Development and Validation of a Nomogram for Predicting All-Cause Mortality in Patients with Hemodialysis Having Pulmonary Hypertension.

INTRODUCTION: Patients with end-stage renal disease receiving hemodialysis (HD) have a high morbidity and mortality rate associated with pulmonary hypertension (PH). A nomogram was developed to predict all-cause mortality in HD patients with PH. In this study, we aimed to validate the usefulness of this nomogram. METHODS: A total of 274 HD patients with PH were hospitalized at the Affiliated Hospital of Xuzhou Medical University between January 2014 and June 2019 and followed up for 3 years. Echocardiography detected PH when the peak tricuspid regurgitation velocity (TRV) was more than 2.8 m/s. To evaluate the all-cause mortality for long-term HD patients with PH, Cox regression analysis was performed to determine the factors of mortality that were included in the prediction model. Next, the area under the receiver-operating characteristic curve (AUC-ROC) was used to assess the predictive power of the model. Calibration plots and decision curve analysis (DCA) were used to assess the accuracy of the prediction results and the clinical utility of the model. RESULTS: The all-cause mortality rate was 29.20% throughout the follow-up period. The nomogram comprised six commonly available predictors: age, diabetes mellitus, cardiovascular disease, hemoglobin, left ventricular ejection fraction, and TRV. The 1-year, 2-year, and 3-year AUC-ROC values were 0.842, 0.800, and 0.781, respectively. The calibration curves revealed excellent agreement with the nomogram, while the DCA demonstrated favorable clinical practicability. CONCLUSION: The first developed nomogram for predicting all-cause mortality in HD patients with PH could guide clinical decision-making and intervention planning.

Preliminary assessment of cardiotoxicity in chimeric antigen receptor T cell therapy: a systematic review and meta-analysis.

As a novel anticancer therapy, chimeric antigen receptor T (CAR T) cell therapy may lead to cardiotoxic reactions. However, the exact incidence remains unclear. Our study aimed to preliminarily assess the prevalence of cardiotoxicity after CAR T cell treatment using a systematic review and meta-analysis. PubMed, Embase, Web of Science, and Cochrane databases were searched for potentially relevant studies. All types of relevant clinical studies were screened and assessed for risk bias. In most instances, random-effect models were used for data analysis, and heterogeneity between studies was evaluated. Standard quality assessment tools were used to assess quality. The study was registered with PROSPERO (CRD42022304611). Eight eligible studies comprising 3567 patients, including seven observational studies and one controlled study, were identified. The incidence of cardiovascular events was 16.7% [95% confidence interval (CI) 0.138-0.200, P < 0.01)]. Arrhythmia was the most common disorder, with an incidence of 6.5% (95% CI 0.029-0.115, P < 0.01). The occurrence of cardiotoxicity was associated with cytokine release syndrome (CRS), with a prevalence of 18.7% (95% CI 0.107-0.315, P < 0.01). Moreover, such adverse reactions were more common when CRS > 2 (OR = 0.07, 95% CI 0.02-0.29, P < 0.01). The risk of cardiotoxicity was not notably higher in patients receiving CAR T cell therapy than in those receiving traditional anticancer treatment. However, sufficient attention should be paid to this. And further evidence from large-scale clinical trials are needed.

Effects of Remote Ischemic Preconditioning on Decreasing Troponin Release in Patients Not Taking Sulfonylureas After Cardiac Surgery - A Meta-Analysis.

INTRODUCTION: Remote ischemic preconditioning (RIPC) is a new noninvasive myocardial protection strategy that uses blood pressure cuf inflation to simulate transient non-fatal ischemia to protect the myocardium and reduce ischemia-reperfusion injury. Sulfonylureas may mask the effects of RIPC due to their cardioprotec-tive effect. This meta-analysis aimed to evaluate whether RIPC, in the absence of sulfonylureas, reduces troponin release in patients undergoing cardiac surgery. METHODS: We conducted a meta-analysis of randomized controlled clinical trials to determine whether RIPC can reduce postoperative troponin release in cardiac surgery patients undergoing cardiopulmonary bypass without treatment with sulfonylureas. The data were normalized to equivalent units prior to the analysis. A random-effects model was used to provide more conservative estimate of the effects in the presence of known or unknown heterogeneity. RESULTS: Six studies with a total of 570 participants were included. The analysis showed that troponin release was lower in the RIPC group than in the control group at six hours (test of standardized mean differences = 0, Z=3.64, P<0.001) and 48 hours (Z=2.72, P=0.007) postoperatively. When the mean of cross-clamping time was > 60 minutes, RIPC reduced troponin release at six hours (Z=2.84, P=0.005), 24 hours (Z=2.64, P=0.008), and 48 hours (Z=2.87, P=0.004) postoperatively. CONCLUSION: In cardiac surgery patients who are not taking sulfonylureas, RIPC can reduce troponin release at six and 48 hours postoperatively; hence, RIPC may serve significant benefits in certain cardiac surgery patients.

