Assessing GERAADA Score Mortality Predictions in Type A Aortic Dissection Patients

doi:10.21203/rs.3.rs-3933237/v1

Objective: This study seeks to assess the predictive precision of the GERAADA score for 30-day mortality in patients with Type A aortic dissection.

Methods: A retrospective study analyzed data from 382 survivors and 90 non-survivors, examining demographic, clinical, and surgical variables. GERAADA scores were calculated by a blinded cardiac surgeon using a web-based application.

Results: The overall mortality is 19.06% and 18.18% for GERAADA prediction.

The presence of malperfusion in more than two organs emerged as a significant risk factor for hospital mortality p=0.028. Longer surgery times were significantly associated with elevated mortality p=0.002. Moreover, postoperative ECMO, CPR, and IABP were significantly linked to increased mortality rates. Additionally, ICU stay duration, lung infection, MODS, and respiratory failure p<0.05 independently posed as risk factors for hospital mortality.

Patients with Hemiparesis and peripheral malperfusion experienced no deaths, as predicted by GERAADA score. Additionally, patients with a dissection tear located at the root of the aorta exhibited a lower mortality rate of 7.14%, contrasting the higher 19.87% GERAADA prediction.

Conclusion: GERAADA predictions were mostly accurate, but exceptions occurred with inotrope use, hemiparesis, peripheral malperfusion, and aortic dissection at the root. We suggest enhancing the GERAADA score by incorporating intraoperative and postoperative factors.

type A aortic dissection

surgery

risk factors

prediction score

mortality

Acute Type A Aortic Dissection (ATAAD) stands as a formidable challenge in the realm of cardiovascular medicine, characterized by its life-threatening nature and high mortality rates¹. Despite the availability of well-equipped cardiac centers capable of providing precise and timely diagnoses, along with advanced surgical techniques for aortic dissection, the mortality rate remains alarmingly high². In-hospital mortality for ATAAD still varies between 5% and 25% ³⁴. Mortality risk factors in Type A aortic dissection have long been a subject of concern in the medical community. Gaining a comprehensive understanding of these factors is instrumental not only for risk assessment but also for the development of more effective and informed treatment strategies.

Recently, a novel risk assessment tool for forecasting 30-day mortality in patients afflicted with ATAAD has emerged, akin to the EuroSCORE and the Society of Thoracic Surgeons score. Referred to as the German Registry of Acute Aortic Dissection Type A (GERAADA) score, this system employs straightforward and readily obtainable parameters, making it specially tailored for the prediction of 30-day mortality rates in aortic dissection patients undergoing surgical intervention⁵. Our clinical study aimed to retrospectively analyze our institutional results in the context of the newly introduced GERAADA score, to evaluate its accuracy in a consecutive series of Chinese patients diagnosed with ATAAD.

This study constitutes a retrospective analysis encompassing consecutive patients diagnosed with Type A Aortic Dissection at the Cardiovascular Surgery Department of Tongji Hospital during the period spanning January 2021 to December 2022. Patient data were meticulously gathered through a review of medical records. Exclusion criteria comprised patients who had succumbed either before or during surgery, as well as those who did not undergo surgical intervention. In total, 472 patients met the inclusion criteria for analysis. In cases where emergency surgical procedures were not immediately performed, patients underwent intubation and sedation to mitigate the risk of aortic rupture and associated mortality before their scheduled surgeries. Data collection encompassed the 11 key preoperative parameters essential for GERAADA score computation, including age, gender, prior cardiac surgeries, inotropic support upon referral, pre-surgery resuscitation, aortic regurgitation, preoperative hemiparesis, intubation/ventilation status at referral, preoperative organ malperfusion, extent of aortic dissection, and primary entry site location. The GERAADA score calculations were meticulously conducted by a cardiac surgeon, blinded to the study, for all patients using the dedicated web-based application GERAADA_score.

Surgical procedure

Operative Approach

The primary strategy for cases of Type A aortic dissection encompassed emergency central repair within 24 hours for over 70% of cases, addressing rupture, and potentially revascularizing unresolved malperfused areas. The procedure involved a median sternotomy combined with a conventional cardiopulmonary bypass. Cannulation utilized either a femoral, subclavian artery, or a combination of both, with a single atriocaval cannula employed for right atrial cannulation. Myocardial protection for all patients was ensured through antegrade or retrograde infusion of a cold blood cardioplegic solution. Furthermore, a left ventricular drain was inserted through the right upper pulmonary vein.

