Risk Factors for the Development of Intraoperative Hypoxia in Patients Undergoing Nonintubated Video-Assisted Thoracic Surgery: A Retrospective Study from a Single Center

Study on risk factors and treatment strategies of hypoxemia after acute type a aortic dissection surgery

Acute type A aortic dissection is a life-threatening cardiovascular disease characterized by rapid onset and high mortality. Emergency surgery is the preferred and reliable treatment option. However, postoperative complications significantly impact patient prognosis. Hypoxemia, a common complication, poses challenges in clinical treatment, negatively affecting patient outcomes and increasing the risk of mortality. Therefore, it is crucial to study and comprehend the risk factors and treatment strategies for hypoxemia following acute type A aortic dissection to facilitate early intervention.

Role of oxygen reserve index monitoring in patients undergoing robot-assisted radical prostatectomy: a retrospective study

PURPOSE

Robot-assisted radical prostatectomy (RARP) is a common surgical procedure for the treatment of prostate cancer. Although beneficial, it can lead to intraoperative hypoxia due to high-pressure pneumoperitoneum and Trendelenburg position. This study explored the use of oxygen reserve index (ORi) to monitor and predict hypoxia during RARP.

METHODS

A retrospective analysis was conducted on 329 patients who underwent RARP at the Seoul National University Bundang Hospital between July 2021 and March 2023. Various pre- and intraoperative variables were collected, including ORi values. The relationship between ORi values and hypoxia occurrence was assessed using receiver operating characteristic curves and logistic regression analysis.

RESULTS

Intraoperative hypoxia occurred in 18.8% of the patients. The receiver operating characteristic curve showed a satisfactory area under the curve of 0.762, with the ideal ORi cut-off value for predicting hypoxia set at 0.16. Sensitivity and specificity were 64.5% and 75.7%, respectively. An ORi value of < 0.16 and a higher body mass index were identified as independent risk factors of hypoxia during RARP.

CONCLUSIONS

ORi monitoring provides a non-invasive approach to predict intraoperative hypoxia during RARP, enabling early management. Additionally, the significant relationship between a higher body mass index and hypoxia underscores the importance of individualized patient assessment.

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.

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.

Preoperative Nomogram and Risk Calculator for Postoperative Hypoxemia and Related Clinical Outcomes Following Stanford Type A Acute Aortic Dissection Surgery

Background

Hypoxemia is a common complication after Stanford type A acute aortic dissection surgery (AADS), however, few studies about hypoxemia after AADS exist. The aims of this study were to identify independent risk factors for hypoxemia after AADS and to clarify its association with clinical outcomes.

Methods

Patients undergoing AADS from 2016 to 2019 in our hospital were identified and used as a training set. Preoperative variables were first screened by univariate analysis and then entered into a multivariate logistic regression analysis to identify independent risk factors. A nomogram and an online risk calculator were constructed based on the logistic model to facilitate clinical practice and was externally validated in an independent dataset.

Results

Severe hypoxemia developed in 119 of the 492 included patients (24.2%) and poorer clinical outcomes were observed in these patients. Five independent risk factors for severe hypoxemia after AADS were identified by multivariate analysis, including older age, smoking history, renal insufficiency, higher body mass index, and white blood cell count. The model showed good calibration, discrimination, and clinical utility in the training set, and was well validated in the validation set. Risk stratification was performed and three risk groups were defined as low, medium, and high risk groups. Hypertension was identified as an independent risk factor for moderate hypoxemia besides the five predictors mentioned above, and renal insufficiency was not significant for mild hypoxemia by multivariate analysis. In addition, although frozen elephant trunk was associated with increased risk of postoperative hypoxemia in the univariate analysis, frozen elephant trunk was also not identified as an independent risk factor for postoperative hypoxemia in the multivariate analysis.

Conclusion

Hypoxemia was frequent following AADS, related to poorer clinical outcomes. Predictors were identified and a nomogram as well as an online risk calculator predicting severe hypoxemia after AADS was developed and validated, which may be helpful for risk estimation and perioperative management.

Effects of Non-intubated Video-Assisted Thoracic Surgery on Patients With Pulmonary Dysfunction

Background: Non-intubated video-assisted thoracic surgery (NIVATS) can be safely performed in lung volume reduction surgery for patients with severe pulmonary dysfunction. However, there is still no cohort observation on the effects of NIVATS on patients with pulmonary dysfunction undergoing different types of thoracic procedures. This retrospective study aimed to observe the effects of NIVATS for this kind of patients.

Methods: Three hundred and twenty-eight patients with moderate to severe obstructive pulmonary dysfunction, who underwent video-assisted thoracic surgery (VATS), were retrospectively collected from June 1st, 2017 to September 30th, 2019. Patients in NIVATS were case-matched with those in intubated video-assisted thoracic surgery (IVATS) by a propensity score-matched analysis. The primary outcome was the comparison of perioperative values, the secondary outcome was the risk factors for postoperative clinical complications (PCP) which were identified by binary logistic regression analysis.

Results: After being matched, there were no differences in demographics and preoperative values of pulmonary function between NIVATS and IVATS groups. The duration of surgery and anesthesia had no difference (P = 0.091 and P = 0.467). As for the postoperative recovery, except for the mean intensive care unit (ICU) stay was longer in the IVATS group than in the NIVATS group (P = 0.015), the chest tube removal time and the postoperative hospital stay had no difference (P = 0.394 and P = 0.453), and the incidence of PCP also had no difference (P = 0.121). The binary logistic regression analysis revealed that the history of pulmonary disease, anesthesia method, and surgical location were risk factors of PCP.

Conclusion: For patients with pulmonary dysfunction when undergoing different types of thoracic procedures, the NIVATS can be performed as effectively and safely as the IVATS, and can reduce the ICU stay.