A preoperative mortality risk assessment model for Stanford type A acute aortic dissection

Prediction Model of in Hospital Death for Stanford Type A Aortic Dissection Based on a Meta-analysis of 24 Cohorts

AIMS

Patients with Stanford type A aortic dissection (TAAD) have high postoperative mortality. This study aimed to develop a prediction model for in-hospital death after surgery in patients with TAAD .

METHODS

The derivation cohort came from a meta-analysis. Major risk factors were counted. The corresponding hazard ratio was reported to establish a prediction model for in-hospital death in patients with TAAD. Validation cohorts from 2 centres were used to evaluate the prediction model.

RESULTS

The meta-analysis included 24 cohort studies with a total of 11404 patients and 1554 patients died early after surgery. Risk factors for the prediction model included age, body mass index, smoking, coronary heart disease, preoperative stroke, shock, preoperative cardiopulmonary resuscitation, pericardial tamponade and malperfusion. Patients with TAAD admitted to the First and the Fourth Hospital of Hebei Medical University between January 2020 and June 2024 were retrospectively collected. Patients from the 2 hospitals constituted validation cohorts A (n = 262) and B (n = 138). Risk scores were calculated for model validation and the prediction model demonstrated better differentiation for validation cohort A, with an area under the curve of 0.886 (95% confidence interval 0.842-0.931).

CONCLUSION

This study established a simple risk prediction model, including 13 risk factors, to predict in-hospital death in patients with TAAD. However, multi-center data is still needed to evaluate the prediction accuracy of the model.

Influence of Surgical Expertise on Repair of Acute Type a Aortic Dissection in a Standardized Operative Setting

Background/Objectives: The influence of surgeon expertise on patients' outcomes after repair of acute type A aortic dissection (ATAAD) is not well established. The aim of this paper is to report the results of ATAAD repair performed by expert (ES) and not expert aortic surgeons (NES) in our center. Methods: We have retrospectively divided 199 patients into two groups according to the first surgeon experience (ES = 138 patients and NES = 61 patients), all being members of the aortic team. We evaluated and compared early and long-term outcomes. Results: Although the two groups were comparable in terms of clinical presentation and intraoperative setting, ES performed more aortic arch repairs (40% vs. 26%, p = 0.06) and frozen elephant trunk procedures (15% vs. 3%, p = 0.02), albeit with similar intraoperative times (median cardiopulmonary bypass time of 203 min in ES vs. 201 min in NES, respectively, p = 0.88). The 30-day mortality was the same in the two groups (8%, p = 1), and the postoperative course was similar except for a shorter in-hospital stay in the NES group (10 vs. 17 days, p = 0.04). Conclusions: In our experience, repair of ATAAD could be achieved with similar results between ES and NES. However, NES performed less technically demanding repairs. With standardization of pre-, intra-, and post-operative management, NES can be expected to increase their technical skills and be progressively involved in more complex ATAAD repairs without adversely affecting surgical results.

Predictors of In-Hospital Mortality in Type A Acute Aortic Syndrome: Data From the RENADA-RO Registry

BACKGROUND

This study aimed to analyse the baseline characteristics of patients admitted with acute type A aortic syndrome (ATAAS) and to identify the potential predictors of in-hospital mortality in surgically managed patients.

METHODS

Data regarding demographics, clinical presentation, laboratory work-up, and management of 501 patients with ATAAS enrolled in the National Registry of Aortic Dissections-Romania registry from January 2011 to December 2022 were evaluated. The primary endpoint was in-hospital all-cause mortality. Multivariate logistic regression was conducted to identify independent predictors of mortality in patients with acute Type A aortic dissection (ATAAD) who underwent surgery.

RESULTS

The mean age was 60±11 years and 65% were male. Computed tomography was the first-line diagnostic tool (79%), followed by transoesophageal echocardiography (21%). Cardiac surgery was performed in 88% of the patients. The overall mortality in the entire cohort was 37.9%, while surgically managed ATAAD patients had an in-hospital mortality rate of 29%. In multivariate logistic regression, creatinine value (OR 6.76), ST depression on ECG (OR 6.3), preoperative malperfusion (OR 5.77), cardiogenic shock (OR 5.77), abdominal pain (OR 4.27), age ≥70 years (OR 3.76), and syncope (OR 3.43) were independently associated with in-hospital mortality in surgically managed ATAAD patients.

CONCLUSIONS

Risk stratification based on the variables collected at admission may help to identify ATAAS patients with high risk of death following cardiac surgery.

