Development and Validation of a Score to Identify Cardiac Surgery Patients at High Risk of Prolonged Mechanical Ventilation

Factors affecting the prolongation of mechanical ventilation in patients after cardiac surgery

BACKGROUND

This study aimed to investigate the major predictive factors associated with prolonged mechanical ventilation(PMV) following cardiac surgery.

METHODS

This retrospective, cross-sectional, descriptive-analytical study was conducted from September 2021 to March 2022, involving 244 patients who underwent cardiac surgery. PMV was defined as mechanical ventilation for more than 24 h. Potential risk factors before, during, and after surgery were examined and recorded. Logistic regression analysis was performed to assess the relationship between demographic, clinical variables, and prolonged mechanical ventilation. A significance level of 0.05 was used for data analysis.

RESULTS

The study population consisted of 68.4% male and 31.6% female patients, with 86.9% undergoing CABG surgery. PMV was observed in 13.1% of the patients. The findings revealed that the incidence of postoperative pneumonia increased the likelihood of PMV by more than 7 times [OR = 7.24, 95% CI=(5.12,8.14), P-value = 0.001]. Similarly, respiratory failure was associated with a 7.5-fold increase in the odds of PMV [OR = 7.56, 95% CI=(4.48,8.77), P-value = 0.042]. Drainage of one liter of blood on the first postoperative day increased the risk of PMV by 2.2 times [OR = 2.21, 95% CI=(1.98,2.46), P-value = 0.032], and the use of epinephrine was associated with a 2.73-fold increase in the odds [OR = 2.73, 95% CI=(2.24,3.11), P-value = 0.022]. Risk of PMV in the patients who had cardiac dysfunctin increased by more than 2 times.[OR = 2.58, 95%; CI = (1.33.2.87); P-value = 0.042]. In the patients need an Intra Aortic Balloon Pump(IABP) risk of PMV increased by more than 2 times. (OR = 2.74,95%,CI = 1.36,5.47: Pvalue = 0.03). The risk of PMV in the patients who had cerebrovascular accident(CVA) increased by more than three times [OR = 3.75, 95% CI = 1.26,4.84; P-value = 0.044]. For each unit increase in Euro Score 2 the chance of PMV increased by 1.38 TIMES. Furthermore ICU Mortality had a significant relationship with PMV.(Pvalue < 0.001).

CONCLUSION

The study identified postoperative complications, such as pneumonia, respiratory failure, high drainage, need to an IABP, higher EURO Score 2, Cardiac dysfunction, CVA and the use of epinephrine, as independent risk factors for PMV following cardiac surgery.

A novel nomogram for predicting prolonged mechanical ventilation after acute type A aortic dissection surgery: a retrospective study investigating the impact of ventilation duration on postoperative outcomes

OBJECTIVE

Acute type A aortic dissection (ATAAD) is a devastating cardiovascular disease with extraordinary morbidity and mortality. Prolonged mechanical ventilation (PMV) is a common complication following ATAAD surgery, leading to adverse outcomes. This study aimed to investigate the correlation between mechanical ventilation time (MVT) and prognosis and to devise a nomogram for predicting PMV after ATAAD surgery.

METHODS

This retrospective study enrolled 1049 ATAAD patients from 2011 to 2019. Subgroups were divided into < 12 h, 12 h to < 24 h, 24 h to < 48 h, 48 h to < 72 h, and ≥ 72 h according to MVT. Clinical characteristics and outcomes were compared among the groups. Using multivariable logistic regression analyses, we investigated the relationship between each stratification of MVT and mortality. A nomogram was constructed based on the refined multivariable logistic regression model for predicting PMV.

RESULTS

The total mortality was 11.8% (124/1049). The results showed that the groups with MVT 48 h to < 72 h and ≥ 72 h had significantly higher operative mortality compared to other MVT categories. Multivariate logistic regression analysis showed that MVT ≥72 h was significantly associated with higher short-term mortality. Thus, a nomogram was presented to elucidate the association between PMV (MVT ≥72 h) and risk factors including advanced age, preoperative cerebral ischemia, ascending aorta replacement, concomitant coronary artery bypass grafting (CABG), longer cardiopulmonary bypass (CPB), and large-volume intraoperative fresh frozen plasma (FFP) transfusion. The nomogram exhibited strong predictive performance upon validation.

CONCLUSIONS

Safely extubating patients within 72 h after ATAAD surgery is crucial for achieving favorable outcomes. The developed and validated nomogram provides a valuable tool for predicting PMV and optimizing postoperative care to improve patient prognosis. This novel nomogram has the potential to guide clinical decision-making and resource allocation in the management of ATAAD patients.

Study on the Predictive Value of a Pulmonary Edema Imaging Score for Delayed Extubation in Patients after Heart Valve Surgery on Cardiopulmonary Bypass

Background

Delayed extubation with mechanical ventilation after cardiac valve surgery is an important clinical challenge. Early extubation can improve the survival rate and prognosis of patients. The study aims to explore the predictive value of a chest X-ray pulmonary edema imaging score on the first day after surgery for delayed extubation in patients after cardiac valve surgery on cardiopulmonary bypass.

