP2C19, FREM2, MT1H, NRG1, and THBS1). The area under the ROC curve (AUC) values for the training and validation groups of the DP.MASLD model were 0.864 and 0.782, 0.932 and 1.000, and 0.920 and 0.969 when differentiating between the steatosis and normal liver, steatohepatitis and steatosis, and steatohepatitis and normal liver groups, respectively. The AUCs for DP.HCC were 0.980 and 0.997 in the training and validation groups, respectively. The oncogenesis of female MASLD-HCC is associated with molecular pathways, including cytochrome P450-associated drug metabolism, tyrosine metabolism, fatty acid degradation, focal adhesion, extracellular matrix receptor interactions, and protein digestion and absorption. A novel and effective method to quantitatively assess the risk of MASLD-HCC progression in female patients was developed, and this method will aid in the generation of precise diagnostic, preventive, and therapeutic strategies.

The value of restriction spectrum imaging in predicting lymph node metastases in rectal cancer: a comparative study with diffusion-weighted imaging and diffusion kurtosis imaging.

To investigate the efficacy of three-compartment restriction spectrum imaging (RSI), diffusion kurtosis imaging (DKI), and diffusion-weighted imaging (DWI) in the assessment of lymph node metastases (LNM) in rectal cancer. A total of 77 patients with rectal cancer who underwent pelvic MRI were enrolled. RSI-derived parameters (f1, f2, and f3), DKI-derived parameters (Dapp and Kapp), and the DWI-derived parameter (ADC) were calculated and compared using a Mann-Whitney U test or independent samples t-test. Logistic regression (LR) analysis was used to identify independent predictors of LNM status. Area under the receiver operating characteristic curve (AUC) and Delong analysis were performed to assess the diagnostic performance of each parameter. The LNM-positive group exhibited significantly higher f1 and Kapp levels and significantly lower f3, Dapp, and ADC levels compared to the LNM-negative group (p < 0.05). There was no difference in f2 levels between the two groups (p = 0.783). LR analysis showed that Dapp and Kapp were independent predictors of a positive LNM status. AUC and Delong analysis showed that DKI (Dapp + Kapp) exhibited significantly higher diagnostic efficacy (AUC = 0.908; sensitivity = 87.10%; specificity = 86.96%) than RSI (f1 + f3) and DWI (ADC), with AUCs were 0.842 and 0.771 (Z = 2.113, 3.453; p = 0.035, < 0.001, respectively). The AUC performance between RSI and DWI was also statistically significant (Z = 1.972, p = 0.049). The RSI model is superior to conventional DWI but inferior to DKI in differentiation between LNM-positive and LNM-negative rectal cancers. Further study is needed before it could serve as a promising biomarker for guiding effective treatment strategies. The three-compartment restriction spectrum imaging was able to differentiate between LNM-positive and LNM-negative rectal cancers with high accuracy, which has the potential to serve as a promising biomarker that could guide treatment strategies. Three-compartment restriction spectrum imaging could differentiate lymph node metastases in rectal cancer. Diffusion kurtosis imaging and diffusion-weighted were associated with lymph node metastases in rectal cancer. The combination of different parameters has the potential to serve as a promising biomarker.

Reliability and Optimal Cut-Off Points of the Test for Upper Limb Apraxia (TULIA) for Spanish-Speaking Post-Stroke Patients.

