Laboratory signatures differentiate the tolerance to hypothermic circulatory arrest in acute type A aortic dissection surgery

Hong Liu, Si-Chong Qian, Lu Han, Zhi-Qiang Dong, Yong-Feng Shao, Hai-Yang Li, Wei Zhang, Hong-Jia Zhang, Hong Liu, Si-Chong Qian, Lu Han, Zhi-Qiang Dong, Yong-Feng Shao, Hai-Yang Li, Wei Zhang, Hong-Jia Zhang

Abstract

Objectives: Our goal was to investigate whether laboratory signatures on admission could be used to identify risk stratification and different tolerance to hypothermic circulatory arrest in acute type A aortic dissection surgery.

Methods: Patients from 10 Chinese hospitals participating in the Additive Anti-inflammatory Action for Aortopathy & Arteriopathy (5A) study were randomly divided into derivation and validation cohorts at a ratio of 7:3 to develop and validate a simple risk score model using preoperative variables associated with in-hospital mortality using multivariable logistic regression. The performance of the model was assessed using the area under the receiver operating characteristic curve. Subgroup analyses were performed to investigate whether the laboratory signature-based risk stratification could differentiate the tolerance to hypothermic circulatory arrest.

Results: There were 1443 patients and 954 patients in the derivation and validation cohorts, respectively. Multivariable analysis showed the associations of older age, larger body mass index, lower platelet-neutrophile ratio, higher lymphocyte-monocyte ratio, higher D-dimer, lower fibrinogen and lower estimated glomerular filtration rate with in-hospital death, incorporated to develop a simple risk model (5A laboratory risk score), with an area under the receiver operating characteristic of 0.736 (95% confidence interval 0.700-0.771) and 0.715 (95% CI 0.681-0.750) in the derivation and validation cohorts, respectively. Patients at low risk were more tolerant to hypothermic circulatory arrest than those at middle to high risk in terms of in-hospital mortality [odds ratio 1.814 (0.222-14.846); odds ratio 1.824 (1.137-2.926) (P = 0.996)].

Conclusions: The 5A laboratory-based risk score model reflecting inflammatory, immune, coagulation and metabolic pathways provided adequate discrimination performances in in-hospital mortality prediction, which contributed to differentiating the tolerance to hypothermic circulatory arrest in acute type A aortic dissection surgery.Clinical Trials. gov number NCT04918108.

Keywords: Aortic dissection; Circulatory arrest; Hypothermia; Mortality; Risk model.

© The Author(s) 2022. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery.

Figures

Figure 1:
Figure 1:
Restricted cubic splines of in-hospital deaths by selected variables. (A–G) Univariable analysis splines of in-hospital mortality by age, body mass index, platelet-neutrophil ratio, eGFR, D-dimer, fibrinogen and lymphocyte–monocyte ratio. eGFR: estimated glomerular filtration rate.
Figure 2:
Figure 2:
Adjusted odds ratios of in-hospital deaths by selected variables. eGFR: estimated glomerular filtration rate.
Figure 3:
Figure 3:
5A laboratory-based risk score and in-hospital mortality in derivation cohort. (A) Functional relationship between risk score and in-hospital mortality. (B) Association between risk classifications and in-hospital mortality. OR: odds ratio; CI: confidence interval.
Figure 4:
Figure 4:
Prediction performances of 5A laboratory-based risk score in the derivation and validation cohorts. (A, B) ROC curve in the derivation and validation cohort. (C, D) Calibration curve of this risk model in the derivation and validation cohort. (E, F) Decision curve analysis of this risk model in the derivation and validation cohort. ROC: receiver operating characteristic curve; AUC: the area under the receiver operating characteristic curve; CI: confidence interval.
Figure 5:
Figure 5:
Prediction performances of currently existing models in the total cohort. (A, B) ROC curve of IRAD and GERAADA risk score. (C, D) Calibration curve of IRAD and GERAADA risk score. (E, F) Decision curve analysis of IRAD and GERAADA risk score. AUC: area under the receiver operating characteristic curve; CI: confidence interval; GERAAD: German Registry for Acute Aortic Dissection Type A; IRAD: International Registry of Acute Aortic Dissection; ROC: receiver operating characteristic curve.
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/9645440/bin/ivac267f6.jpg

