The elevated admission white blood cell count relates to adverse surgical outcome of acute Stanford type a aortic dissection

Major adverse outcomes in patients with acute type A aortic dissection undergoing total arch replacement with frozen elephant trunk procedure

BACKGROUND

The objective of this investigation was to identify the risk factors linked to major adverse outcomes (MAO) subsequent to total arch replacement with frozen elephant trunk procedure (TAR+FET) surgery among patients diagnosed with acute type A aortic dissection (ATAAD). Additionally, the study aimed to elucidate the influence of these adverse outcomes on the long-term prognosis of the patients.

METHOD

670 ATAAD patients received the TAR+FET procedure. Multivariable logistic regression was used to investigate the risk factors associated with in-hospital MAO. Additionally, long-term survival outcomes were assessed through follow-up observations of all patients.

RESULTS

The overall in-hospital mortality was 4.33%. Among 670 patients, 169 patients (25.22%) developed postoperative MAO. Multivariate analysis showed that in-hospital MAO was positively associated with age (OR = 1.025, 95%CI: 1.005-1.045, P = 0.014), lower limb symptoms (OR = 2.562, 95%CI: 1.407-4.666, P = 0.002), involvement of coronary artery (OR = 2.027, 95%CI: 1.312-3.130, P = 0.001), involvement of left renal artery (OR = 1.998, 95%CI: 1.359-2.938, P < 0.001), CPB time (OR = 1.011, 95%CI: 1.007-1.015, P < 0.001) and WBC counts (OR = 1.045, 95%CI: 1.007-1.083, P = 0.019). MAO group showed a worse long-term prognosis than those non-MAO group (P = 0.002).

CONCLUSIONS

While TAR+FET can be an effective treatment option for ATAAD patients, careful patient selection and management are essential in minimizing the risk of MAO and ensuring long-term success.

Inflammatory Trajectory and Anti-Inflammatory Pharmacotherapy in Frozen Elephant Trunk-Treated Acute Type I Aortic Dissection

Background

Acute DeBakey type I aortic dissection is associated with high morbidity and mortality. Little is known regarding the role of leukocyte trajectory in prognosis.

Methods

We included adult acute DeBakey type I aortic dissection patients with emergency frozen elephant trunk and total arch replacement in 2 cardiovascular centers (2020-2022). We used latent class mixed model to group patients according to their leukocyte patterns from hospital admission to the first 5 days after surgery. We investigated the association of leukocyte trajectory and 30-day and latest follow-up mortality (October 31, 2023), exploratorily analyzing the effects of ulinastatin treatment on outcome.

Results

Of 255 patients included, 3 distinct leukocyte trajectories were identified: 196 in group I (decreasing trajectory), 34 in group II (stable trajectory), and 25 in group III (rising trajectory). Overall, 30-day mortality was 25 (9.8%), ranging from 8.2% (16/196) in group I, 8.8% (3/34) in group II, to 24.0% (6/25) in group III (P for trend = .036). Group III was associated with higher mortality both at 30 days (adjusted hazard ratio, 3.260; 95% CI, 1.071-9.919; P = .037) and at the last follow-up (adjusted hazard ratio, 2.840; 95% CI, 1.098-7.345; P = .031) compared with group I.

Conclusions

Distinct and clinically relevant groups can be identified by analyzing leukocyte trajectories, and a rising trajectory was associated with higher short-term and midterm mortality.

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.

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.

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.

A predictive model for postoperative adverse outcomes following surgical treatment of acute type A aortic dissection based on machine learning

Acute type A aortic dissection (AAAD) has a high probability of postoperative adverse outcomes (PAO) after emergency surgery, so exploring the risk factors for PAO during hospitalization is key to reducing postoperative mortality and improving prognosis. An artificial intelligence approach was used to build a predictive model of PAO by clinical data-driven machine learning to predict the incidence of PAO after total arch repair for AAAD. This study included 380 patients with AAAD. The clinical features that are associated with PAO were selected using the LASSO regression analysis. Six different machine learning algorithms were tried for modeling, and the performance of each model was analyzed comprehensively using receiver operating characteristic curves, calibration curve, precision recall curve, and decision analysis curves. Explain the optimal model through Shapley Additive Explanation (SHAP) and perform an individualized risk assessment. After comprehensive analysis, the authors believe that the extreme gradient boosting (XGBoost) model is the optimal model, with better performance than other models. The authors successfully built a prediction model for PAO in AAAD patients based on the XGBoost algorithm and interpreted the model with the SHAP method, which helps to identify high-risk AAAD patients at an early stage and to adjust individual patient-related clinical treatment plans in a timely manner.