To evaluate the reliability, identify the optimal cut-off points, and determine the diagnostic accuracy of the TULIA Apraxia test in a sample of Spanish-speaking post-stroke patients. Cross-sectional. Public primary care. 201 post-stroke patients. Reliability was assessed using Cronbach's alpha. Cut-off points were identified for each TULIA Apraxia sub-test and stratified for age (≤65 years, > 65 years) using ROC curve analysis, area under the curve, and Youden index. Diagnostic accuracy was evaluated using sensitivity, specificity, and predictive values. Cronbach's alpha of the sub-tests varied from 0.716 (95% CI 0.653-0.772) for pantomime intransitive to 0.824 (95% CI 0.784-0.858) for imitation non-symbolic. Cut-off points ranged from ≤25 to ≤35 points. For individuals aged ≤65 years, the cut-offs that best balanced sensitivity and specificity were ≤25 points for detecting alterations in imitation transitive and ≤33 points for pantomime non-symbolic. For individuals over 65 years, the imitation transitive cut-off (≤26 points) presented the most adjusted balance. The minimum positive predictive value was 0.667 (95% CI 0.542-0.777), indicating that the TULIA Apraxia tests correctly classified more than 67% of patients with apraxia. The minimum negative predictive value was 0.763 (95% CI 0.644-0.859), showing that the test accurately identified more than 76% of patients without apraxia. The TULIA Apraxia test is reliable in Spanish-speaking post-stroke patients. Optimal cut-off points, along with their respective sensitivity and specificity values, exhibit adequate test accuracy. Predictive values indicate that the test correctly identifies individuals with and without apraxia.

Utilizing network analysis to identify core items of quality of life for children with autism spectrum disorder.

The purpose of this study was to develop and validate an ultra-short scale called the Quality of Life for Children with Autism Spectrum Disorder 3 (QOLASD-C3) from the full 16-item QOLASD-C scale. We first used network analysis to identify three core items to be retained on the QOLASD-C3 scale. Second, we used Cronbach's alpha and Pearson Product Moment correlations to determine the reliability and validity of the scale. Third, an optimal cut-off score of 6 was identified for the using receiver operating characteristic curve analysis. Finally, we used logistic regression to examine the similarities in the classification status based on demographic characteristics between the quality of life (QOL) status using the QOLASD-C and the QOLASD-C3 scales. Results were similar across the two versions and suggested variations in QOL status based on race/ethnicity, autism spectrum disorder (ASD) severity, and parents' socio-economic status. Implications for research and practice are discussed.

A two-stage model for precise identification and Gleason grading of clinically significant prostate cancer: a hybrid approach.

Accurate identification and grading of clinically significant prostate cancer (csPCa, Gleason Score ≥ 7) without invasive procedures remains a significant clinical challenge. This study aims to develop and evaluate a two-stage model designed for precise Gleason grading. The model initially uses radiomics-based multiparametric MRI to identify csPCa and then refines the Gleason grading by integrating clinical indicators and radiomics features. We retrospectively analysed 399 patients with PI-RADS ≥ 3 lesions, categorising them into non-significant prostate cancer (nsPCa, 263 cases) and csPCa (136 cases, subdivided by GGs). Regions of interest (ROIs) for the prostate and lesions were manually delineated on T2-weighted and apparent diffusion coefficient (ADC) images, followed by the extraction of radiomics features. A two-stage model was developed: the first stage identifies csPCa using radiomics-based MRI, and the second integrates clinical indicators for Gleason grading. Model efficacy was evaluated by sensitivity, specificity, accuracy and area under the curve (AUC), with external validation on 100 patients. The first-stage model demonstrated excellent diagnostic accuracy for csPCa, achieving AUCs of 0.989, 0.982 and 0.976 in the training, testing and external validation cohorts, respectively. The second-stage model exhibited commendable Gleason grading capabilities, with AUCs of 0.82, 0.844 and 0.83 across the same cohorts. Decision curve analysis supported the clinical applicability of both models. This study validated the potential of T2W and ADC image radiomics features as biomarkers in distinguishing csPCa. Combining these features with clinical indicators for csPCa Gleason grading provides superior predictive performance and significant clinical benefit.

Comparative analysis of MRI-based VBQ and EBQ score for predicting cage subsidence in PILF surgery