Central nervous injury risk factors after endovascular repair of a thoracic aortic aneurysm with type B aortic dissection

BACKGROUND

Aortic dissection is the deadliest disease of the cardiovascular system. Type B aortic dissection accounts for 30%-60% of aortic dissections and is mainly treated by endovascular repair of thoracic endovascular aneurysm repair (TEVAR). However, patients are prone to various complications after surgery, with central nervous system injury being the most common, which seriously affects their prognosis and increases the risk of disability and death. Therefore, exploring the risk factors of central nervous system injury after TEVAR can provide a basis for its prevention and control.

AIM

To investigate the risk factors for central nervous system injury after the repair of a thoracic endovascular aneurysm with type B aortic dissection.

METHODS

We enrolled 306 patients with type B aortic dissection who underwent TEVAR at our hospital between December 2019 and October 2022. The patients were categorized into injury (n = 159) and non-injury (n = 147) groups based on central nervous system injury following surgery. The risk factors for central nervous system injury after TEVAR for type B aortic dissection were screened by comparing the two groups. Multivariate logistic regression analysis was performed.

RESULTS

The Association between age, history of hypertension, blood pH value, surgery, mechanical ventilation, intensive care unit stay, postoperative recovery times on the first day after surgery, and arterial partial pressure of oxygen on the first day after surgery differed substantially (P < 0.05). Multivariate logistic regression analysis indicated that age, surgery time, history of hypertension, duration of mechanical ventilation, and intensive care unit stay were independent risk factors for central nervous system injury after TEVAR of type B aortic dissection (P < 0.05).

CONCLUSION

For high-risk patients with central nervous system injury after TEVAR of type B aortic dissection, early intervention measures should be implemented to lower the risk of neurological discomfort following surgery in high-risk patients with central nervous system injury after TEVAR for type B aortic dissection.

Innominate Artery Translocation with Hemiarch Replacement Strategy for Acute Type A Aortic Dissection: a Single-Center Study

BACKGROUND

 Aggressive surgical methods for acute type A aortic dissection (ATAD) can cause extended operating times and postoperative complications. less extensive techniques may increase the risk of needing further aortic reintervention. To prevent the need for extensive aortic arch surgery and subsequent re-sternotomy, hemiarch replacement (HAR) with innominate artery (a.) translocation is performed to create a suitable proximal landing zone for future endovascular repair.

METHODS

 Retrospective study of 112 patients with ATAD who underwent aortic surgery from January 2009 to December 2020. Forty-one patients underwent HAR with innominate artery translocation, 16 underwent total arch replacement (TAR), and 55 underwent only HAR. Multivariable Cox regression and logistic regression analyses were used to study the outcomes and risk factors.

RESULTS

 The TAR group had a higher incidence of postoperative acute kidney injury. The overall mortality rate of the TAR group was 25%, compared with 20% in the HAR group and 14.6% in the translocation group. The 5-year overall survival rates for the groups were 81.9%, 75.0%, and 77.7%, respectively. False lumen thrombosis at the aortic arch and descending aorta level were factors associated with reduced mortality in both univariable and multivariable analyses. The translocation group had a significantly higher reintervention rate of 41.5% compared with the TAR and HAR groups, with rates of 31.3% and 16.4%, respectively. The median reintervention time for the translocation group was 4.72 years.

CONCLUSION

 Despite the innominate translocation technique having a higher reintervention rate, it had similar mortality outcomes to HAR and TAR. Thus, it could be a more convenient option for reintervention, including creating a proximal landing zone, which could benefit patients needing endovascular repair.

Role of Helicopter Transfer and Cloud-Type Imaging for Acute Type A Aortic Dissection

BACKGROUND

 This study explored if long-distance transfer was safe for patients suffering from acute aortic dissection type A (AADA) and also analyzed the effectiveness of helicopter transfer and cloud-type imaging transfer systems for such patients in northern Hokkaido, Japan.

