Development and validation of a risk prediction model for postoperative pneumonia in adult patients undergoing Stanford type A acute aortic dissection surgery: a case control study

Risk Factors and Early Outcomes for Gastrointestinal Complications in Patients Undergoing Open Surgery for Type A Aortic Dissection

BACKGROUND

Gastrointestinal complications need to be paid more attention, especially in critically ill patients. The purpose of this study was to identify the risk factors and short-term outcomes of gastrointestinal complications after open surgery for type A aortic dissection.

METHODS

A retrospective single-institutional study including patients who underwent open surgery for type A aortic dissection during 2012-2020 was conducted. Univariate analysis and logistic regression analysis were used to identify risk factors associated with gastrointestinal complications. The related clinical outcomes were compared between the patients with and without gastrointestinal complications.

RESULTS

Among the 2746 patients, 150 developed gastrointestinal complications. The development of gastrointestinal complications contributed to the higher rate of mortality (P = .008), longer stay in the intensive care unit (P < .001), and longer hospital stay (P < .001). Logistic regression analysis showed that age (odds ratio [OR] 1.020; 95% confidence interval [CI] 1.005-1.057; P = .011), American Society of Anesthesiologists classification greater than grade III (OR 1.724; 95%CI 1.179-2.521, P = .005), pre-induction mean arterial pressure (OR 0.978; 95%CI 0.965-0.990, P = .001), aortic cross-clamp time (OR 1.012; 95%CI 1.005-1.019, P = .001), cardiopulmonary bypass time (OR 1.007; 95%CI 1.002-1.011, P = .002), and intraoperative transfusion of red blood cells (OR 1.214; 95%CI 1.122-1.314, P = .001) were independent risk factors for gastrointestinal complications.

CONCLUSIONS

The incidence of gastrointestinal complications after open surgery for type A aortic dissection was 5.5%, resulting in increased mortality and prolonged hospital stay. It is necessary to take suitable strategies to reduce the incidence of gastrointestinal complications.

Machine learning algorithms for prediction of ventilator associated pneumonia in traumatic brain injury patients from the MIMIC-III database

BACKGROUND

Ventilator associated pneumonia (VAP) is a common complication and associated with poor prognosis of traumatic brain injury (TBI) patients.

OBJECTIVES

This study was conducted to explore the predictive performance of different machine-learning algorithms for VAP in TBI patients.

METHODS

TBI patients receiving mechanical ventilation more than 48 hours from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for the study. The VAP was confirmed based on the ICD-9 code. Included patients were separated to the training cohort and the validation cohort with a ratio of 7:3. Predictive models based on different machine learning algorithms were developed using 5-fold cross validation in the training cohort and then verified in the validation cohort by evaluating the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy and F score.

RESULTS

786 TBI patients from the MIMIC-III were finally included with the VAP incidence of 44.0%. The random forest performed the best on predicting VAP in the training cohort with a AUC of 1.000. The XGBoost and AdaBoost were ranked the second and the third with a AUC of 0.915 and 0.789 in the training cohort. While the AdaBoost performed the best on predicting VAP in the validation cohort with a AUC of 0.706. The XGBoost and random forest were ranked the second and the third with the AUC of 0.685 and 0.683 in the validation cohort. Generally, the random forest and XGBoost were likely to be over-fitting while the AdaBoost was relatively stable in predicting the VAP.

CONCLUSIONS

The AdaBoost performed well and stably on predicting the VAP in TBI patients. Developing programs using AdaBoost in portable electronic devices may effectively assist physicians in assessing the risk of VAP in TBI.

