Ventilator-associated events, not ventilator-associated pneumonia, is associated with higher mortality in trauma patients

Relationship between microaspiration and ventilator-associated events: A post-hoc analysis of a randomized controlled trial

OBJECTIVE

The relationship between ventilator-associated events (VAE) and microaspiration in intubated patients has not be studied. The objective of this study was to evaluate the relationship between abundant microaspiration of oropharyngeal secretions or gastric contents and the incidence of VAE.

PATIENTS AND METHODS

This was a post hoc analysis of the BESTCUFF study, which was a multicenter, cluster randomized, cross-over, controlled, open-label trial in adult patients ventilated for over 48 h. All tracheal aspirates were sampled for 48 h following enrollment, with quantitative measurement of pepsin and alpha-amylase. VAE were identified using National Healthcare Safety Network criteria, based on PEEP or FiO2 variations compared to stable parameters in previous days. The primary objective was to assess the relationship between abundant global microaspiration and the incidence of VAE, adjusted for pre-specified confounding factors (sex, SAPS II score and Glasgow coma scale).

RESULTS

261 patients were included, of which 31 (11.9%) developed VAE, with an overall median age of 65 (interquartile range 52-74), a majority of male patients (164, 62.8%), a median SAPS II score of 50 [40-61], a median SOFA score of 8 [5-11], and acute respiratory failure as main reason for ICU admission (117, 44.8%).The incidence of VAE was not significantly associated with abundant global microaspiration (adjusted cause-specific hazard ratio (cHR): 1.55 [0.46-5.17), abundant gastric microaspiration (adjusted cHR: 1.24 [0.61-2.53), or with abundant oropharyngeal microaspiration (adjusted HR: 1.07 [0.47-2.42]).

CONCLUSIONS

Our results suggest no significant association between abundant global, gastric or oropharyngeal microaspiration and the incidence of VAE.

IMPLICATIONS FOR CLINICAL PRACTICE

This study underscores that measuring microaspiration in intubated critically ill patients might not be useful to predict the diagnosis of VAE or to evaluate interventions aiming at preventing these complications.

Impact of a national collaborative project to improve the care of mechanically ventilated patients

This prospective quasi-experimental study from the NASAM (National Approach to Standardize and Improve Mechanical Ventilation) collaborative assessed the impact of evidence-based practices including subglottic suctioning, daily assessment for spontaneous awakening trial (SAT), spontaneous breathing trial (SBT), head of bed elevation, and avoidance of neuromuscular blockers unless otherwise indicated. The study outcomes included VAE (primary) and intensive care unit (ICU) mortality. Changes in daily care process measures and outcomes were evaluated using repeated measures mixed modeling. The results were reported as incident rate ratio (IRR) for each additional month with 95% confidence interval (CI). A comprehensive program that included education on evidence-based practices for optimal care of mechanically ventilated patients with real-time benchmarking of daily care process measures to drive improvement in forty-two ICUs from 26 hospitals in Saudi Arabia (>27,000 days of observation). Compliance with subglottic suctioning, SAT and SBT increased monthly during the project by 3.5%, 2.1% and 1.9%, respectively (IRR 1.035, 95%CI 1.007-1.064, p = 0.0148; 1.021, 95% CI 1.010-1.032, p = 0.0003; and 1.019, 95%CI 1.009-1.029, p = 0.0001, respectively). The use of neuromuscular blockers decreased monthly by 2.5% (IRR 0.975, 95%CI 0.953-0.998, p = 0.0341). The compliance with head of bed elevation was high at baseline and did not change over time. Based on data for 83153 ventilator days, VAE rate was 15.2/1000 ventilator day (95%CI 12.6-18.1) at baseline and did not change during the project (IRR 1.019, 95%CI 0.985-1.053, p = 0.2812). Based on data for 8523 patients; the mortality was 30.4% (95%CI 27.4-33.6) at baseline, and decreased monthly during the project by 1.6% (IRR 0.984, 95%CI 0.973-0.996, p = 0.0067). A national quality improvement collaborative was associated with improvements in daily care processes. These changes were associated with a reduction in mortality but not VAEs. Registration The study is registered in clinicaltrials.gov (NCT03790150).