METHODS AND RESULTS

 The study included 112 consecutive patients who underwent emergency surgical treatment for AADA from April 2014 to September 2020. The patients were divided into two groups according to the location of referral source hospitals: the Asahikawa city group (group A, n = 49) and the out-of-the-city group (group O, n = 63). Use of helicopter transfer (n = 13) and cloud-type telemedicine (n = 20) in group O were reviewed as subanalyses.Transfer distance differed between groups (4.2 ± 3.5 km in group A vs 107.3 ± 69.2 km in group O; p = 0.0001), but 30-day mortality (10.2% in group A vs 7.9% in group O; p = 0.676) and hospital mortality (12.2% in group A vs 9.5% in group O; p = 0.687) did not differ. Operative outcomes did not differ with or without helicopter and cloud-type telemedicine, but diagnosis-to-operation time was shorter with helicopter (240.0 ± 70.8 vs 320.0 ± 78.5 minutes; p = 0.031) and telemedicine (242.0 ± 75.2 vs 319.0 ± 83.8 minutes; p = 0.007).

CONCLUSION

 We found that long-distance transfer did not impair surgical outcomes in AADA patients, and both helicopter transfer and cloud-type telemedicine system could contribute to the reduction of diagnosis-to-operation time in the large Hokkaido area. Further studies are mandatory to investigate if both the systems will improve clinical outcomes.

Prognostic value of TCBI for short-term outcomes in ATAD patients undergoing surgery

OBJECTIVE

Nutritional status has been reported to be associated with the prognosis of cardiovascular diseases. The study aimed to investigate the prognostic value of Triglycerides-total Cholesterol-Body weight-Index (TCBI) for short-term mortality in acute type A aortic dissection (ATAD) patients undergoing surgery.

METHODS AND RESULTS

Totally, the data of 290 ATAD patients undergone surgery were, retrospectively, analyzed. After logistic regression analysis, TCBI was identified as an independent predictor of short-term mortality in ATAD surgery. The development of receive operating characteristic (ROC) curve demonstrated that TCBI (AUC = 0.745, P < 0.001) could provide well prognostic value for short-term mortality. Accordingly, the optimal cut-off value was identified as 883.5 and patients were divided into high TCBI (> 883.5) and low TCBI (≤ 883.5) groups. Furthermore, Kaplan-Meier analysis illustrated that short-term mortality increased significantly in the low TCBI group than in the high TCBI group (P < 0.0001). In addition, the incidence of postoperative renal failure was also elevated in the low TCBI group (P = 0.0011).

CONCLUSION

Malnutrition by preoperative TCBI presented strong prognostic value for patients following ATAD surgery. And TCBI could be applied for risk stratification and therapeutic strategy-making in ATAD.

Endovascular Treatment of Type A Aortic Dissection: A Systematic Review and Meta-Analysis Using Reconstructed Time-to-Event Data

OBJECTIVE

The undisputed gold standard of treatment for type A aortic dissections (TAAD) is open surgery. Anecdotal reports have assessed thoracic endovascular aortic repair (TEVAR) as a last resort for highly selected candidates. The present study aims to evaluate endovascular outcomes in TAAD patients who are unsuitable for open surgery whilst having TEVAR-compatible aortic anatomy.

METHODS

A PRISMA-compliant systematic search of the PubMed, Scopus, and Cochrane databases was performed up to 19 May 2022. Time-to-event data were reconstructed using Kaplan-Meier curves from the source literature.

RESULTS

In 20 eligible studies, 311 patients underwent TEVAR for acute, subacute, or chronic TAAD. Mean age at the time of the operation was 60.70 ± 8.00 years and 75.48% (95% Confidence Interval [CI], 60.33-88.46%) of the included patients were males. Mean operative time was 169.40 ± 30.70 min. Overall, 0.44% (95% CI, 0.00-4.83%) of the cases were converted to salvage open surgery. Technical failure, stroke, and endoleaks occurred in 0.22%, 0.1%, and 8.52% of the cohort, respectively. Thirty-day postoperative complication rate was 7.08% (95% CI, 1.52-14.97%), whereas late complications developed in 16.89% (95% CI, 7.75-27.88%) of the patients. One-, three-, and five-year survival rates were estimated at 87.15%, 82.52% and 82.31%, respectively. Reintervention was required in 8.38% of the cohort over a mean follow-up of 32.40 ± 24.40 months.

CONCLUSIONS

TEVAR seems to be feasible in highly selected patients with TAAD who cannot tolerate open surgery. Overcoming technical limitations and acquiring long-term data are warranted to safely define the place of endovascular treatment in the armamentarium of TAAD repair.

Preoperative arterial lactate and outcome after surgery for type A aortic dissection: The ERTAAD multicenter study

Background

Acute type A aortic dissection (TAAD) is associated with significant mortality and morbidity. In this study we evaluated the prognostic significance of preoperative arterial lactate concentration on the outcome after surgery for TAAD.