Operative technique

FET frozen elephant trunk was performed in most of the cases in this study.The technique consists of the implantation of the stented distal segment of the hybrid-prosthesis into the descending aorta through the opened aortic arch, while the proximal non-stented segment is used for conventional replacement of the upstream aorta.The stent that was used with the FET procedure was inserted into the descending aorta under direct vision. Then, the aortic arch was replaced by a 4-branch graft. The left carotid artery, the innominate artery and the left subclavian artery were reconstructed sequentially.

Statistical analysis

The mean and standard deviation were used to describe continuous variables. The difference between the two groups was compared using the Student's t-test. Categorical variables were presented as percentages or frequency distributions, and differences between the groups were assessed using the χ2 test or Fisher exact test. Multivariate logistic regression modeling was used to determine independent perioperative predictors of in-hospital death. Odds ratios (ORs) and hazard ratios (HRs) are presented with 95% confidence intervals (CIs).

We defined 30-day mortality as any death occurring within the initial 30 days following surgery. Categorical variables were presented as counts and percentages, while continuous variables were represented as either median with interquartile or means with standard deviations. We conducted binomial testing to compare the GERAADA score's predicted mortality percentage to the observed mortality percentage for both the overall study cohort and its respective subgroups. Within each patient group, GERAADA scores served as the expected probability of adverse events (or predictive values), while the number of deaths and patient observations represented the count of events and trials⁶. The two-sided binomial tests were subsequently employed to rigorously test the binomial hypothesis. Additionally, receiver operating characteristic analyses were carried out for each group comparison. To assess the influence of available variables on 30-day mortality, a multivariable regression model was applied.A P-value<0.05 was considered to be statistically significant and all statistical analyses were performed using R version 4.2.3 (2023-03-15 ucrt).

The baseline characteristics were similar between the two groups for the majority of variables considered as shown in table1. However, a noteworthy finding was the significant difference observed in cases of malperfusion involving more than two organs. In this regard, the incidence was 5.8% in the group of survivors compared to 13.3% in the non-survivors, with a p-value of 0.023.

Patients in the non-survivor group had a longer surgery duration, with an average of 573.01±129.72 minutes, compared to 535.62±122.42 minutes in the survivor group (table 2).

The non-survivor group had significantly higher percentages of using ECMO and IABP (6.7% vs. 0.3%, p<0.001), (6.7% vs. 0.5%,p<0.001).Most CPR (10% vs. 0%, p<0.001) and postoperative tracheotomy (18.9% vs. 9.2%, p=0.014) were performed on death group, and the same group patients stayed longer in ICU (17.31% vs. 10.39%, p<0.001). The survived group patients were extubating after surgery earlier than the death group (14.10% vs. 6.11%, p<0.001 table3).

Additionally, the non-survivor group experienced higher rates of paralysis (8.9% vs. 2.4%, p=0.007), lung infection (36.7% vs. 7.3%, p<0.001), GI bleeding (14.4% vs. 2.9%, p<0.001), MODS (20% vs. 0.3%, p<0.001), respiratory failure (22.2% vs. 0.3%, p<0.001), and cardiac failure (16.7% vs. 0%, p<0.001). These differences were statistically significant and emerged as univariate predictors for 30-day mortality(table3).

ICU stay (OR 1.08, 95% CI 1.02-1.14, p=0.012), lung infection (OR 15.35, 95% CI 5.49-45.26, p<0.001), MODS (OR 159.19, 95% CI 17.54-5320.35, p<0.001), and respiratory failure (OR 229.91, 95% CI 34.55-5654.37, p<0.001) were identified as independent risk factors associated with 30-day mortality (Table 4).

In table 5 we presented GERAADA prediction mortality and actual mortality rates in various subgroups of patients with Type A aortic dissection (AAD). It provides valuable insights into the accuracy of the GERAADA score in predicting 30-day mortality. The GERAADA prediction for patients aged below 50 was 17.94%, with an actual mortality of 19.3%, while for patients aged 50 and above, the prediction was 18.07%, and the actual mortality was 18.92%. In both age groups, the prediction closely approximated the actual mortality, with p-values of 0.642 and 0.7163, respectively.