Postoperative pulmonary complications in patients undergoing aortic surgery: A single-center retrospective study

Postoperative pulmonary complications (PPCs) are among the most common complications after cardiovascular surgery. This study aimed to explore the real incidence of and risk factors for PPC in patients with acute type A aortic dissection (ATAAD) who underwent total aortic arch replacement combined with the frozen elephant trunk (TAR + FET). In total, 305 ATAAD patients undergoing TAR + FET from January 2021 to August 2022 in a single-center were divided into PPCs or non-PPCs group. The incidence of PPCs was calculated, risk factors of PPCs were analyzed, and postoperative outcomes were compared between these 2 groups. The incidence of any PPC was 29.2%. And the incidence of respiratory infection, respiratory failure, pleural effusion, atelectasis, pneumothorax, acute respiratory distress syndrome, aspiration pneumonitis, pulmonary edema and bronchospasm was 23.0%, 12.5%, 10.5%, 1.0%, 0.7%, 1.0%, 0%, 0.7%, 0%, respectively. The logistic regression analysis revealed that the history of diabetes, history of renal dysfunction, preoperative SpO2 <90%, cardiopulmonary bypass duration, fresh frozen plasma volume and platelet concentrates volume were independent risk factors for PPCs. Among 2 groups, postoperative ventilation duration, postoperative length of stay in intensive care unit and hospital were (73.5 ± 79.0 vs 24.8 ± 35.2 hours; P < .001), (228.3 ± 151.2 vs 95.2 ± 72.0 hours; P < .001) and (17.9 ± 8.8 vs 11.5 ± 6.2 days; P < .001). There was no difference between 2 groups of in-hospital mortality rate. Additionally, other short-term outcomes were also significantly poorer in patients with PPCs. PPCs are common in ATAAD patients undergoing TAR + FET, and could be multifactorial. PPCs occurrence are associated with poor patient outcomes postoperatively and worth further investigation.

Influence and risk factors of postoperative infection after surgery for ischemic cardiomyopathy

Background

Studies on postoperative infection (POI) after surgery for ischemic cardiomyopathy are still lacking. This study aimed to investigate the risk factors of POI and its influence on clinical outcomes in patients undergoing ischemic cardiomyopathy surgery.

Methods

The Surgical Treatment for Ischemic Heart Failure (STICH) trial randomized patients with ischemic cardiomyopathy [coronary artery disease (CAD) with left ventricular ejection fraction ≤35%] to surgical and medical therapy. In this study, a post hoc analysis of the STICH trial was performed to assess the risk factors and clinical outcomes of POI in those undergoing coronary artery bypass graft (CABG). Patients were divided according to whether POI developed during hospitalization or within 30 days from operation.

Results

Of the 2,136 patients randomized, 1,460 patients undergoing CABG per-protocol was included, with a POI rate of 10.2% (149/1,460). By multivariable analysis, POI was significantly related to patients' age, body mass index, depression, chronic renal insufficiency, Duke CAD Index, and mitral valve procedure. Compared to patients without POI, patients with POI had significantly longer durations of intubation, CCU/ICU and hospital stay, and higher rates of re-operation, in-hospital death and failed discharge within 30 days postoperatively. In addition, these patients had significantly higher risks of all-cause death, cardiovascular death, heart failure death, and all-cause hospitalization during long-term follow-up. However, the influence of POI on all-cause death was mainly found during the first year after operation, and the influence was not significant for patients surviving for more than 1 year.

Conclusions

POI was prevalent after surgery for ischemic cardiomyopathy and was closely related to short-term and long-term clinical outcomes, and the effect of POI mainly occurred within the first postoperative year. This study first reported and clarified the relationship between POI and long-term prognosis and the predictors for POI after surgery for ischemic cardiomyopathy worldwide, which may have certain guiding significance for clinical practice.

Clinical Trial Registration

https://www.clinicaltrials.gov, identifier (NCT00023595).

Risk assessment and disease burden of extreme precipitation on hospitalizations for acute aortic dissection in a subtropical coastal Chinese city

Background

Extreme precipitation events are becoming more frequent due to climate change. The present study aimed to explore the impacts of extreme precipitation on hospitalizations for acute aortic dissection (AAD) and to identify susceptible populations and quantify the corresponding disease burden.

Methods

The present study used a distributed lag nonlinear model (DLNM) with a quasi-Poisson function to investigate the association between extreme precipitation (≥95th percentile) and the risk of hospitalizations for AAD from 2015 to 2020 in Shantou, Guangdong Province, China.