Multidimensional machine learning models predicting outcomes after trauma

BACKGROUND

An emerging body of literature supports the role of individualized prognostic tools to guide the management of patients after trauma. The aim of this study was to develop advanced modeling tools from multidimensional data sources, including immunological analytes and clinical and administrative data, to predict outcomes in trauma patients.

METHODS

This was a prospective study of trauma patients at Level 1 centers from 2015 to 2019. Clinical, flow cytometry, and serum cytokine data were collected within 48 hours of admission. Sparse logistic regression models were developed, jointly selecting predictors and estimating the risk of ventilator-associated pneumonia, acute kidney injury, complicated disposition (death, rehabilitation, or nursing facility), and return to the operating room. Model parameters (regularization controlling model sparsity) and performance estimation were obtained via nested leave-one-out cross-validation.

RESULTS

A total of 179 patients were included. The incidences of ventilator-associated pneumonia, acute kidney injury, complicated disposition, and return to the operating room were 17.7%, 28.8%, 22.5%, and 12.3%, respectively. Regarding extensive resource use, 30.7% of patients had prolonged intensive care unit stay, 73.2% had prolonged length of stay, and 23.5% had need for prolonged ventilatory support. The models were developed and cross-validated for ventilator-associated pneumonia, acute kidney injury, complicated dispositions, and return to the operating room, yielding predictive areas under the curve from 0.70 to 0.91. Each model derived its optimal predictive value by combining clinical, administrative, and immunological analyte data.

CONCLUSION

Clinical, immunological, and administrative data can be combined to predict post-traumatic outcomes and resource use. Multidimensional machine learning modeling can identify trauma patients with complicated clinical trajectories and high resource needs.

A Method to Explore Variations of Ventilator-Associated Event Surveillance Definitions in Large Critical Care Databases in the United States

The Centers for Disease Control has well-established surveillance programs to monitor preventable conditions in patients supported by mechanical ventilation (MV). The aim of the study was to develop a data-driven methodology to examine variations in the first tier of the ventilator-associated event surveillance definition, described as a ventilator-associated condition (VAC). Further, an interactive tool was designed to illustrate the effect of changes to the VAC surveillance definition, by applying different ventilator settings, time-intervals, demographics, and selected clinical criteria.

DESIGN

Retrospective, multicenter, cross-sectional analysis.

SETTING

Three hundred forty critical care units across 209 hospitals, comprising 261,910 patients in both the electronic Intensive Care Unit Clinical Research Database and Medical Information Mart for Intensive Care III databases.

PATIENTS

A total of 14,517 patients undergoing MV for 4 or more days.

MEASUREMENTS AND MAIN RESULTS

We designed a statistical analysis framework, complemented by a custom interactive data visualization tool to depict how changes to the VAC surveillance definition alter its prognostic performance, comparing patients with and without VAC. This methodology and tool enable comparison of three clinical outcomes (hospital mortality, hospital length-of-stay, and ICU length-of-stay) and provide the option to stratify patients by six criteria in two categories: patient population (dataset and ICU type) and clinical features (minimum Fio₂, minimum positive end-expiratory pressure, early/late VAC, and worst first-day respiratory Sequential Organ Failure Assessment score). Patient population outcomes were depicted by heatmaps with mortality odds ratios. In parallel, outcomes from ventilation setting variations and clinical features were depicted with Kaplan-Meier survival curves.

CONCLUSIONS

We developed a method to examine VAC using information extracted from large electronic health record databases. Building upon this framework, we developed an interactive tool to visualize and quantify the implications of variations in the VAC surveillance definition in different populations, across time and critical care settings. Data for patients with and without VAC was used to illustrate the effect of the application of this method and visualization tool.