Methods

The ERTAAD registry included consecutive patients who underwent surgery for acute type A aortic dissection (TAAD) at 18 European centers of cardiac surgery.

Results

Data on arterial lactate concentration immediately before surgery were available in 2798 (71.7 %) patients. Preoperative concentration of arterial lactate was an independent predictor of in-hospital mortality (mean, 3.5 ± 3.2 vs 2.1 ± 1.8 mmol/L, adjusted OR 1.181, 95%CI 1.129-1.235). The best cutoff value preoperative arterial lactate concentration was 1.8 mmol/L (in-hospital mortality, 12.0 %, vs. 26.6 %, p < 0.0001). The rates of in-hospital mortality increased along increasing quintiles of arterial lactate and it was 12.1 % in the lowest quintile and 33.6 % in the highest quintile (p < 0.0001). The difference between multivariable models with and without preoperative arterial lactate was statistically significant (p = 0.0002). The NRI was 0.296 (95%CI 0.200-0.391) (p < 0.0001) with -17 % of events correctly reclassified (p = 0.0002) and 46 % of non-events correctly reclassified (p < 0.0001). The IDI was 0.025 (95%CI 0.016-0.034) (p < 0.0001). Six studies from a systematic review plus the present one provided data for a pooled analysis which showed that the mean difference of preoperative arterial lactate between 30-day/in-hospital deaths and survivors was 1.85 mmol/L (95%CI 1.22-2.47, p < 0.0001, I2 64 %).

Conclusions

Hyperlactatemia significantly increased the risk of mortality after surgery for acute TAAD and should be considered in the clinical assessment of these critically ill patients.

Analysis of risk factors for postoperative mortality in acute type A aortic dissection patients under different critical levels

We built up a risk stratification model to divide acute type A aortic dissection (aTAAD) patients into low- and high-risk groups, further, to evaluate the risk factors for postoperative mortality. A total of 1364 patients from 2010 to 2020 in our center were retrospectively analyzed. More than twenty clinical variables were related with postoperative mortality. The postoperative mortality of the high-risk patients was doubled than the low-risk ones (21.8% vs 10.1%). The increased operation time, combined coronary artery bypass graft, cerebral complications, re-intubation, continuous renal replacement therapy and surgical infection were risk factors of postoperative mortality in low-risk patients. In addition, postoperative lower limbs or visceral malperfusion were risk factors, axillary artery cannulation and moderate hypothermia were protective factors in high-risk patients. A scoring system for quick decision-making is needed to select appropriate surgical strategy in aTAAD patients. For low-risk patients, different surgical treatments can be performed with similar clinical prognosis. Limited arch treatment and appropriate cannulation approach are crucial in high-risk aTAAD patients.

Prediction of preoperative in-hospital mortality rate in patients with acute aortic dissection by machine learning: a two-centre, retrospective cohort study

OBJECTIVES

To conduct a comprehensive analysis of demographic information, medical history, and blood pressure (BP) and heart rate (HR) variability during hospitalisation so as to establish a predictive model for preoperative in-hospital mortality of patients with acute aortic dissection (AD) by using machine learning techniques.

DESIGN

Retrospective cohort study.

SETTING

Data were collected from the electronic records and the databases of Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine and the First Affiliated Hospital of Anhui Medical University between 2004 and 2018.

PARTICIPANTS

380 inpatients diagnosed with acute AD were included in the study.

PRIMARY OUTCOME

Preoperative in-hospital mortality rate.

RESULTS

A total of 55 patients (14.47%) died in the hospital before surgery. The results of the areas under the receiver operating characteristic curves, decision curve analysis and calibration curves indicated that the eXtreme Gradient Boosting (XGBoost) model had the highest accuracy and robustness. According to the SHapley Additive exPlanations analysis of the XGBoost model, Stanford type A, maximum aortic diameter >5.5 cm, high variability in HR, high variability in diastolic BP and involvement of the aortic arch had the greatest impact on the occurrence of in-hospital deaths before surgery. Moreover, the predictive model can accurately predict the preoperative in-hospital mortality rate at the individual level.

CONCLUSION

In the current study, we successfully constructed machine learning models to predict the preoperative in-hospital mortality of patients with acute AD, which can help identify high-risk patients and optimise the clinical decision-making. Further applications in clinical practice require the validation of these models using a large-sample, prospective database.

TRIAL REGISTRATION NUMBER

ChiCTR1900025818.