Development and validation of a risk nomogram model for predicting pulmonary hypertension in patients with stage 3-5 chronic kidney disease.

OBJECTIVES: The occurrence of pulmonary arterial hypertension (PAH) can greatly affect the prognosis of patients with chronic kidney disease (CKD). We aimed to construct a nomogram to predict the probability of PAH development in patients with stage 3-5 CKD to guide early intervention and to improve prognosis. METHODS: From August 2018 to December 2021, we collected the data of 1258 patients with stage 3-5 CKD hospitalized at the Affiliated Hospital of Xuzhou Medical University as a training set and 389 patients hospitalized at Zhongda Hospital as a validation set. These patients were divided into PAH and N-PAH groups with pulmonary arterial systolic pressure ≥ 35 mmHg as the cutoff. The results of univariate and multivariate logistic regression analyses were used to establish the nomogram. Then, areas under the receiver operating characteristic curve (AUC-ROCs), a calibration plot, and decision curve analysis (DCA) were used to validate the nomogram. RESULTS: The nomogram included nine variables: age, diabetes mellitus, hemoglobin, platelet count, serum creatinine, left ventricular end-diastolic diameter, left atrial diameter, main pulmonary artery diameter and left ventricular ejection fraction. The AUC-ROCs of the training set and validation set were 0.801 (95% confidence interval (CI) 0.771-0.830) and 0.760 (95% CI 0.699-0.818), respectively, which showed good discriminative ability of the nomogram. The calibration diagram showed good agreement between the predicted and observed results. DCA also demonstrated that the nomogram could be clinically useful. CONCLUSION: The evaluation of the nomogram model for predicting PAH in patients with CKD based on risk factors showed its ideal efficacy. Thus, the nomogram can be used to screen for patients at high risk for PAH and has guiding value for the subsequent formulation of prevention strategies and clinical treatment.

Effects of Remote Ischemic Preconditioning on Decreasing Troponin Release in Patients Not Taking Sulfonylureas After Cardiac Surgery - A Meta-Analysis

ABSTRACT Introduction: Remote ischemic preconditioning (RIPC) is a new noninvasive myocardial protection strategy that uses blood pressure cuf inflation to simulate transient non-fatal ischemia to protect the myocardium and reduce ischemia-reperfusion injury. Sulfonylureas may mask the effects of RIPC due to their cardioprotec-tive effect. This meta-analysis aimed to evaluate whether RIPC, in the absence of sulfonylureas, reduces troponin release in patients undergoing cardiac surgery. Methods: We conducted a meta-analysis of randomized controlled clinical trials to determine whether RIPC can reduce postoperative troponin release in cardiac surgery patients undergoing cardiopulmonary bypass without treatment with sulfonylureas. The data were normalized to equivalent units prior to the analysis. A random-effects model was used to provide more conservative estimate of the effects in the presence of known or unknown heterogeneity. Results: Six studies with a total of 570 participants were included. The analysis showed that troponin release was lower in the RIPC group than in the control group at six hours (test of standardized mean differences = 0, Z=3.64, P<0.001) and 48 hours (Z=2.72, P=0.007) postoperatively. When the mean of cross-clamping time was > 60 minutes, RIPC reduced troponin release at six hours (Z=2.84, P=0.005), 24 hours (Z=2.64, P=0.008), and 48 hours (Z=2.87, P=0.004) postoperatively. Conclusion: In cardiac surgery patients who are not taking sulfonylureas, RIPC can reduce troponin release at six and 48 hours postoperatively; hence, RIPC may serve significant benefits in certain cardiac surgery patients.

A Clinical Nomogram Based on the Triglyceride-Glucose Index to Predict Contrast-Induced Acute Kidney Injury after Percutaneous Intervention in Patients with Acute Coronary Syndrome with Diabetes Mellitus.