Background contextAs lumbar degenerative diseases become more prevalent in an aging population, there is an increasing demand for surgical interventions, such as posterior lumbar interbody fusion (PLIF). However, cage subsidence (CS), observed in 23.9–54% of cases postoperatively, remains a significant complication. Several factors, including age, bone quality, and endplate damage, contribute to the risk of CS, with bone quality being among the most critical determinants. Although DEXA and QCT are widely employed to assess bone density, their routine use in preoperative evaluations is restricted by cost considerations and radiation exposure. Recent studies suggest that MRI-based vertebral body quality (VBQ) and endplate bone quality (EBQ) score offer a viable, non-invasive alternative for evaluating bone quality; however, there is limited research comparing their predictive value for CS.MethodsIn this retrospective study, 165 patients undergoing single-level PLIF surgery were included. MRI-based VBQ and EBQ score were calculated using T1-weighted images, and preoperative QCT was employed as a clinical standard. Cage subsidence was assessed based on postoperative imaging at 12-month follow-up. Statistical analyses, including t-tests, chi-square tests, and ROC curve analyses, were used to evaluate the predictive accuracy of VBQ and EBQ for CS.ResultsThe study’s findings demonstrated that both VBQ and EBQ scores were significantly correlated with QCT measurements, thereby validating their utility as indicators of bone quality. ROC analysis revealed that VBQ had superior predictive value for CS (AUC = 0.814) compared to EBQ (AUC = 0.719), with both scores demonstrating significant clinical utility in identifying patients at risk for CS. Notably, VBQ exhibited a stronger correlation with preoperative clinical outcomes compared to EBQ, underscoring its greater reliability as a predictor.ConclusionsThis study highlights the effectiveness of MRI-based VBQ and EBQ score as practical, non-invasive tools for assessing bone quality preoperatively, with VBQ demonstrating superior predictive performance for CS risk. The findings underscore the potential of integrating these MRI-based assessments into routine preoperative planning to improve patient outcomes and minimize complications associated with PLIF surgery.

Clinical significance of lactate-to-albumin ratio in patients with influenza A virus-induced acute respiratory distress syndrome: a single-center retrospective study

BackgroundThe lactate-to-albumin ratio (LAR) is predictive of disease prognosis in some cases. However, the clinical significance of LAR in patients with influenza A virus-induced acute respiratory distress syndrome (ARDS) has yet to be explored. This study aims to investigate whether LAR can be used as a predictor of influenza A virus-induced ARDS.MethodsIn this single-center retrospective study, we enrolled 105 patients with influenza A virus pneumonia into the study and divided the patients into an ARDS group (74 patients) and a non-ARDS group (31 patients) during hospitalization. Clinical characteristics and laboratory data were collected within 24 h after admission. We explored the risk factors for ARDS using logistic regression analysis. The predictive performance of potential risk factors for ARDS and ARDS-associated complications were evaluated by receiver operating characteristic (ROC) curves, and Pearson’s correlation analysis was used to evaluate the correlations between risk factors and clinical and laboratory variables.ResultsLAR was an independent predictor for the development of ARDS in patients with influenza A virus pneumonia and was significantly predictive for ARDS. LAR’s area under the curve (AUC) was higher than that of lactate and albumin alone; its AUC was 0.878, with a sensitivity of 71.6% and a specificity of 96.8%. The optimal ROC threshold for distinguishing ARDS from non-ARDS cases was 44.81 × 10− 3. Correlation analysis indicated that LAR was positively associated with duration of invasive ventilation, and APACHE II and SOFA scores in ARDS patients but was negatively associated with PaO2/FiO2 (p < 0.001). Subsequent ROC curve analysis determined that LAR was a robust predictor for the 14-day invasive ventilation (AUC = 0.924), septic shock (AUC = 0.860), and hepatic injury (AUC = 0.905) in hospitalized ARDS patients. It also showed a promising predictive value for 28-day mortality (AUC = 0.881).ConclusionLAR strongly predicted ARDS development in patients with influenza A virus pneumonia. It showed a significant correlation with disease severity and provided promising predictive efficiency for extrapulmonary complications and 28-day mortality in patients with influenza A virus-induced ARDS.

