Predicting respiratory decompensation in mechanically ventilated adult ICU patients.

Introduction: Mechanical ventilation is a life-saving treatment in the Intensive Care Unit (ICU), but often causes patients to be at risk of further respiratory complication. We created a statistical model utilizing electronic health record and physiologic vitals data to predict the Center for Disease Control and Prevention (CDC) defined Ventilator Associated Complications (VACs). Further, we evaluated the effect of data temporal resolution and feature generation method choice on the accuracy of such a constructed model. Methods: We constructed a random forest model to predict occurrence of VACs using health records and chart events from adult patients in the Medical Information Mart for Intensive Care III (MIMIC-III) database. We trained the machine learning models on two patient populations of 1921 and 464 based on low and high frequency data availability. Model features were generated using both basic statistical summaries and tsfresh, a python library that generates a large number of derived time-series features. Classification to determine whether a patient will experience VAC one hour after 35 h of ventilation was performed using a random forest classifier. Two different sample spaces conditioned on five varying feature extraction techniques were evaluated to identify the most optimal selection of features resulting in the best VAC discrimination. Each dataset was assessed using K-folds cross-validation (k = 10), giving average area under the receiver operating characteristic curves (AUROCs) and accuracies. Results: After feature selection, hyperparameter tuning, and feature extraction, the best performing model used automatically generated features on high frequency data and achieved an average AUROC of 0.83 ± 0.11 and an average accuracy of 0.69 ± 0.10. Discussion: Results show the potential viability of predicting VACs using machine learning, and indicate that higher-resolution data and the larger feature set generated by tsfresh yield better AUROCs compared to lower-resolution data and manual statistical features.

Surveillance of device associated infections in intensive care units at a Saudi Arabian Hospital, 2017-2020.

BACKGROUND: Device-associated infections (DAIs) are important components of healthcare associated infection and are associated with increased morbidity and mortality. This study describes DAIs across different intensive care units (ICUs) in a hospital in Saudi Arabia. METHODS: The study was conducted between 2017 and 2020 and followed the definitions of National Healthcare Safety Network (NHSN) for DAIs. The calculated the rates of ventilator-associated events (VAE), catheter-associated urinary tract infections (CAUTI) and central line-associated blood stream infections (CLABSI) followed NHSN definitions. RESULTS: During the study period, there were 82 DAIs in adult ICUs and of these 16 (19.5%) were CLABSI, 26 (31.7%) were CAUTI and 40 (48.7%) were VAE. The overall rates for adult ICUs were 1.6, 1.9, 3.8 per 1000 device-days for CAUTI, CLABSI and VAE, respectively. The device-utilization ratio was 0.5, 0.6, and 0.48 for urinary catheters, central lines, and ventilators, respectively. VAE rates for medical and surgical ICU were about 2.8 times the rate in the coronary care unit and the rates were high in 2020 corresponding with the COVID-19 pandemic. Of the adult ICUS, medical ICU had a CLABSI rate of 2.13/1000 device-days and was about double the rate in surgical and cardiac ICU. For CAUTI, the rates per 1000 device-days were 2.19, 1.73, and 1.65 for medical, surgical, and coronary ICUs, respectively. The rate of CLABSI per 1000 device-days for pediatric and neonatal ICUs were 3.38 and 2.28, respectively. CONCLUSIONS: CAUTI was the most common infections among adult ICUs and medical ICU had higher rates than other adult ICUs. VAE rate was higher in the first year of the COVID-19 pandemic, indicating increased device-use, change in patients characteristics as well as possible change in practices across the ICUs.

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.

ESBL production and carbapenem resistance increased the secondary bloodstream infection rates in intensive care units in Turkey, 2014-2019.

