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

Abstract

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).

Keywords: ATAAD, acute type A aortic dissection; AUC, the area under the curve; DHCA, deep hypothermic circulatory arrest; SCI, systemic coagulation-inflammation index; SII, systemic immune-inflammation index; coagulation; inflammation; mortality; type A aortic dissection.

Graphical abstract

Figure 1

Patient Selection Flow Chart Patients were from 12 Chinese university cardiovascular centers: the First Affiliated Hospital of Nanjing Medical University, Nanjing; the First Affiliated Hospital of Guangzhou Medical University, Guangzhou; the First Affiliated Hospital of Shantou University Medical College, Shantou; Nanjing First Hospital, Nanjing Medical University, Nanjing; the Affiliated Hospital of Qingdao University, Qingdao; Xiamen Cardiovascular Hospital, Xiamen University, Xiamen; Teda International Cardiovascular Hospital, Chinese Academy of Medical Sciences, Tianjin; Shanghai East Hospital, Tongji University, Shanghai; Xiangya Hospital, Central South University, Changsha; Beijing Anzhen Hospital, Capital Medical University, Beijing; the First Affiliated Hospital of Bengbu Medical College, Bengbu; the First Affiliated Hospital of Guilin Medical College, Guilin. ICD 10 = International Classification of Diseases, 10th revision.

Figure 2

Functional Relationship Between SCI Index and the Risk of 90-Day Mortality (A) Crude model for SCI grouping. (B) Adjusted for demographics. (C) Adjusted for demographics and comorbidities. (D) Adjusted for demographics, comorbidities, and disease-specific conditions. (E) Adjusted for demographics, comorbidities, disease-specific conditions, and procedures. SCI = systemic coagulation-inflammation.

Figure 3

Kaplan-Meier Curves Overall and by Stratification of SCI Index (A) Kaplan-Meier survival plot of overall patients. (B) Kaplan-Meier survival plot by stratification of SCI index. Abbreviation as in Figure 2.

Figure 4

Comparative Performance of Hematologic Signatures (A) Receiver operating characteristic (ROC) curves of individual hematologic signatures. (B) ROC curves of collaborative hematologic signatures. AUC = area under the curve; CRP = C-reactive protein; NLR = neutrophil to lymphocyte ratio; PLR = platelet to lymphocyte ratio; SII = systemic immune-inflammation (index); other abbreviation as in Figure 2.

Figure 5

Establishment and Evaluation of Inflammation-Based Nomogram for 90-Day Mortality Prediction (A) Inflammation-based nomogram for 90-day mortality prediction. (B) ROC curves of base model vs inflammation-based nomogram. (C) Calibration plot of base model vs inflammation-based nomogram. (D) The time-dependent AUC of base model vs inflammation-based nomogram. (E) The decision curves of base model vs inflammation-based nomogram. Abbreviations as in Figures 2, 3, and 4.

Figure 6

Kaplan-Meier Survival Plot by DHCA Use Differences was observed in 90-day survival after surgery between patients with and without deep hypothermic circulatory arrest (DHCA).

Central Illustration

Clinical Markers Predictive for Mortality in Acute Type A Aortic Dissection Surgery We focused on routine preoperative baseline and clinical features to develop a risk score model for predicting 90-day mortality in Chinese patients with acute type A aortic dissection who underwent surgical repair, composed of 1 novel derived hematologic marker (systemic coagulation-inflammation [SCI] index) and conventional model 4 conventional factors (age at surgery, serum creatinine, DeBakey class, and location of intimal entry tear). Our results suggest that this inflammation-based model is useful for early prediction of operative mortality risk in that patient population. SCI index was calculated as peripheral platelet count × fibrinogen/white blood cell count on admission.