Day 3 neutrophil-to-lymphocyte ratio and its derived indices predict 90-day poor outcomes following mechanical thrombectomy in acute ischemic stroke patients

ObjectiveTo investigate the dynamic changes in neutrophil–to–lymphocyte ratio (NLR) and its derived indices following mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and evaluate their predictive value for prognosis.MethodsThis single-center retrospective cohort study included AIS patients who underwent MT at Zhongshan Hospital of Xiamen University from January 2018 to February 2024. Peripheral blood samples were collected on admission, day 1, and day 3 after MT to determine the NLR, derived NLR (dNLR), and neutrophil–monocyte–to–lymphocyte ratio (NMLR). The primary endpoint was poor functional outcome at 90 days (modified Rankin scale score 3–6). The secondary endpoints included post-operative hemorrhagic transformation, malignant cerebral edema, in-hospital mortality, and 90-day all-cause mortality. Receiver operating characteristic (ROC) curve analysis was used to evaluate predictive performance, and multivariate logistic regression models were employed to explore the independent associations between inflammatory markers and prognosis.ResultsA total of 423 eligible patients were included. Both groups showed similar dynamic trends in inflammatory markers, peaking on day 1 post-MT and subsequently declining. However, the poor outcome group (n = 255, 60.28%) maintained higher levels on day 3, whereas the good outcome group showed a significant decreasing trend. ROC curve analysis revealed that the NLR (AUC = 0.85, 95% CI: 0.81–0.89), dNLR (AUC = 0.86, 95% CI: 0.82–0.89), and NMLR (AUC = 0.85, 95% CI: 0.81–0.89) on day 3 post-MT had the strongest predictive power for 90-day poor outcomes. After comprehensive adjustment for confounders, these inflammatory markers were independently associated with 90-day poor outcomes: for each unit increase in the NLR, the risk of poor outcome increased by 38% (OR = 1.38, 95% CI: 1.28–1.49, p &amp;lt; 0.001); for dNLR, it increased by 104% (OR = 2.04, 95% CI: 1.73–2.40, p &amp;lt; 0.001); and for NMLR, it increased by 35% (OR = 1.35, 95% CI: 1.26–1.45, p &amp;lt; 0.001).ConclusionInflammatory markers (NLR, dNLR, and NMLR) on day 3 post-MT can serve as independent predictors of prognosis in AIS patients treated with MT. Dynamic monitoring of inflammatory markers may facilitate early risk stratification and guide individualized treatment strategies.

Functional connectivity of paired default mode network subregions in patients with eye trauma.

To study functional brain abnormalities in patients with eye trauma (ET) and to discuss the pathophysiological mechanisms of ET. Totally 31 ET patients and 31 healthy controls (HCs) were recruited. The age, gender, and educational background characteristics of the two groups were similar. After functional magnetic resonance imaging (fMRI) scanning, the subjects' spontaneous brain activity was evaluated with the functional connectivity (FC) method. Receiver operating characteristic (ROC) curve analysis was used to classify the data. Pearson's correlation analysis was used to explore the relationship between FC values in specific brain regions and clinical behaviors in patients with ET. Significantly increased FC between several regions was identified including the medial prefrontal cortex (MPFC) and left hippocampus formations (HF), the MPFC and left inferior parietal lobule (IPL), the left IPL and left medial temporal lobe (MTL), the left IPL and right MTL, and the right IPL and left MTL. No decreased region-to-region connectivity was detected in default mode network (DMN) sub-regions in patients with ET. Compared with HCs, ET patients exhibited significantly increased FC between several paired DMN regions, as follows: posterior cingulate cortex (PCC) and right HF (HF.R, t=2.196, P=0.032), right inferior parietal cortices (IPC.R) and left MTL (MTL.L, t=2.243, P=0.029), and right MTL (MTL.R) and HF.R (t=2.236, P=0.029). FC values in multiple brain regions of ET patients are abnormal, suggesting that these brain regions in ET patients may be dysfunctional, which may help to reveal the pathophysiological mechanisms of ET.