Aim: Secondary bloodstream infections (SBSIs) are caused by another infection and differ from primary bloodstream infections (PBSIs) in terms of prevention and treatment strategies. The aim of this study was to determine the risk factors for bloodstream infections which were secondary to the most common healthcare-associated infections caused by the most common microorganisms in intensive care units (ICUs) and to examine whether extended-spectrum beta lactamase (ESBL) production and carbapenem resistance is related to the higher risk or not. Methods: The study population consisted of patients in ICUs with ventilator-associated pneumonia (VAP), ventilator-associated event (VAE) or catheter-associated urinary tract infection (CAUTI) caused by E. coli, K. pneumoniae, P. aeruginosa or A. baumannii between 2014 and 2019. The data were obtained through the National Healthcare-associated Infections Surveillance Network. Multivariate logistic regression analysis was performed separately for VAP/VAE and CAUTI to determine the risk factors for the development of SBSI. Results: Microorganism, ICU type, bed capasity and carbapenem resistance were found to be risk factors for SBSI for both types of infection. For VAPs/VAEs, female gender and hospital type were also identified as risk factors. The highest risk was in K.pneumoniae and in emergency ICUs. Among the hospitals, the highest risk in VAPs/VAEs was found in government education and research hospitals. ESBL production for K. pneumoniae and E. coli increased the risk in patients with VAP/VAE; however, it did not increase in patients with CAUTI. Discussion: By using the risk factors, it may be possible to recognize SBSIs earlier, especially in patients with CAUTIs or VAPs/VAEs caused by carbapenem-resistant or ESBL-producing K. pneumoniae.

Ventilator-associated events in children: A multicentre prospective cohort study.

BACKGROUND: The Centres for Disease Control and Prevention (CDC) broadened the focus of surveillance from ventilator-associated pneumonia to ventilator-associated event (VAE) for quality purposes. No paediatric definition of VAE (PaedVAE) has been accurately validated. We aimed to analyse the incidence and impact on patient outcomes resulting from the application of the adult and two paediatric VAE (PaedVAE) criteria. SECONDARY OBJECTIVE: to evaluate VAE/PaedVAE as factors associated with increased duration of mechanical ventilation (MV) and Paediatric Intensive Care Unit (PICU) stay. METHODS: Multicentre observational prospective cohort study in 15 PICUs in Spain. VAEs were assessed using the 2013/2015 CDC classification. PaedVAE were assessed using the CDC definition based on mean airway pressure (MAP-PaedVAE) versus a paediatric definition based on positive end-expiratory pressure (PEEP-PaedVAE). Children who underwent MV ≥ 48 h were included. RESULTS: A total of 3626 ventilator-days in 391 patients were analysed. The incidence of VAE, MAP-PaedVAE and PEEP-PaedVAE was 8.55, 5.24 and 20.96 per 1000 ventilator-days, respectively. The median time [IQR] for VAE, MAP-PaedVAE and PEEP-PaedVAE development from the MV onset was 4 [3-12.5], 4 [3-14], and 5 [3-7.75] days, respectively. Among survivors, all three were associated with increased MV duration (> 7 days) and PICU stay (> 10 days) at univariate analysis. Multivariate analysis showed that PEEP-PaedVAE was the only definition independently associated with MV above 7 days [OR = 4.86, 95% CI (2.41-10.11)] and PICU stay [OR = 3.49, 95% CI (1.68-7.80)] above ten days, respectively. CONCLUSIONS: A VAE definition based on slight PEEP increases should be preferred for VAE surveillance in children.

Incidence, Characteristics, and Outcomes of Ventilator-associated Events during the COVID-19 Pandemic.