Predicting Mortality Following Odontoid Fracture Fixation in Elderly Patients: CAADS-16 Score

STUDY DESIGN

Retrospective Review of a National Database.

INTRODUCTION

By utilizing a national database, this study aims to quantify the predictors of 30-day mortality after odontoid fixation and guide appropriate management for patients in whom the choice between operative and non-operative management is unclear.

METHODS

The American College of Surgeons National Surgical Quality Improvement Database was queried using Current Procedural Terminology (CPT) codes and International Classification of Disease (ICD) codes to identify patients 60 or older who underwent surgical fixation of an odontoid fracture from 2005 to 2020. Risk factors for mortality significant in univariate and subsequent multivariate analysis were used to develop a scoring system to predict post-operative mortality.

RESULTS

608 patients were identified. Patients were split into a non-mortality 30 days post-op group, and into a mortality 30 days post-op group. The following risk factors were included in the scoring system: functional dependency, disseminated cancer, albumin less than 3.5, WBC count greater than 16 k, anterior surgical approach, and pre-op SIRS. Using a cutoff value of 2, the CAAD-16 score had a sensitivity and specificity of 82% and 81%, respectively. The ASA score, cutoff at 4, showed a sensitivity and specificity of 64% and 75% respectively.

CONCLUSIONS

This sample of 294 patients represents one of the largest samples of odontoid fracture fixation patients available in the literature and comes from a nationally representative database. We structure relevant risk factors into the CAADS-16 score, which has the potential to be a clinically relevant tool to prevent short-term postoperative mortality.

Risk factors for early death after surgery in patients with acute Stanford type A aortic dissection: A systematic review and meta-analysis

BACKGROUND

There are many risk factors related to early death after surgery among patients with acute Stanford type A aortic dissection (ATAAD) that have been analyzed in previous studies, but no evidence-based study has been conducted to confirm these risk factors.

AIMS

The aims of this study were to investigate risk factors for early death after surgery in patients with ATAAD via systematic review and meta-analysis and assess evidence-based strategies for preventing adverse events.

METHODS

The protocol for this study was prospectively registered with PROSPERO (CRD 42022332772). The authors systematically searched PubMed, Ovid, Scopus, Web of Science and Cochrane Library following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines from database construction to May 2021. Studies that met the selection criteria were determined by two independent researchers, and the odds ratios (ORs) and 95% confidence intervals (95% CIs) were reported for the risk factors and were pooled using Stata 15.0.

RESULTS

A total of 23 studies including 5510 patients met the inclusion criteria, and 10 risk factors were analyzed in this meta-analysis. The preoperative risk factors for early death after surgery in patients with ATAAD were age [(OR: 1.03, 95% CI (1.01, 1.06)], male sex [(OR: 1.43, 95% CI (1.06, 1.92)], shock [(OR: 1.91, 95% CI (1.06, 3.45)], malperfusion [(OR: 3.45, 95% CI (2.24, 5.31)] and cardiac tamponade [(OR: 3.89, 95% CI (1.17, 12.98)].

CONCLUSION

Patients with ATAAD who have an older age, male sex, shock, malperfusion and cardiac tamponade have a higher risk for early death after surgery. However, more highly homogenous studies are needed to demonstrate these results. Clinical staff should pay more attention to these factors and take individual actions to reduce mortality after surgery in patients with ATAAD.

Prediction of in-hospital death following acute type A aortic dissection

Background

Our goal was to create a prediction model for in-hospital death in Chinese patients with acute type A aortic dissection (ATAAD).