Admission D-dimer to lymphocyte counts ratio as a novel biomarker for predicting the in-hospital mortality in patients with acute aortic dissection

BACKGROUND

Inflammatory factors are well-established indicators for vascular disease, but the D-dimer to lymphocyte count ratio (DLR) is not measured in routine clinical care. Screening of DLR in individuals may identify individuals at in-hopital mortality of acute aortic dissection (AD).

METHODS

A retrospective analysis of clinical data from 2013 to 2020 was conducted to identify which factors were related to in-hospital mortality risk of AD. Baseline clinical features, cardiovascular risk factors, and laboratory parameters were obtained from the hospital database. The end point was in-hospital mortality. Forward conditional logistic regression was performed to identify independent risk factors for AA in-hospital death. The cutoff value of the DLR should be ideally calculated by receiver operating characteristic (ROC) analysis.

RESULTS

The in-hospital mortality rate was 15% (48 of 320 patients). Patients with in-hospital mortality had a higher admission mean DLR level than the alive group (1740 vs. 1010, P < .05). The cutoff point of DLR was 907. The in-hospital mortality rate in the high-level DLR group was significantly higher than that in the low-level DLR group (P < .05). Univariate analysis showed that 8 of 38 factors were associated with in-hospital mortality (P < .05), including admission WBC, neutrophils, lymphocytes, neutrophils/lymphocytes (NLR), prothrombin time (PT), heart rate (HR), D-dimer, and DLR. In multivariate analysis, DLR (odds ratio [OR] 2.127, 95% CI 1.034-4.373, P = 0.040), HR (odds ratio [OR] 1.016, 95% CI 1.002-1.030, P = 0.029) and PT (odds ratio [OR] 1.231, 95% CI 1.018-1.189, P = 0.032) were determined to be independent predictors of in-hospital mortality (P < .05).

CONCLUSION

Compared with the common clinical parameters PT and HR, serum DLR level on admission is an uncommon but independent parameter that can be used to assess in-hospital mortality in patients with acute AD.

Predictive value of age, creatinine, and ejection fraction (ACEF) scoring system for operative mortality in patients with Stanford type A aortic dissection

Purpose

Stanford type A aortic dissection (TAAD) is the most common and fatal type of dissection. An easier-to-use risk stratification may help eliminate bias in patients at high risk of dissection. The age, serum creatinine, and ejection fraction (ACEF) score is a simple risk model developed to predict the mortality risk of elective coronary artery bypass graft surgery. This study aimed to evaluate the relationship between preoperative ACEF score and operative mortality in patients with TAAD undergoing emergency surgery.

Methods

In this retrospective cohort study, 113 patients diagnosed with TAAD between January 2017 and September 2021 were evaluated. The primary endpoint was operative mortality. Receiver operating characteristic analysis was performed for the ACEF score, ACEF II score, and European System for Cardiac Operative Risk Evaluation II. Univariate and multivariate analyses of operative mortality were performed using the logistic regression model.

Results

Operative mortality occurred in 23 (20.4%) patients. The cutoff ACEF score was calculated as 1.1 for predicting operative mortality (area under the curve = 0.712, P value = 0.002, sensitivity = 74.0%, specificity = 67.8%, likelihood ratio = 2.3). Based on the cutoff value, 46 (40.7%) patients had a high ACEF score (ACEF ≥ 1.1) and 67 (59.3%) patients had a low ACEF score (ACEF < 1.1). The high ACEF score was associated with an increased incidence of operative mortality compared with the low ACEF score (37.0% vs. 9.0%; P = 0.001).

Conclusions

The ACEF score can be used as a useful and relatively simple tool for risk stratification before TAAD surgery. However, the ACEF score is only indicated for risk assessment and should not affect treatment.

Application of Logistic Regression and Artificial Intelligence in the Risk Prediction of Acute Aortic Dissection Rupture