Ventilator-associated Events Surveillance in a Trauma Intensive Care Unit: A Prospective Study of Incidence, Predictive Values, Sensitivity, Specificity, Accuracy, and Concordance with Ventilator-associated Pneumonia

Introduction

The Centres for Disease Control and Prevention (CDC) introduced a new definition of ventilator-associated events (VAEs) in 2013 in place of longstanding ventilator-associated pneumonia (VAP) definition. Three entities under VAE, ventilator-associated condition (VAC), infection-related ventilator-associated complication (IVAC), and possible ventilator-associated pneumonia (PVAP), were introduced.

Objectives

To assess the incidence of all VAEs in a tertiary care trauma ICU and to find the predictive value of VAE and sensitivity of VAE definitions for VAP.

Design

Cohort prospective study at trauma intensive care unit (ICU) of PGIMER, Chandigarh, from July 2018 till June 2019.

Materials and methods

Patients admitted in trauma ICU were checked for VAP and VAE criteria defined by CDC.

Results

Four hundred and sixty five patients were observed. Around 378 patients were included in the study with 4046 patient days and 3031 mechanical ventilation (MV) days. Incidence rate of PVAP, IVAC, VAC, and VAP was 2.97, 6.60, 10.23, and 9.24 per 1000 ventilator days, respectively. Sensitivity, specificity, positive predictive value, and negative predictive value (NPV) of diagnosing VAP were 0.61, 0.97, 0.68, and 0.97 for VAC; 0.80, 0.97, 0.57, and 0.99 for IVAC; and 0.78, 0.94, 0.25, and 0.9 for PVAP, respectively. Kendall's W test showed that there was very poor concordance between VAP and VAE.

How to cite this article

Kaur K, Jain K, Biswal M, Dayal SK. Ventilator-associated Events Surveillance in a Trauma Intensive Care Unit: A Prospective Study of Incidence, Predictive Values, Sensitivity, Specificity, Accuracy, and Concordance with Ventilator-associated Pneumonia. Indian J Crit Care Med 2022;26(5):584–590.

Respiratory events after intensive care unit discharge in trauma patients: Epidemiology, outcomes, and risk factors

BACKGROUND

Respiratory complications are associated with significant morbidity and mortality in trauma patients. The care transition from the intensive care unit (ICU) to the acute care ward is a vulnerable time for injured patients. There is a lack of knowledge about the epidemiology of respiratory events and their outcomes during this transition.

METHODS

Retrospective cohort study in a single Level I trauma center of injured patients 18 years and older initially admitted to the ICU from 2015 to 2019 who survived initial transfer to the acute care ward. The primary outcome was occurrence of a respiratory event, defined as escalation in oxygen therapy beyond nasal cannula or facemask for three or more consecutive hours. Secondary outcomes included unplanned intubation for a primary pulmonary cause, adjudicated via manual chart review, as well as in-hospital mortality and length of stay. Multivariable logistic regression was used to examine patient characteristics associated with posttransfer respiratory events.

RESULTS

There were 6,561 patients that met the inclusion criteria with a mean age of 52.3 years and median Injury Severity Score of 18 (interquartile range, 13-26). Two hundred and sixty-two patients (4.0%) experienced a respiratory event. Respiratory events occurred early after transfer (median, 2 days, interquartile range, 1-5 days), and were associated with high mortality (16% vs. 1.8%, p < 0.001), and ICU readmission rates (52.6% vs. 4.7%, p < 0.001). Increasing age, male sex, severe chest injury, and comorbidities, including preexisting alcohol use disorder, congestive heart failure, and chronic obstructive pulmonary disease, were associated with increased odds of a respiratory event. Fifty-eight patients experienced an unplanned intubation for a primary pulmonary cause, which was associated with an in-hospital mortality of 39.7%.

CONCLUSION

Respiratory events after transfer to the acute care ward occur close to the time of transfer and are associated with high mortality. Interventions targeted at this critical time are warranted to improve patient outcomes.

LEVEL OF EVIDENCE

Prognostic and Epidemiological study, level III.