Identification of hub programmed cell death-related genes and immune infiltration in Crohn’s disease using bioinformatics

BackgroundCrohn’s disease (CD) is an immune-mediated disorder characterized by immune cell infiltration that induces persistent chronic inflammation of the gastrointestinal tract. Programmed cell death (PCD) plays a critical role in the pathogenesis of CD. This study identified vital PCD-related genes in CD based on immune infiltration using bioinformatic analysis.MethodsWe obtained two CD datasets from the Gene Expression Omnibus (GEO) database and examined immune cell infiltration to investigate immune cell dysregulation in CD. PCD-related genes were retrieved from the GeneCards database. Based on the differentially expressed genes (DEGs) and PCD gene sets, PCD-related DEGs were identified. Candidate hub genes were identified using a protein-protein interaction (PPI) network, and their diagnostic effectiveness was predicted using receiver operating characteristic (ROC) curve analysis. Functional enrichment and immune infiltration analyses were used to assess the distinct roles of the hub genes. Finally, the miRWalk and ENCORI databases were used to predict which microRNAs (miRNAs) regulated the hub genes and to verify gene expression in CD colonic tissues via transcriptome sequencing.ResultsA total of 335 PCD-related DEGs and 3 hub genes (MMP1, SAA1, and PLAU) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses indicated the enrichment of these genes in the immune response. Infiltration analysis of immune cells showed abundant endothelial cells, plasma cells, dendritic cells, and monocytes in the CD samples. Based on the correlation analysis, the three hub genes were positively correlated with monocytes and negatively correlated with CD8 naïve T-cells. MMP1, SAA1, and PLAU correlated with the pathogenicity of CD and had good diagnostic value for CD. The three hub genes were highly expressed in the CD tissues, as confirmed using transcriptome sequencing.ConclusionThis study identified MMP1, SAA1, and PLAU as hub genes involved in PCD in patients with CD. These genes regulate immune cell function and their expression levels are closely related to immune cell infiltration. These findings provide novel insights into the mechanisms underlying CD pathogenesis. The identified PCD genes and regulatory miRNAs are potential biomarkers and therapeutic targets for CD.

Clinical value of contrast-enhanced ultrasound combined with quantitative analysis in Bosniak ≥ II cystic renal masses.

The 2019 Bosniak classification has improved the precise and detailed quantitative evaluation criteria, making the diagnosis of cystic renal masses (CRMs) more accurate and objective. This study addresses the clinical value of quantitative analysis and aims to investigate the feasibility of combining contrast-enhanced ultrasound (CEUS) with quantitative analysis for diagnosing Bosniak ≥ II CRMs. We retrospectively obtained 58 CRMs with confirmed pathology, which underwent CEUS and Contrast-enhanced computer tomography (CECT) evaluations according to Bosniak classification between January 2013 and August 2024. These lesions were divided into benign and malignant groups, followed by a quantitative analysis of the morphological details detected by CEUS. All morphological parameters were compared, and the diagnostic efficiencies were evaluated using receiver operating characteristics (ROC) curves, logistic regression (LR) analysis, and diagnostic curve analysis (DCA). Additionally, a cohort of 72 lesions was monitored for a period of ≥ 3years, and changes in Bosniak classification were analyzed by categorizing them into stable, upgraded, and downgraded categories. The analysis revealed no statistically significant difference between CEUS and CECT in our cohort's malignancy predictive rates across different Bosniak grades (p = 0.640). All morphological quantitative parameters showed statistically significant differences between the two groups (p < 0.001). ROC curve analysis revealed that the sum of enhanced wall thickness and enhanced septum thickness among quantitative parameters had the highest AUC value (AUC: 0.9226). Both LR models demonstrated superior clinical diagnostic performance with similar level of accuracy between qualitative and quantitative analysis, as evidenced by ROC (AUC: 0.9470, 0.9619, respectively) and DCA analyses. None of the lesions in the follow-up cohort were upgraded, suggesting that CRMs are relatively stable tumors with a low malignant potential. This retrospective study demonstrated that CEUS combined with Bosniak classification and quantitative analysis could enhance diagnostic confidence in differentiating Bosniak ≥ II CRMs and could serve as a viable alternative to CECT in specific cases.

