Pneumonia After Cardiovascular Surgery: Incidence, Risk Factors and Interventions

Wang, Dashuai; Lu, Yang; Sun, Manda; Huang, Xintang; Du, Xiaona; Jiao, Zhouyang; Sun, Fuqiang; Xie, Fei

doi:10.3389/fcvm.2022.911878

Cited by 17 publications

(17 citation statements)

References 113 publications

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“…Although RBC transfusions are routine in traditional cardiovascular surgery to deal with bleeding and improve tissue oxygen delivery, there is growing evidence that the restrictive RBC transfusion strategy is safe and effective, which has been recommended by practice guidelines [ 31 , 32 , 33 , 34 ]. In addition, previous studies have found that the risk factors identified in this study are related to the development of various postoperative respiratory complications, such as pneumonia to some extent, which may indirectly increase the risk of the need for POTs [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ].…”

Section: Discussionmentioning

confidence: 73%

Nomogram and Risk Calculator for Postoperative Tracheostomy after Heart Valve Surgery

Ding

Sun

Liu

et al. 2023

JCDD

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Postoperative tracheostomy (POT) is an important indicator of critical illness, associated with poorer prognoses and increased medical burdens. However, studies on POTs after heart valve surgery (HVS) have not been reported. The objectives of this study were first to identify the risk factors and develop a risk prediction model for POTs after HVS, and second to clarify the relationship between POTs and clinical outcomes. Consecutive adults undergoing HVS from January 2016 to December 2019 in a single cardiovascular center were enrolled, and a POT was performed in 1.8% of the included patients (68/3853). Compared to patients without POTs, the patients with POTs had higher rates of readmission to the ICU and in-hospital mortality, as well as longer ICU and hospital stays. Five factors were identified to be significantly associated with POTs after HVS by our multivariate analysis, including age, diabetes mellitus, pulmonary edema, intraoperative transfusion of red blood cells, and surgical types. A nomogram and a risk calculator were constructed based on the five factors, showing excellent discrimination, calibration, and clinical utility. Three risk intervals were defined as low-, medium-, and high-risk groups according to the nomogram and clinical practice. The findings of this study may be helpful for early risk assessment and perioperative management.

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Section: Discussionmentioning

confidence: 73%

Nomogram and Risk Calculator for Postoperative Tracheostomy after Heart Valve Surgery

Ding

Sun

Liu

et al. 2023

JCDD

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“…Similarly, pneumonia was considered the most common pulmonary complications after pediatric congenital heart surgery 18 , 34 . Compared with other pulmonary complications such as atelectasis, pleural effusion and pneumothorax, pneumonia has a higher rate, greater severity, and poor prognosis after surgery.…”

Section: Discussionmentioning

confidence: 99%

Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study

Tong,

Du,

Chen

et al. 2024

International Journal of Surgery

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Background: Major adverse postoperative outcomes (APOs) can greatly affect mortality, hospital stay, care management and planning, and quality of life. This study aimed to evaluate the performance of five machine learning (ML) algorithms for predicting four major APOs after pediatric congenital heart surgery and their clinically meaningful model interpretations. Methods: Between August 2014 and December 2021, 23,000 consecutive pediatric patients receiving congenital heart surgery were enrolled. Based on the split date of 1 January 2019, we selected 13,927 participants for the training cohort, and 9,073 participants for the testing cohort. Four predefined major APOs including low cardiac output syndrome (LCOS), pneumonia, renal failure, and deep venous thrombosis (DVT) were investigated. 39 clinical and laboratory features were inputted in five ML models: light gradient boosting machine (LightGBM), logistic regression (LR), support vector machine, random forest, and CatBoost. The performance and interpretations of ML models were evaluated using the area under the receiver operating characteristic curve (AUC) and Shapley Additive Explanations (SHAP). Results: In the training cohort, CatBoost algorithms outperformed others with the mean AUCs of 0.908 for LCOS and 0.957 for renal failure, while LightGBM and LR achieved the best mean AUCs of 0.886 for pneumonia and 0.942 for DVT, respectively. In the testing cohort, the best-performing ML model for each major APOs with the following mean AUCs: LCOS (LightGBM), 0.893 (95% confidence interval (CI), 0.884-0.895); pneumonia (LR), 0.929 (95% CI, 0.926-0.931); renal failure (LightGBM), 0.963 (95% CI, 0.947-0.979), and DVT (LightGBM), 0.970 (95% CI, 0.953-0.982). The performance of ML models using only clinical variables was slightly lower than those using combined data, with the mean AUCs of 0.873 for LCOS, 0.894 for pneumonia, 0.953 for renal failure, and 0.933 for DVT. The SHAP showed that mechanical ventilation time was the most important contributor of four major APOs. Conclusions: In pediatric congenital heart surgery, the established ML model can accurately predict the risk of four major APOs, providing reliable interpretations for high-risk contributor identification and informed clinical decisions making.

