Inpatient Complications Predict Tracheostomy Better than Admission Variables After Traumatic Brain Injury

Early Versus Late Tracheostomy in Patients with Traumatic Brain Injury: A US Nationwide Analysis

BACKGROUND

One of the most critical issues in patients suffering from traumatic brain injury (TBI) is protecting the airway and attempting to keep a secure airway. It is evident that tracheostomy in patients with TBI after 7-14 days can have favorable outcomes if the patient cannot be extubated; however, some clinicians have recommended early tracheostomy before 7 days.

METHODS

A retrospective cohort of inpatient study participants was queried from the National Inpatient Sample to include patients with TBI between 2016 and 2020 undergoing tracheostomy and outcomes between the two groups of early tracheostomy (ET) (< 7 days from admission) and late tracheostomy (LT) (≥ 7 days from admission) were compared.

RESULTS

We reviewed 219,005 patients with TBI, out of whom 3.04% had a tracheostomy. Patients in the ET group were younger than those in the LT group (45.02 ± 19.38 years old vs. 48.68 ± 20.50 years old, respectively, p < 0.001), mainly men (76.64% vs. 73.73%, respectively, p = 0.01), and mainly White race (59.88% vs. 57.53%, respectively, p = 0.33). The patients in the ET group had a significantly shorter length of stay as compared with those in the LT group (27.78 ± 25.96 days vs. 36.32 ± 29.30 days, respectively, p < 0.001) and had a significantly lower hospital charge ($502,502.436 ± 427,060.81 vs. $642,739.302 ± 516,078.94 per patient, respectively, p < 0.001). The whole TBI cohort mortality was reported at 7.04%, which was higher within the ET group compared with the LT group (8.69% vs. 6.07%, respectively, p < 0.001). Patients in the LT had higher odds of developing any infection (odds ratio [OR] 1.43 [1.22-1.68], p < 0.001), emerging sepsis (OR 1.61 [1.39-1.87], p < 0.001), pneumonia (OR 1.52 [1.36-1.69], p < 0.001), and respiratory failure (OR 1.30 [1.09-1.55], p = 0.004).

CONCLUSIONS

This study shows that ET can provide notable and significant benefits for patients with TBI. Future high-quality prospective studies should be performed to investigate and shed more light on the ideal timing of tracheostomy in patients with TBI.

A nomogram for predicting the necessity of tracheostomy after severe acute brain injury in patients within the neurosurgery intensive care unit: A retrospective cohort study

Objective

This retrospective study was aimed to develop a predictive model for assessing the necessity of tracheostomy (TT) in patients admitted to the neurosurgery intensive care unit (NSICU).

Method

We analyzed data from 1626 NSICU patients with severe acute brain injury (SABI) who were admitted to the Department of NSICU at the Affiliated People's Hospital of Jiangsu University between January 2021 and December 2022. Data of the patients were retrospectively obtained from the clinical research data platform. The patients were randomly divided into training (70%) and testing (30%) cohorts. The least absolute shrinkage and selection operator (LASSO) regression identified the optimal predictive features. A multivariate logistic regression model was then constructed and represented by a nomogram. The efficacy of the model was evaluated based on discrimination, calibration, and clinical utility.

Results

The model highlighted six predictive variables, including the duration of NSICU stay, neurosurgery, orotracheal intubation time, Glasgow Coma Scale (GCS) score, systolic pressure, and respiration rate. Receiver operating characteristic (ROC) analysis of the nomogram yielded area under the curve (AUC) values of 0.854 (95% confidence interval [CI]: 0.822-0.886) for the training cohort and 0.865 (95% CI: 0.817-0.913) for the testing cohort, suggesting commendable differential performance. The predictions closely aligned with actual observations in both cohorts. Decision curve analysis demonstrated that the numerical model offered a favorable net clinical benefit.

Conclusion

We developed a novel predictive model to identify risk factors for TT in SABI patients within the NSICU. This model holds the potential to assist clinicians in making timely surgical decisions concerning TT.

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.