Rationale: Ventilator-associated event (VAE) surveillance provides an objective means to measure and compare complications that develop during mechanical ventilation by identifying patients with sustained increases in ventilator settings after a period of stable or decreasing ventilator settings. The impact of the coronavirus disease (COVID-19) pandemic on VAE rates and characteristics is unknown. Objectives: To compare the incidence, causes, and outcomes of VAE during the COVID-19 pandemic year versus prepandemic years and among ventilated patients with and without COVID-19. Methods: In this retrospective cohort study of mechanically ventilated adults at four academic and community hospitals in Massachusetts, we compared VAE incidence rates between March 1 and August 31 for each year from 2017 to 2020 (corresponding to the time frame of the pandemic first wave in 2020) and among COVID-19-positive and COVID-19-negative patients in 2020. The medical records of 200 randomly selected patients with VAEs in 2020 (100 with COVID-19 and 100 without COVID-19) were analyzed to compare conditions precipitating VAEs in patients with versus without COVID-19. Results: VAEs per 100 episodes of mechanical ventilation were more common in 2020 than in prior years (11.2 vs. 6.7; P < 0.01) but the rate of VAEs per 1,000 ventilator-days was similar (14.2 vs. 12.7; P = 0.08). VAEs were more frequent in COVID-19-positive patients than in COVID-19-negative patients in 2020 (29.0 vs. 7.1 per 100 ventilator episodes [P < 0.01] and 17.2 vs. 12.2 per 1,000 ventilator-days [P < 0.01]). Compared with patients without COVID-19 with VAEs, patients with COVID-19 and VAEs had similar rates of infection-related ventilator-associated complications, longer median durations of mechanical ventilation (22 vs. 14 d; P < 0.01), and similar in-hospital mortality (30% vs. 38%; P = 0.15). Progressive acute respiratory distress syndrome (ARDS) accounted for 53% of VAEs in patients with COVID-19, whereas it accounted for 14% of VAEs among patients without COVID-19. Conclusions: VAE rates per 100 episodes of mechanical ventilation and per 1,000 ventilator-days were higher among COVID-19-positive patients than among COVID-19-negative patients. Over 50% of VAEs in patients with COVID-19 were caused by progressive ARDS, whereas less than 15% of VAEs in patients without COVID-19 were caused by progressive ARDS. These findings provide insight into the natural history of COVID-19 in ventilated patients and may inform targeted strategies to mitigate complications in this population.

Does a Starting Positive End-Expiratory Pressure of 8 cmH2O Decrease the Probability of a Ventilator-Associated Event?

Introduction: Ventilator-associated events (VAEs) are objective measures as defined by the Centers for Disease Control and Prevention (CDC). To reduce VAEs, some hospitals have started patients on higher baseline positive end-expiratory pressure (PEEP) to avoid triggering VAE criteria due to respiratory fluctuations. Methods: At our institution, VAEs were gathered from January 2014 through December 2019. Using the CDC-defined classifications, VAEs were split into two groups to separate patients with hypoxemia only (VAC) and those with hypoxemia and evidence of inflammation or infection (IVAC-plus). We used the geometric distribution to calculate the daily event probability before and after the protocol implementation. A probability threshold was used to determine if the days between events was exceeded during the post-protocol period. Results: A total of 306 VAEs were collected over the study period. Of those, 155 were VACs and 107 were IVAC-plus events during the pre-protocol period. After implementing the protocol, 24 VACs and 20 IVAC-plus events were reported. There was a non-significant decrease in daily event probabilities in both the VAC and IVAC-plus groups (0.083 vs. 0.068 and 0.057 vs. 0.039, respectively). Conclusion: We concluded a starting PEEP of 8 cmH2O is unlikely to be an effective intervention at reducing the probability of a VAE. Until specific guidelines by the CDC are established, hospitals should consider alternative methods to reduce VAEs.

Automated Near Real-Time Ventilator Data Feedback Reduces Incidence of Ventilator-Associated Events: A Retrospective Observational Study.

OBJECTIVES: Critical care teams are encouraged to follow best practice protocols to help wean mechanically ventilated patients from the ventilator to reduce ventilator-associated events including ventilator-associated conditions, probable ventilator-associated pneumonias, and infection-related ventilator-associated conditions. Providers monitor for alerts suggestive of possible ventilator-associated events and advise when patients should undergo spontaneous breathing trials. Compliance with protocols in most units is suboptimal. DESIGN: Retrospective review of clinical data over 24 months. SETTING: St. Joseph Mercy Hospital Candler Hospital Medical-Surgical ICU. PATIENTS: All mechanically ventilated patients. INTERVENTIONS: The Respiratory Knowledge Portal was implemented in our ICU. For 13 months, Respiratory Knowledge Portal data were ported to ICU workstations (control). For the following 11 months, Respiratory Knowledge Portal data were also presented on tablet computers (intervention) for use during multidisciplinary rounds. We performed a retrospective review of Respiratory Knowledge Portal data from before and after the implementation of the tablet computers. MEASUREMENTS AND MAIN RESULTS: Data were collected from 337 patients (187 control group, 150 intervention group). A decrease in the occurrence of ventilator-associated events was observed during the intervention group compared with the control group. Only 2.0% of patients in the intervention group experienced any category of ventilator-associated event, while 11.2% of patients in the control group experienced one event (p = 0.003). Intervention patients experienced less ventilator-associated conditions (p = 0.002), infection-related ventilator-associated conditions (p = 0.026), and probable ventilator-associated pneumonias (p = 0.036) than control patients. Twenty-one of the 24 patients with any ventilator-associated events were in the control group. There was no significant difference between the days spent on ventilation nor hospital length of stay in the control compared with intervention group patients. CONCLUSIONS: Fewer ventilator-associated events, ventilator-associated conditions, infection-related ventilator-associated conditions, and probable ventilator-associated pneumonias were seen during the period when Respiratory Knowledge Portal monitoring data was presented on tablet computers. There was no difference in time on ventilator nor overall length of stay.