Methods

A retrospective derivation cohort was made up of 340 patients with ATAAD from Tianjin, and the retrospective validation cohort was made up of 153 patients with ATAAD from Nanjing. For variable selection, we used least absolute shrinkage and selection operator analysis, and for risk scoring, we used logistic regression coefficients. We categorized the patients into low-, middle-, and high-risk groups and looked into the correlation with in-hospital fatalities. We established a risk classifier based on independent baseline data using a multivariable logistic model. The prediction performance was determined based on the receiver operating characteristic curve (ROC). Individualized clinical decision-making was conducted by weighing the net benefit in each patient by decision curve analysis (DCA).

Results

We created a risk prediction model using risk scores weighted by five preoperatively chosen variables [AUC: 0.7039 (95% CI, 0.643–0.765)]: serum creatinine (Scr), D-dimer, white blood cell (WBC) count, coronary heart disease (CHD), and blood urea nitrogen (BUN). Following that, we categorized the cohort's patients as low-, intermediate-, and high-risk groups. The intermediate- and high-risk groups significantly increased hospital death rates compared to the low-risk group [adjusted OR: 3.973 (95% CI, 1.496–10.552), P &lt; 0.01; 8.280 (95% CI, 3.054–22.448), P &lt; 0.01, respectively). The risk score classifier exhibited better prediction ability than the triple-risk categories classifier [AUC: 0.7039 (95% CI, 0.6425–0.7652) vs. 0.6605 (95% CI, 0.6013–0.7197); P = 0.0022]. The DCA showed relatively good performance for the model in terms of clinical application if the threshold probability in the clinical decision was more than 10%.

Conclusion

A risk classifier is an effective strategy for predicting in-hospital death in patients with ATAAD, but it might be affected by the small number of participants.

Prognostic significance of neutrophil count on in-hospital mortality in patients with acute type A aortic dissection

Backgrounds

The goal of this study was to assess the impact of neutrophil count, in patients with acute type A aortic dissection (ATAAD).

Methods

This study retrospectively collected data from patients between September 2017 and June 2021. Youden's index was used to determine the optimal cut-off value for the neutrophil count and patients were divided into two subgroups. A restricted cubic spline (RCS) was used to model the relationship between variables and in-hospital mortality. The least absolute shrinkage and selection operator (LASSO) method and multivariate logistic regression analyses were used to investigate the independent prognostic factors for in-hospital mortality in patients with ATAAD.

Results

A total of 467 patients were enrolled in this study. In-hospital mortality was 7.28%. The group with elevated neutrophil counts had significantly higher mortality than the group with decreased neutrophil counts (10.8% vs. 3.2%, P = 0.02). This data shows that elevated neutrophil count was significantly associated with in-hospital mortality (OR 3.07, 95% CI 1.22-7.62, P = 0.02).

Conclusions

Neutrophil count is an independent risk factor for in-hospital mortality in patients with ATAAD. It is an effective inflammatory index, which can be individualized for patients.

Prognostic Impact of Systemic Coagulation-Inflammation Index in Acute Type A Aortic Dissection Surgery

BACKGROUND

A novel hematologic parameter, systemic coagulation-inflammation (SCI) index reflecting inflammation and coagulation pathways could be easily obtained from clinically routine laboratory findings. We hypothesize that the SCI index has prognostic implication in predicting operative mortality for patients with acute type A aortic dissection (ATAAD).

OBJECTIVES

This study aims to investigate the prognostic value of the SCI index and to establish an SCI-adding nomogram for mortality prediction in ATAAD patients.

METHODS

A total of 1,967 ATAAD patients surgically repaired were collected from 12 Chinese cardiovascular centers by the 5A (Additive Anti-inflammatory Action for Aortopathy & Arteriopathy [Multicenter Retrospective Study]) study III (2016-2020). SCI index was calculated as platelet count × fibrinogen/white blood cell count on admission. By adding SCI index, a nomogram was developed and evaluated for 90-day mortality prediction with conventional predictors via the Cox model with 10-fold cross-validation.