Sex, previous surgery, inotrope use and specific aortic regurgitation levels did not show a notable difference. Patients without malperfusion had a GERAADA prediction of 18.01% and an actual mortality of 17.5%. Cerebral malperfusion patients had a prediction of 17.99%, with an actual mortality of 23.5%. For cardiac malperfusion, the prediction was 18.45%, and the actual mortality was 24.4%. Visceral malperfusion had a GERAADA prediction of 7.99%, and the actual mortality was 16.21%. Patients with peripheral malperfusion had a prediction of 18.45%, and there were no actual mortalities. Other malperfusion patients had a GERAADA prediction of 17.38%, while the actual mortality was 35.71%. The highest discrepancy between prediction and actual mortality was observed in the other malperfusion group, with a p-value of 0.05708. Hemiparesis patients had a GERAADA prediction of 18.59%, and there were no actual mortalities in this group. Patients with aortic entry had a GERAADA prediction of 18.07%, and the actual mortality was 19.50%. Ascending entry patients had a prediction of 17.97%, and the actual mortality was 20.9%. Patients with descending entry had a GERAADA prediction of 18.36%, and the actual mortality was 19.4%. Root entry patients had a prediction of 17.88%, with an actual mortality of 7.14%. The most significant difference between prediction and actual mortality was observed in the "root entry" group, with a p-value of 0.01095.

The German Registry of Acute Aortic Dissection Type A (GERAADA) score uses very basic and easily retrievable parameters and was specifically designed for predicting the 30-day mortality rate in patients undergoing surgery for acute aortic dissection.Czerny et al. stressed that the GERAADA score should not be viewed as an absolute decision-making tool for accepting or rejecting treatment. Instead, it should be considered a valuable instrument for predicting postoperative outcomes using easily accessible and fundamental parameters⁵. Given the elevated mortality rate associated with type A aortic dissection, this predictive scoring system can be a valuable asset for surgeons.

The overall mortality rate in our study stands at 19.06%, while the GERAADA score predicted a mortality of 18.18%.No significant difference was found between the mortality group and the predicted group with an Area Under Curve of 0.599 (95% CI 0.558, 0.622) (Fig. 1).In their study, M. Ma et al. found that the GERAADA score and EuroSCORE II predicted 30-day mortality rates of 14.7% and 3.1%, respectively, while the observed rate was 12.5%⁷. On a similar note, K. Sugiyama et al. calculated an overall 30-day mortality for their study cohort using the GERAADA score as 14.3%(8.1–77.6%),whereas the actual mortality rate was 6%⁸.GERAADA has the particularity to be focused on aortic dissection and take in consideration some aspect of complications of ATAAD like malperfusion.

Malperfusion is recognized to occur in a significant portion of ATAAD cases, affecting approximately 20–30% of patients⁹. Consequently, the mortality rate for individuals experiencing this complication varies significantly, falling within the range of 17–44%¹⁰. It is crucial to emphasize that aortic dissection complicated by malperfusion is intimately associated with heightened mortality rates. This risk is amplified as the extent of organ involvement increases, making the management of multiple organ malperfusion an especially formidable challenge. Our study further supports this connection by revealing a noteworthy correlation between multiple organ malperfusion and in-hospital mortality. This finding is consistent with the research conducted by Kawahito and colleagues¹¹. Numerous studies have examined mortality risk factors, and many of them have identified independent risk factors, as reflected in our study. Recent research conducted by Khan et al a range of independent risk factors associated with prolonged ICU stays have been identified. These factors encompass age, preoperative D-dimer levels, CPB time, the use of deep hypothermic circulatory arrest, the occurrence of postoperative stroke, postoperative acute respiratory failure, and postoperative acute renal failure⁹¹²¹³. Our study corroborates these recent research findings, highlighting that the duration of ICU stay, lung infections, and respiratory failure identified as risk factors for in-hospital mortality¹⁴¹⁵. This association can primarily be attributed to postoperative interventions within the ICU, such as ECMO, IABP, CPR, tracheotomy, and the prolonged use of mechanical ventilation, all of which have been identified in our study as contributing factors to hospital mortality.