Method

Retrospective analysis of the clinical data of patients undergoing cardiac valve surgery under extracorporeal circulation admitted to the intensive care unit of Zhongshan Hospital Affiliated with Fudan University (Xiamen) from January 2020 to October 2023. The patients were divided into an early extubation group according to the postoperative mechanical ventilation time (time: <24 h) and a delayed extubation group (time: ≥24 h). The radiographic assessment of lung edema (RALE) score was performed on the chest X-ray of the patient on the first day after surgery to analyze the correlation between delayed extubation of mechanical ventilation and the chest radiograph RALE score on the first day after surgery and to verify its predictive performance.

Results

Significant differences in age, the incidence of hypertension, body mass index (BMI), left ventricular ejection fraction (LVEF), pump time, RALE score, ventilation time, oxygenation index, PaCO2, and brain natriuretic peptide (BNP) levels after the first 24 h were seen between patients who were extubated before and 24 h post operation (p = 0.013, 0.001, 0.034, <0.001, <0.001, <0.001, <0.001, <0.001, 0.014, and <0.001, respectively). No significant differences were observed in the proportion of males and the lactate level after the first 24 h between the two groups (p = 0.792 and 0.191, respectively). The time of mechanical ventilation was positively correlated with the RALE score in all patients, and the correlation coefficient was 0.419; the difference was statistically significant (p < 0.001). Multivariate binary logistic regression analysis with stepwise regression was performed on each research factor, and it was found that RALE score, pump time, oxygenation index, and postoperative BNP were independent risk factors for predicting delayed extubation in patients undergoing cardiac surgery on cardiopulmonary bypass. A 10-fold cross-validation revealed that the mean accuracy, sensitivity, specificity, and area under the curve (AUC) of the regression model were 0.737, 0.749, 0.741, and 0.825, respectively.

Conclusions

The RALE score on the chest radiograph on the first day after surgery is an independent risk factor for predicting delayed extubation in patients after cardiac valve surgery on cardiopulmonary bypass and has good predictive value.

Risk factors and clinical prediction models for prolonged mechanical ventilation after heart valve surgery

OBJECTIVES

Prolonged mechanical ventilation (PMV) is a common complication following cardiac surgery linked to unfavorable patient prognosis and increased mortality. This study aimed to search for the factors associated with the occurrence of PMV after valve surgery and to develop a risk prediction model.

METHODS

The patient cohort was divided into two groups based on the presence or absence of PMV post-surgery. Comprehensive preoperative and intraoperative clinical data were collected. Univariate and multivariate logistic regression analyses were employed to identify risk factors contributing to the incidence of PMV. Based on the logistic regression results, a clinical nomogram was developed.

RESULTS

The study included 550 patients who underwent valve surgery, among whom 62 (11.27%) developed PMV. Multivariate logistic regression analysis revealed that age (odds ratio [OR] = 1.082, 95% confidence interval [CI] = 1.042-1.125; P < 0.000), current smokers (OR = 1.953, 95% CI = 1.007-3.787; P = 0.047), left atrial internal diameter index (OR = 1.04, 95% CI = 1.002-1.081; P = 0.041), red blood cell count (OR = 0.49, 95% CI = 0.275-0.876; P = 0.016), and aortic clamping time (OR = 1.031, 95% CI = 1.005-1.057; P < 0.017) independently influenced the occurrence of PMV. A nomogram was constructed based on these factors. In addition, a receiver operating characteristic (ROC) curve was plotted, with an area under the curve (AUC) of 0.782 and an accuracy of 0.884.

CONCLUSION

Age, current smokers, left atrial diameter index, red blood cell count, and aortic clamping time are independent risk factors for PMV in patients undergoing valve surgery. Furthermore, the nomogram based on these factors demonstrates the potential for predicting the risk of PMV in patients following valve surgery.

A systematic review of cardiac surgery clinical prediction models that include intra-operative variables

BACKGROUND

Most cardiac surgery clinical prediction models (CPMs) are developed using pre-operative variables to predict post-operative outcomes. Some CPMs are developed with intra-operative variables, but none are widely used. The objective of this systematic review was to identify CPMs with intra-operative variables that predict short-term outcomes following adult cardiac surgery.

METHODS

Ovid MEDLINE and EMBASE databases were searched from inception to December 2022, for studies developing a CPM with at least one intra-operative variable. Data were extracted using a critical appraisal framework and bias assessment tool. Model performance was analysed using discrimination and calibration measures.

RESULTS

A total of 24 models were identified. Frequent predicted outcomes were acute kidney injury (9/24 studies) and peri-operative mortality (6/24 studies). Frequent pre-operative variables were age (18/24 studies) and creatinine/eGFR (18/24 studies). Common intra-operative variables were cardiopulmonary bypass time (16/24 studies) and transfusion (13/24 studies). Model discrimination was acceptable for all internally validated models (AUC 0.69-0.91). Calibration was poor (15/24 studies) or unreported (8/24 studies). Most CPMs were at a high or indeterminate risk of bias (23/24 models). The added value of intra-operative variables was assessed in six studies with statistically significantly improved discrimination demonstrated in two.