Ventilator-Associated Events: Epidemiology, Risk Factors, and Prevention

The Centers for Disease Control and Prevention shifted the focus of safety surveillance in mechanically ventilated patients from ventilator-associated pneumonia to ventilator-associated events in 2013 to increase the objectivity and reproducibility of surveillance and to encourage quality improvement programs to focus on preventing a broader array of complications. Ventilator-associated events are associated with a doubling of the risk of dying. Prospective studies have found that minimizing sedation, increasing spontaneous awakening and breathing trials, and conservative fluid management can decrease event rates and the duration of ventilation. Multifaceted interventions to enhance these practices can decrease ventilator-associated event rates.

Tertiary peritonitis: considerations for complex team-based care

Peritonitis, as a major consequence of hollow visceral perforation, anastomotic disruption, ischemic necrosis, or other injuries of the gastrointestinal tract, often drives acute care in the emergency department, operating room, and the ICU. Chronic critical illness (CCI) represents a devastating challenge in modern surgical critical care where successful interventions have fostered a growing cohort of patients with prolonged dependence on mechanical ventilation and other organ supportive therapies who would previously have succumbed much earlier in the acute phase of critical illness. An important subset of CCI patients are those who have survived an emergency abdominal operation, but who subsequently require prolonged open abdomen management complicated by persistent peritoneal space infection or colonization, fistula formation, and gastrointestinal (GI) tract dysfunction; these patients are described as having tertiary peritonitis (TP).The organ dysfunction cascade in TP terminates in death in between 30 and 64% of patients. This narrative review describes key—but not all—elements in a framework for the coordinate multiprofessional team-based management of a patient with tertiary peritonitis to mitigate this risk of death and promote recovery. Given the prolonged critical illness course of this unique patient population, early and recurrent Palliative Care Medicine consultation helps establish goals of care, support adjustment to changes in life circumstance, and enable patient and family centered care.

An integrative model using flow cytometry identifies nosocomial infection after trauma

BACKGROUND

Flow cytometry (FCM) is a rapid diagnostic tool for monitoring immune cell function. We sought to determine if assessment of cell phenotypes using standardized FCM could be used to identify nosocomial infection after trauma.

METHODS

Prospective study of trauma patients at a Level I center from 2014 to 2018. Clinical and FCM data were collected within 24 hours of admission. Random forest (RF) models were developed to estimate the risk of severe sepsis (SS), organ space infection (OSI), and ventilator-associated pneumonia (VAP). Variables were selected using backward elimination and models were validated with leave-one-out.

RESULTS

One hundred and thirty-eight patients were included (median age, 30 years [23-44 years]; median Injury Severity Score, 20 (14-29); 76% (105/138) Black; 60% (83/138) gunshots). The incidence of SS was 8.7% (12/138), OSI 16.7% (23/138), and VAP 18% (25/138). The final RF SS model resulted in five variables (RBCs transfused in first 24 hours; absolute counts of CD56- CD16+ lymphocytes, CD4+ T cells, and CD56 bright natural killer [NK] cells; percentage of CD16+ CD56+ NK cells) that identified SS with an AUC of 0.89, sensitivity of 0.98, and specificity of 0.78. The final RF OSI model resulted in four variables (RBC in first 24 hours, shock index, absolute CD16+ CD56+ NK cell counts, percentage of CD56 bright NK cells) that identified OSI with an AUC of 0.76, sensitivity of 0.68, and specificity of 0.82. The RF VAP model resulted in six variables (Sequential [Sepsis-related] Organ Failure Assessment score: Injury Severity Score; CD4- CD8- T cell counts; percentages of CD16- CD56- NK cells, CD16- CD56+ NK cells, and CD19+ B lymphocytes) that identified VAP with AUC of 0.86, sensitivity of 0.86, and specificity of 0.83.

CONCLUSIONS

Combined clinical and FCM data can assist with early identification of posttraumatic infections. The presence of NK cells supports the innate immune response that occurs during acute inflammation. Further research is needed to determine the functional role of these innate cell phenotypes and their value in predictive models immediately after injury.