Logistic regression (LR) and artificial intelligence algorithms were used to analyze the risk factors for the early rupture of acute type A aortic dissection (ATAAD). Data from electronic medical records of 200 patients diagnosed with ATAAD from the Department of Emergency of Guangdong Provincial People’s Hospital from April 2012 to March 2017 were collected. Logistic regression and artificial intelligence algorithms were used to establish prediction models, and the prediction effects of four models were analyzed. According to the LR models, we elucidated independent risk factors for ATAAD rupture, which included age > 63 years (odds ratio (OR) = 1.69), female sex (OR = 1.77), ventilator assisted ventilation (OR = 3.05), AST > 80 U/L (OR = 1.59), no distortion of the inner membrane (OR = 1.57), the diameter of the aortic sinus > 41 mm (OR = 0.92), maximum aortic diameter > 48 mm (OR = 1.32), the ratio of false lumen area to true lumen area > 2.12 (OR = 1.94), lactates > 1.9 mmol/L (OR = 2.28), and white blood cell > 14.2 × 109 /L (OR = 1.23). The highest sensitivity and accuracy were found with the convolutional neural network (CNN) model. Its sensitivity was 0.93, specificity was 0.90, and accuracy was 0.90. In this present study, we found that age, sex, select biomarkers, and select morphological parameters of the aorta are independent predictors for the rupture of ATAAD. In terms of predicting the risk of ATAAD, the performance of random forests and CNN is significantly better than LR, but the performance of the support vector machine (SVM) is worse than LR.

A Novel Inflammation-Based Risk Score Predicts Mortality in Acute Type A Aortic Dissection Surgery: The Additive Anti-inflammatory Action for Aortopathy and Arteriopathy Score

OBJECTIVE

To develop an inflammation-based risk stratification tool for operative mortality in patients with acute type A aortic dissection.

METHODS

Between January 1, 2016 and December 31, 2021, 3124 patients from Beijing Anzhen Hospital were included for derivation, 571 patients from the same hospital were included for internal validation, and 1319 patients from other 12 hospitals were included for external validation. The primary outcome was operative mortality according to the Society of Thoracic Surgeons criteria. Least absolute shrinkage and selection operator regression were used to identify clinical risk factors. A model was developed using different machine learning algorithms. The performance of the model was determined using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves, and Brier score for calibration. The final model (5A score) was tested with respect to the existing clinical scores.

RESULTS

Extreme gradient boosting was selected for model training (5A score) using 12 variables for prediction-the ratio of platelet to leukocyte count, creatinine level, age, hemoglobin level, prior cardiac surgery, extent of dissection extension, cerebral perfusion, aortic regurgitation, sex, pericardial effusion, shock, and coronary perfusion-which yields the highest AUC (0.873 [95% confidence interval (CI) 0.845-0.901]). The AUC of 5A score was 0.875 (95% CI 0.814-0.936), 0.845 (95% CI 0.811-0.878), and 0.852 (95% CI 0.821-0.883) in the internal, external, and total cohort, respectively, which outperformed the best existing risk score (German Registry for Acute Type A Aortic Dissection score AUC 0.709 [95% CI 0.669-0.749]).

CONCLUSION

The 5A score is a novel, internally and externally validated inflammation-based tool for risk stratification of patients before surgical repair, potentially advancing individualized treatment.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT04918108.

Total arch replacement versus proximal aortic replacement in acute type A aortic dissection: Aggressive versus conservative

BACKGROUND

Acute type A aortic dissection (ATAAD) is a life-threatening medical condition requiring urgent surgical attention. It is estimated that 50% of ATAAD die within 24 h of onset, with the mortality rate is increasing by 1%-2% every additional hour without prompt intervention. A variety of ATAAD surgical repair techniques exist which has sparked controversy within the literature, with the main two strategies being proximal aortic replacement (PAR) and total arch replacement (TAR). Nevertheless, the question of which of these two strategies if the more optimal is still debatable.

AIMS

This commentary aims to discuss the recent study by Sa and colleagues which presents a pooled analysis of Kaplan-Meier-derived individual patient data from studies with follow-up comparing aggressive (TAR) and conservative (PAR) approaches to manage ATAAD patients.

METHODS

A comprehensive literature search was performed using multiple electronic databases including PubMed, Ovid, Google Scholar, EMBASE, and Scopus to collate the relevant research evidence.

RESULTS

The more aggressive TAR approach for treating ATAAD seems to yield more favorable results including more optimal long-term survival as well as a lower need for reoperation. The frozen elephant trunk (FET) technique can be considered the mainstay TAR technique.

CONCLUSION

It is valid to conclude that TAR with FET is the superior strategy for managing ATAAD patients.

ALDH2 knockout protects against aortic dissection

Background

The incidence and mortality of aortic dissection (AD) are increasing. In pathological studies, macrophages, T lymphocytes and dendritic cells were found in the tunica media of the aorta. Acetaldehyde dehydrogenase 2 (ALDH₂) gene polymorphisms are associated with a high incidence of hypertension in Asian populations. However, there is no clear evidence of the relationship between ALDH₂ and aortic dissection in Asians. The aim of this study was to investigate the incidence of aortic dissection in different ALDH₂ genotypes and explore changes in the vasculature.

