Wenhua Li

Remnant cholesterol (RC) serves as an important indicator for assessing atherosclerotic cardiovascular disease, however, correlation with contrast-induced acute kidney injury (CI-AKI) remains unclear. This research investigated the relationship between RC and the occurrence of CI-AKI in STEMI patients following percutaneous coronary intervention (PCI). A cohort of 1288 patients with STEMI undergoing PCI were enrolled and stratified into CI-AKI and non-CI-AKI groups based on standard diagnostic criteria. Independent risk factors for CI-AKI were identified using Boruta analysis and logistic regression. The association between RC and CI-AKI was evaluated for nonlinearity using restricted cubic splines (RCS). The predictive performance of RC for identifying CI-AKI was assessed using the receiver operating characteristic (ROC) curve, while its incremental value to an existing risk model was determined by the net reclassification index (NRI) and integrated discrimination index (IDI). The ROC analysis showed that the area under the curve (AUC) for predicting CI-AKI based on blood urea nitrogen, left ventricular ejection fraction, and fasting plasma glucose was 0.739 (95% CI 0.703–0.775, P < 0.001), while the AUC increased to 0.803 (95% CI 0.772–0.834, P < 0.001) when RC was integrated into the model. Additionally, the NRI (0.618, 95% CI 0.470–0.766, P < 0.001) and the IDI (0.053, 95% CI 0.036–0.076, P < 0.001) both highlight improved prediction performance. RC is an independent predictor of CI-AKI in patients with STEMI undergoing PCI. The inclusion of RC significantly enhances the predictive accuracy of a model based on established clinical parameters.

Background: ST-segment elevation myocardial infarction (STEMI), the most severe form of acute coronary syndrome (ACS), requires timely percutaneous coronary intervention (PCI) to restore coronary blood flow. However, contrast-induced acute kidney injury (CI-AKI), the third most common cause of hospital-acquired renal failure, remains a critical complication of PCI. Objective: To develop a machine learning model predicting CI-AKI risk in elderly patients with STEMI patients using clinical features. Methods: Data from 2120 elderly patients with STEMI treated with PCI at Xuzhou Medical University Affiliated Hospital (2019– 2023) were used for model development and testing. An external validation cohort, comprising 236 individuals, was derived from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database (2008– 2019). Lasso regression selected predictors, and nine Machine Learning (ML) algorithms were evaluated via Receiver Operating Characteristic (ROC) analysis. Overlapping top-ranked features from high-performing models (AUC > 0.8) informed a nomogram. Performance was assessed using AUC and decision curve analysis (DCA). Results: The final model included five independent predictors: lymphocyte-to-monocyte ratio, diuretic use, residual cholesterol, serum creatinine, and blood urea nitrogen. This model was developed as a simple-to-use online dynamic nomogram. It demonstrated robust discrimination, with C-statistics of 0.782 in the testing dataset and 0.791 in the validation dataset. DCA confirmed its clinical utility across a wide range of risk thresholds. Conclusion: A new online dynamic nomogram was developed to provide a practical tool for CI-AKI risk stratification in elderly STEMI patients, aiding personalized prevention strategies.

Background: Contrast-induced acute kidney injury (CI-AKI) refers to the acute renal dysfunction caused by the injection of contrast agents. CI-AKI is currently a common complication after percutaneous coronary intervention (PCI). Objective: To investigate the predictive value of the combined systemic inflammatory index (SII) and urate/high-density lipoprotein cholesterol ratio (UHR) for CI-AKI after PCI in patients with AMI. Methods: A total of 1222 patients with AMI who underwent PCI were randomly divided into a training group and a validation group in an 8:2 ratio. According to the definition of CI-AKI diagnostic criteria, the training group was divided into CI-AKI group and non-CI-AKI group. Collect patient’s blood and biochemical data, then calculate SII and UHR. The risk factors for CI-AKI were identified using LASSO and multivariate logistic regression analyses. A predictive column was created by using R language.Evaluate the predictive value of SII, UHR and their combination for CI-AKI after PCI using the area under the ROC curve (AUC). Results: Diabetes, Cystatin C, Diuretics, UHR, and LnSII were independent risk factors for CI-AKI in AMI patients after PCI. The ROC curve showed that the AUC of UHR and SII combined for predicting CI-AKI in AMI patients after PCI was 0.761 (95% CI: 0.709– 0.812), with a sensitivity of 65.20% and a specificity of 76.70%, which was better than the prediction by either factor alone. Conclusion: High SII and high UHR are risk factors for AMI, and their combination can improve the accuracy of predicting CI-AKI in AMI patients after PCI.The prognosis of CI-AKI in AMI patients is worse than in the general population.