Short-Acting Sedative-Analgesic Drugs Protect Against Development of Ventilator-Associated Events in Children: Secondary Analysis of the EUVAE Study.

BACKGROUND: The U.S. Centers for Disease Control and Prevention proposed a shift in its surveillance paradigm from ventilator-associated pneumonia to ventilator-associated events (VAE) to broaden the focus of prevention and achieve a greater impact on outcomes. The main objective of the present study was to identify factors associated with pediatric VAEs in children undergoing mechanical ventilation ≥ 48 h. METHODS: This was a secondary analysis of a pediatric cohort of a multicenter prospective study. Children who underwent mechanical ventilation ≥ 48 h were included. Exclusion criteria were previous ventilation, extracorporeal life support, and right-to-left shunt or pulmonary hypertension. In the subjects with multiple episodes of mechanical ventilation, only the first episode was considered. Remifentanil and propofol are classified as short-acting sedative and analgesic agents. Pediatric VAE is defined as an "increase in PEEP ≥ 2 cm of H2O, an increase in [Formula: see text] of 0.20, or an increase in [Formula: see text] of 0.15 plus an increase in PEEP ≥ 1 cm of H2O sustained for ≥1 d. Associations with pediatric VAE were estimated through multivariate Cox proportional hazards analysis. Hazard ratios and 95% CI were computed. RESULTS: In a cohort of 90 children, 24 pediatric VAEs were documented in 906 ventilator-days. Pediatric VAEs developed after a median of 4.5 (interquartile range, 4-7.25) d. Surgical admissions, spontaneous breathing trials, early mobility, vasopressors, red blood cell units transfusion, type of sedation (continuous vs intermittent), benzodiazepine use for >3 d, and pharmacologic paralysis were not associated with pediatric VAE, whereas the use of continuous short-acting sedative-analgesic agents was identified as a strong protective factor against pediatric VAE (hazard ratio 0.06 [95% CI 0.007-0.5]). CONCLUSIONS: Treatment with short-acting sedative-analgesic agents should be preferred for sedation of mechanically ventilated children in intensive care.

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.

Airway Management and Ventilator-Associated Events.

Airway management techniques are aimed at reducing complications associated with artificial airways and mechanical ventilation, such as retained secretions. The impact of airway management techniques on ventilator-associated events (VAEs) varies considerably by modality. Closed-suction techniques are generally recommended but have limited, if any, impact on VAEs. Normal saline instillation during suctioning is not recommended. Devices designed specifically to remove biofilm from the inside of endotracheal tubes appear to be safe, but their role in VAE prevention is uncertain. Subglottic secretion clearance by artificial cough maneuvers is promising, but more research is needed to assess its clinical feasibility. Continuous cuff-pressure management appears to be effective in reducing microaspiration of subglottic secretions.

National Approach to Standardize and Improve Mechanical Ventilation.

NASAM (National Approach to Standardize and Improve Mechanical Ventilation) is a national collaborative quality improvement project in Saudi Arabia. It aims to improve the care of mechanically ventilated patients by implementing evidence-based practices with the goal of reducing the rate of ventilator-associated events and therefore reducing mortality, mechanical ventilation duration and intensive care unit (ICU) length of stay. The project plans to extend the implementation to a total of 100 ICUs in collaboration with multiple health systems across the country. As of March 22, 2019, a total of 78 ICUs have registered from 6 different health sectors, 48 hospitals, and 27 cities. The leadership support in all health sectors for NASAM speaks of the commitment to improve the care of mechanically ventilated patients across the kingdom.