Materials and methods

Three-week-old male mice were administered freshly prepared β-aminopropionitrile solution dissolved in drinking water (1 g/kg/d) for 28 days to induce TAD. An animal ultrasound imaging system was used to observe the formation of arterial dissection and changes in cardiac function. Subsequently, mice were euthanized by cervical dislocation. The aortas were fixed for HE staining and EVG staining to observe aortic elastic fiber tears and pseudoluma formation under a microscope.

Results

Knockout of ALDH₂ mitigated β-aminopropionitrile-induced TAD formation in animal studies. Ultrasound results showed that ALDH₂ knockout reduced the degree of ascending aortic widening and the incidence of aortic dissection rupture. Pathological sections of multiple aortic segments showed that the protective effect of ALDH₂ knockout was observed in not only the ascending aorta but also the aortic arch and descending aorta. The expression levels of genes related to NK CD56bright cells, Th17 cells, T cells and T helper cells were decreased in ALDH₂ knockout mice treated with β-aminopropionitrile for 28 days.

Conclusion

ALDH₂ knockout protects against aortic dissection by altering the inflammatory response and immune response and protecting elastic fibers.

Preliminary evaluation of the Chinese version of the patient-reported outcomes measurement information system 29-item profile in patients with aortic dissection

BACKGROUND

The Patient-Reported Outcomes Measurement Information System 29-item Profile (PROMIS-29) has been widely used to measure health outcomes from the patient's perspective. It has not been validated in adults with aortic disease. The aim of this study was to explore the reliability and validity of the Chinese PROMIS-29 among patients undergoing surgery for aortic dissection (AD).

METHODS

A cross-sectional design was applied. Eligible patients completed a questionnaire that contained the PROMIS-29 and legacy measures, including the Short Form-12 Health Survey (SF-12), 8-item Somatic Symptom Scale (SSS-8), Generalized Anxiety Disorder-2 (GAD-2), and Patient Health Questionnaire-2 (PHQ-2). The structural validity of the PROMIS-29 was evaluated using confirmatory factor analysis (CFA). Reliability was evaluated with Cronbach's α. Construct validity was assessed by calculating Spearman's rank correlations and comparing known-group differences.

RESULTS

In total, a sample of 327 AD patients was included in the final analysis. Most of them were male (89%) with a mean age of 52.7 (± 10.3). CFA revealed good model fit of the seven-factor structure within PROMIS-29, as well as most domains in single-factor analysis. Reliability was confirmed with Cronbach's α > 0.90. Correlations between comparable domains of the PROMIS-29 and those of legacy questionnaires and most know-group comparisons were observed as hypothesized.

CONCLUSIONS

This study found evidence for acceptable structural validity, construct validity and internal consistency of the PROMIS-29 in a sample of AD patients. It can be applied to AD survivors by researchers or clinicians, measuring outcomes after surgery and identifying those with worse health status.

Early Prediction Model of Acute Aortic Syndrome Mortality in Emergency Departments

Purpose

Acute aortic syndrome is a constellation of life-threatening medical conditions for which rapid assessment and targeted intervention are important for the prognosis of patients who are at high risk of in-hospital death. The current study aims to develop and externally validate an early prediction mortality model that can be used to identify high-risk patients with acute aortic syndrome in the emergency department.

Patients and Methods

This retrospective multi-center observational study enrolled 1088 patients with acute aortic syndrome admitted to the emergency departments of two hospitals in China between January 2017 and March 2021 for model development. A total of 210 patients with acute aortic syndrome admitted to the emergency departments of Peking University Third Hospital between January 2007 and December 2021 was enrolled for model validation. Demographics and clinical factors were collected at the time of emergency department admission. The predictive variables were determined by referring to the results of previous studies and the baseline analysis of this study. The study’s endpoint was in-hospital death. To assess internal validity, we used a fivefold cross-validation method. Model performance was validated internally and externally by evaluating model discrimination using the area under the receiver-operating characteristic curve (AUC). A nomogram was developed based on the binary regression results.

