Prevalence of peri-intubation major adverse events among critically ill patients: A systematic review and meta analysis

The Airway Lead and the Creation of a Comprehensive Emergency Airway Quality Program

BACKGROUND

Emergency Department (ED) Intubation is one of the most critical times during a patient's hospital course. Ideal performance requires training, equipment, and mindset to overcome the barriers of anatomy, physiology, and human factors.

OBJECTIVES

We believe that EDs should use the same model of quality improvement and leadership for intubation as other critical procedures such as ED ultrasound.

DISCUSSION

This paper delineates one program's creation of a comprehensive airway quality improvement (QI) program and will hopefully serve as a roadmap for other centers.

CONCLUSIONS

The creation of an airway QI program headed by a designated airway lead has the potential to improve patient care and procedural success in the ED.

Peri-intubation adverse events and clinical outcomes in emergency department patients: the BARCO study

BACKGROUND

Emergency tracheal intubation in critically ill patients carries a high risk of complications, and practices vary substantially across different settings. Identifying risk factors and understanding how peri-intubation adverse events affect patient outcomes may guide standardization of care and improve survival.

METHODS

This prospective cohort study involved 18 emergency departments in Brazil (March 2022-April 2024). We included adults (≥ 18 years) undergoing emergency intubation and excluded patients intubated electively or for cardiac arrest. We defined major peri-intubation adverse events as severe hypoxemia, new hemodynamic instability, or cardiac arrest occurring within 30 min of initiating intubation. The primary outcome was 28-day mortality. Multivariable regression analyses assessed associations between adverse events and mortality, controlling for potential confounders.

RESULTS

Among 2846 patients, major adverse events occurred in 919 (32.3%) intubations, most frequently new hemodynamic instability (20.0%), followed by severe hypoxemia (12.5%) and cardiac arrest (3.5%). The overall 28-day mortality was 45.1%. Patients experiencing any major adverse event had a significantly higher 28-day mortality (57.6 vs 39.2%; aHR 1.43, 95% CI 1.26-1.62; p < 0.001). Sensitivity analyses confirmed these findings. Successful first-attempt intubation was associated with a reduced likelihood of major adverse events (aOR 0.52; 95% CI 0.41-0.65; p < 0.001).

CONCLUSION

One in three patients undergoing emergency intubation experienced a major peri-intubation adverse event, which was associated with higher 28-day mortality. These results underscore the importance of optimizing intubation strategies to reduce complications and potentially improve patient outcomes in critically ill patients.

A nomogram to predict pulmonary complications after gastrointestinal surgery: a retrospective study

OBJECTIVE

We aimed at developing a nomogram able to predict postoperative pulmonary complications (PPC) after gastrointestinal surgery.

METHODS

We retrospectively analyzed the clinical data of patients who underwent gastrointestinal surgery at Jiangnan University Affiliated Hospital from December 2017 to May 2022. Patients were randomly divided into training cohort and validation cohort at a 7:3 ratio. The training cohort is divided into PPC group and Non-PPC group. The Least Absolute Shrinkage and Selection Operator (LASSO) method and logistic regression were used to determine the independent risk factors. The identified risk factors were used to construct a nomogram model for predicting the risk of PPC after gastrointestinal surgery. The nomogram model was validated by the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

RESULTS

A total of 563 patients were admitted. The incidence of PPC was 17.6% (99/563). In the training cohort, multiple logistic regression showed that age, hypertension, history of respiratory diseases, preoperative albumin, intraoperative blood loss, postoperative intensive care unit (ICU) time, postoperative arterial oxygen partial pressure (PaO2), and postoperative tracheal intubation time were identified as the influencing factors of PPC (P < 0.05). We constructed a nomogram model for predicting the PPC of the training cohort, with a C-index of 0.857 (95%CI 0.812-0.902). In the validation cohort, the C-index of the model is 0.936 (95%CI 0.890-0.982). The ROC curve of the training cohort is 0.875 (95%CI 0.832-0.918), similar with validation cohort 0.929 (0.876-0.982). The calibration curve indicates that the predicted results are correlated with the observed results.

CONCLUSIONS

The constructed nomogram model has certain predictive value, and can provide a scientific reference for predicting the occurrence of PPC after gastrointestinal surgery.

Non-Invasive Ventilation as a Pre-Oxygenation Strategy During In-Flight Rapid Sequence Intubation: A Case Report

Noninvasive ventilation has been used as a pre-oxygenation strategy for rapid sequence intubation in the emergency department and the intensive care unit, yet, limited research has examined its use in the transport setting. These case reports discuss the use of noninvasive ventilation via a Hamilton T1 ventilator (Hamilton Medical) during transport by an air medical crew for pre-oxygenation before intubation in two cases. In both cases, a noninvasive, bilevel-positive airway pressure mode with a backup rate was used to achieve adequate airway pressures while allowing for a two-handed seal by one emergency medical services clinician as the other prepared the equipment and medications. This method of pre-oxygenation in a space and resource-limited setting was associated with first-pass success without hypoxia in both cases. This adds another method of pre-oxygenation to facilitate safe intubation in similar settings.