References

    1. Bossone E, Eagle KA.. Epidemiology and management of aortic disease: aortic aneurysms and acute aortic syndromes. Nat Rev Cardiol 2021;18:331–48.
    1. Wang A, Montgomery D, Brinster DR, Gilon D, Upchurch GR Jr, Gleason TG. et al. Predicting In-Hospital Survival in Acute Type A Aortic Dissection Medically Treated. J Am Coll Cardiol 2020;75:1360–1.
    1. Evangelista A, Isselbacher EM, Bossone E, Gleason TG, Eusanio MD, Sechtem U, IRAD Investigators et al.Insights From the International Registry of Acute Aortic Dissection: a 20-Year Experience of Collaborative Clinical Research. Circulation 2018;137:1846–60.
    1. Narayan P, Rogers CA, Benedetto U, Caputo M, Angelini GD, Bryan AJ.. Malperfusion rather than merely timing of operative repair determines early and late outcome in type A aortic dissection. J Thorac Cardiovasc Surg 2017;154:81–6.
    1. Mehta RH, Suzuki T, Hagan PG, Bossone E, Gilon D, Llovet A, International Registry of Acute Aortic Dissection (IRAD) Investigators et al Predicting death in patients with acute type A aortic dissection. Circulation 2002;105:200–6.
    1. Benedetto U, Dimagli A, Kaura A, Sinha S, Mariscalco G, Krasopoulos G. et al. Determinants of outcomes following surgery for type A acute aortic dissection: the UK National Adult Cardiac Surgical Audit. Eur Heart J 2021;43:44–52.
    1. Erbel R, Aboyans V, Boileau C, Bossone E, Bartolomeo RD, Eggebrecht H. et al. 2014 ESC Guidelines on the diagnosis and treatment of aortic diseases: document covering acute and chronic aortic diseases of the thoracic and abdominal aorta of the adult. The Task Force for the Diagnosis and Treatment of Aortic Diseases of the European Society of Cardiology (ESC. Eur Heart J 2014;35:2873–926. [Database]).
    1. Zeng T, Shi L, Ji Q, Shi Y, Huang Y, Liu Y. et al. Cytokines in aortic dissection. Clin Chim Acta 2018;486:177–82.
    1. Ghoreishi M, Wise ES, Croal-Abrahams L, Tran D, Pasrija C, Drucker CB. et al. A Novel Risk Score Predicts Operative Mortality After Acute Type A Aortic Dissection Repair. Ann Thorac Surg 2018;106:1759–66.
    1. Zhang Y, Chen T, Chen Q, Min H, Nan J, Guo Z.. Development and evaluation of an early death risk prediction model after acute type A aortic dissection. Ann Transl Med 2021;9:1442.
    1. Guo T, Fang Z, Yang G, Zhou Y, Ding N, Peng W. et al. Machine Learning Models for Predicting In-Hospital Mortality in Acute Aortic Dissection Patients. Front Cardiovasc Med 2021;8:727773.
    1. Rios F, Perez D, Soca G, Robaina R, Dayan V.. Predictive Factors of Mortality in Acute Aortic Dissection and Validity of the EuroSCORE Algorithm in a Small-Sized Cardiac Surgery Institution. Braz J Cardiovasc Surg 2020;35:878–83.
    1. Wang S, Wang D, Huang X, Wang H, Le S, Zhang J. et al. Risk factors and in-hospital mortality of postoperative hyperlactatemia in patients after acute type A aortic dissection surgery. BMC Cardiovasc Disord 2021;21:431.
    1. Kuang J, Yang J, Wang Q, Yu C, Li Y, Fan R.. A preoperative mortality risk assessment model for Stanford type A acute aortic dissection. BMC Cardiovasc Disord 2020;20:508.
    1. Rampoldi V, Trimarchi S, Eagle KA, Nienaber CA, Oh JK, Bossone E, International Registry of Acute Aortic Dissection (IRAD) Investigators et al Simple risk models to predict surgical mortality in acute type A aortic dissection: the International Registry of Acute Aortic Dissection score. Ann Thorac Surg 2007;83:55–61.
    1. Czerny M, Siepe M, Beyersdorf F, Feisst M, Gabel M, Pilz M. et al. Prediction of mortality rate in acute type A dissection: the German Registry for Acute Type A Aortic Dissection score. Eur J Cardiothorac Surg 2020;58:700–6.
    1. Morello F, Cavalot G, Giachino F, Tizzani M, Nazerian P, Carbone F. et al. White blood cell and platelet count as adjuncts to standard clinical evaluation for risk assessment in patients at low probability of acute aortic syndrome. Eur Heart J Acute Cardiovasc Care 2017;6:389–95.
    1. Wang Y, Qiao T, Zhou J.. The short-term prognostic value of serum platelet to hemoglobin in patients with type A acute aortic dissection. Perfusion 2022;37:95–9.