LEVEL OF EVIDENCE

Prognostic, level III.

Subglottic suction frequency and adverse ventilator-associated events during critical illness

OBJECTIVE

Tracheal intubation and mechanical ventilation provide essential support for patients with respiratory failure, but the course of mechanical ventilation may be complicated by adverse ventilator-associated events (VAEs), which may or may not be associated with infection. We sought to understand how the frequency of subglottic suction, an indicator of the quantity of sputum produced by ventilated patients, relates to the onset of all VAEs and infection-associated VAEs.

DESIGN

We performed a case-crossover study including 87 patients with VAEs, and we evaluated 848 days in the pre-VAE period at risk for a VAE.

SETTING AND PARTICIPANTS

Critically ill patients were recruited from the medical intensive care unit of an academic medical center.

METHODS

We used the number of as-needed subglottic suctioning events performed per calendar day to quantify sputum production, and we compared the immediate pre-VAE period to the preceding period. We used CDC surveillance definitions for VAE and to categorize whether events were infection associated or not.

RESULTS

Sputum quantity measured by subglottic suction frequency is greater in the period immediately prior to VAE than in the preceding period. However, it does not discriminate well between infection-associated VAEs and VAEs without associated infection.

CONCLUSIONS

Subglottic suction frequency may serve as a valuable marker of sputum quantity, and it is associated with risk of a VAE. However, our results require validation in a broader population of mechanically ventilated patients and intensive care settings.

The epidemiology and clinical outcomes of ventilator-associated events among 20,769 mechanically ventilated patients at intensive care units: an observational study

Background

Ventilator-associated pneumonia (VAP) is the most common hospital-acquired infection (HAI) in intensive care units (ICUs). Ventilator-associated event (VAE), a more objective definition, has replaced traditional VAP surveillance and is now widely used in the USA. However, the adoption outside the USA is limited. This study aims to describe the epidemiology and clinical outcomes of VAEs in China, based on a prospectively maintained registry.

Methods

An observational study was conducted using an ICU-HAI registry in west China. Patients that were admitted to ICUs and underwent mechanical ventilation (MV) between April 1, 2015, and December 31, 2018, were included. The characteristics and outcomes were compared between patients with and without VAEs. The rates of all VAEs dependent on different ICUs were calculated, and the pathogen distribution of patients with possible VAP (PVAP) was described.

Results

A total of 20,769 ICU patients received MV, accounting for 21,723 episodes of mechanical ventilators and 112,697 ventilator-days. In all, we identified 1882 episodes of ventilator-associated condition (VAC) events (16.7 per 1000 ventilator-days), 721 episodes of infection-related ventilator-associated complications (IVAC) events (6.4 per 1000 ventilator-days), and 185 episodes of PVAP events (1.64 per 1000 ventilator-days). The rates of VAC varied across ICUs with the highest incidence in surgical ICUs (23.72 per 1000 ventilator-days). The median time from the start of ventilation to the onset of the first VAC, IVAC, and PVAP was 5 (3–8), 5 (3–9), and 6 (4–13) days, respectively. The median length of hospital stays was 28.00 (17.00–43.00), 30.00 (19.00–44.00), and 30.00 (21.00–46.00) days for the three VAE tiers, which were all longer than that of patients without VAEs (16.00 [12.00–23.00]). The hospital mortality among patients with VAEs was more than three times of those with non-VAEs.

Conclusions

VAE was common in ICU patients with ≥ 4 ventilator days. All tiers of VAEs were highly correlated with poor clinical outcomes, including longer ICU and hospital stays and increased risk of mortality. These findings highlight the importance of VAE surveillance and the development of new strategies to prevent VAEs.

Device associated infections at a trauma surgical center of India: Trend over eight years

BACKGROUND

Device-associated infections (DAIs) are an important cause of excessive stay and mortality in ICUs. Trauma patients are predisposed to acquire such infections due to various factors. The prevalence of HAIs is underreported from developing nations due to a lack of systematic surveillance. This study reports the rates and outcomes of DAIs at a dedicated Trauma Center in trauma patients and compares the rates with a previous pilot observation.

