Short- and Long-term survival prediction in patients with acute type A aortic dissection undergoing open surgery.

BACKGROUND: Acute Type A aortic dissection (ATAAD) is a life-threatening cardiovascular disease associated with high mortality rates, where surgical intervention remains the primary life-saving treatment. However, the mortality rate for ATAAD operations continues to be alarmingly high. To address this critical issue, our study aimed to assess the correlation between preoperative laboratory examination, clinical imaging data, and postoperative mortality in ATAAD patients. Additionally, we sought to establish a reliable prediction model for evaluating the risk of postoperative death. METHODS: In this study, a total of 384 patients with acute type A aortic dissection (ATAAD) who were admitted to the emergency department for surgical treatment were included. Based on preoperative laboratory examination and clinical imaging data of ATAAD patients, logistic analysis was used to obtain independent risk factors for postoperative in-hospital death. The survival prediction model was based on cox regression analysis and displayed as a nomogram. RESULTS: Logistic analysis identified several independent risk factors for postoperative in-hospital death, including Marfan syndrome, previous cardiac surgery history, previous renal dialysis history, direct bilirubin, serum phosphorus, D-dimer, white blood cell, multiple aortic ruptures and age. A survival prediction model based on cox regression analysis was established and presented as a nomogram. The model exhibited good discrimination and significantly improved the prediction of death risk in ATAAD patients. CONCLUSIONS: In this study, we developed a novel survival prediction model for acute type A aortic dissection based on preoperative clinical features. The model demonstrated good discriminatory power and improved accuracy in predicting the risk of death in ATAAD patients undergoing open surgery.

Liraglutide attenuates angiotensin II-induced aortic dissection and aortic aneurysm via inhibiting M1 macrophage polarization in APOE -/- mice.

BACKGROUND: Aortic Aneurysm and Dissection (AAD) are severe cardiovascular conditions with potentially lethal consequences such as aortic rupture. Existing studies suggest that liraglutide, a long-acting glucagon-like peptide receptor (GLP-1R) agonist, offers protective benefits across various cardiovascular diseases. However, the efficacy of liraglutide in mitigating AAD development is yet to be definitively elucidated. METHODS: Ang II (Angiotension II) infusion of APOE-/- mouse model with intraperitoneal injection of liraglutide (200 µg/kg) to study the role of GLP-1R in AAD formation. Bone Marrow Derived Macrophages (BMDM) and Raw264.7 were incubated with LPS, liraglutide, exendin 9-39 or LY294002 alone or in combination. SMC phenotype switching was examined in a macrophage and vascular smooth muscle cell (VSMC) co-culture system. An array of analytical methods, including Western Blot, Immunofluorescence Staining, Enzyme-LinkedImmunosorbent Assay, Real-Time Quantitative Polymerase Chain Reaction, RNA-seq, and so on were employed. RESULTS: Our investigation revealed a significant increase in M1 macrophage polarization and GLP-1R expression in aortas of AD patients and Ang II-induced AAD APOE-/- mice. Administering liraglutide in APOE-/- mice notably reduced Ang II-induced AAD incidence and mortality. It was found that liraglutide inhibits M1 macrophage polarization primarily via GLP-1R activation, and subsequently modulates vascular smooth muscle cell phenotypic switching was the primary mechanism. RNA-Seq and subsequent KEGG enrichment analysis identified CXCL3, regulated by the PI3K/AKT signaling pathway, as a key element in liraglutide's modulation of M1 macrophage polarization. CONCLUSION: Our study found liraglutide exhibits protective effects against AAD by modulating M1 macrophage polarization, suppressing CXCL3 expression through the PI3K/AKT signaling pathway. This makes it a promising therapeutic target for AAD, offering a new avenue in AAD management.

Postoperative hyper-inflammation as a predictor of poor outcomes in patients with acute type A aortic dissection (ATAAD) undergoing surgical repair.

BACKGROUND: Postoperative hyper-inflammation is a frequent event in patients with acute Stanford type A aortic dissection (ATAAD) after surgical repair. This study's objective was to determine which inflammatory biomarkers could be used to make a better formula for identifying postoperative hyper-inflammation, and which risk factors were associated with hyper-inflammation. METHODS: A total of 405 patients were enrolled in this study from October 1, 2020 to April 1, 2023. Of these patients, 124 exhibited poor outcomes. In order to investigate the optimal cut-off values for poor outcomes, logistic and receiver operating characteristic analyses were performed on the following parameters on the first postoperative day: procalcitonin (PCT), C-reactive protein (CRP), interleukin-6 (IL-6), and systemic immune-inflammation index (SII). These cut-off points were used to separate the patients into hyper-inflammatory (n = 52) and control (n = 353) groups. Finally, the logistic were used to find the risk factors of hyper-inflammatory. RESULTS: PCT, CRP, IL-6, and SII were independent risk factors of poor outcomes in the multivariate logistic model. Cut-off points of these biomarkers were 2.18 ng/ml, 49.76 mg/L, 301.88 pg/ml, 2509.96 × 109/L respectively. These points were used to define postoperative hyper-inflammation (OR 2.97, 95% CI 1.35-6.53, P < 0.01). Cardiopulmonary bypass (CPB) > 180 min, and deep hypothermia circulatory arrest (DHCA) > 40 min were the independent risk factors for hyper-inflammation. CONCLUSIONS: PCT > 2.18, CRP > 49.76, IL-6 > 301.88, and SII < 2509.96 could be used to define postoperative hyper-inflammation which increased mortality and morbidity in patients after ATAAD surgery. Based on these findings, we found that CPB > 180 min and DHCA > 40 min were separate risk factors for postoperative hyper-inflammation.

