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Prediction Model For Postoperative Severe Acute Lung Injury In Patients Undergoing Acute Type A Aortic Dissection Surgery
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  • Qiuji Wang,
  • Weiqi Feng,
  • Juntao Kuang,
  • Jinlin Wu,
  • JUE YANG,
  • Chenxi Li,
  • Ruixin Fan
Qiuji Wang
Guangdong Cardiovascular Institute

Corresponding Author:956239560@qq.com

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Weiqi Feng
Guangdong Cardiovascular Institute
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Juntao Kuang
Guangzhou First People's Hospital
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Jinlin Wu
Guangdong Cardiovascular Institute
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JUE YANG
Guangdong Cardiovascular Institute
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Chenxi Li
Guangdong Cardiovascular Institute
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Ruixin Fan
Guangdong Cardiovascular Institute
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Abstract

Objective: This study aimed to establish a risk assessment model to predict postoperative severe acute lung injury (ALI) risk in patients with acute type A aortic dissection (ATAAD). Methods: Consecutive patients with ATAAD admitted to our hospital were included in this retrospective assessment and placed in the postoperative severe ALI and non-severe ALI groups based on the presence or absence of ALI within 72 h postoperatively (oxygen index (OI) ≤100 mmHg). Patients were then randomly divided into training and validation groups in a ratio of 8:2. Logistic regression analyses were used to statistically assess data and establish the prediction model. The prediction model’s effectiveness was evaluated via tenfold cross-validation of the validation group to facilitate construction of a nomogram. Results: After screening, 479 patients were included in the study: 132 (27.5%) in the postoperative severe ALI group and 347 (72.5%) in the postoperative non-severe ALI group. Based on logistics regression analyses, the following variables were included in the model: coronary heart disease (CHD), cardiopulmonary bypass (CPB) ≥257.5 min, left atrium (LA) diameter ≥35.5 mm, hemoglobin ≤139.5 g/L, preCPB OI ≤100 mmHg, intensive care unit (ICU) OI ≤100 mmHg, left ventricular posterior wall thickness (LVPWT) ≥10.5 mm, and neutrophilic granulocyte percentage (NEUT) ≥0.824. The area under the receiver operating characteristic (ROC) curve of the modeling group was 0.805, and differences between observed and predicted values were not deemed statistically significant via the Hosmer–Lemeshow test (χ2=6.037, df=8, P=0.643). For the validation group, the area under the ROC curve was 0.778, and observed and predicted value differences were insignificant when assessed using the Hosmer–Lemeshow test (χ 2=3.3782, df=7; P=0.848). The average tenfold cross-validation score was 0.756. Conclusions: This study established a prediction model and developed a nomogram to determine the risk of postoperative severe ALI after ATAAD. Variables used in the model were easy to obtain clinically and the effectiveness of the model was good.
18 Jan 2022Submitted to Journal of Cardiac Surgery
19 Jan 2022Submission Checks Completed
19 Jan 2022Assigned to Editor
19 Jan 2022Reviewer(s) Assigned
09 Feb 2022Review(s) Completed, Editorial Evaluation Pending
10 Feb 2022Editorial Decision: Revise Major
24 Feb 20221st Revision Received
24 Feb 2022Submission Checks Completed
24 Feb 2022Assigned to Editor
24 Feb 2022Reviewer(s) Assigned
24 Feb 2022Review(s) Completed, Editorial Evaluation Pending
25 Feb 2022Editorial Decision: Accept
Jun 2022Published in Journal of Cardiac Surgery volume 37 issue 6 on pages 1602-1610. 10.1111/jocs.16447