Effects of Positive End-Expiratory Pressure on the Risk of Postoperative Pulmonary Complications in Patients Undergoing Elective Craniotomy

Comparison of lung aeration loss in open abdominal oncologic surgeries after ventilation with electrical impedance tomography-guided PEEP versus conventional PEEP: a pilot feasibility study

BACKGROUND

Existing literature lacks high-quality evidence regarding the ideal intraoperative positive end-expiratory pressure (PEEP) to minimize postoperative pulmonary complications (PPCs). We hypothesized that applying individualized PEEP derived from electrical impedance tomography would reduce the severity of postoperative lung aeration loss, deterioration in oxygenation, and PPC incidence.

METHODS

A pilot feasibility study was conducted on 36 patients who underwent open abdominal oncologic surgery. The patients were randomized to receive individualized PEEP or conventional PEEP at 4 cmH2O. The primary outcome was the impact of individualized PEEP on changes in the modified lung ultrasound score (MLUS) derived from preoperative and postoperative lung ultrasonography. A higher MLUS indicated greater lung aeration loss. The secondary outcomes were the PaO2/FiO2 ratio and PPC incidence.

RESULTS

A significant increase in the postoperative MLUS (12.0 ± 3.6 vs 7.9 ± 2.1, P < 0.001) and a significant difference between the postoperative and preoperative MLUS values (7.0 ± 3.3 vs 3.0 ± 1.6, P < 0.001) were found in the conventional PEEP group, indicating increased lung aeration loss. In the conventional PEEP group, the intraoperative PaO2/FiO2 ratios were significantly lower but not the postoperative ratios. The PPC incidence was not significantly different between the groups. Post-hoc analysis showed the increase in lung aeration loss and deterioration of intraoperative oxygenation correlated with the deviation from the individualized PEEP.

CONCLUSIONS

Individualized PEEP appears to protect against lung aeration loss and intraoperative oxygenation deterioration. The advantage was greater in patients whose individualized PEEP deviated more from the conventional PEEP.

Multiple Machine Learning Approaches Based on Postoperative Prediction of Pulmonary Complications in Patients With Emergency Cerebral Hemorrhage Surgery

Objective

This study aimed to create a prediction model of postoperative pulmonary complications for the patients with emergency cerebral hemorrhage surgery.

Methods

Patients with hemorrhage surgery who underwent cerebral hemorrhage surgery were included and divided into two groups: patients with or without pulmonary complications. Patient characteristics, previous history, laboratory tests, and interventions were collected. Univariate and multivariate logistic regressions were used to predict postoperative pulmonary infection. Multiple machine learning approaches have been used to compare their importance in predicting factors, namely K-nearest neighbor (KNN), stochastic gradient descent (SGD), support vector classification (SVC), random forest (RF), and logistics regression (LR), as they are the most successful and widely used models for clinical data.

Results

Three hundred and fifty four patients with emergency cerebral hemorrhage surgery between January 1, 2017 and December 31, 2020 were included in the study. 53.7% (190/354) of the patients developed postoperative pulmonary complications (PPC). Stepwise logistic regression analysis revealed four independent predictive factors associated with pulmonary complications, including current smoker, lymphocyte count, clotting time, and ASA score. In addition, the RF model had an ideal predictive performance.

Conclusions

According to our result, current smoker, lymphocyte count, clotting time, and ASA score were independent risks of pulmonary complications. Machine learning approaches can also provide more evidence in the prediction of pulmonary complications.

Effects of ipratropium bromide on the occurrence of postoperative respiratory complications in craniectomy patients with COPD: A nationwide multicenter retrospective study

INTRODUCTION

Postoperative pulmonary complications (PPCs) are common and associated with increased morbidity, mortality, and medical cost. They are gaining increasing concerns among patients receiving neurological surgery. Chronic obstructive pulmonary disease (COPD) affect a large section of whole population and is also one of the risk factors of PPCs in the perioperative setting. Ipratropium bromide is the inhalation solution for the treatment of COPD. Studies showed the perioperative nebulization of ipratropium bromide could increase the lung function and decrease the incidence of postoperative pneumonia in COPD patients underwent thoracic surgery. The purpose of this study is to investigate the effect of perioperative nebulization of ipratropium bromide on PPCs in COPD patients underwent neurosurgical surgery.

METHODS AND ANALYSIS

This study is a multicenter retrospective study in China. Patients who meet the inclusion/exclusion criteria are selected from 7 neurosurgical centers in China. According to whether ipratropium bromide is used in perioperative period, the patients are divided into exposure group and control group. The primary outcome is the incidence of postoperative pneumonia. Secondary outcomes are unplanned intubation, postoperative mechanical ventilation ≥ 48 hours, respiratory failure, atelectasis, death, and length of stay.

ETHICS AND DISSEMINATION

This study was approved by the ethics committee (EC) of the School of Public Health, Fudan University, Shanghai, China. Waived by the ethics committee, no written consent form was obtained since we used the registry data. The study results will be communicated via publication.

TRIAL REGISTRATION NUMBER

ChiCTR1900022552.

Postoperative Pulmonary Complications Following Brain Tumor Resection: A National Database Analysis

OBJECTIVE

There is sparse literature that investigates the adverse effects of postoperative pulmonary complication (PPCs) specifically in postcraniotomy tumor patients. In this study, we describe the rate of PPCs, determine predictive factors, and delineate associations with adverse outcomes.

METHODS

The National Surgical Quality Improvement Program (2006-2016) database was queried for patients who underwent craniotomy for brain tumors. A total of 28,700 eligible patients were identified. Univariate tests and/or multivariate logistic regression were used to determine predictors of PPC and associations with adverse outcomes.

RESULTS

A total of 19 predictors of PPC across 14 different categories were identified: age 65-79 years (odds ratio [OR] 1.6; P < 0.001), age ≥80 years (OR 2.3; P < 0.001), male sex (OR 1.3; P < 0.001), operative time ≥360 minutes (OR 4.3; P < 0.001), operative time 300-359 minutes (OR 2.5; P < 0.001), operative time 240-299 minutes (OR 1.8; P < 0.001), operative time 180-239 minutes (OR 1.3; P < 0.001), total functional dependence (OR 3.8; P < 0.001), partial functional dependence (OR 1.7; P < 0.001), insulin-dependent diabetes (OR 1.5; P < 0.001), preoperative dyspnea (OR 1.3; P = 0.01), chronic steroid use (OR 1.4; P < 0.001), chronic obstructive pulmonary disease (OR 1.8; P < 0.001), preoperative leukocytosis (OR 1.4; P < 0.001), anemia (OR 1.2; P < 0.001), American Society of Anesthesiologists (ASA) classification ≥3 (OR 2.0; P < 0.001), emergency case status (OR 2.0; P < 0.001), and infratentorial lesions (OR 1.4; P < 0.001). PPCs were significantly associated with higher reoperation, readmission, and mortality rates as well as longer length of stay (univariate).

CONCLUSIONS

There are several predictive factors of PPCs in patients that undergo surgical resection of brain tumors, and PPC development is associated with numerous adverse outcomes. It is critically important to understand and, if possible, mitigate controllable circumstances that may reduce morbidity and mortality associated with PPCs.