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“…The composite items were based on published cohorts evaluating postoperative complications. [16][17][18][19][20][21] The secondary end points comprise acute renal injury, stroke, pneumoniae, in-hospital death, ICU, and hospital LOS.…”

Section: End Pointsmentioning

confidence: 99%

Balanced Nonopioid General Anesthesia With Lidocaine Is Associated With Lower Postoperative Complications Compared With Balanced Opioid General Anesthesia With Sufentanil for Cardiac Surgery With Cardiopulmonary Bypass: A Propensity Matched Cohort Study

Guinot

Andrei

Durand

et al. 2023

Anesthesia &Amp; Analgesia

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BACKGROUND: There are no data on the effect of balanced nonopioid general anesthesia with lidocaine in cardiac surgery with cardiopulmonary bypass. The main study objective was to evaluate the association between nonopioid general balanced anesthesia and the postoperative complications in relation to opioid side effects. METHODS: Patients undergoing cardiac surgery with cardiopulmonary bypass between 2019 and 2021 were identified. After exclusion of patients for heart transplantation, left ventricular assistance device, and off-pump surgery, we classified patients according to an opioid general balanced anesthesia or a nonopioid balanced anesthesia with lidocaine. The primary outcome was a collapsed composite of postoperative complications that comprise respiratory failure and confusion, whereas secondary outcomes were acute renal injury, pneumoniae, death, intensive care unit (ICU), and hospital length of stay. RESULTS: We identified 859 patients exposed to opioid-balanced general anesthesia with lidocaine and 913 patients exposed to nonopioid-balanced general anesthesia. Propensity score matching yielded 772 individuals in each group with balanced baseline covariates. Two hundred thirty-six patients (30.5%) of the nonopioid-balanced general anesthesia versus 186 patients (24.1%) presented postoperative composite complications. The balanced lidocaine nonopioid general anesthesia group was associated with a lower proportion with the postoperative complication composite outcome OR, 0.72 (95% CI, 0.58–0.92; P = .027). The number of patients with acute renal injury, death, and hospital length of stay did not differ between the 2 groups. CONCLUSIONS: A balanced nonopioid general anesthesia protocol with lidocaine was associated with lower odds of postoperative complication composite outcome based on respiratory failure and confusion.

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Pneumonia After Cardiovascular Surgery: Incidence, Risk Factors and Interventions

Cited by 17 publications

References 113 publications

Nomogram and Risk Calculator for Postoperative Tracheostomy after Heart Valve Surgery

Nomogram and Risk Calculator for Postoperative Tracheostomy after Heart Valve Surgery

Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study

Balanced Nonopioid General Anesthesia With Lidocaine Is Associated With Lower Postoperative Complications Compared With Balanced Opioid General Anesthesia With Sufentanil for Cardiac Surgery With Cardiopulmonary Bypass: A Propensity Matched Cohort Study

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