Introduction: C-X-C motif chemokine ligand 1 (CXCL1) is a potent neutrophil chemoattractant that plays a pivotal role in recruiting neutrophils during inflammatory conditions. This study explored the role of CXCL1 in modulating the gut microbiota, influencing neutrophil infiltration, and contributing to the development of colitis. Methods: We employed quantitative PCR to assess CXCL1 expression in colon samples. A mouse model of dextran sulfate sodium (DSS)-induced colitis was utilized to explore the progression of colitis in wild-type (WT) and CXCL1-deficient (CXCL1−/−) mice. Results: Colitis attenuation was evident in CXCL1−/− mice. Significant alterations were observed in the gut microbiome, as revealed by 16S rRNA gene sequencing. Furthermore, CXCL1−/− mice exhibited reduced gut permeability and diminished endotoxin levels in peripheral blood following DSS treatment compared to WT mice. In response to DSS treatment, WT mice showed a clear increase in neutrophil infiltration, while CXCL1−/− mice exhibited lower levels of infiltration. Fecal microbiota transplantation (FMT) using stools from CXCL1−/− mice alleviated DSS-induced colitis. Interestingly, FMT from patients with colitis increased CXCL1 and Ly6G expression in the colons of gut-sterilized mice. Clinical data analysis revealed elevated CXCL1 and CD15 expression in patients with colitis, with a positive correlation between the severity of colitis and the expression of CXCL1 and CD15. Conclusion: These findings shed light on the pivotal role of CXCL1 in promoting colitis by modulating the gut microbiota.

Objective: Our objective was to develop and validate a nomogram model aiming at predicting the risk of contrast-induced acute kidney injury (CI-AKI) following percutaneous coronary intervention (PCI) in patients suffering from type 2 diabetes mellitus (T2DM) and also diagnosed with acute coronary syndrome (ACS). Methods: The study gathered data from 722 T2DM patients with ACS who received PCI treatment at the Affiliated Hospital of Xuzhou Medical University between February 2019 and December 2022, serving as the training set. Considering the validation set, the study included 217 patients who received PCI at the East Affiliated Hospital of Xuzhou Medical University. The patients were classified into CI-AKI and non-CI-AKI groups. The study employed univariate and multivariate logistic analysis for identifying independent risk factors for CI-AKI, followed by developing a predictive nomogram model for CI-AKI risk using R software. The predictive performance and clinical utility of the nomogram were assessed through internal and external validation, utilizing the areas under the receiver operating characteristic curve (AUC-ROC), the Hosmer-Lemeshow test and calibration correction curve, and decision curve analysis (DCA). Results: The nomogram comprised four variables: age, estimated glomerular filtration rate (eGFR), triglyceride-glucose (TyG) index, and prognostic nutritional index (PNI). The AUC-ROC were 0.785 (95% confidence interval (CI) 0.729– 0.841) and 0.802 (95% CI 0.699– 0.905) for the training and validation cohorts, respectively, indicating a high discriminative ability of the nomogram. The calibration assessment and decision curve analysis have substantiated the strong concordance and clinical usefulness of the aforementioned. Conclusion: The nomogram exhibits favorable discrimination and accuracy, enabling it to visually and individually identify pre-procedure high-risk patients, and possesses a predictive capacity regarding CI-AKI incidence after PCI in patients diagnosed with both T2DM and ACS.

Objective To investigate the relationship between the incidence of contrast-induced acute kidney injury (CI-AKI) after emergency percutaneous coronary intervention (PCI) and preoperative systemic immune-inflammation index (SII) and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels in patients with acute ST-segment elevation myocardial infarction (STEMI), and to further analyze the predictive value of the combination of SII and NT-proBNP for CI-AKI. Methods The clinical data of 1543 patients with STEMI who underwent emergency PCI in our hospital from February 2019 to December 2022 were retrospectively analyzed. All patients were divided into training cohort (n = 1085) and validation cohort (n = 287) according to chronological order. The training cohort was divided into CI-AKI (n = 95) and non-CI-AKI (n = 990) groups according to the 2018 European Society of Urogenital Radiology definition of CI-AKI. Multivariate Logistic regression analysis was used to determine the independent risk factors for CI-AKI. Restricted cubic spline (RCS) was used to explore the relationship between SII, NT-proBNP, and the risk of CI-AKI. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of SII, NT-proBNP, and their combination in CI-AKI. Results The incidence of CI-AKI was 8.8% (95/1085). Multivariate logistic regression analysis showed that SII, NT-proBNP, age, baseline creatinine, fasting blood glucose, and diuretics were independent risk factors for CI-AKI. RCS analysis showed that SII > 1084.97 × 10⁹/L and NT-proBNP > 296.12 pg/mL were positively associated with the incidence of CI-AKI. ROC curve analysis showed that the area under the curve of SII and NT-proBNP combined detection in predicting CI-AKI was 0.726 (95% CI 0.698–0.752, P < 0.001), the sensitivity was 60.0%, and the specificity was 77.7%, which were superior to the detection of SII or NT-proBNP alone. Conclusion Preprocedural high SII and NT-proBNP are independent risk factors for CI-AKI after emergency PCI in patients with STEMI. The combined detection of SII and NT-proBNP can more accurately predict CI-AKI risk than the single detection.