    1. Mousavizadeh M, Daliri M, Aljadayel HA, Mohammed I, Rezaei Y, Bashir M. et al. Hypothermic circulatory arrest time affects neurological outcomes of frozen elephant trunk for acute type A aortic dissection: a systematic review and meta-analysis. J Card Surg 2021;36:3337–51.
    1. Schechter MA, Shah AA, Englum BR, Williams JB, Ganapathi AM, Davies JD. et al. Prolonged postoperative respiratory support after proximal thoracic aortic surgery: is deep hypothermic circulatory arrest a risk factor? J Crit Care 2016;31:125–9.
    1. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) et al.A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–12.
    1. Overman DM, Jacobs JP, Prager RL, Wright CD, Clarke DR, Pasquali SK et al Report from the Society of Thoracic Surgeons National Database Workforce: clarifying the definition of operative mortality. World J Pediatr Congenit Heart Surg 2013;4:10–2.
    1. Collins GS, Reitsma JB, Altman DG, Moons KG.. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. Bmj 2015;350:g7594.
    1. Durrleman S, Simon R.. Flexible regression models with cubic splines. Stat Med 1989;8:551–61.
    1. Hosmer DW, Hosmer T, Le Cessie S, Lemeshow S.. A comparison of goodness-of-fit tests for the logistic regression model. Statist Med 1997;16:965–80.
    1. Wu YC, Lee WC.. Alternative performance measures for prediction models. PLoS One 2014;9:e91249.
    1. Alba AC, Agoritsas T, Walsh M, Hanna S, Iorio A, Devereaux PJ. et al. Discrimination and calibration of clinical prediction models: users’ guides to the medical literature. Jama 2017;318:1377–84.
    1. Vickers AJ, Elkin EB.. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 2006;26:565–74.
    1. DeLong ER, DeLong DM, Clarke-Pearson DL.. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837–45.
    1. Yang G, Zhou Y, He H, Pan X, Li X, Chai X.. A nomogram for predicting in-hospital mortality in acute type A aortic dissection patients. J Thorac Dis 2020;12:264–75.
    1. Nežić DG, Živković IS, Miličić MD, Milačić PA, Košević DN, Boričić MI et al On-line risk prediction models for acute type A aortic dissection surgery: validation of the German Registry of Acute Aortic Dissection Type A score and the European System for Cardiac Operative Risk Evaluation II. Eur J Cardiothorac Surg 2022;61:1068–75.
    1. Liu H, Qian S, Zhang Y, Wu Y, Hong L, Yang J. et al. 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. Mayo Clin Proc Innov Qual Outcomes 2022;6:497–510.
    1. Arima D, Suematsu Y, Kurahashi K, Nishi S, Yoshimoto A.. Use of coagulation-fibrinolysis markers for prognostication of Stanford type A acute aortic dissection. JRSM Cardiovasc Dis 2021;10:20480040211047122.
    1. Zindovic I, Sjögren J, Bjursten H, Ingemansson R, Ingimarsson J, Larsson M. et al. The Coagulopathy of Acute Type A Aortic Dissection: a Prospective, Observational Study. J Cardiothorac Vasc Anesth 2019;33:2746–54.
    1. Mitsuoka M, Inoue N, Mori S, Matsumoto T, Meguro T.. Renal dysfunction on admission as a predictor for in-hospital mortality of patients with Stanford type B acute aortic dissection. Ann Vasc Dis 2013;6:624–30.
    1. Zhou T, Li J, Sun Y, Gu J, Zhu K, Wang Y. et al. Surgical and early outcomes for Type A aortic dissection with preoperative renal dysfunction stratified by estimated glomerular filtration rate. Eur J Cardiothorac Surg 2018;54:940–5.
    1. Heuts S, Adriaans BP, Kawczynski MJ, Daemen JHT, Natour E, Lorusso R. et al. Editor's Choice - Extending Aortic Replacement Beyond the Proximal Arch in Acute Type A Aortic Dissection: a Meta-Analysis of Short Term Outcomes and Long Term Actuarial Survival. Eur J Vasc Endovasc Surg 2022;63:674–87.
    1. Fang Z, Wang G, Liu Q, Zhou H, Zhou S, Lei G. et al. Moderate and deep hypothermic circulatory arrest has a comparable effect on acute kidney injury after total arch replacement with frozen elephant trunk procedure in type A aortic dissection. Interact CardioVasc Thorac Surg 2019;29:130–6.
    1. Chang Q, Tian C, Wei Y, Qian X, Sun X, Yu C.. Hybrid total arch repair without deep hypothermic circulatory arrest for acute type A aortic dissection (R1). J Thorac Cardiovasc Surg 2013;146:1393–8.

Source: PubMed

스폰서 및 공동 작업자

건강 상태

약물 개입

3
구독하다