Serum hemoglobin and albumin levels serve as prognostic predictors after adrenal metastasectomy

PurposeAdrenal metastasectomy is a common local treatment for adrenal metastases, with a lack of serum prognostic factors. Here, we identified the prognostic significance of preoperative hemoglobin and albumin levels in patients undergoing adrenal metastasectomy.Materials and MethodsData from 93 patients who underwent adrenal metastasectomy were assessed retrospectively. Receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff values of hemoglobin and albumin for survival. Overall survival (OS) and disease-free survival (DFS) were evaluated using the Kaplan–Meier method, thereafter Cox regression models and subgroup analyses were applied to adjust confounding factors. A risk stratification developed by joint use of serum hemoglobin and albumin levels was also tested.ResultsOptimal cut-off points were 130.5 g/L and 44.8 g/L for hemoglobin and albumin, respectively. Multivariate Cox regression analysis identified decreased hemoglobin (HR [95% CI]: 0.41 [0.18—0.91], P = 0.029) and albumin (HR [95% CI]: 0.12 [0.02—0.88], P = 0.038) levels as independent factors for poorer OS. Patient with both decreased hemoglobin and albumin levels had the worst OS (P = 0.001) and DFS (P = 0.001) than other risk groups. Subgroup analyses proved decreased hemoglobin and albumin levels predicted poorer OS independent of cancer types.ConclusionsPreoperative hemoglobin and albumin levels may serve as prognostic predictors after adrenal metastasectomy. A prognostic model that combines hemoglobin and albumin can improve accuracy in predicting patient outcomes and be easily implemented in clinical practice.

Photodissociation of the CH2Cl radical: A high-level abinitio study.

Photodissociation of the CH2Cl radical is investigated by using high-level multireference configuration interaction abinitio methods, including the spin-orbit coupling. All possible fragmentation pathways, namely, CH2Cl + hν → CH2 + Cl, HCCl + H, and CCl + H2, have been analyzed. The potential-energy curves of the ground and several excited electronic states along the corresponding dissociating bond distance of each pathway have been calculated. Inclusion of the spin-orbit couplings is found to be crucial because it strongly determines the shape of the curves of the different excited states and, therefore, their photodissociation dynamics behavior. Analysis of the potential curves indicates that the pathways producing CH2 + Cl and HCCl + H can occur through a fast direct dissociation mechanism, while the pathway leading to CCl + H2 involves much slower dissociation mechanisms such as internal conversion between electronic states, predissociation, or tunneling through exit barriers. The main implications are that the two faster channels are predicted to be dominant, while the slower pathway is expected to be very unlikely and rather irrelevant. Appreciable actinic fluxes of solar irradiation are available at stratospheric altitudes where ozone is abundant, in the wavelength range where absorption of the first low-lying excited states of CH2Cl has been observed experimentally. Our results show that in this excitation energy range, the above-mentioned two dominant dissociation pathways are open and then could contribute to stratospheric ozone depletion.

A comparison between lipid-based vs. glycemic-based insulin sensitivity indices for the association with abnormal ECG findings and 20-year mortality among older adults

BackgroundA direct comparison between glycemic-based and lipid-based insulin sensitivity indices (ISIs) for ECG findings and all-cause and cardiovascular mortality is lacking.Methods963 community-dwelling older adults, examined as part of the third phase of the Glucose intolerance, Obesity, and Hypertension study between 1999 and 2008, were followed until December 2016 and December 2019 for cardiovascular and all-cause mortality, respectively. Eleven different ISIs were calculated and evaluated against ECG findings, all-cause, and cardiovascular mortality with multivariable regression models. The area under the receiver operating curve (AUC) and net reclassification improvement (NRI) analysis were implemented to compare ISIs performance.ResultsMean age was 72.3 ± 7 years and 471 (49%) were females. Ischemic ECG changes were observed in 107 (11.2%) individuals. Upper quartile (Q4) of triglyceride-glucose waist-to-height ratio (TyG-WTHR) was associated with 220% greater odds for ischemic changes on ECG compared with lower quartiles (Q1-3) (95%CI:1.3–3.7, p = 0.004), an association that was not observed with other ISIs. During a median follow-up of 13 [IQR-8] and 11 [IQR-6] years for all-cause and CV mortality, respectively, 466 (48.4%) participants died, of them, 179 (38.4%) were attributed to cardiovascular causes. TyG-WTHR was the only ISI that was associated with both all-cause (HR = 1.3, 95%CI:1.0–1.6, p = 0.04) and cardiovascular (HR = 1.7, 95%CI:1.2–2.4, p = 0.004) mortality. Lipid based and glycemic ISIs showed similar predicative ability with slightly better predictive performance for TyG-WTHR for all-cause mortality (AUC = 0.46, 95%CI:0.4–0.5, p = 0.02). The NRI analysis revealed better reclassification ability for triglyceride-high-density-lipoprotein ratio (95%CI: 0.02–0.27, p = 0.03) and TyG-WTHR (95%CI: 0.0004–0.01, p = 0.03) for all-cause mortality while TyG-WTHR-based model correctly reclassified 19% of participants (95%CI: 0.02–0.36, p = 0.03) for cardiovascular mortality compared with model unadjusted for any ISIs and correctly reclassified 3% (95%CI:0.003–0.05, p = 0.02) compared with QUICKI based-model for all-cause mortality.ConclusionsTyG-WTHR was the only ISI associated with ischemic changes on ECG and all-cause and cardiovascular mortality and significantly improved the predictive performance for all-cause cardiovascular mortality. While most glycemic-based and lipid-based ISIs showed similar predictive ability, TyG-WTHR stands as the preferred ISI and should be considered for screening at-risk individuals for cardiovascular morbidity and mortality.Graphical