RESULTS

Patients were stratified with low SCI (<40), middle SCI (40-100), or high SCI (>100). The 90-day survival rates increased with SCI index (low 86.9%; [95% CI: 84.9%-89.0%], middle 92.7% [95% CI: 90.9%-94.9%], and high 96.4% [95% CI: 94.2%-98.6%]; log-rank P < 0.001). SCI index is independently associated with 90-day mortality (adjusted hazard ratio: 0.549; 95% CI: 0.424-0.710; P < 0.001). The addition of SCI index provided significantly incremental prognostic value to base model including age, serum creatinine, DeBakey class, and location of intimal entry (area under the curve: 0.677; 95% CI: 0.641-0.716 vs 0.724; 95% CI: 0.685-0.760; P = 0.002), which was confirmed by net reclassification improvement index (0.158; 95% CI: 0.065-0.235; P < 0.001) and integrated discrimination improvement index (0.070; 95% CI: 0.007-0.036; P < 0.001).

CONCLUSIONS

SCI index is easily obtainable, performs moderately well as a predictor of short-term mortality in ATAAD patients, and may be useful for risk stratification in emergency settings. (Additive Anti-inflammatory Action for Aortopathy & Arteriopathy [Multicenter Retrospective Study] III NCT04918108).

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.

Less Known but Clinically Relevant Comorbidities of Atrial Fibrillation: A Narrative Review

BACKGROUND

The important risk factors for atrial fibrillation (AF) in the general population are not always equally important in specific and relatively prevalent diseases.

OBJECTIVE

The main goal of this narrative review is to focus attention on the presence and the relationship of AF with several important diseases, such as cancer or sepsis, in order to: 1) stimulate further research in the field, and 2) draw attention to this relationship and search for AF in clinical practice.

METHODS

We searched PubMed, SCOPUS, Elsevier, Wiley, Springer, Oxford Journals, Cambridge, SAGE, and Google Scholar for less-known comorbidities of AF. The search was limited to publications in English. No time limits were applied.

RESULTS

AF is widely represented in cardiovascular and other important diseases, even in those in which AF is rarely mentioned. In some specific clinical subsets of AF patients (e.g., patients with sepsis or cancer), the general risk factors for AF may not be so important. Patients with new-onset AF have a several-fold increase in relative risk of cancer, deep vein thrombosis, and pulmonary thromboembolism (PTE) during the follow-up.

CONCLUSION

AF presence, prognosis, and optimal therapeutic approach are insufficiently recognised in several prevalent diseases, including life-threatening ones. There is a need for a better search for AF in PTE, pulmonary oedema, aortic dissection, sepsis, cancer and several gastrointestinal diseases. Improved AF detection would influence treatment and improve outcomes.

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

Background

Eosinophils are pro-inflammatory cells involved in thrombosis and have been proposed as a prognosis marker in acute ischemic stroke and ST-elevation myocardial Infarction. Here, we sought to clarify the prognostic value of eosinophil percentage (EOS%) in patients with acute type A aortic dissection (AAAD).

Methods

We examined 183 consecutive AAAD patients. Based on the optimum cut-off value of EOS% determined by X-tile software, patients were classified into the low EOS% (EOS% ≤ 0.1) and high EOS% groups (EOS% > 0.1). We performed multivariate regression analysis and Kaplan–Meier (KM) survival curves to assess the association between EOS% and mortality. Eosinophil accumulation in aortic dissection intraluminal thrombus was confirmed using hematoxylin–eosin (H&E) staining. An external cohort from Medical Information Mart for Intensive Care IV was performed to validate the results.

Results

Relative to surviving patients, those who died during hospitalization had significantly lower EOS% (p = 0.001) but significantly higher WBC (p = 0.002) and neutrophil (p = 0.001) counts. Multivariate regression analysis identified EOS% as an independent predictor of in-hospital and 1-year mortality. KM curves revealed that 1-year cumulative mortality was significantly higher in the low EOS% group, although it was mainly attributed to the higher 30-day mortality. H&E staining revealed massive infiltration of eosinophils in all 20 thrombus specimens. The external validation confirmed that relative to survivors, patients with in-hospital mortality (p = 0.010) had significantly lower EOS%. Moreover, multivariate regression analyses identified that decreased EOS% was independently significantly associated with in-hospital mortality.

Conclusions

Low EOS% is significantly related to increased mortality rates in AAAD patients.