The aim of the study was to investigate the factors influencing contrast-induced acute kidney injury (CI-AKI) after percutaneous intervention (PCI) in patients with acute coronary syndrome (ACS) with diabetes mellitus (DM). A total of 1073 patients with ACS combined with DM who underwent PCI at the Affiliated Hospital of Xuzhou Medical University were included in this study. We divided the patients into the CI-AKI and non-CI-AKI groups according to whether CI-AKI occurred or not. The patients were then randomly assigned to the training and validation sets at a proportion of 7 : 3. Based on the results of the LASSO regression and multivariate analyses, we determined that the subtypes of ACS, age, multivessel coronary artery disease, hyperuricemia, low-density lipoprotein cholesterol, triglyceride-glucose index, and estimated glomerular filtration rate were independent predictors on CI-AKI after PCI in patients with ACS combined with DM. Using the above indicators to develop the nomogram, the AUC-ROC of the training and validation sets were calculated to be 0.811 (95% confidence interval (CI): 0.766-0.844) and 0.773 (95% CI: 0.712-0.829), respectively, indicating high prediction efficiency. After verification by the Bootstrap internal verification, we found that the calibration curves showed good agreement between the nomogram predicted and observed values. And the DCA results showed that the nomogram had a high clinical application. In conclusion, we constructed and validated the nomogram to predict CI-AKI risk after PCI in patients with ACS and DM. The model can provide a scientific reference for predicting the occurrence of CI-AKI and improving the prognosis of patients.

Novel grading system for ischemia‒reperfusion injury manifestations in patients with acute ST-segment elevation myocardial infarction undergoing percutaneous coronary intervention.

To establish a simple myocardial ischemia‒reperfusion injury (MIRI) manifestation grading system based on clinical manifestations and coronary angiography during primary percutaneous coronary intervention (PPCI). All STEMI patients treated with PPCI from June 2018 to November 2019 were included. According to the MIRI manifestation grade, patients were divided into four grades (I-IV). Laboratory and clinical indicators of the patients and the occurrence of major adverse cardiac events (MACEs) within one year of follow-up were analyzed. A total of 300 patients were included. The higher the MIRI manifestation grade, the lower was the high-density lipoprotein cholesterol (HDL-C); the higher were the C-reactive protein (CRP), lipoprotein(a) [LP(a)], and peak levels of high-sensitivity troponin T (hs-cTnT), creatine kinase (CK-MB), and N-terminal pro-B-type natriuretic peptide (NT-proBNP); and the higher were the proportions of right coronary artery (RCA) and multivessel lesions (P < 0.05). The left ventricular end-diastolic dimension (LVEDD) and E/e' values of patients with higher grades were significantly increased, while the LVEF, left ventricular short-axis functional shortening (LVFS) and E/A values were significantly decreased (P < 0.05). The one-year cumulative incidence of major adverse cardiac events (MACEs) in patients with grade I-IV disease was 7.7% vs. 26.9% vs. 48.4% vs. 93.3%, respectively, P < 0.05. The higher the MIRI manifestation grade, the more obvious is the impact on diastolic and systolic function and the higher is the cumulative incidence of MACEs within one year, especially in patients with multivessel disease, low HDL-C, high CRP, high LP(a) levels, and the RCA as the infarction-related artery.

Development and Validation of a Nomogram Model for Predicting the Risk of Readmission in Patients with Heart Failure with Reduced Ejection Fraction within 1 Year.

The high incidence of readmission for patients with reduced ejection fraction heart failure (HFrEF) can seriously affect the prognosis. In this study, we aimed to build a simple predictive model to predict the risk of heart failure (HF) readmission in patients with HFrEF within one year of discharge from the hospital. This retrospective study enrolled patients with HFrEF evaluated in the Heart Failure Center of the Affiliated Hospital of Xuzhou Medical University from January 2018 to December 2020. The patients were allocated into the readmission or nonreadmission group, according to whether HF readmission occurred within 1 year of hospital discharge. Subsequently, all patients were randomly divided into training and validation sets in a 7 : 3 ratio. A nomogram was established according to the results of univariate and multivariate logistic regression analysis. Finally, the area under the receiver operating characteristic curve (AUC-ROC), calibration plot, and decision curve analysis (DCA) were used to validate the nomogram. Independent risk factors for HF readmission of patients with HFrEF within 1 year of hospital discharge were as follows: age, body mass index, systolic blood pressure, diabetes mellitus, left ventricular ejection fraction, and angiotensin receptor-neprilysin inhibitors. The AUC-ROC of the training and validation sets were 0.833 (95% confidence interval (CI): 0.793-0.866) and 0.794 (95% CI: 0.727-0.852), respectively, which have an excellent distinguishing ability. The predicted and observed values of the calibration curve also showed good consistency. DCA also confirmed that the nomogram had good clinical value. In conclusion, we constructed an accurate and straightforward nomogram model for predicting the 1-year HF readmission risk in patients with HFrEF. This nomogram can guide early clinical intervention and improve patient prognosis.