Evidence map›Paper›PMID 36185465›Full record

ArticleMayo Clinic proceedings. Innovations, quality & outcomes2022

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.

Hong Liu, Si-Chong Qian, Ying-Yuan Zhang, Ying Wu, Liang Hong, Ji-Nong Yang, Ji-Sheng Zhong, Yu-Qi Wang, Dong Kai Wu, Guo-Liang Fan and 6 more

Erratum issued Registry-linked trialAbstract read
In one paragraph

Article in Mayo Clinic proceedings. Innovations, quality & outcomes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT04918108 (Inflammatory Response and Anti-inflammatory Action for Aortopathy & Arteriopathy), which is not on this map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04918108 completednot on this map

Inflammatory Response and Anti-inflammatory Action for Aortopathy & Arteriopathy (5A-Plan): A Multicenter Cohort Study

TypeobservationalSponsorNanjing Medical UniversityRan2021 to 2021Enrolled2,000ConditionsAortic DissectionArmsinflammatory response
3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

  • Erratum issued
    2024
5 · Who and what money

Authors and funding

16 authors.

Hong LiuDepartment of Cardiovascular Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Si-Chong QianDepartment of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Ying-Yuan ZhangDepartment of Cardiovascular Surgery, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China.
Ying WuDepartment of Laboratory, the First Affiliated Hospital of Shantou University Medical College, Shantou, People's Republic of China.
Liang HongDepartment of Cardiovascular Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, People's Republic of China.
Ji-Nong YangDepartment of Cardiovascular Surgery, the Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China.
Ji-Sheng ZhongDepartment of Cardiovascular Surgery, Xiamen Cardiovascular Hospital, Xiamen University, Xiamen, People's Republic of China.
Yu-Qi WangDepartment of Cardiovascular Surgery, Teda International Cardiovascular Hospital, Chinese Academy of Medical Sciences, Tianjin, People's Republic of China.
Dong Kai WuDepartment of Cardiovascular Surgery, Xiangya Hospital, Central South University, Changsha, People's Republic of China.
Guo-Liang FanDepartment of Cardiovascular Surgery, Shanghai East Hospital, Tongji University, Shanghai, People's Republic of China.
Jun-Quan ChenDepartment of Cardiovascular Surgery, Tianjin Chest Hospital, Tianjin Medical University, Tianjin, People's Republic of China.
Sheng-Qiang ZhangDepartment of Cardiovascular Surgery, the First Affiliated Hospital of Bengbu Medical College, Bengbu, People's Republic of China.
Xing-Xing PengDepartment of Cardiovascular Surgery, the First Affiliated Hospital of Guilin Medical University, Guilin, People's Republic of China.
Yong-Feng ShaoDepartment of Cardiovascular Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Hai-Yang LiDepartment of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Hong-Jia ZhangDepartment of Cardiovascular Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

5A, Additive Anti-inflammatory Action for Aortopathy & ArteriopathyATAAD, acute type A aortic dissectionAUC, area under the receiver operating characteristics curveAVR, aortic valve regurgitationCT, computed tomographyGERAADA, German Registry for Acute Type A Aortic DissectionICU, intensive care unitKNN, K-nearest neighborLASSO, least absolute shrinkage and selection operatorNB, naïve BayesRF, random forestSTI, systemic thrombo-inflammatorySVM, support vector machineWBC, white blood cell

Identifiers

PMID36185465
PMCPMC9519496

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.