Key result
An 8-variable model predicts severe postoperative ALI after acute type A aortic dissection with ~0.78 AUC.
Why the study?
The study aimed to establish a risk assessment model to predict postoperative severe acute lung injury risk in patients with acute type A aortic dissection.
Observational (n=479)
No
Effect estimate: AUC 0.778
A novel nomogram incorporating clinical and procedural variables can effectively predict the risk of severe acute lung injury after surgery for acute type A aortic dissection.
May aid perioperative risk stratification after acute type A aortic dissection repair; leaves open prospective validation before clinical adoption.
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.
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Wang et al. (2022) conducted an observational in Acute type A aortic dissection (ATAAD) (n=479). Clinical and perioperative risk factors vs. Absence of risk factors was evaluated on Postoperative severe acute lung injury (ALI) within 72 h postoperatively (AUC 0.778). A multivariable prediction model incorporating 8 clinical and perioperative variables effectively predicted postoperative severe acute lung injury after acute type A aortic dissection (validation AUC 0.778).
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