Development and validation of a risk prediction model for postoperative pneumonia in adult patients undergoing Stanford type A acute aortic dissection surgery: a case control study

Background

Pneumonia is a common complication after Stanford type A acute aortic dissection surgery (AADS) and contributes significantly to morbidity, mortality, and length of stay. The purpose of this study was to identify independent risk factors associated with pneumonia after AADS and to develop and validate a risk prediction model.

Methods

Adults undergoing AADS between 2016 and 2019 were identified in a single-institution database. Patients were randomly divided into training and validation sets at a ratio of 2:1. Preoperative and intraoperative variables were included for analysis. A multivariate logistic regression model was constructed using significant variables from univariate analysis in the training set. A nomogram was constructed for clinical utility and the model was validated in an independent dataset.

Results

Postoperative pneumonia developed in 170 of 492 patients (34.6%). In the training set, multivariate analysis identified seven independent predictors for pneumonia after AADS including age, smoking history, chronic obstructive pulmonary disease, renal insufficiency, leucocytosis, low platelet count, and intraoperative transfusion of red blood cells. The model demonstrated good calibration (Hosmer–Lemeshow χ² = 3.31, P = 0.91) and discrimination (C-index = 0.77) in the training set. The model was also well calibrated (Hosmer–Lemeshow χ² = 5.73, P = 0.68) and showed reliable discriminatory ability (C-index = 0.78) in the validation set. By visual inspection, the calibrations were good in both the training and validation sets.

Conclusion

We developed and validated a risk prediction model for pneumonia after AADS. The model may have clinical utility in individualized risk evaluation and perioperative management.

Back-Table Modified Stent-Graft for Endovascular Repair of Ascending Aorta

OBJECTIVES

To investigate the effectiveness of modified stent-grafts (SGs) for the management of ascending aortic pathologies.

MATERIALS AND METHODS

From January 2015 to December 2019, 31 individuals were treated by ascending aortic endovascular repair with a back-table modified SG for acute (n=4) or chronic (n=1) type A aortic dissections, penetrating aortic ulcers (n=18), pseudoaneurysms (n=2), anastomotic fistula (n=1), and endoleaks after thoracic endovascular aortic repair (TEVAR) (n=5). The commercially available thoracic aortic SGs were modified with a fenestration or truncation technique on the back-table according to aortography during the operation.

RESULTS

The 30-day mortality and aorta-related mortality rates were 12.9% and 6.5%, respectively. There were 2 strokes, 3 respiratory insufficiencies, and 6 endoleaks during hospitalization. During a mean follow-up of 28.8±16.6 months, the overall survival rates at 1 year and 3 years were both 80.6%. Free from adverse event rates at 1 year and 3 years were 88.9% and 84.7%, respectively. There were 2 deaths during follow-up: One patient died of cachexia 1 month after discharge, and the other patient died of acute myocardial infarction 3 months after discharge. One patient with a pseudoaneurysm underwent open ascending aorta replacement 3 months after discharge for a type Ia endoleak. Another patient suffered from cerebellar infarction 17 months after discharge.

CONCLUSION

The modified SG for endovascular repair of the ascending aorta is a practicable alternative and presents acceptable outcomes in high-risk patients.

The risk factors for postoperative acute respiratory distress syndrome in Stanford type a acute aortic dissection patients

OBJECTIVE

To explore the risk factors for postoperative acute respiratory distress syndrome (ARDS) in Stanford type A acute aortic dissection (AAD) patients.

METHODS

This study included 64 patients with Stanford type A AAD who underwent Sun's procedure. The patients were divided into an ARDS group (PaO₂/FiO₂ < 200 mmHg) and a non-ARDS group (PaO₂/FiO₂ ≥ 200 mmHg). We compared the patients' perioperative clinical features in the two groups. A multivariate binary logistic regression was used to analyze the risk factors for ARDS in the Stanford type A AAD patients.