CONCLUSION

Weak reporting and methodological limitations may restrict wider applicability and adoption of existing CPMs that include intra-operative variables. There is some evidence that CPM discrimination is improved with the addition of intra-operative variables. Further work is required to understand the role of intra-operative CPMs in the management of cardiac surgery patients.

Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery

Background

Weaning patients from mechanical ventilation is a critical clinical challenge post cardiac surgery. The effective liberation of patients from the ventilator significantly improves their recovery and survival rates. This study aimed to develop and validate a clinical prediction model to evaluate the likelihood of successful extubation in post-cardiac surgery patients.

Method

A predictive nomogram was constructed for extubation success in individual patients, and receiver operating characteristic (ROC) and calibration curves were generated to assess its predictive capability. The superior performance of the model was confirmed using Delong's test in the ROC analysis. A decision curve analysis (DCA) was conducted to evaluate the clinical utility of the nomogram.

Results

Among 270 adults included in our study, 107 (28.84%) experienced delayed extubation. A predictive nomogram system was derived based on five identified risk factors, including the proportion of male patients, EuroSCORE II, operation time, pump time, bleeding during operation, and brain natriuretic peptide (BNP) level. Based on the predictive system, five independent predictors were used to construct a full nomogram. The area under the curve values of the nomogram were 0.880 and 0.753 for the training and validation cohorts, respectively. The DCA and clinical impact curves showed good clinical utility of this model.

Conclusion

Delayed extubation and weaning failure, common and potentially hazardous complications following cardiac surgery, vary in timing based on factors such as sex, EuroSCORE II, pump duration, bleeding, and postoperative BNP reduction. The nomogram developed and validated in this study can accurately predict when extubation should occur in these patients. This tool is vital for assessing risks on an individual basis and making well-informed clinical decisions.

The Effects of Different Doses of Sufentanil on Intraoperative Cardiovascular Response and Postoperative Recovery in Patients Undergoing Cardiac Surgery: A Retrospective Cohort Study

Objective

To investigate the correlation between the amount of sufentanil used during anesthesia and intraoperative hemodynamic fluctuation and postoperative recovery in patients undergoing cardiopulmonary bypass (CPB).

Materials and Methods

A retrospective analysis was performed on 454 patients undergoing elective heart surgery under CPB. Patients were divided into two groups according to the amount of sufentanil used during anesthesia: Group L (induced sufentanil 0.4-0.6 ug /kg, maintained sufentanil 0.01-0.02 ug/kg/min, n = 223) and Group H (induced sufentanil 4-6 ug/kg, maintained sufentanil 0.02-0.03 ug/kg/min, n = 231). Propensity score matching (PSM) was used at a 1:1 nearest-neighbor ratio to compare the two groups. Intraoperative use of vasoactive drugs, spontaneous heart rebound, secondary endotracheal intubation, postoperative mechanical ventilation time, the length of stay (LOS) in ICU, postoperative LOS in hospital, postoperative in-hospital mortality were analyzed.

Results

After matching, a total of 144 patients were included (72 patients in Group L, and 72 patients in Group H). Multivariate logistic regression analysis showed that the dosage of sufentanil during anesthesia was significantly correlated with the utilization rate of intraoperative vasoactive drugs (P < 0.001) and the success rate of spontaneous heart rebound (p = 0.001). The utilization rate of vasoactive drugs decreased significantly in Group H (OR, 0.062; 95% CI, 0.019-0.200) compared to that of Group L. The success rate of spontaneous heart rebound (OR, 0.187; 95% CI, 0.071-0.491) was higher in Group H. There were no differences on postoperative recovery outcomes between the two groups.

Conclusion

On the basis of our data, the use of high-dose sufentanil is beneficial to keep the cardiovascular response of patients in a stable state, but there is no significant effect on the quality of early postoperative recovery.

Development and Validation of Scores to Predict Prolonged Mechanical Ventilation after Cardiac Surgery

OBJECTIVES

To optimize the early prediction of prolonged postoperative mechanical ventilation after cardiac surgery (>24 hours postoperatively).

DESIGN

The authors performed a retrospective analysis.

SETTING

The Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) database was utilized.

PARTICIPANTS

All patients included in the ANZSCTS database between January 2015 and December 2018 were analyzed.

INTERVENTIONS

No interventions were performed in this observational study.

MEASUREMENTS AND MAIN RESULTS

A previously developed model was modified to allow retrospective risk calculation and model assessment (Modified Hessels score). The database was split into development and validation sets. A new risk model was developed using forward and backward stepwise elimination (ANZ-PreVent score). The authors assessed 48,382 patients, of whom 5004 (10.3%) were ventilated mechanically for >24 hours post-operatively. The Modified Hessels score demonstrated good performance in this database, with a c-index of 0.78 (95% CI 0.77-0.78) and a Brier score of 0.08. The newly developed ANZ-PreVent score demonstrated better performance (validation cohort, n = 12,229), with a c-index of 0.84 (95% CI 0.83-0.85) (p < 0.0001) and a Brier score of 0.07. Both scores performed better than the severity of illness scores commonly used to predict outcomes in intensive care.

