Impacts of eosinophil percentage on prognosis acute type A aortic dissection patients

Utilizing Machine Learning Techniques to Predict Negative Remodeling in Uncomplicated Type B Intramural Hematoma

BACKGROUND

To evaluate the effectiveness of machine learning (ML) techniques in predicting negative remodeling in uncomplicated Stanford type B intramural hematoma (IMHB) during the acute phase.

METHODS

Univariate logistic regression and 8 ML models were used for prediction. The least absolute shrinkage and selection operator (LASSO) method was used to minimize regression coefficients and reduce the likelihood of overfitting. Hyperparameter tuning was achieved using randomized and grid searches. Model performance was evaluated using the area under the curve (AUC), F1 score, and Brier score. Shapley additive explanations (SHAP) values were calculated, allowing us to meticulously rank the significance of the input features and elucidate the outcomes of the prediction models.

RESULTS

One hundred fifty-four cases of uncomplicated IMHB diagnosed between January 2020 and January 2023 were included. The LASSO method identified 7 features that were significantly associated with negative remodeling in uncomplicated IMHB as follows: lymphocytes, white blood cells, neutrophil-to-lymphocyte ratio, eosinophils, monocytes, hypertension, and statins. The CatBoost model (which handles categorical features, simplifies data preprocessing, mitigates overfitting, and provides feature importance tools for better model interpretability) outperformed the other models in terms of the AUC (0.969), F1 score (0.94), and Brier score (0.0625). The SHAP method revealed that in the CatBoost model, the top 3 features associated with negative remodeling in uncomplicated IMHB patients were monocyte count (1.250), lymphocyte count (0.296), and eosinophil count (0.249) on admission.

CONCLUSION

The CatBoost model effectively predicts negative remodeling in uncomplicated IMHB patients during the acute phase by integrating clinical features (monocyte, lymphocyte, and eosinophil counts), representing a tool to improve patient outcomes.

Differential roles of eosinophils in cardiovascular disease

Eosinophils are essential innate immune cells in allergic responses. Accumulating evidence indicates that eosinophils also participate in the pathogenesis of cardiovascular diseases (CVDs). In clinical studies, high blood eosinophil counts and eosinophil cationic protein levels have been associated with an increased risk of CVD, including myocardial infarction (MI), cardiac hypertrophy, atrial fibrillation, abdominal aortic aneurysm (AAA) and atherosclerosis. However, low blood eosinophil counts have also been reported to be a risk factor for MI, heart failure, aortic dissection, AAA, deep vein thrombosis, pulmonary embolism and ischaemic stroke. Although these conflicting clinical observations remain unexplained, CVD status, timing of eosinophil data collection, and tissue eosinophil phenotypic and functional heterogeneities might account for these discrepancies. Preclinical studies suggest that eosinophils have protective actions in MI, cardiac hypertrophy, heart failure and AAA. By contrast, cationic proteins and platelet-activating factor from eosinophils have been shown to promote vascular smooth muscle cell proliferation, vascular calcification, thrombomodulin inactivation and platelet activation and aggregation, thereby exacerbating atherosclerosis, atrial fibrillation, thrombosis and associated complications. Therefore, eosinophils seem to promote calcification and thrombosis in chronic CVD but are protective in acute cardiovascular settings. In this Review, we summarize the available clinical and preclinical data on the different roles of eosinophils in CVD.

Prognostic prediction of long-term survival in patients with type A aortic dissection undergoing surgical repair: development of a novel prognostic index

BACKGROUND

This study developed and investigated the prognostic significance of a comprehensive biomarker for postoperative type A aortic dissection (TAAD) patients.

METHODS

A retrospective cohort of 175 TAAD patients who underwent open surgery at the First Affiliated Hospital of Chongqing Medical University, China, between September 2017 to December 2020, was included in the analysis. The least absolute shrinkage and selection operator (LASSO) method was employed to select indicators, thereby constructing a comprehensive biomarker, termed the comprehensive physiological response indicator (CPRI). The prognostic significance of the CPRI was assessed employing the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression model were applied to identify independent prognostic factors for TAAD. A prognostic nomogram was constructed based on the CPRI and other nine blood and clinical indicators. The predictive performance of prognostic models and individual indicators was evaluated by determining the area under the curve (AUC) of the receiver operating characteristic (ROC) analysis.