Liberation from Mechanical Ventilation and Tracheostomy Practice in Traumatic Brain Injury

Liberating patients with severe traumatic brain injury (TBI) from mechanical ventilation is often a challenging task. These patients frequently require prolonged ventilation and have persistent alterations in the level and content of consciousness. Questions about their ability to protect their airway are common. Pulmonary complications and copious respiratory secretions are also very prevalent. Thus, it is hardly surprising that rates of extubation failure are high. This is a major problem because extubation failure is associated with a host of poor outcome measures. When the safety of an extubation attempt is uncertain, direct tracheostomy is favored by some, but there is no evidence that this practice leads to better outcomes. Current knowledge is insufficient to reliably predict extubation outcomes in TBI, and practices vary substantially across trauma centers. Yet observational studies provide relevant information that must be weighted when considering the decision to attempt extubation in patients with head injury. This review discusses available evidence on liberation from mechanical ventilation in TBI, proposes priorities for future research, and offers practical advice to guide decisions at the bedside.

Weaning from mechanical ventilation in neurocritical care

In the intensive care unit (ICU), weaning from mechanical ventilation follows a step-by-step process that has been well established in the general ICU population. However, little data is available in brain injury patients, who are often intubated to protect airways and prevent central hypoventilation. In this narrative review, we describe the general principles of weaning and how these principles can be adapted to brain injury patients. We focus on three major issues regarding weaning from mechanic ventilation in brain injury patients: (1) sedation protocol, (2) weaning and extubation protocol and criteria, (3) criteria, timing and technique for tracheostomy.

Pediatric Tracheostomy-Related Complications: A Cross-sectional Analysis

OBJECTIVE

To determine the rate of tracheostomy-related complications in pediatric patients from nationally representative databases.

STUDY DESIGN

Cross-sectional analysis.

SETTING

2016 Kids' Inpatient Database and 2016 Nationwide Readmission Database.

METHODS

All pediatric tracheostomy procedures were included. Complication type, admission outcomes, and readmission rates were recorded with a logistic regression analysis to determine patient characteristics associated with complications.

RESULTS

An estimated 5309 tracheostomies were performed among pediatric patients in 2016, 8% (n = 432) of whom developed tracheostomy-related complications. This group was younger (4.7 vs 8.7 years, P < .001) and required longer hospital admissions (68.7 vs 33.2 days, P < .001) than children without tracheostomy-related complications. Mean costs ($459,324 vs $397,937, P < .001) and mean total charges ($1,573,964 vs $1,099,347, P < .001) were increased if a tracheostomy-related complication occurred. These events occurred more often in those with bronchopulmonary dysplasia (24% vs 12%, P < .001), heart disease (24% vs 12%, P = .001), gastroesophageal reflux disease (31% vs 19%, P < .001), short gestational age (24% vs 14%, P < .001), and subglottic stenosis (9.9% vs 5.4%, P = .001). The estimated 30-day readmission rate was 24% (SE, 1.7%) but did not increase after tracheostomy complications (27% vs 15%, P = .04). Tracheostomy-related complications were predicted by gastroesophageal reflux disease (odds ratio [OR], 1.50; 95% CI, 1.14-1.97; P = .004), younger age (OR, 1.12; 95% CI, 1.04-1.22; P = .002), and lengthier hospitalization (OR, 1.00; 95% CI, 1.00-1.01; P < .001) on multiple logistic regression analysis.

CONCLUSION

Tracheostomy-related complications occur in approximately 8% of pediatric patients and are higher in younger children or those with longer admission lengths. These data have implications for benchmarking standards of posttracheostomy complications across institutions.

Absence of calvarial fracture could predict the need for tracheostomy in traumatic brain injury

Aim

Tracheostomy is a common procedure for intubated patients with traumatic brain injury (TBI) in the intensive care unit (ICU) but optimal timing and the predictors of tracheostomy are still unclear. The aim of our study was to explore whether the traumatic variables of head injury predict the need for tracheostomy in intubated TBI patients.