In our actual mortality group, a notable increase in mortality is observed, particularly reaching 35.71% in cases categorized as other malperfusion, where multiple organ malperfusion is present. This contrasts with the lower prediction of 17.38% (± 1.80). Luehr et al., in their literature, reported a similar trend with more deaths in the study group, particularly in the prediction score for coronary malperfusion, where the actual mortality was 29.6% compared to the predicted 30% (± 19.4)⁶ and for other malperfusion the reported 19.9% (± 19.4) for GERAADA prediction score vs 24%for the study group. No deaths were observed in patients with hemiparesis or those experiencing peripheral malperfusion, contrary to the predictions. This underscores the effectiveness of prompt aortic and organ reperfusion¹⁶. Patients with hemiparesis and peripheral malperfusion experienced significant post-surgery recovery, with their symptoms greatly alleviated.

The GERAADA prediction score in our study, with an Area Under Curve (AUC) of 0.599 (95% CI: 0.558–0.622) as depicted in Fig. 1, does not represent a robust model for predicting mortality in ATAAD patients.Similar to the findings of I.Zivkovi whose study concluded that EuroSCORE II demonstrates superior discriminative power for predicting operative mortality in ATAAD surgery compared to the GERAADA score. Both scoring systems demonstrate good calibration ability.In a recent assessment of popular online prediction models, Ma et al. discovered that the EuroSCORE II displayed superior predictive accuracy for surgical mortality in ATAAD patients, with the observed 30-day mortality rate validating the GERAADA score's excellent calibration⁷.

Furthermore, S. Lilyanna et al. propose that the optimal utilization of the new GERAADA score should not be for patient selection or decision-making but rather for quality control and performance comparison between different hospitals, facilitating retrospective evaluation and improved resource management.

Some recent studies have proposed more effective models tailored to ATAAD patients¹⁷¹⁸. H. Lin et al. introduced a straightforward nomogram based on six predictors, including left ventricular end-diastolic diameter < 45mm, estimated glomerular filtration rate < 50 ml/min/1.73 m², persistent abdominal pain, radiological celiac trunk malperfusion, concomitant coronary artery bypass grafting, and cardiopulmonary bypass time > 4 hours, to predict 30-day mortality. Meanwhile, T. Guo et al. in their literature presented a highly effective machine learning model with an AUC of 0.927 (95% CI: 0.860–0.968) ¹⁹²⁰.

These results indicate a potential avenue for improving the predictive precision of the GERAADA score, designed for aortic dissection, by integrating intraoperative factors, given the continual advancements in surgical techniques. This enhancement gains significance, especially in the backdrop of ongoing progress in surgical methods and postoperative ICU care.K.Sugiyama suggest to add parameters such as the time from onset to arrival, family background, and hemodialysis for further accuracy.

Study limitation

This study has certain limitations that should be acknowledged. It is a retrospective, single-center investigation that incorporates various surgical approaches and involves multiple surgeons. Furthermore, the criteria and diagnosis of malperfusion may deviate from those established by the GERAADA score.

While the GERAADA predictions generally exhibited reliable accuracy, occasional discrepancies were identified in specific cases involving inotrope utilization, hemiparesis, peripheral malperfusion, and aortic dissection at the root. The GERAADA score, designed for acute Type A aortic dissection, can be refined through the inclusion of intraoperative and postoperative factors particularly in the face of advancing surgical techniques and improved postoperative ICU care.

ATAAD acute Type A aortic dissection , ECMO extracorporeal membrane oxygenation, CRRT continuous renal replacement therapy, ICU intensive care unit, IABP intra-aortic balloon pump, CPR cardiopulmonary resuscitation. GERAADA German Registry of Acute Aortic Dissection type A, FET frozen elephant trunk.

Ethical Approval and Consent to participate

The study has been approved by the Medical Ethics Committee of Tongji Hospital TJ-IRB202402062.Written informed consent was deemed unnecessary in accordance with the local legislation and institutional requirements.

Consent for publication

Not applicable.

Availability of supporting data

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

None

Funding

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Authors' contributions

Author contributions Dr Barnabo Nampoukime performed the conception and design of the paper, the patient data acquisition and analysis, and the draft of the article. Dr. Fortes Gomes, Sultani, NOUANI helped with patient data acquisition, and Dr. Pan, Dr. Wang, and Dr. Hu ,Dr Zha helped design the paper and the draft as well as the revision of the article. All authors read and approved the final manuscript.

Acknowledgments

We appreciate the surgeons and nurses from the Department of Cardiovascular Surgery for their advice and helpful information.