RESULTS

The incidence of postoperative ARDS was 56.25%. There were 13 deaths in the 6-month follow-up, including 8 in the ARDS group and 5 in the non-ARDS group. There were differences in the body mass index (BMI) levels, the times from onset to operation, the preoperative white blood cell counts, the preoperative hemoglobin levels, the preoperative alanine aminotransferase levels, the preoperative blood creatinine levels, the preoperative PaO₂/FiO₂, intraoperative blood transfusion volumes, the assisted mechanical ventilation times, and the durations of the intensive care unit stays between the two groups (all P < 0.05). The logistic regression analysis revealed that a BMI ≥ 25 kg/m², a time from onset to operation ≥ 24 hours, a preoperative white blood cell count ≥ 10×10⁹/L, and a preoperative PaO₂/FiO₂ < 300 mmHg were the independent risk factors for postoperative ARDS in patients with Stanford type A AAD.

CONCLUSIONS

ARDS occurs often in Stanford type A AAD patients. A BMI ≥ 25 kg/m², a time from onset to operation ≥ 24 hours, a preoperative white blood cell count ≥ 10×10⁹/L, and a preoperative PaO₂/FiO₂ < 300 mmHg are the independent risk factors for postoperative ARDS in these patients.

Identification of Molecular Regulatory Features and Markers for Acute Type A Aortic Dissection

BACKGROUND

Acute type A aortic dissection (ATAAD) is one of the most lethal cardiovascular diseases, and its molecular mechanism remains unclear.

METHODS

Differentially expressed genes (DEGs) between ATAAD and control were detected by limma R package in GSE52093, GSE153434, GSE98770, and GSE84827, respectively. The coexpression network of DEGs was identified by the WGCNA package. Enrichment analysis was performed for module genes that were positively correlated with ATAAD using clusterProfiler R package. In addition, differentially methylated markers between aortic dissection and control were identified by ChAMP package. After comparing with ATAAD-related genes, a protein-protein interaction (PPI) network was established based on the STRING database. The genes with the highest connectivity were identified as hub genes. Finally, differential immune cell infiltration between ATAAD and control was identified by ssGSEA.

RESULTS

From GSE52093 and GSE153434, 268 module genes were obtained with consistent direction of differential expression and high correlation with ATAAD. They were significantly enriched in T cell activation, HIF-1 signaling pathway, and cell cycle. In addition, 2060 differentially methylated markers were obtained from GSE84827. Among them, 77 methylation markers were ATAAD-related DEGs. Using the PPI network, we identified MYC, ITGA2, RND3, BCL2, and PHLPP2 as hub genes. Finally, we identified significantly differentially infiltrated immune cells in ATAAD.

CONCLUSION

The hub genes we identified may be regulated by methylation and participate in the development of ATAAD through immune inflammation and oxidative stress response. The findings may provide new insights into the molecular mechanisms and therapeutic targets for ATAAD.

Prognostic role of neutrophil-to-lymphocyte ratio in aortic disease: a meta-analysis of observational studies

OBJECTIVE

Recent studies have reported that neutrophil-to-lymphocyte ratio (NLR) is associated with cardiovascular disease. The aim of the present study was to investigate the prognostic value of NLR in aortic disease.

METHODS

We systematically searched electronic databases (Cochrane, PubMed, Elsevier, Medline, and Embase) from their inception to March 2020. Observational studies that evaluated the relationship between NLR and aortic disease were eligible for critical appraisal. Data were extracted from applicable articles, risk ratio (RR), weighted mean differences (MD) and 95% confidence intervals (CI) were calculated by RevMan 5.3, and statistical heterogeneity was assessed by the I² statistic.

RESULTS

Fourteen studies enrolling 4066 individuals were included in the meta-analysis. Compared with the control group, NLR was significantly higher in the aortic disease group (MD 3.44, 95%CI: 0.81-6.07, P = 0.01, I² = 99%). The NLR was also significantly higher in non-survivors with aortic disease, compared to the survivors (MD 4.62, 95%CI: 2.75-6.50, P < 0.00001, I² = 60%). Compared with the aortic disease patients with a low NLR, mortality was significantly higher in those with a high NLR (RR 2.63, 95%CI: 1.79-3.86, P < 0.00001, I² = 67%).

CONCLUSION

Based on current evidence, an elevated NLR was associated with aortic disease and in-hospital mortality. Raised NLR also demonstrated a significantly increased the risk of mortality after surgical repair in aortic disease patients. NLR may be a good prognostic biomarker in aortic disease and deserve further research in this area.