METHODS

The study reports the finding of ongoing surveillance and the use of an indigenous software at a level-1 trauma center in India. Surveillance for ventilator-associated pneumonia, central line-associated bloodstream infections, and catheter-associated urinary tract infections was done based on standard definitions. The rates of HAIs and the profile of pathogens isolated from June 2010 to December 2018 were analyzed.

RESULTS

A total of 7485 patients were included in the analysis, amounting to 68,715 patient days. The rates of VAP, CLABSI, and CA-UTI were respectively 12, 9.8 1st 8.5/1000 device days. There was a significant correlation between device days and the propensity to develop infections. Of the 1449 isolates recovered from cases of DAIs, Acinetobacter sp (28.2%) was the most common isolate, followed by Candida sp. A high rate of multi-resistance was observed.

CONCLUSION

Automated surveillance was easy and useful for data entry and analysis. Surveillance data should be used for implementing preventive programs.

Making Ventilator Associated Pneumonia Rate a Meaningful Quality Marker

INTRODUCTION

Ventilator associated pneumonia (VAP) rate has been tracked as a comparable quality measure but there is significant variation between types of ICUs. We sought to understand variability and improve its utility as a marker of quality.

METHODS

The National Trauma Database was surveyed to identify risk factors for VAP. Logistic regression, χ², Student's T-test or Mann-Whitney U test were used.

RESULTS

Risk factors associated with developing VAP were: injury severity score (ISS) (OR 1.03, 95% CI 1.03 -1.04), prehospital assisted respiration (PHAR) (OR 1.10, 1.03 -1.17), thoracic injuries (OR 2.28, 1.69-3.08), diabetes (OR 1.32, 1.20 -1.46), male gender (OR 1.38, 1.28 -1.60), care at a teaching hospital (OR 1.40, 1.29 -1.47) and unplanned intubation (OR 2.76, 2.52-3.03).

DISCUSSION

ISS, PHAR, diabetes, male gender, care at a teaching hospital and unplanned intubation are risk factors for the development of VAP. These factors should be accounted for in order to make VAP an effective quality marker.

Minor change in initial PEEP setting decreases rates of ventilator-associated events in mechanically ventilated trauma patients

Background

Surveillance of ventilator-associated events (VAEs) as defined by the National Healthcare Safety Network (NHSN) is performed at many US trauma centers and considered a measure of healthcare quality. The surveillance algorithm relies in part on increases in positive end-expiratory pressure (PEEP) to identify VAEs. The purpose of this cohort study was to evaluate the effect of initiating mechanically ventilated trauma patients at marginally higher PEEP on incidence of VAEs.

Methods

Analysis of level-1 trauma center patients mechanically ventilated 2+ days from 2017 to 2018 was performed after an institutional ventilation protocol increased initial PEEP setting from 5 (2017) to 6 (2018)cm H₂O. Incidence of VAEs per 1000 vent days was compared between PEEP groups. Logistic regression modelling was performed to evaluate the impact of the PEEP setting change adjusted to account for age, ventilator days, injury mechanism and injury severity.

Results

519 patients met study criteria (274 PEEP 5 and 245 PEEP 6). Rates of VAEs were significantly reduced among patients with initial PEEP 5 versus 6 (14.61 per 1000 vent days vs. 7.13 per 1000 vent days; p=0.039). Logistic regression demonstrated that initial PEEP 6 was associated with 62% reduction in VAEs.

Conclusions

Our data suggest that an incrementally increased baseline PEEP setting was associated with a significantly decreased incidence of VAEs among trauma patients. This minor change in practice may have a major impact on a trauma center’s quality metrics.

Level of evidence

IV.

Patient-ventilator asynchrony in conventional ventilation modes during short-term mechanical ventilation after cardiac surgery: randomized clinical trial

INTRODUCTION AND AIM

Studies regarding asynchrony in patients in the cardiac postoperative period are still only a few. The main objective of our study was to compare asynchronies incidence and its index (AI) in 3 different modes of ventilation (volume-controlled ventilation [VCV], pressure-controlled ventilation [PCV] and pressure-support ventilation [PSV]) after ICU admission for postoperative care.