Results

The significant adverse effects of extreme precipitation (relative to no precipitation) on daily AAD hospitalizations lasted from lag 5 [relative risk (RR): 1.0318, 95% confidence interval (CI): 1.0067-1.0575] to lag 9 (RR: 1.0297, 95% CI: 1.0045-1.0555) and reached its maximum at lag 7 (RR: 1.0382, 95% CI: 1.0105-1.0665). Males and older adult individuals (≥60 years) were more susceptible to extreme precipitation. A total of 3.68% (118 cases) of AAD hospitalizations were due to extreme precipitation.

Conclusion

Extreme precipitation was significantly correlated with AAD hospitalizations. Government departments should actively implement extreme precipitation intervention measures to strengthen the protection of males and the older adult (≥60 years) and effectively reduce AAD hospitalizations.

Hotspots and development frontiers of postoperative complications of AD: Bibliometric analysis - a review

The research on the postoperative complications of aortic dissection (AD) has received great attention from scholars all over the world, and the number of research articles in this field has consistently increased year after year. However, no bibliometric reports have been published yet to analyze the scientific output and the current situation in this field. The Bibliometrix R-package, VOSviewer, and CiteSpace software were used to conduct a bibliometric analysis of the hotspots and development frontiers of AD. A total of 1242 articles were retrieved. The USA, China, and Japan had the highest number of publications. The five keywords with the highest frequency were "analysis," "incidence," "acute type," "graft," and "risk factor." The results also indicated that the research in related fields had shifted from surgical treatment and utilizing experience to the evidence-based exploration of risk factors and the construction of prediction models to help better manage postoperative complications of AD. This is the first bibliometric analysis of global publications on the postoperative complications of AD. The current research hotspots focus on three areas: common postoperative complications of AD, exploration of the related risk factors, and management of complications. Future research could focus on identifying risk factors through meta-analysis and using a multicenter database for AD as well as building relevant models to predict the development of complications to better facilitate the clinical management of AD patients.

Nomogram and Risk Calculator for Postoperative Tracheostomy after Heart Valve Surgery

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.

Prediction and prognosis of reintubation after surgery for Stanford type A aortic dissection

Background

Reintubation is a serious adverse respiratory event after Stanford type A aortic dissection surgery (AADS), however, published studies focused on reintubation after AADS are very limited worldwide. The objectives of the current study were to establish an early risk prediction model for reintubation after AADS and to clarify its relationship with short-term and long-term prognosis.

Methods

Patients undergoing AADS between 2016–2019 in a single institution were identified and divided into two groups based on whether reintubation was performed. Independent predictors were identified by univariable and multivariable analysis and a clinical prediction model was then established. Internal validation was performed using bootstrap method with 1,000 replications. The relationship between reintubation and clinical outcomes was determined by univariable and propensity score matching analysis.

Results

Reintubation were performed in 72 of the 492 included patients (14.6%). Three preoperative and one intraoperative predictors for reintubation were identified by multivariable analysis, including older age, smoking history, renal insufficiency and transfusion of intraoperative red blood cells. The model established using the above four predictors showed moderate discrimination (AUC = 0.753, 95% CI, [0.695–0.811]), good calibration (Hosmer-Lemeshow χ² value = 3.282, P = 0.915) and clinical utility. Risk stratification was performed and three risk intervals were identified. Reintubation was closely associated with poorer in-hospital outcomes, however, no statistically significant association between reintubation and long-term outcomes has been observed in patients who were discharged successfully after surgery.

Conclusions

The requirement of reintubation after AADS is prevalent, closely related to adverse in-hospital outcomes, but there is no statistically significant association between reintubation and long-term outcomes. Predictors were identified and a risk model predicting reintubation was established, which may have clinical utility in early individualized risk assessment and targeted intervention.

Nomogram and risk calculator for severe hypoxemia after heart valve surgery

Background

Hypoxemia is a very common issue in patients undergoing heart valve surgery (HVS), related to poor clinical outcomes. However, studies on severe hypoxemia (SH) after HVS have not been reported. The aims of this study were to identify predictors for SH in patients undergoing HVS and to develop and validate a risk prediction model.