Methods

A single‐center, retrospective observational study including a series of TBI patients admitted to Fukui Prefectural Hospital from April 1, 2004 to March 31, 2020 was carried out. Our primary outcome was tracheostomy. Patients with TBI who were intubated and admitted into the ICU within 24 h after injury were enrolled. Exclusion criteria were age less than 18 years, pregnancy, mortality within 24 h, post‐cardiac arrest syndrome, and patients for whom life‐sustaining interventions were withheld. Radiologic images were also reviewed and the morphology of the head injury was categorized.

Results

Seventy‐six patients were included. Forty‐six patients (60.5%) underwent tracheostomy and 30 patients (39.5%) were successfully extubated. Calvarial fracture (odds ratio [OR] 0.34; 95% confidence interval [CI], 0.13–0.88; P = 0.03), Injury Severity Score (OR 1.07; 95% CI, 1.00–1.15; P = 0.04), and Glasgow Comas Scale score (OR 0.84; 95% CI, 0.73–0.96) were statistically significant in the univariable analysis. Multivariate logistic regression identified calvarial fracture as an independent predictor for tracheostomy. The model involving calvarial fracture, Injury Severity Score ≥16, and Glasgow Coma Scale score ≤8 showed the area under the receiver operating characteristic curve for the model was 0.737 (95% CI, 0.629–0.846).

Conclusions

The absence of calvarial fracture could predict the necessity for tracheostomy in intubated TBI patients when combined with other factors. Further prospective randomized trials are necessary to confirm the findings.

Epidemiology and Outcomes of Acute Respiratory Distress Syndrome Following Isolated Severe Traumatic Brain Injury

Patients with traumatic brain injury (TBI) are at risk for extra-cranial complications, such as the acute respiratory distress syndrome (ARDS). We conducted an analysis of risk factors, mortality, and healthcare utilization associated with ARDS following isolated severe TBI. The National Trauma Data Bank (NTDB) dataset files from 2007-2014 were used to identify adult patients who suffered isolated [other body region-specific Abbreviated Injury Scale (AIS) < 3] severe TBI [admission total Glasgow Coma Scale (GCS) from 3 to 8 and head region-specific AIS >3]. In-hospital mortality was compared between patients who developed ARDS and those who did not. Utilization of healthcare resources (ICU length of stay, hospital length of stay, duration of mechanical ventilation, and frequency of tracheostomy and gastrostomy tube placement) was also examined. This retrospective cohort study included 38,213 patients with an overall ARDS occurrence of 7.5%. Younger age, admission tachycardia, pre-existing vascular and respiratory diseases, and pneumonia were associated with the development of ARDS. Compared to patients without ARDS, patients that developed ARDS experienced increased in-hospital mortality (OR 1.13, 95% CI 1.01-1.26), length of stay (p = <0.001), duration of mechanical ventilation (p = < 0.001), and placement of tracheostomy (OR 2.70, 95% CI 2.34-3.13) and gastrostomy (OR 2.42, 95% CI 2.06-2.84). After isolated severe TBI, ARDS is associated with increased mortality and healthcare utilization. Future studies should focus on both prevention and management strategies specific to TBI-associated ARDS.

Mechanical ventilation in neurocritical care setting: A clinical approach

Neuropatients often require invasive mechanical ventilation (MV). Ideal ventilator settings and respiratory targets in neuro patients are unclear. Current knowledge suggests maintaining protective tidal volumes of 6-8 ml/kg of predicted body weight in neuropatients. This approach may reduce the rate of pulmonary complications, although it cannot be easily applied in a neuro setting due to the need for special care to minimize the risk of secondary brain damage. Additionally, the weaning process from MV is particularly challenging in these patients who cannot control the brain respiratory patterns and protect airways from aspiration. Indeed, extubation failure in neuropatients is very high, while tracheostomy is needed in one-third of the patients. The aim of this manuscript is to review and describe the current management of invasive MV, weaning, and tracheostomy for the main four subpopulations of neuro patients: traumatic brain injury, acute ischemic stroke, subarachnoid hemorrhage, and intracerebral hemorrhage.