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Table 1:preoperative characteristics for 30 days hospital mortality

Variables	Survived	Death	P-value
n	382	90
Sex,male,mean±SD	287 (75.1)	73 (81.1)	0.288
Age,y,mean±SD	51.92 ±11.30	52.01 ±12.65	0.944
BMI	25.38 ±3.96	25.89 ±4.72	0.290
Ejection fraction,,mean±SD	57.97 ±6.72	56.92 ±7.83	0.198
Lactate dehydrogenase(135-214U/L),mean±SD	296.15 ±226.77	271.20 ±131.70	0.316
Creatinine(59-104umol/l),mean±SD	107.02 ±125.86	133.75 ±108.86	0.064
Cardiac troponin<34.2pg/ml,mean±SD	1635.11 ±7386.28	574.61 ±2215.64	0.179
Myoglobin(<154.9ng/ml),mean±SD	169.04 ±277.81	216.11 ±344.80	0.169
Creatinine kinase(<7.2ng/ml ),mean±SD	5.99 ±20.95	7.71 ±26.91	0.507
Smoker	94 (24.6)	24 (26.7)	0.787
Diabetes	37 (9.7)	6 (6.7)	0.489
Coronary Artery Disease	21 (5.5)	10 (11.1)	0.090
Hypertension	228 (59.7)	62 (68.9)	0.135
Pericardial effusion	107 (28.0)	30 (33.3)	0.383
History of cardiac surgery	28 (7.3)	8 (8.9)	0.779
Marfan Syndrome	5 (1.3)	4 (4.4)	0.126
Intubate before surgery	172 (45.0)	42 (46.7)	0.870
Cerebral malperfusion	18 (4.7)	5 (5.6)	0.950
Visceral malperfusion	47 (12.3)	11 (12.2)	1.000
Kidneys malperfusion	24 (6.3)	2 (2.2)	0.207
Limbs malperfusion	11 (2.9)	1 (1.1)	0.557
Cardiac malperfusion	34 (8.9)	13 (14.4)	0.166
Malperfusion in more than two organs	22 (5.8)	12 (13.3)	0.023

Data are presented as mean ±SD or as number (%)

Table 2: intraoperative characteristics for 30 days hospital mortality

Variables	Survived	Death	P-value
n	382	90
Surgery time(min)	535.62 ±122.42	573.01 ±129.72	0.010
Aorta cannulation	8 (2.1)	0 (0.0)	0.352
Femoral cannulation	47 (12.3)	14 (15.6)	0.514
Axillary cannulation	98 (25.7)	26 (28.9)	0.621
Axillary and femoral cannulation	138 (36.1)	31 (34.4)	0.859
Subclavian artery cannulation	26 (6.8)	5 (5.6)	0.846
Subclavian and femoral artery cannulation	42 (11.0)	12 (13.3)	0.658
CPB time (min),mean±SD	239.66± 113.87	264.83± 86.03	0.050
Aorta clamping time (min),mean±SD	123.29 ±46.44	132.51 ±36.00	0.079
Lowest temperature(C),mean±SD	26.34 ±2.42	26.18 ±2.36	0.565
HCA (min)	9.56 ±13.92	12.13 ±14.05	0.116

Data are presented as mean SD or as number (%), HCA hypothermic circulatory arrest, CPB cardiopulmonary bypass.

Table 3: postoperative risks factors for 30 days hospital mortality

Variables	Survived	Death	p
n	382	90
ECMO	1 (0.3)	6 (6.7)	<0.001
CRRT	31 (8.1)	14 (15.6)	0.050
CPR	0 (0.0)	9 (10.0)	<0.001
Tracheotomy	35 (9.2)	17 (18.9)	0.014
IABP	2 (0.5)	6 (6.7)	<0.001
ICU Stay(days)	11.24 ±10.39	16.34 ±17.31	<0.001
Time of extubation (days )	3.97 ±6.11	8.45 ±14.10	<0.001
Reexploration	21 (5.5)	8 (8.9)	0.336
Coma	19 (5.0)	7 (7.8)	0.428
Paralysis	9 (2.4)	8 (8.9)	0.007
Stroke	18 (4.7)	3 (3.3)	0.774
Lung infection	28 (7.3)	33 (36.7)	<0.001
GI bleeding	11 (2.9)	13 (14.4)	<0.001
TND	9 (2.4)	4 (4.4)	0.465
MODS	1 (0.3)	18 (20.0)	<0.001
Respiratory failure	1 (0.3)	20 (22.2)	<0.001
Cardiac failure	0 (0.0)	15 (16.7)	<0.001
Kidney failure	12 (3.1)	5 ( 5.6)	0.429