CONCLUSIONS

The authors validated a modified version of an existing prediction score and developed the ANZ-PreVent score, with improved performance for identifying patients at risk of ventilation for >24 hours. The improved score can be used to identify high-risk patients for targeted interventions in future randomized controlled trials.

Establishment of a nomogram for predicting prolonged mechanical ventilation in cardiovascular surgery patients

AIMS

This study aimed to develop a nomogram model for predicting prolonged mechanical ventilation (PMV) in patients undergoing cardiovascular surgery.

METHODS AND RESULTS

In total, 693 patients undergoing cardiovascular surgery at an Affiliated Hospital of Nantong University between January 2018 and June 2020 were studied. Postoperative PMV was required in 147 patients (21.2%). Logistic regression analysis showed that delirium [odds ratio (OR), 3.063; 95% confidence interval (CI), 1.991-4.713; P < 0.001], intraoperative blood transfusion (OR, 2.489; 95% CI, 1.565-3.960; P < 0.001), obesity (OR, 2.789; 95% CI, 1.543-5.040; P = 0.001), postoperative serum creatinine level (mmol/L; OR, 1.012; 95% CI, 1.007-1.017; P < 0.001), postoperative serum albumin level (g/L; OR, 0.937; 95% CI, 0.902-0.973; P = 0.001), and postoperative total bilirubin level (μmol/L; OR, 1.020; 95% CI, 1.005-1.034; P = 0.008) were independent risk factors for PMV. The area under the receiver operating characteristic curve for our nomogram was found to be 0.770 (95% CI, 0.727-0.813). The goodness-of-fit test indicated that the model fitted the data well (χ2 = 12.480, P = 0.131). After the model was internally validated, the calibration plot demonstrated good performance of the nomogram, as supported by the Harrell concordance index of 0.760. Decision curve analysis demonstrated that the nomogram was clinically useful in identifying patients at risk for PMV.

CONCLUSION

We established a new nomogram model that may provide an individual prediction of PMV. This model may provide nurses, social workers, physicians, and administrators with an accurate and objective assessment tool to identify patients at high risk for PMV after cardiovascular surgery.

Factors associated with long-term mechanical ventilation in patients undergoing cardiovascular surgery

BACKGROUND

One of the main therapy for coronary artery disease is surgery. Prolonged mechanical ventilation in patients with cardiac surgery is associated with high mortality. This study aimed to determine the factors related to long-term mechanical ventilation (LTMV) in patients undergoing cardiovascular surgery.

METHODS

The present study was a descriptive-analytical study in which the records of 1361 patients who underwent cardiovascular surgery and were on a mechanical ventilator during 2019-2020 at the Imam Ali Heart Center in Kermanshah city were examined. The data collection tool was a three-part researcher-made questionnaire including demographic characteristics, health records, and clinical variables. Data analysis was done using descriptive and inferential statistical tests and SPSS Version 25 software.

RESULTS

In this study, of the 1361 patients, 953 (70%) were male. The results indicated that 78.6% of patients had short-term mechanical ventilation, and 21.4% had long-term mechanical ventilation. There was a statistically significant relationship between the history of smoking, drug use, and baking bread with the type of mechanical ventilation (P < 0.05). Also, based on the regression test, some parameters, such as the history of respiratory conditions, could predict the prolongation of mechanical ventilation. Creatinine levels before surgery, chest secretions after surgery, central venous pressure after surgery, and the status of cardiac enzymes before surgery also affect this issue.

CONCLUSION

This study investigated some factors related to prolonged mechanical ventilation in patients undergoing heart surgery. For optimizing the care and therapeutic measures, It is suggested, healthcare workers have a detailed assessment on patients with factors such as the history of baking bread, history of obstructive pulmonary disease, history of kidney disease, use of an intra-aortic pump, number of respirations and systolic blood pressure 24 h after surgery, creatinine level 24 h after surgery, chest secretions after surgery, and the amount of pre-operative ejection fraction and cardiac enzymes (CK-MB).

Developing an explainable machine learning model to predict the mechanical ventilation duration of patients with ARDS in intensive care units

BACKGROUND

Acute respiratory distress syndrome (ARDS) is common in intensive care units with high mortality rate and mechanical ventilation (MV) is the most important related treatment. Early prediction of MV duration has benefit for patients risk stratification and care strategies support.

OBJECTIVE

To develop an explainable model for predicting mechanical ventilation (MV) duration in patients with ARDS using the machine learning (ML) approach.

METHOD

The number of 1,148, 1,697, and 29 ARDS patients admitted to intensive care units (ICU) in the MIMIC-IV, eICU-CRD, and AmsterdamUMCdb databases were included in the study. Features at MV initiation from the MIMIC-IV dataset were used to train prediction models based on seven supervised machine learning algorithms. After 5-fold cross-validation for hyperparameters tuning, the hyperparameters- optimized model of different algorithms was tested by external datasets extracted from eICU-CRD and Amsterdamumcdb. Finally, three descriptive machine learning explanation methods were conducted for the model explanation.