METHODS

A prospective parallel randomised trialin the setting of a non-profitable hospital in Brazil. The participants were patients scheduled for cardiac surgery. Patients were randomly allocated to VCV or PCV modes of ventilation and later both groups were transitioned to PSV mode.

RESULTS

All data were recorded for 5 minutes in each of the three different phases: T1) in assisted breath, T2) initial spontaneous breath and T3) final spontaneous breath, a marking point prior to extubation. Asynchronies were detected and counted by visual inspection method by two independent investigators. Reliability, inter-rater agreement of asynchronies, asynchronies incidence, total and specific asynchrony indexes (AIt and AIspecific) and odds of AI ≥10% weighted by total asynchrony were analysed. A total of 17 patients randomly allocated to the VCV (n=9) or PCV (n=8) group completed the study. High inter-rated agreement for AIt (ICC 0.978; IC95%, 0,963-0.987) and good reliability (r=0.945; p<0.001) were found. Eighty-two % of patients presented asynchronies, although only 7% of their total breathing cycles were asynchronous. Early cycling and double triggering had the highest rates of asynchrony with no difference between groups. The highest odds of AI ≥10% were observed in VCV regardless the phase: OR 2.79 (1.36-5.73) in T1 vs T2, p=0.005; OR 2.61 (1.27-5.37) in T1 vs T3, p=0.009 and OR 4.99 (2.37-10.37) in T2 vs T3, p<0.001.

CONCLUSIONS

There was a high incidence of breathing asynchrony in postoperative cardiac patients, especially when initially ventilated in VCV. VCV group had a higher chance of AI ≥10% and this chance remained high in the following PSV phases.

Prevalence, Clinical Characteristics, and Outcomes Related to Ventilator-Associated Events in Neurocritically Ill Patients

Background

The prevalence, characteristics, and outcomes related to the ventilator-associated event(s) (VAE) in neurocritically ill patients are unknown and examined in this study.

Methods

A retrospective study was performed on neurocritically ill patients at a 413-bed level 1 trauma and stroke center who received three or more days of mechanical ventilation to describe rates of VAE, describe characteristics of patients with VAE, and examine the association of VAE on ventilator days, mortality, length of stay, and discharge to home.

Results

Over a 5-year period from 2014 through 2018, 855 neurocritically ill patients requiring mechanical ventilation were identified. A total of 147 VAEs occurred in 130 (15.2%) patients with an overall VAE rate of 13 per 1000 ventilator days and occurred across age, sex, BMI, and admission Glasgow Coma Scores. The average time from the start of ventilation to a VAE was 5 (range 3–48) days after initiation of mechanical ventilation. Using Centers for Disease Control and Prevention definitions, VAEs met criteria for a ventilator-associated condition in 58% of events (n = 85), infection-related VAE in 22% of events (n = 33), and possible ventilator-associated pneumonia in 20% of events (n = 29). A most common trigger for VAE was an increase in positive end-expiratory pressure (84%). Presence of a VAE was associated with an increase in duration of mechanical ventilation (17.4[IQR 20.5] vs. 7.9[8.9] days, p < 0.001, 95% CI 7.86–13.92), intensive care unit (ICU) length of stay (20.2[1.1] vs. 12.5[0.4] days, p < 0.001 95% CI 5.3–10.02), but not associated with in-patient mortality (34.1 vs. 31.3%. 95% CI 0.76–1.69) or discharge to home (12.7% vs. 16.3%, 95% 0.47–1.29).

Conclusions

VAE are prevalent in the neurocritically ill. They result in an increased duration of mechanical ventilation and ICU length of stay, but may not be associated with in-hospital mortality or discharge to home.

Electronic supplementary material

The online version of this article (10.1007/s12028-019-00910-5) contains supplementary material, which is available to authorized users.