Acute kidney injury with hypernatremia and major adverse kidney events

Abstract Introduction Consequences of hypernatremia in AKI (AKI-HyperNa) is poorly understood. We analyzed the risk of major adverse kidney events (MAKE) in comparison with AKI and normal serum sodium (AKI-normalNa). Such data could help in understanding this complex interaction. Methods In this retrospective cohort we compared the AKI-hyperNa with the AKI-normalNa regarding the risk of MAKE, which include death, new dialysis requirement, and worsening kidney function (≥ 25% decrease in eGFR), at 10 (MAKE10) and at 30–90 days (MAKE30–90) using multivariate logistic regression and area under the curve (AUC) analysis. Also the association between serum sodium levels (per 1 mEq/L increase) and the number of days with hypernatremia. Results A total of 357 patients were included (78 with AKI-hyperNa and 279 with AKI-normalNa). Compared to the AKI-normalNa, AKI-hyperNa were predominantly male (73% vs. 59%), experienced hypernatremia for a longer duration (3 days vs. 0 days), and took 5 days to normalize serum sodium levels. After multivariate regression analysis AKI-hyperNa group had higher risk of MAKE10 (OR 5.7, CI 2.5–12.89, p &amp;lt; 0.001) with an AUC of 0.79. Also its components such as mortality and decreased eGFR (OR 2.13, CI 1.11–4.07, p = 0.021 and OR 20.14, CI 7.69–10.03, p = 0.001, respectively). A similar trend for MAKE30–90 (OR 4.17, CI 1.73–10.03, p ≤ 0.001).A gradual increase in serum sodium was associated with a higher risk of MAKE (OR 1.07, CI 1.04–1.11, p ≤ 0.001), as was the number of days spend with hypernatremia (OR 1.51, CI 1.22–1.87, p = 0.001). Conclusions In this cohort, AKI-hyperNa compared with AKI-normalNa, had a 5-fold risk of short- and long-term MAKE. This event was more frequently observed as serum sodium increased and it was closely related to the number of days that hypernatremia persisted.

Predictive value of CA-153, CA-125 and Apo A for ocular metastasis in menopausal female patients with breast cancer.

To establish a meaningful standard for diagnosing ocular metastasis (OM) in menopausal breast cancer (BC) women, and explore the relationship between CA-153, CA-125, apolipoprotein A, and OM. A total of 1362 menopausal female BC patients with OM volunteered to take part in this study between July 2012 and July 2022. Women with BC who are menopausal were found to have an OM incidence of 1.6%. Furthermore, CA-153, CA-125, and apolipoprotein A (Apo A) all contributed to OM in women with BC who are postmenopausal according to binary logistic regression. Receiver operating curve (ROC) analysis was used to assess the diagnostic value of OM in patients with BC. Both CA-153 and CA-153+CA-125 showed a higher sensitivity of 95.45%, whereas CA-153+Apo A illustrated the highest specificity of 99.02%. Moreover, CA-153 and CA-153+CA-125 had higher areas under the curve (AUC) of 0.973. The data indicate that the serum concentrations of CA-153 exhibited the most significant predictors of the diagnosis of OM in menopausal women with BC. The current study researches the utility of risk factors in predicting of OM in menopausal BC women and put forward the latest suggestions on their clinical application.