RESULT

The XGBoosting model showed the most stable and accurate performance among two testing datasets (RMSE= 5.57 and 5.46 days in eICU-CRD and AmsterdamUMCdb) and was selected as the optimal model. The model explanation based on SHAP, LIME, and DALEX results showed a consistent result, vasopressor, PH, and SOFA score had the highest effect on MV duration prediction.

CONCLUSION

ML models with features at MV initiation can accurate predict MV duration in patients with ARDS in ICUs. Among seven algorithms, XGB models showed the best performance (RMSE= 5.57 and 5.46 in two external datasets). LIME, SHAP, and Breakdown methods showed good performance as AXI methods.

Early identification of delayed extubation following cardiac surgery: Development and validation of a risk prediction model

Background

Successful weaning and extubation after cardiac surgery is an important step of postoperative recovery. Delayed extubation is associated with poor prognosis and high mortality, thereby contributing to a substantial economic burden. The aim of this study was to develop and validate a prediction model estimate the risk of delayed extubation after cardiac surgery based on perioperative risk factors.

Methods

We performed a retrospective cohort study of adult patients undergoing cardiac surgery from 2014 to 2019. Eligible participants were randomly assigned into the development and validation cohorts, with a ratio of 7:3. Variables were selected using least absolute shrinkage and selection operator (LASSO) logistic regression model with 10-fold cross-validation. Multivariable logistic regression was applied to develop a predictive model by introducing the predictors selected from the LASSO regression. Receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis (DCA) and clinical impact curve were used to evaluate the performance of the predictive risk score model.

Results

Among the 3,919 adults included in our study, 533 patients (13.6%) experienced delayed extubation. The median ventilation time was 68 h in the group with delayed extubation and 21 h in the group without delayed extubation. A predictive scoring system was derived based on 10 identified risk factors based on 10 identified risk factors including age, BMI ≥ 28 kg/m², EF < 50%, history of cardiac surgery, type of operation, emergency surgery, CPB ≥ 120 min, duration of surgery, IABP and eGFR < 60 mL/min/1.73 m². According to the scoring system, the patients were classified into three risk intervals: low, medium and high risk. The model performed well in the validation set with AUC of 0.782 and a non-significant p-value of 0.901 in the Hosmer-Lemeshow test. The DCA curve and clinical impact curve showed a good clinical utility of this model.

Conclusions

We developed and validated a prediction score model to predict the risk of delayed extubation after cardiac surgery, which may help identify high-risk patients to target with potential preventive measures.

Vasoactive-inotropic score/inotropic score and short-term outcomes in pediatrics undergoing cardiac surgery: A retrospective analysis from single center

BACKGROUND AND AIM OF THE STUDY

This study aimed to investigate the association between vasoactive-inotropic score/inotropic score (VIS/IS) and short-term outcomes in pediatric patients after cardiac surgery at a tertiary care center in an unselected pediatric population in China.

METHODS

This study carried out retrospective observation of 401 patients between April and June 2021 at a tertiary care center. VIS and IS were assessed intraoperatively (VIS-op, IS-op) and 2 h (VIS2h, IS2h), 24 h (VIS24h, IS24h), and 48 h (VIS48h, IS48h) postoperatively. The primary outcome was prolonged mechanical ventilation (PMV). Secondary outcomes included poor prognosis and length of stay in the pediatric intensive care unit and hospital.

RESULTS

Mean age of the included pediatric patients was 26.5 months. Pediatric cardiac procedures were performed within an average operation duration of 167.6 ± 70.8 min. Overall, the PMV group (n = 93) experienced significantly longer ACC duration, cardiopulmonary bypass duration, operation duration, and a higher prevalence of fluid accumulation overload than the non-PMV group (n = 93). Multivariate logistic regression analysis revealed that longer operation duration (odds ratio [OR]: 1.015; 95% confidence interval [95% CI]: 1.003, 1.026; p = .012) and higher VIS48h (OR: 1.188; 95% CI: 1.077, 1.311; p = .001) were strongest predictors for PMV. VIS48h had better discrimination power for PMV than other time intervals, and the area under the curve was 0.780 (95% CI, 0.721, 0.839; p = .000).

CONCLUSIONS

VIS48h independently predicted short-term outcomes after cardiac surgery in an unselected pediatric population in China and showed better prediction accuracy and discrimination capability than other time intervals.

Blood Transfusion Predicts Prolonged Mechanical Ventilation in Acute Stanford Type A Aortic Dissection Undergoing Total Aortic Arch Replacement

Background

This research aimed to evaluate the impacts of transfusing packed red blood cells (pRBCs), fresh frozen plasma (FFP), or platelet concentrate (PC) on postoperative mechanical ventilation time (MVT) in patients with acute Stanford type A aortic dissection (ATAAD) undergoing after total arch replacement (TAR).

Methods

The clinical data of 384 patients with ATAAD after TAR were retrospectively collected from December 2015 to October 2017 to verify whether pRBCs, FFP, or PC transfusion volumes were associated with postoperative MVT. The logistic regression was used to assess whether blood products were risk factors for prolonged mechanical ventilation (PMV) in all three endpoints (PMV ≥24 h, ≥48 h, and ≥72 h).