Endodermal sinus tumor (EST) occurs most frequently in the gonads and is relatively rare in other sites, particularly in the spinal cavity. We report a 19-year-old woman who presented with back pain and weakness of both lower extremities who was found to have an EST in the spinal canal cavity. She had severely elevated serum alpha-fetoprotein (AFP) level at presentation. Magnetic resonance imaging (MRI) revealed the mass in the spinal canal. The tumor was excised. Serum AFP returned to normal after three cycles of chemotherapy. We describe the imaging findings and the macroscopic and microscopic features of this rare tumor. EST is a relatively rare malignant germ cell tumor that usually originates in the gonads and has poor prognosis. This is a rare case of the primary EST in the spinal canal. Radiologists need to be aware of the MRI appearance of extragonadal EST.

Figure S1. NK cell and T cell numbers in the peripheral blood, non-tumor and tumor tissues of GC patients. Figure S2. Expression of activating and inhibitory receptors on NK cells in the peripheral blood, non-tumor and tumor tissues of GC patients. Figure S3. Expression of CD56 and CD16 on NK cells in the peripheral blood, non-tumor and tumor tissues of GC patients. Figure S4. The expression of HLA-DR on tissue-associated monocytes/macrophages in GC patients. Figure S5. The expression of CD48, PD-L1 and PD-L2 on tissue-associated monocytes/macrophages in GC patients. Figure S6. Co-expression of CD68 and TGF-beta1 in tumors of GC patients. Figure S7. Surface expression levels of TGF-beta1 on tumor-associated monocytes/macrophages in GC patients. Table S1. Clinical characteristics of 65 GC patients. Table S2. Fluorochrome-conjugated antibodies used in flow cytometry. Table S3. Univariate and multivariate analyses of factors associated with survival.

Objective To investigate the value of systemic immune–inflammation index (SII) combined with CHA2DS2-VASC score in predicting the risk of contrast-induced acute kidney injury (CI-AKI) in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI) treatment. Methods 1531 consecutive patients with ACS and undergoing PCI were recruited from January 2019 to December 2021. All patients were divided into CI-AKI and non-CI-AKI groups according to the pre-procedure and post-procedure creatinine changes, and the baseline data were compared between the two groups. Binary logistic regression analysis was used to investigate the factors influencing CI-AKI in ACS patients after PCI. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of SII, CHA2DS2-VASC, and their combined levels on CI-AKI after PCI. Results Patients with high SII and high CHA2DS2-VASC score had a higher incidence of CI-AKI. For SII, the area under the ROC curve (AUC) for predicting CI-AKI was 0.686. The optimal cut-off value was 736.08 with a sensitivity of 66.8% and a specificity of 66.3% [95% confidence interval (CI) 0.662–0.709; P < 0.001]. For CHA2DS2-VASC score, the AUC was 0.795, the optimal cut-off value was 2.50 with a sensitivity of 80.3% and a specificity of 62.7% (95% CI 0.774–0.815; P < 0.001). When combining SII and CHA2DS2-VASC score, the AUC was 0.830, the optimal cut-off value was 0.148 with a diagnostic sensitivity of 76.1% and a specificity of 75.2% (95% CI 0.810–0.849; P < 0.001). The results showed that SII combined with CHA2DS2-VASC score resulted in improved predictive accuracy of CI-AKI. Multifactorial logistic regression analysis showed that albumin level (OR = 0.967, 95% CI 0.936–1.000; P = 0.047), lnSII level (OR = 1.596, 95% CI 1.010–1.905; P < 0.001), and CHA2DS2-VASC score level (OR = 1.425, 95% CI 1.318–1.541; P < 0.001) were independent risk factors for CI-AKI in patients with ACS treated with PCI. Conclusion High SII and high CHA2DS2-VASC score are risk factors for the development of CI-AKI, and the combination of the two improves the accuracy of predicting the occurrence of CI-AKI in patients with ACS undergoing PCI.