Data are presented as mean SD or as number (%), ECMO extracorporeal membrane oxygenation, CRRT continuous renal replacement therapy, ICU intensive care unit, IABP intra-aortic balloon pump, CPR cardiopulmonary resuscitation.TND transient Neurologic dysfunction

Table 4: multivariate analysis of risks factors for 30 days hospital mortality

Variables	Odds	CI	P-value
Surgery time	1.00	1.00-1.00	0.121
ECMO	2.86	0.05-213.00	0.640
Tracheotomy	1.31	0.39-4.33	0.658
IABP	4.59	0.31-70.31	0.267
ICU stay(days)	1.08	1.02-1.14	0.012
Time of extubation	1.00	0.96-1.05	0.863
Paralysis	3.07	0.49-15.85	0.200
Lung infection	15.35	5.49-45.26	<0.001
GI bleeding	3.61	0.80-15.36	0.088
MODS	159.19	17.54-5320.35	<0.001
Respiratory failure	229.91	34.55-5654.37	<0.001
Malperfusion in more than two organs	2.19	0.95-4.89	0.060

Data are presented as mean SD or as number (%), ECMO extracorporeal membrane oxygenation, CRRT continuous renal replacement therapy, ICU intensive care unit, IABP intra-aortic balloon pump, CPR cardiopulmonary resuscitation.

Table 5: GERAADA prediction score versus actual study group

Variables	GERAADA prediction mortality	Actual Mortality Study group	p-value	95%CI Lower Upper		AUC
AGE <50	17.94%（±1.93）	19.3%	0.642	0.4063	0.618	0.5121
AGE ≥50	18.07%（±2.04）	18.92%	0.7163	0.5761	0.7403	0.6582
Sex female	18.08%（±2.32）	15.17%	0.3973	0.5883	0.8297	0.709
Sex male	18.10%（±1.89）	20.3%	0.4955	0.6484	0.793	0.572
History of cardiac surgery	18.31%（±1.96）	22.22%	0.5816	0.3078	0.8172	0.5625
Resuscitation before surgery	18.08%（±2.09）	19.62%	0.1228	0.4823	0.4823	0.5815
Inotrope at referral	18.31%（±1.97）	15.27%	0.3161	0.5411	0.783	0.6621
Aortic regurgitation
AR I-II	17.96%（±1.83）	11.32%	0.1376	0.4927	0.4927	0.727
ARIII-IV	24.21%（±2.08）	18.02%	0.1656	0.5417	0.5417	0.6685
No regurgitation	18.03%（±2.00）	18.82%	0.7137	0.482	0.647	0.5645
Malperfusion
No malperfusion	18.01%（±2.03）	17.5%	0.8087	0.5323	0.6924	0.6124
Cerebral malperfusion	17.99%（±2.06）	23.5%	0.6092	0.3287	0.902	0.6154
Cardiac malperfusion	18.45%（±2.16）	24.4%	0.3607	0.3539	0.7798	0.5668
Visceral malperfusion	17.99%（±1.54）	16.21%	0.775	0.3693	0.9533	0.6613
Peripheral malperfusion	18.45%（±1.96）	0%	<0.00001	-	-	-
Other malperfusion	17.38%（±1.80）	35.71%	0.05708	0.3561	0.8217	0.5889
Hemiparesis	18.59%（±2.07）	0%	<0.00001	-	-	-
Extension of the tear
Aortic	18.12%（±2.09）	19.20%	0.76	0.4758	0.7436	0.6097
Supra aortic	18.00%（±2.09）	18.01%	0.9729	0.4952	0.6844	0.5898
Descending	17.96%（±1.75）	20.43%	0.4746	0.4647	0.728	0.5963
Entry of the tear
Aortic	18.07% （±2.12）	19.50%	0.6426	0.5297	0.7359	0.6328
Ascending	17.97%（±1.97）	20.9%	0.2793	0.4804	0.6692	0.5748
Descending	18.36%（±2.01）	19.4%	0.8911	0.2493	0.8707	0.56
Root	17.88%（±1.62）	7.14%	0.01095	0.7433	0.9832	0.8632

No competing interests reported.

Assessing GERAADA Score Mortality Predictions in Type A Aortic Dissection Patients

Status:

Version 1

Abstract

Figures

Introduction

Patients and methods

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Status:

Version 1