Results

The mean age of 384 patients was 47.6 ± 10.689 years, and 301 (78.39%) patients were men. Median MVT was 29.5 (4–574) h (h), and 213 (55.47%), 136 (35.42%), and 96 (25.00%) patients had PMV ≥24 h, ≥48 h, and ≥72 h, respectively. A total of 36 (9.38%) patients did not have any blood product transfusion, the number of patients with transfusion of pRBCs, FFP, and PC were 334 (86.98%), 286 (74.48%), and 189 (49.22%), respectively. According to the multivariate logistic regression of three PMV time-endpoints, age was a risk factor [PMV ≥ 24 h odds ratio (ORPMV≥24) = 1.045, p = 0.005; ORPMV≥48 = 1.060, p = 0.002; ORPMV≥72 = 1.051, p = 0.011]. pRBC transfusion (ORPMV≥24 = 1.156, p = 0.001; ORPMV≥48 = 1.156, p &lt; 0.001; ORPMV≥72 = 1.135, p ≤ 0.001) and PC transfusion (ORPMV≥24 = 1.366, p = 0.029; ORPMV≥48 = 1.226, p = 0.030; ORPMV≥72 = 1.229, p = 0.011) were independent risk factors for PMV. FFP had no noticeable effect on PMV [ORPMV≥48 = 0.999, 95% confidence interval (CI) 0.998–1.000, p = 0.039; ORPMV≥72 = 0.999, 95% CI: 0.998–1.000, p = 0.025].

Conclusions

In patients with ATAAD after TAR, the incidence of PMV was very high. Blood products transfusion was closely related to postoperative mechanical ventilation time. pRBC and PC transfusions and age increased the incidence of PMV at all three endpoints.

Prolonged mechanical ventilation after cardiac surgery: substudy of the Transfusion Requirements in Cardiac Surgery III trial

PURPOSE

Prolonged mechanical ventilation (MV) is a major complication following cardiac surgery. We conducted a secondary analysis of the Transfusion Requirements in Cardiac Surgery (TRICTS) III trial to describe MV duration, identify factors associated with prolonged MV, and examine associations of prolonged MV with mortality and complications.

METHODS

Four thousand, eight hundred and nine participants undergoing cardiac surgery at 71 hospitals worldwide were included. Prolonged MV was defined based on the Society of Thoracic Surgeons definition as MV lasting 24 hr or longer. Adjusted associations of patient and surgical factors with prolonged MV were examined using multivariable logistic regression. Associations of prolonged MV with complications were assessed using odds ratios, and adjusted associations between prolonged MV and mortality were evaluated using multinomial regression. Associations of shorter durations of MV with survival and complications were explored.

RESULTS

Prolonged MV occurred in 15% (725/4,809) of participants. Prolonged MV was associated with surgical factors indicative of complexity, such as previous cardiac surgery, cardiopulmonary bypass duration, and separation attempts; and patient factors such as critical preoperative state, left ventricular impairment, renal failure, and pulmonary hypertension. Prolonged MV was associated with perioperative but not long-term complications. After risk adjustment, prolonged MV was associated with perioperative mortality; its association with long-term mortality among survivors was weaker. Shorter durations of MV were not associated with increased risk of mortality or complications.

CONCLUSION

In this substudy of the TRICS III trial, prolonged MV was common after cardiac surgery and was associated with patient and surgical risk factors. Although prolonged MV showed strong associations with perioperative complications and mortality, it was not associated with long-term complications and had weaker association with long-term mortality among survivors.

STUDY REGISTRATION

www.

CLINICALTRIALS

gov (NCT02042898); registered 23 January 2014. This is a substudy of the Transfusion Requirements in Cardiac Surgery (TRICS) III trial.

Development and Validation of a Predictive Score for Prolonged Mechanical Ventilation After Cardiac Surgery

OBJECTIVES

The authors aimed to identify risk factors associated with prolonged mechanical ventilation (PMV) after scheduled cardiac surgery under cardiopulmonary bypass (CPB).

DESIGN

A single-center, observational study.

SETTING

Tertiary hospital.

PARTICIPANTS

All adult patients who underwent scheduled cardiac surgery under cardiopulmonary bypass between January 2017 and December 2017.

INTERVENTIONS

None.

MEASUREMENT AND MAIN RESULTS

Among the 568 patients included, 68 (12.0%) presented a PMV. The median ventilation time was 5.7 hours in the group without PMV and 85.2 hours in the group with PMV. A logistic regression found five variables independently associated with the occurrence of PMV: (1) prior cardiac surgery, (2) preoperative congestive heart failure, (3) preoperative creatinine clearance <30 mL/min/1.73 m², (4) intraoperative implantation of extracorporeal membrane oxygenation, and (5) serum lactate >4 mmol/L on admission. A predictive score to allow the authors to anticipate PMV was developed from the regression coefficient of perioperative factors independently associated with PMV. With a threshold of 2/13, the score had a sensitivity of 80.9%, a specificity of 80.5%, a positive predictive value of 37.2%, and a negative predictive value of 96.7%. The score then was validated in a distinct cohort.