Ventilator-associated events in children: A review of literature.

BACKGROUND: The complexity and variation in ventilator associated pneumonia (VAP) definitions in paediatrics may pose threats to the reliable identification of VAP. The revision of the surveillance definition to ventilator-associated event (VAE) has been mandated in adult populations, to overcome these issues. However, the evidence for application of the definition is unknown in children. OBJECTIVES: To review the evidence on the application of the new VAE surveillance definition in paediatric population and examine the potential challenges in clinical practice. REVIEW METHODS: A systematic approach was used to locate and synthesise the relevant paediatric literature. Studies were appraised according to epidemiological appraisal instrument (EAI) and the grades of evidence in the National Health Medical Research Council (NHMRC) guidelines. RESULTS: Seven studies met the inclusion criteria. Quality of study methods was above 50% on the EAI. The overall grade of evidence was assessed as C (satisfactory). The incidence of VAE in children ranged from 1.1 to 20.9 per 1000 ventilator days as a result of variations in surveillance criteria across included studies. There is little agreement between the new VAE and PNU/VAP surveillance definition in the identification of VAP. Challenges in the application of VAE surveillance were related to; the difference in modes of ventilation used in children versus adults, inconclusive criteria tailored to paediatric samples and a lack of data that support for automatic data extraction applied in paediatric studies. CONCLUSION: This review demonstrated promising evidence using the new VAE surveillance definition to define the VAE in children, but the level of the evidence is low. Before the possibility of real implementation in clinical settings, challenges related to VAE paediatric specific criteria' and the value of automated data collection need to be considered.

Hospital-Acquired Infections in Critically Ill Patients With Cancer.

Hospital-acquired infections are a common and costly problem facing critically ill patients in the intensive care unit (ICU). Critically ill patients with cancer are a particularly vulnerable subpopulation who possesses additional, nonmodifiable risk factors for developing these infections and, in many cases, are at increased risk of death as a result. This review will describe the most common nosocomial infections patients with cancer acquire while in the ICU: ventilator-associated events, central line-associated bloodstream infection, catheter-associated urinary tract infections, and Clostridium difficile infection.

Research progress in ventilator-associated events and prevention / 中国感染控制杂志

Healthcare-associated pneumonia (HAP) is a key factor affecting the clinical prognosis of critically ill patients undergoing long-term mechanical ventilation.In the past, ventilator-associated pneumonia (VAP) was an important mean of monitoring complications of ventilator-associated infection, but it is highly controversial because of its high subjectivity, low specificity and poor sensitivity.Therefore, the definition of ventilator-associated event (VAE) was proposed by Centers for Disease Control and Prevention of USA in 2013, the monitoring definition adopts objective and quantitative criteria, which can better predict the clinical outcomes of patients.This paper summarizes the research progress of VAE in recent years, and provides some new ideas for better prevention and control of VAE.

Limiting ventilator-associated complications in ICU intubated subjects: strategies to prevent ventilator-associated events and improve outcomes.

Introduction: Intubation is required to maintain the airways in comatose patients and enhance oxygenation in hypoxemic or ventilation in hypercapnic subjects. Recently, the Centers of Disease Control (CDC) created new surveillance definitions designed to identify complications associated with poor outcomes. Areas covered: The new framework proposed by CDC, Ventilator-Associated Events (VAE), has a range of definitions encompassing Ventilator-Associated Conditions (VAC), Infection-related Ventilator-Associated Complications (IVAC), or Possible Ventilator-Associated Pneumonia - suggesting replacing the traditional definitions of Ventilator-Associated Tracheobronchitis (VAT) and Ventilator-Associated Pneumonia (VAP). They focused more on oxygenation variations than on Chest-X rays or inflammatory biomarkers. This article will review the spectrum of infectious (VAP & VAT) complications, as well as the main non-infectious complications, namely pulmonary edema, acute respiratory distress syndrome (ARDS) and atelectasis. Strategies to limit these complications and improve outcomes will be presented. Expert commentary: Improving outcomes should be the objective of implementing bundles of prevention, based on risk factors amenable of intervention. Promotion of measures that reduce the exposition or duration of intubation should be a priority.