Methods

Patients undergoing HVS between 2016 and 2019 in a cardiovascular center were enrolled and were assigned to training and validation sets by a 7:3 ratio. Based on whether patients developed SH, they were divided into two groups. By univariate and multivariate analysis, predictors for SH were identified. Based on the predictors and logistic rule, a nomogram and a risk calculator were generated. The model was evaluated using calibration, discrimination and clinical utility.

Results

The incidence rates of SH, moderate hypoxemia and mild hypoxemia were respectively 2.4, 23.9, and 58.2%. By multivariate analysis, seven independent risk factors for SH after HVS were identified, including body mass index, chronic obstructive pulmonary disease, renal insufficiency, white blood cell count, serum globulin, cardiopulmonary bypass time, and surgical types. The logistic model demonstrated satisfactory discrimination, calibration and clinical utility in both the training and validation sets. A nomogram and a risk calculator based on the logistic model were generated for easy application. Risk stratification was performed and three risk intervals were defined according to the nomogram and clinical practice. In addition, compared to patients without SH, patients with SH had significantly poorer clinical outcomes.

Conclusions

Postoperative hypoxemia was prevalent after HVS, related to poor clinical outcomes. A logistic model including seven independent predictors for SH after HVS were established and validated, which demonstrated satisfactory discrimination, calibration and clinical utility. The results of this study may provide help to individualized risk assessment, early prevention and perioperative management.

Pneumonia After Cardiovascular Surgery: Incidence, Risk Factors and Interventions

Postoperative pneumonia (POP) is prevalent in patients undergoing cardiovascular surgery, associated with poor clinical outcomes, prolonged hospital stay and increased medical costs. This article aims to clarify the incidence, risk factors, and interventions for POP after cardiovascular surgery. A comprehensive literature search was performed to identify previous reports involving POP after cardiovascular surgery. Current situation, predictors and preventive measures on the development of POP were collected and summarized. Many studies showed that POP was prevalent in various cardiovascular surgical types, and predictors varied in different studies, including advanced age, smoking, chronic lung disease, chronic kidney disease, cardiac surgery history, cardiac function, anemia, body mass index, diabetes mellitus, surgical types, cardiopulmonary bypass time, blood transfusion, duration of mechanical ventilation, repeated endotracheal intubation, and some other risk factors. At the same time, several targeted interventions have been widely reported to be effective to reduce the risk of POP and improve prognosis, including preoperative respiratory physiotherapy, oral care and subglottic secretion drainage. Through the review of the current status, risk factors and intervention measures, this article may play an important role in clinical prevention and treatment of POP after cardiovascular surgery.

Incidence, Risk Factors, and Outcomes of Severe Hypoxemia After Cardiac Surgery

Background

Hypoxemia is common in patients undergoing cardiac surgery, however, few studies about severe hypoxemia (SH) after cardiac surgery exist. The objectives of this study were to clarify the incidence, risk factors, and outcomes of SH after cardiac surgery.

Methods

Patients undergoing cardiac surgery from 2016 to 2019 in a single center were enrolled and were divided into two groups based on whether postoperative SH developed. Independent risk factors for SH were identified by univariate and multivariate analysis. Model selection statistics were applied to help determine the most parsimonious final model.

Results

Severe hypoxemia developed in 222 of the 5,323 included patients (4.2%), was associated with poorer clinical outcomes. Six independent risk factors for SH after cardiac surgery were identified by multivariate analysis, such as surgical types, white blood cell (WBC) count, body mass index (BMI), serum albumin, cardiopulmonary bypass (CPB) time, and intraoperative transfusion of red blood cells (RBCs). After comprehensively considering the discrimination, calibration, and simplicity, the most appropriate and parsimonious model was finally established using four predictors, such as WBC count, BMI, CPB time, and intraoperative transfusion of RBCs. A nomogram and a web-based risk calculator based on the final model were constructed to facilitate clinical practice. Patients were stratified into three risk groups based on the nomogram and clinical practice.

Conclusion

Severe hypoxemia was common after cardiac surgery and was associated with poorer clinical outcomes. A parsimonious final model with good discrimination, calibration, and clinical utility was constructed, which may be helpful for personalized risk assessment and targeted intervention.