CONCLUSIONS

The study authors have developed a simple score to predict PMV in patients undergoing cardiac surgery with CPB. This score could allow clinicians to identify a high-risk population that might benefit from specific management upon arrival in the intensive care unit.

Linkage of Australian national registry data using a statistical linkage key

Background

Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581). Our aim was to investigate the ability to link data using SLK-581 between two national databases, and to compare this linkage to that achieved with direct identifiers or other non-identifying variables.

Methods

The Australian and New Zealand Society of Cardiothoracic Surgeons database (ANZSCTS-CSD) contains fully identified data. The Australian and New Zealand Intensive Care Society database (ANZICS-APD) contains non-identified data together with SLK-581. Identifying data is removed at participating hospitals prior to central collation and storage. We used the local hospital ANZICS-APD data at a large single tertiary centre prior to deidentification and linked this to ANZSCTS-CSD data. We compared linkage using SLK-581 to linkage using non-identifying variables (dates of admission and discharge, age and sex) and linkage using a complete set of unique identifiers. We compared the rate of match, rate of mismatch and clinical characteristics between unmatched patients using the different methods.

Results

There were 1283 patients eligible for matching in the ANZSCTS-CSD. 1242 were matched using unique identifiers. Using non-identifying variables 1151/1242 (92.6%) patients were matched. Using SLK-581, 1202/1242 (96.7%) patients were matched. The addition of non-identifying data to SLK-581 provided few additional patients (1211/1242, 97.5%). Patients who did not match were younger, had a higher mortality risk and more non-standard procedures vs matched patients. The differences between unmatched patients using different matching strategies were small.

Conclusion

All strategies provided an acceptable linkage. SLK-581 improved the linkage compared to non-identifying variables, but was not as successful as direct identifiers. SLK-581 may be used to improve linkage between national registries where identifying information is not available or cannot be released.

Adverse Outcomes Associated With Delaying or Withholding β-Blockers After Cardiac Surgery: A Retrospective Single-Center Cohort Study

BACKGROUND

Ideal timing of postoperative β-blockers is unclear. We hypothesized that patients who do not receive β-blockers immediately after cardiac surgery would have increased in-hospital mortality (primary outcome) and postoperative hemodynamic, pulmonary, neurologic, or respiratory complications (secondary outcomes).

METHODS

We performed a retrospective cohort study evaluating patients who underwent cardiac surgery at our institution from January 1, 2013 to September 30, 2017. We compared outcomes between patients who received β-blockers by postoperative day (POD) 5 with outcomes in patients who did not receive β-blockers at any time or received them after POD 5. Inverse probability of treatment weighting was used to minimize confounding. Univariate logistic regression analyses were performed on the weighted sets using absent or delayed β-blockers as the independent variable and each outcome as dependent variables in separate analyses. A secondary analysis was performed in patients prescribed preoperative β-blockers. E-values were calculated for significant outcomes.

RESULTS

All results were confounder adjusted. Among patients presenting for cardiac surgery, not receiving β-blockers by POD 5 or at any time was not associated with the primary outcome in-hospital mortality, estimated odds ratio (OR; 99.5% confidence interval [CI]) of 1.6 (0.49-5.1), P = .28. Not receiving β-blockers by POD 5 or at any time was associated with postoperative atrial fibrillation, estimated OR (99.5% CI) of 1.5 (1.1-2.1), P < .001, and pulmonary complications, estimated OR (99.5% CI) of 3.0 (1.8-5.2), P < .001. E-values were 2.4 for postoperative atrial fibrillation and 5.6 for pulmonary complications. Among patients presenting for cardiac surgery taking preoperative β-blockers, not receiving β-blockers by POD 5 or at any time was not associated with the primary outcome mortality, with estimated OR (99.5% CI) of 1.3 (0.43-4.1), P = .63. In this subset, not receiving β-blockers by POD 5 or at any time was associated with increased adjusted ORs of postoperative atrial fibrillation (OR = 1.6; 99.5% CI, 1.1-2.4; P < .001) and postoperative pulmonary complications (OR = 2.8; 99.5% CI, 1.6-5.2; P < .001). Here, e-values were 2.7 for postoperative atrial fibrillation and 5.1 for pulmonary complications. For the sensitivity analyses for secondary outcomes, exposure and outcome periods overlap. Outcomes may have occurred before or after postoperative β-blocker administration.

CONCLUSIONS

Among patients who undergo cardiac surgery, not receiving postoperative β-blockers within the first 5 days after cardiac surgery or at any time is not associated with in-hospital mortality and is associated with, but may not necessarily cause, postoperative atrial fibrillation and pulmonary complications.

Early respiratory outcomes following cardiac surgery in patients with COVID-19

BACKGROUND

Both coronavirus disease (COVID-19) and cardiac surgery have a negative impact on pulmonary function. This study aimed to determine the postoperative respiratory outcomes of patients with COVID-19 who underwent cardiac surgery.