Identification of pyroptosis-associated miRNAs in the immunoscape and prognosis of hepatocellular carcinoma

BackgroundHepatocellular carcinoma is one of the most prevalent types of liver malignancy and poses a severe threat to global health. Despite recent improvements in therapeutic approaches, treatment options for patients with advanced or recurrent HCC are still limited.Materials and methodsOur study analyzed miRNA differential expression using data from hepatocellular carcinoma patients in the Cancer Genome Atlas. Pyroptosis-related genes were identified from gene cards. Differential expression of miRNAs was analyzed using DESeq2 and visualized using ggplot2 and pheatmap. A prognostic risk model for pyroptosis-associated miRNAs was constructed using LASSO regression and validated by principal component analysis, Kaplan-Meier survival and ROC curve analysis. We also performed gene and pathway enrichment analysis. Immune cell infiltration and function in HCC were assessed using single-sample genomic enrichment analysis, and correlations with immune cells and function were explored. Also, CCK-8 assay as well as migration and invasion assays were performed after knockdown of miR-6844.ResultsWe have established and validated a prognostic risk model based on ten DEmiRNAs, which is important for the survival of HCC patients. Significant changes in immune cell infiltration and immune function were also found in high-risk patients. It also demonstrated that knockdown of miR-6844 inhibited HCC cell proliferation, migration and invasion, highlighting its role in HCC progression.ConclusionOur study reveals the implications of pyroptosis-associated differential miRNAs on the prognosis of patients with hepatocellular carcinoma and provides a foundation for novel HCC therapies, especially immunotherapy.

Construction and validation of a readmission risk prediction model for elderly patients with coronary heart disease

BackgroundTo investigate the risk factors for readmission of elderly patients with coronary artery disease, and to construct and validate a predictive model for readmission risk of elderly patients with coronary artery disease within 3 years by applying machine learning method.MethodsWe selected 575 elderly patients with CHD admitted to the Affiliated Lu’an Hospital of Anhui Medical University from January 2020 to January 2023. Based on whether patients were readmitted within 3 years, they were divided into two groups: those readmitted within 3 years (215 patients) and those not readmitted within 3 years (360 patients). Lasso regression and multivariate logistic regression were used to compare the predictive value of these models. XGBoost, LR, RF, KNN and DT algorithms were used to build prediction models for readmission risk. ROC curves and calibration plots were used to evaluate the prediction performance of the model. For external validation, 143 patients who were admitted between February and June 2023 from a different associated hospital in Lu'an City were also used.ResultsThe XGBoost model demonstrated the most accurate prediction performance out of the five machine learning techniques. Diabetes, Red blood cell distribution width (RDW), and Triglyceride glucose-body mass index (TyG-BMI), as determined by Lasso regression and multivariate logistic regression. Calibration plot analysis demonstrated that the XGBoost model maintained strong calibration performance across both training and testing datasets, with calibration curves closely aligning with the ideal curve. This alignment signifies a high level of concordance between predicted probabilities and observed event rates. Additionally, decision curve analysis highlighted that both decision trees and XGBoost models achieved higher net benefits within the majority of threshold ranges, emphasizing their significant potential in clinical decision-making processes. The XGBoost model's area under the ROC curve (AUC) reached 0.903, while the external validation dataset yielded an AUC of 0.891, further validating the model's predictive accuracy and its ability to generalize across different datasets.ConclusionTyG-BMI, RDW, and diabetes mellitus at the time of admission are the factors affecting readmission of elderly patients with coronary artery disease, and the model constructed based on the XGBoost algorithm for readmission risk prediction has good predictive efficacy, which can provide guidance for identifying high-risk patients and timely intervention strategies.