Results

In the development cohort, 1088 patients with acute aortic syndromes were included, and 88 (8.1%) patients died during hospitalization. In the validation cohort, 210 patients were included, and 20 (9.5%) patients died during hospitalization. The final model included the following variables: digestive system symptoms (OR=2.25; P=0.024), any pulse deficit (OR=7.78; P<0.001), creatinine (µmol/L)(OR=1.00; P=0.018), lesion extension to iliac vessels (OR=4.49; P<0.001), pericardial effusion (OR=2.67; P=0.008), and Stanford type A (OR=10.46; P<0.001). The model’s AUC was 0.838 (95% CI 0.784–0.892) in the development cohort and 0.821 (95% CI 0.750–0.891) in the validation cohort, and the Hosmer–Lemeshow test showed p=0.597. The fivefold cross-validation demonstrated a mean accuracy of 0.94, a mean precision of 0.67, and a mean recall of 0.13.

Conclusion

This risk prediction tool uses simple variables to provide robust prediction of the risk of in-hospital death from acute aortic syndrome and validated well in an independent cohort. The tool can help emergency clinicians quickly identify high-risk acute aortic syndrome patients, although further studies are needed for verifying the prospective data and the results of our study.

Lactate levels: A reliable tool to predict mortality in acute type A aortic dissections?

Lactate levels are surrogate markers of malperfusion in patients presenting with type A aortic dissections. Lactate measurement is simple, easy to perform, universally available, and thus can be an important tool for predicting mortality. However, the discriminatory power varies between studies and no cut-off point has been defined that can determine outcomes in the most reliable fashion. The risk prediction based on lactate levels can be improved when combined with other clinical and laboratory prognostic factors. Further studies with a much larger sample size, need to be carried out using serial measurements at well-defined time points to try and identify a cut-off value. The addition of lactate values to existing risk prediction scores or developing a new score based on it should be the subject of future research.

Risk factors for 30-day mortality in patients who received DeBakey type I aortic dissection repair surgery

Objective

This study aimed to identify risk factors for 30-day mortality in patients who received DeBakey type I aortic dissection (AD) repair surgery.

Methods

A total of 830 consecutive patients who received acute DeBakey type I AD surgery between 2014 and 2019 were included in the study. The associations between 30-day mortality and perioperative parameters were examined in order to identify risk factors.

Results

Our data suggested that the overall 30-day mortality rate of all enrolled patients was 11.7%. Unsurprisingly, non-survivors were older and more frequently accompanied with histories of cardiovascular diseases. For intraoperative parameters, the prevalence of coronary artery bypass grafting and cardiopulmonary bypass times were increased in non-survivors. In addition, acute kidney injury (AKI), dialysis, stroke, and deep sternal wound infection were more commonly seen among non-survivors. The multivariate logistic regression analysis suggested that cardiovascular disease history, preoperative D-dimer level, drainage volume 24 h after surgery, and postoperative AKI were independent risk factors for 30-day mortality after DeBakey type I aortic dissection repair surgery.

Conclusions

Our study demonstrated that cardiovascular disease history, preoperative D-dimer level, drainage volume 24 h after surgery as well as postoperative AKI were risk factors for 30-day mortality after DeBakey type I aortic dissection repair surgery.

Risk factors and in-hospital mortality of postoperative hyperlactatemia in patients after acute type A aortic dissection surgery

Background

Hyperlactatemia may be caused by increased production due to tissue hypoxia or non-hypoxia. The aim of this study was first to identify risk factors for postoperative hyperlactatemia (POHL) after Stanford type A acute aortic dissection surgery (AADS) and construct a predictive model, and second to evaluate the impact of POHL on prognosis.

Methods

This retrospective study involved patients undergoing AADS from January 2016 to December 2019 in Wuhan Union Hospital. Multivariate logistic regression analysis was performed to identify independent risk factors for POHL. A nomogram predicting POHL was established based on these factors and was validated in the original dataset. The receiver operating characteristic curve was drawn to assess the ability of postoperative lactate levels to predict the in-hospital mortality.

Results

A total of 188 patients developed POHL after AADS (38.6%). Male gender, surgery history, red blood cell transfusion and cardiopulmonary bypass time were identified as independent predictors. The C-index of the prediction model for POHL was 0.72, indicating reasonable discrimination. The model was well calibrated by visual inspection and goodness-of-fit test (Hosmer–Lemeshow χ² = 10.25, P = 0.25). Decision and clinical impact curves of the model showed good clinical utility. The overall in-hospital mortality rate was 10.1%. Postoperative lactate levels showed a moderate predictive power for postoperative in-hospital mortality (C-index: 0.72).

Conclusion

We developed and validated a prediction model for POHL in patients undergoing AADS, which may have clinical utility in personal risk evaluation and preventive interventions. The POHL could be a good predictor for in-hospital mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02244-7.