METHODS

In this retrospective study, we reviewed and analyzed the patient characteristics and clinical data of 25 asymptomatic patients with COVID-19 who underwent urgent or emergency cardiac surgery at Tehran Heart Center Hospital, Iran, between 29 February and 10 April 2020.

RESULTS

The mean age, EuroSCORE, and body mass index were 57.3 ± 15.1 years, 6.65 ± 1.29, and 25.7 ± 3.7 kg/m² , respectively. Four patients underwent off-pump cardiac surgery and 21 underwent on-pump cardiac surgery with a median cardiopulmonary bypass time of 85 minutes (interquartile range (IQR, 50-147). The overall mortality rate and the length of stay in the intensive care unit (ICU) were higher compared to those of a propensity-matched group of patients who underwent cardiac surgery in the pre-COVID era. The median intubation time was 13 hours (IQR, 9.5-18), which was comparable to that of pre-COVID cardiac surgery patients. The readmission rate to the ICU was 16%. In this ICU readmitted group, the mean oxygen index, FiO₂ , and mortality rate were higher and the PaO₂ /FiO₂ ratio was lower than those of the nonreadmitted patients.

CONCLUSIONS

Although early respiratory outcomes of asymptomatic COVID-19 patients who underwent early cardiac surgery appeared to be satisfactory, compared to the propensity-scored matched non-COVID group, the postoperative outcomes were worse, especially in the ICU readmitted patients. We suggest postponing cardiac operations unless the patient requires emergency surgery.

Continuous Magnesium Infusion to Prevent Atrial Fibrillation After Cardiac Surgery: A Sequential Matched Case-Controlled Pilot Study

OBJECTIVE

The authors aimed to test whether a bolus of magnesium followed by continuous intravenous infusion might prevent the development of atrial fibrillation (AF) after cardiac surgery.

DESIGN

Sequential, matched, case-controlled pilot study.

SETTING

Tertiary university hospital.

PARTICIPANTS

Matched cohort of 99 patients before and intervention cohort of 99 consecutive patients after the introduction of a continuous magnesium infusion protocol.

INTERVENTIONS

The magnesium infusion protocol consisted of a 10 mmol loading dose of magnesium sulphate followed by a continuous infusion of 3 mmol/h over a maximum duration of 96 hours or until intensive care unit discharge.

MEASUREMENTS AND MAIN RESULTS

The study groups were balanced except for a lower cardiac index in the intervention cohort. The mean duration of magnesium infusion was 27.93 hours (95% confidence interval [CI]: 24.10-31.76 hours). The intervention group had greater serum peak magnesium levels: 1.72 mmol/L ± 0.34 on day 1, 1.32 ± 0.36 on day 2 versus 1.01 ± 1.14 and 0.97 ± 0.13, respectively, in the control group (p < 0.01). Atrial fibrillation occurred in 25 patients (25.3%) in the intervention group and 40 patients (40.4%) in the control group (odds ratio 0.49, 95% CI, 0.27-0.92; p = 0.023). On a multivariate Cox proportional hazards model, the hazard ratio for the development of AF was significantly less in the intervention group (hazard ratio 0.45, 95% CI, 0.26-0.77; p = 0.004).

CONCLUSION

The magnesium delivery strategy was associated with a decreased incidence of postoperative AF in cardiac surgery patients. These findings provide a rationale and preliminary data for the design of future randomized controlled trials.

The Effects of Escalation of Respiratory Support and Prolonged Invasive Ventilation on Outcomes of Cardiac Surgical Patients: A Retrospective Cohort Study

Objectives

The aim of this study was to determine the effects of escalation of respiratory support and prolonged postoperative invasive ventilation on patient-centered outcomes, and identify perioperative factors associated with these 2 respiratory complications.

Design

A retrospective cohort analysis of cardiac surgical patients admitted to the cardiothoracic intensive care unit (ICU) between August 2015 and January 2018. Escalation of respiratory support was defined as “unplanned continuous positive airway pressure,” “non-invasive ventilation,” or “reintubation” after surgery; prolonged invasive ventilation was defined as “invasive ventilation beyond the first 12 hours following surgery.” The primary endpoint was the composite of escalation of respiratory support and prolonged ventilation.

Setting

Tertiary cardiothoracic ICU.

Participants

A total of 2,098 patients were included and analyzed.

Interventions

None.

Measurements and Main Results

The composite of escalation of support or prolonged ventilation occurred in 509 patients (24.3%). Patients who met the composite had higher mortality (2.9% v 0.1%; p < 0.001) and longer median [interquartile range] length of ICU (2.1 [1.0-4.9] v 0.9 [0.8-1.0] days; p < 0.0001) and hospital (10.6 [8.0-16.0] v 7.2 [6.2-10.0] days; p < 0.0001) stay. Hypoxemia and anemia on admission to ICU were the only 2 factors independently associated with the need for escalation of respiratory support or prolonged invasive ventilation.

Conclusions

Escalation of respiratory support or prolonged invasive ventilation is frequently seen in cardiac surgery patients and is highly associated with increased mortality and morbidity. Hypoxemia and anemia on admission to the ICU are potentially modifiable factors associated with escalation of respiratory support or prolonged invasive ventilation.