Sivelestat in Patients at a High Risk of Postoperative Acute Lung Injury After Scheduled Cardiac Surgery: A Prospective Cohort Study.

Background: Sivelestat, a neutrophil elastase inhibitor, is specifically developed to mitigate the occurrence of acute lung injury (ALI) in individuals who are undergoing cardiovascular surgery. However, its impact on patients who are at a heightened risk of developing ALI after scheduled cardiac surgery has yet to be determined. In order to address this knowledge gap, we undertook a study to assess the efficacy of sivelestat in protecting the lungs of these patients. Methods: We conducted a prospective cohort study involving 718 patients who were at high risk of developing postoperative acute lung injury (ALI) and underwent scheduled cardiac surgery between April 25th, 2022, and September 7th, 2023. Among them, 52 patients received sivelestat (administered at a dosage of 0.2mg/kg/h for 3 days), while 666 patients served as controls, not receiving sivelestat. The control conditions were the same for all patients, including ventilation strategy, extubating time, and fluid management. Subsequently, a propensity-score matched cohort was established, consisting of 40 patients in both the sivelestat and control groups. The primary outcome measure encompassed a composite of adverse outcomes, including 30-day mortality, ALI, acute respiratory distress syndrome (ARDS), and others. Secondary outcomes assessed included pneumonia, ventricular arrhythmias, mechanical ventilation (MV) time, and more. Results: After conducting propensity matching in our study, we observed that there were no significant differences in 30-day mortality between the sivelestat and control groups (0% vs 2.5%, P=0.32). However, the use of sivelestat exhibited a significant reduction in the incidence of acute lung injury/acute respiratory distress syndrome (ALI/ARDS) compared to the control group (0% vs 55%, P<0.01), pneumonia (0 vs 37.5%, P<0.01), MV time (median:8 hours, IQR:4-14.8 hours vs median: 15.2 hours, IQR:14-16.3 hours, P<0.01). Compared to the control group, the sivelestat could significantly decrease white cell count (P<0.01), neutrophile percentage (P<0.01) and C-reactive protein (P<0.01) in the period of postoperative 5 days. Conclusion: The prophylactic administration of sivelestat has shown promising results in reducing the occurrence of acute lung injury/acute respiratory distress syndrome (ALI/ARDS) in patients with a heightened risk of developing these conditions after elective cardiac surgery. Our study findings indicate that sivelestat may provide protective effects by suppressing inflammation triggered by neutrophil activation, thereby safeguarding pulmonary function. Registration: ChiCTR2200059102, https://www.chictr.org.cn/showproj.html?proj=166643.

Short- and Mid-Term Survival Prediction in Patients with Acute Type A Aortic Dissection Undergoing Surgical Repair: Based on the Systemic Immune-Inflammation Index.

Purpose: The postoperative survival of patients with acute type A aortic dissection (aTAAD) remains unsatisfactory. The current study developed an easy-to-use survival prediction model and calculator. Methods: A total of 496 patients with aTAAD undergoing surgical repair were included in this study. The systemic immune-inflammation index (SII) and other clinical features were collected and subjected to logistic and Cox regression analyses. The survival prediction model was based on Cox regression analyses and exhibited as a nomogram. For convenience of use, the nomogram was further developed into calculator software. Results: We demonstrated that a higher preoperative SII was associated with in-hospital death (OR: 4.116, p < 0.001) and a higher postoperative overall survival rate (HR: 2.467, p < 0.001) in aTAAD patients undergoing surgical repair. A survival prediction model and calculator based on SII and four other clinical features were developed. The overall C-index of the model was 0.743. The areas under the curves (AUCs) of the 1- and 3-month and 1- and 3-year survival probabilities were 0.73, 0.71, 0.71 and 0.72, respectively. The model also showed good calibration and clinical utility. Conclusion: Preoperative SII is significantly associated with postoperative survival. Based on SII and other clinical features, we created the first easy-to-use prediction model and calculator for predicting the postoperative survival rate in aTAAD patients, which showed good prediction performance.