RESULTS

A comprehensive prognostic biomarker (CPRI) was developed, incorporating cardiac troponin T (cTnT), red blood cell count (RBC), white blood cell count (WBC), absolute neutrophil count (ANC), and absolute lymphocyte count (ALC). In the cohort of type A aortic dissection (TAAD) patients who underwent open surgery, those with lower preoperative CPRI values exhibited significantly poorer overall survival, with a HR of 2.325 (95% CI: 1.126-4.802) in a multivariate Cox regression analysis. The CPRI was identified as an independent prognostic factor for TAAD patients. Additionally, a nomogram constructed based on the CPRI demonstrated superior predictive accuracy compared to other models, with an area under the curve (AUC) of 0.874 versus 0.592, 0.514, and 0.577 for the respective models.

CONCLUSION

Our study suggested that CPRI may be a useful comprehensive prognostic biomarker for predicting the long-term survival of TAAD patients. The nomogram based on CPRI can be considered a valuable tool to identify high risk TAAD patients with poor prognosis.

Eosinophil Recovery Time Is Associated with Clinical Outcomes in Patients with Type A Acute Aortic Dissection: a Retrospective Cohort Study

Type A acute aortic dissection (TA-AAD) patients are prone to life-threatening complications and death. This study aimed to analyze the association between eosinophil (EOS) recovery and clinical outcomes in TA-AAD. A total of 274 patients with TA-AAD were eligible for inclusion, and 54 patients died within 1 month. The patients with poor clinical outcomes showed significantly lower EOS count within 8 days after surgery. The time-dependent ROC analysis showed that EOS recovery days predicted 1-month death with an AUC of 0.886 and a cutoff of 6 days. EOS recovery within 6 days was associated with a lower incidence of postoperative infection, a poorer prognosis, and a lower risk of 1-month and 6-month mortality than those requiring more recovery days. Collectively, postoperative early recovery of EOS predicted lower mortality and better prognosis and may be applied as an effective, rapid, and simple tool for the risk stratification and prognostic prediction of patients with TA-AAD.Clinical trial registration number: NCT05409677.

Peripheral Eosinophil Count Is Associated With the Prognosis of Patients With Type B Aortic Dissection Undergoing Endovascular Aortic Repair: A Retrospective Cohort Study

Background Eosinophil count (EOS) has been proposed to provide prognostic information in multiple cardiovascular disorders. However, few researchers have investigated the predictive value of EOS for patients with type B aortic dissection who had thoracic endovascular repair. Methods and Results The authors reviewed the records of 912 patients with type B aortic dissection who were treated with thoracic endovascular repair in Changhai Hospital, Shanghai. By using receiver operating characteristic curve analysis, patients were divided into 2 groups based on the admission EOS cutoff value (<7.4×10⁶/L [n=505] and ≥7.4×10⁶/L [n=407]). To reduce selection bias, propensity score matching was applied. Multivariable regression analysis and Kaplan-Meier curves were performed to assess the association between EOS and long-term outcomes. Furthermore, we investigated nonlinear correlations between EOS and outcomes using general additive models with restricted cubic splines. In the matched population, lower EOS was associated with significantly higher 30-day mortality (4.1% vs 0%, P=0.007). There was no statistically difference in 30-day adverse events between the 2 groups (all P>0.05). Kaplan-Meier analysis revealed that patients with an EOS <7.4×10⁶/L had a higher incidence of 1-year all-cause death (7.95% vs. 2.34%, P=0.008) and aortic-related death (5.98% vs 1.81%, P=0.023) than those with higher EOS. Multivariable Cox analysis showed that continuous EOS was independently associated with 1-year mortality (hazard ratio, 3.23 [95% CI, 1.20-8.33], P=0.019). In addition, we discovered a nonlinear association between EOS and 1-year outcomes. Conclusions Lower admission EOS values predict higher short- and long-term mortality after thoracic endovascular repair.