Frequent Versus Infrequent Monitoring of Endotracheal Tube Cuff Pressures.

BACKGROUND: Currently there is no accepted standard of practice for the optimal frequency of endotracheal tube cuff pressure monitoring in mechanically ventilated patients. Therefore, we conducted a study to compare infrequent endotracheal tube cuff pressure monitoring (immediately after intubation and when clinically indicated for an observed air leak or due to tube migration) with frequent endotracheal tube cuff pressure monitoring (immediately after intubation, every 8 h, and when clinically indicated). METHODS: We performed a prospective clinical trial with subjects assigned to study groups based on room assignment. The primary outcome was the occurrence of a ventilator-associated event (VAE) and was adjudicated by individuals blinded to the conduct of this study. RESULTS: We enrolled 305 subjects, with 166 (54.4%) assigned to frequent monitoring and 139 (45.6%) assigned to infrequent monitoring. The total number of endotracheal tube cuff pressure monitoring events for both groups was 1,531 versus 336, respectively. The occurrence of VAEs was infrequent and similar for both groups (3.6% vs 5.8%, P = .37). Witnessed aspiration events (0.6% vs 0%, P = .36), ventilator-associated pneumonia (0% vs 0.7%, P = .27), 30-d mortality (31.3% vs 30.2%, P = .83), and hospital length of stay (10 d [6 d, 21 d] vs 11 d [6 d, 21 d], P = .34) were also similar for both study groups. The 30-d hospital readmission rate was statistically lower for the group that received infrequent monitoring (15.1% vs 6.5%, P = .02). CONCLUSIONS: More frequent cuff pressure monitoring was not associated with any identifiable clinical outcome benefit.

Assessing prediction accuracy for outcomes of ventilator-associated events and infections in critically ill children: a prospective cohort study.

OBJECTIVES: To assess the prediction accuracy of the 2008 US Centers for Disease Control and Prevention (CDC) definitions for ventilator-associated pneumonia (VAP)/ventilator-associated tracheobronchitis (VAT), 2013 CDC definitions for ventilator-associated events (VAE) and a new VAE algorithm in the paediatric (Ped) population, the Ped-VAE. METHODS: We performed a prospective 13-month cohort study at a multidisciplinary paediatric intensive care unit (PICU). Primary endpoints were duration of ventilation episode, PICU or hospitalization length of stay from episode and episode mortality. Episodes without VAE (or VAP/VAT) served as comparison groups. RESULTS: One hundred eight episodes of ventilation (99 children) with 2554 ventilator-days were assessed. In episodes not meeting 2008 CDC definitions, a median of 6 ventilator-days (PICU stay 11 days) was documented (with eight deaths), not significantly different from episodes not meeting VAE or Ped-VAE definitions. Using 2008 CDC criteria, 11 (10.2%) respiratory infections (eight tracheobronchitis) were identified, seven VAEs using 2013 CDC criteria (6.4%) and 29 (26.8%) using Ped-VAE criteria (relative risk vs. 2008 CDC criteria 2.58; 95% confidence interval 1.36-4.91). In contrast with their comparison groups, episodes meeting 2008 CDC criteria did not significantly predict outcomes, whereas VAEs (only four possible VAPs) were associated with significantly more ventilation and PICU length of stay (12-day/8-day increase) and sevenfold increase in mortality. Ped-VAE did not increase mortality, but it was associated with 4-day increase in ventilation and PICU length of stay, with ten possible VAPs, and atelectasis (9/12) as the main paediatric ventilator-associated condition. CONCLUSIONS: The 2008 CDC criteria did not predict outcomes, whereas VAE only identified very severe events. The Ped-VAE algorithm had more accuracy predicting outcomes by characterizing lower oxygenation changes and identifying hypoxaemia severity, a major driver of management.

Prospective surveillance of device-associated health care-associated infection in an intensive care unit of a tertiary care hospital in New Delhi, India.