Development and external validation of an interpretable machine learning model for the prediction of intubation in the intensive care unit

Given the limited capacity to accurately determine the necessity for intubation in intensive care unit settings, this study aimed to develop and externally validate an interpretable machine learning model capable of predicting the need for intubation among ICU patients. Seven widely used machine learning (ML) algorithms were employed to construct the prediction models. Adult patients from the Medical Information Mart for Intensive Care IV database who stayed in the ICU for longer than 24 h were included in the development and internal validation. The model was subsequently externally validated using the eICU-CRD database. In addition, the SHapley Additive exPlanations method was employed to interpret the influence of individual parameters on the predictions made by the model. A total of 11,988 patients were included in the final cohort for this study. The CatBoost model demonstrated the best performance (AUC: 0.881). In the external validation set, the efficacy of our model was also confirmed (AUC: 0.750), which suggests robust generalization capabilities. The Glasgow Coma Scale (GCS), body mass index (BMI), arterial partial pressure of oxygen (PaO2), respiratory rate (RR) and length of stay (LOS) before ICU were the top 5 features of the CatBoost model with the greatest impact. We developed an externally validated CatBoost model that accurately predicts the need for intubation in ICU patients within 24 to 96 h of admission, facilitating clinical decision-making and has the potential to improve patient outcomes. The prediction model utilizes readily obtainable monitoring parameters and integrates the SHAP method to enhance interpretability, providing clinicians with clear insights into the factors influencing predictions.

Emergency medicine updates: Endotracheal intubation

INTRODUCTION

Airway management including endotracheal intubation (ETI) is a key skill for emergency clinicians. Therefore, it is important for emergency clinicians to be aware of the current evidence regarding the identification and management of patients requiring ETI.

OBJECTIVE

This paper evaluates key evidence-based updates concerning ETI for the emergency clinician.

DISCUSSION

ETI is commonly performed in the emergency department (ED) setting but has many nuanced components. There are several tools that have been used to predict a difficult airway which incorporate anatomic and physiologic features. While helpful, these tools should not be used in isolation. Preoxygenation and apneic oxygenation are recommended to reduce the risk of desaturation and patient decompensation, particularly with noninvasive ventilation in critically ill patients. Induction and neuromuscular blocking medications should be tailored to the clinical scenario. Video laryngoscopy is superior to direct laryngoscopy among novice users, while both techniques are reasonable among more experienced clinicians. Recent literature suggests using a bougie during the first attempt. Point-of-care ultrasound is helpful for confirming correct placement and depth of the endotracheal tube.

CONCLUSIONS

An understanding of literature updates can improve the ED care of patients requiring emergent intubation.

Influence of Patient Weight on Prehospital Advanced Airway Procedure Success Rates

OBJECTIVE

Previous investigations of the relationship between obesity and difficult airway management have provided mixed results. Almost universally, these studies were conducted in the hospital setting, and the influence of patient body weight on successful prehospital airway management remains unclear. Because patient weight could be one readily identifiable risk factor for problematic airway interventions, we sought to evaluate this relationship.

METHODS

We conducted a retrospective analysis using the 2020 ESO Data Collaborative dataset. The inclusion criteria consisted of adult patients weighing >30kg with an attempted orotracheal intubation (OTI) and/or blind insertion airway device (BIAD) placement. Separate logistic regression models were developed to determine the influence of weight (dichotomized at 100 kg) on cumulative procedure success for OTI and BIAD, and linear regression models were used to identify trends for each across weight strata.

RESULTS

A total of 45,344 patients met inclusionary criteria, among which 40,668(89.7%) suffered from a medical emergency, followed by 3,130(6.9%) with traumatic injuries, and 1,546(3.4%) attributable to a combined medical-trauma etiology. Cardiac arrest occurred either prior to EMS arrival or at some point during EMS care in 38,210(84.3%) patients. OTI was attempted in 18,153(40.0%) patients, while 21,597(47.6%) had a BIAD attempt and 5,594(12.3%) had both airway types attempted. The overall cumulative insertion success rates for OTI and BIAD were 79.5% and 92.7%, respectively. Altogether, 2,711(6.0%) had no advanced airway of any type successfully placed, which represents the overall failed advanced airway rate. After controlling for patient age, sex, minority status, and call type (medical vs. trauma), weight >100kg was associated with decreased likelihood of cumulative OTI success (OR = 0.64, p < 0.001), but higher likelihood of cumulative BIAD success (OR = 1.31, p < 0.001). Cumulative OTI success was associated with a negative 0.6% linear trend per 5 kg of body weight (p < 0.001) while cumulative BIAD success had a 0.2% positive trend (p < 0.001).

CONCLUSION

This retrospective analysis of a national EMS database revealed that increasing patient weight was negatively associated with intubation success. A positive, but smaller, linear trend was observed for BIAD placement. Patient weight may be an easily identifiable predictor of difficult oral intubation and may be a consideration when selecting an airway management strategy.