BACKGROUND: Surveillance of health care-associated infections (HAIs) plays a key role in the hospital infection control program and reduction of HAIs. In India, most of the surveillance of HAIs is reported from private sector hospitals that do not depict the situation of government sector hospitals. Other studies do not confirm with the Centers for Disease Control and Prevention's (CDC) National Healthcare Safety Network (NHSN) surveillance criterion, or deal with ventilator-associated pneumonia (VAP) instead of ventilator-associated event (VAE). The aim of this study was to identify the incidences of 3 device-associated HAIs (DA-HAIs) (VAE, central line-associated bloodstream infection [CLABSI], and catheter-associated urinary tract infection [CAUTI]) by active surveillance using CDC's NHSN surveillance criteria and to identify the pathogens associated with these DA-HAIs. METHODS: This was a prospective surveillance study (January 2015-December 2016) conducted in an intensive care unit (ICU) of a large, tertiary care, government hospital situated in Delhi, India. Targeted surveillance was done as per the CDC's NHSN 2016 surveillance criteria. RESULTS: There were 343 patients admitted to the ICU that were included in the study. The surveillance data was reported over 3,755 patient days. A DA-HAIs attack rate of 20.1 per 100 admissions and incidence of 18.3 per 1,000 patient days was observed. The duration of use for each device for patients with DA-HAIs was significantly longer than for patients without DA-HAIs. The device utilization ratios of central line, ventilator, and urinary catheters were 0.57, 0.85, and 0.72, respectively. The crude excess length of stay for patients with DA-HAI was 13 days, and crude excess mortality rate was 11.8%. VAE, CLABSI, and CAUTI rates were 11.8, 7.4, and 9.7 per 1,000 device days, respectively. Among 69 DA-HAIs reported, pathogens could be identified for 49 DA-HAI cases. Klebsiella spp was the most common organism isolated, accounting 28.5% for all DA-HAI cases, followed by Enterococcus spp (24.4%). The most common organisms causing VAE, CAUTI, and CLABSI were Acinetobacter (6/15, 40%), Enterococcus spp (11/31, 35.4%), and Candida spp (5/19, 26.3%), respectively. Most of the gram-negative organisms were carbapenem resistant; however, none of the isolates were colistin resistant. CONCLUSIONS: To reduce the risk of infection in hospitalized patients, DA-HAI surveillance is of primary importance because it effectively describes and addresses the importance and characteristics of the threatening situation created by DA-HAIs. The present surveillance shows high rates of ICU-onset DA-HAIs and high resistance patterns of organisms causing HAIs, representing a major risk to patient safety.

The Impact of Ventilator-Associated Events in Critically Ill Subjects With Prolonged Mechanical Ventilation.

BACKGROUND: The Centers for Disease Control and Prevention recently released a surveillance definition for respiratory complications in ventilated patients, ventilator-associated events (VAEs), to replace ventilator-associated pneumonia (VAP). VAEs consist of ventilator-associated conditions (VAC), infection-related ventilator-associated complications (IVAC), and possible VAP. A duration of mechanical ventilation of at least 4 d is required to diagnose VAE. However, the observed duration of mechanical ventilation was < 4 d in many previous studies. We evaluated the impact of VAEs on clinical outcomes in critically ill subjects who required mechanical ventilation for ≥ 4 d. METHODS: This single-center retrospective cohort study was conducted in the general ICU of an academic hospital. We included 407 adult subjects who were admitted to the ICU and required mechanical ventilation for at least 4 d. VAC and IVAC were identified from the electronic medical records. VAP was defined according to the Centers for Disease Control and Prevention 2008 criteria and was identified from the surveillance data of the infection control team of our hospital. Clinical outcomes were studied in the VAC, IVAC, and VAP groups. Possible VAP was not investigated. RESULTS: Higher mortality was seen in VAC and IVAC subjects, but not in VAP subjects, compared with those without VAEs and VAP. By multivariable hazard analysis for hospital mortality, IVAC was independently associated with hospital mortality (hazard ratio 2.42, 95% CI 1.39-4.20, P = .002). VAC also tended to show a similar association with hospital mortality (hazard ratio 1.45, 95% CI 0.97-2.18, P = .07). On the other hand, VAP did not increase a hazard of hospital death (hazard ratio 1.08, 95% CI 0.44-2.66, P = .87). CONCLUSIONS: We found that a VAE was related to hospital mortality in critically ill subjects with prolonged mechanical ventilation, and that VAP was not.