Ventilator-associated events versus ventilator-associated respiratory infections-moving into a new paradigm or merging both concepts, instead?

Surveillance of ventilator associated pneumonia in a network of indian hospitals using modified definitions: a pilot study

Background

Ventilator-associated pneumonia (VAP) is a major cause of morbidity and mortality in patients receiving mechanical ventilation in India. Surveillance of VAP is essential to implement data-based preventive measures. Implementation of ventilator-associated events (VAE) criteria for surveillance has major constraints for low resource settings, which can lead to significant underreporting. Surveillance of VAP using common protocols in a large network of hospitals would give meaningful estimates of the burden of VAP in low resource settings. This study leverages a previously established healthcare-associated infections (HAI) surveillance network to develop and test a modified VAP definition adjusted for Indian settings.

Methods

In this observational pilot study, thirteen hospitals from the existing HAI surveillance network were selected for developing and testing a modified VAP definition between February 2021 and April 2023. The criteria used for diagnosing VAP were adapted from the CDC's Pediatric VAP definition and modified to cater to the needs of Indian hospitals. Designated nurses recorded each VAP event in a case report form (CRF) and also collected denominator data. The data was entered into an indigenously developed database for validation and analysis. At the time of data analysis, a questionnaire was sent to sites to get feedback on the performance of the modified VAP definitions.

Findings

Out of 133,445 patient days and 40,533 ventilator days, 261 VAP events were recorded, with an overall VAP rate of 6.4 per 1000 ventilator days and a device utilization ratio (DUR) of 0.3. A total of 344 organisms were reported from the VAP events. Of these, Acinetobacter spp (29.6%, 102) was the most frequent, followed by Klebsiella spp (26.7%, 92). Isolates of Acinetobacter spp (98%) and Enterobacterales (85.5%) showed very high resistance against Carbapenem. Colistin resistance was observed in 6% of Enterobacterales and 3.2% of Acinetobacter spp.

Interpretation

Data from this pilot study needs to validated in the larger Indian HAI surveillance network so that it can help in wider implementation of this protocol in order to assess its applicability p VAP across India.

Funding

This work was supported by a grant received from the Indian Council of Medical Research (code I-1203).

Outcomes associated with ventilator-associated events (VAE), respiratory infections (VARI), pneumonia (VAP) and tracheobronchitis (VAT) in ventilated pediatric ICU patients: A multicentre prospective cohort study

OBJECTIVES

An objective categorization of respiratory infections based on outcomes is an unmet clinical need. Ventilator-associated pneumonia and tracheobronchitis remain used in clinical practice, whereas ventilator-associated events (VAE) are limited to surveillance purposes.

RESEARCH METHODOLOGY/DESIGN

This was a secondary analysis from a multicentre observational prospective cohort study. VAE were defined as a sustained increase in minimum Oxygen inspired fraction (FiO2) and/or Positive end-expiratory pressures (PEEP) of ≥ 0.2/2 cm H2O respectively, or an increase of 0.15 FiO2 + 1 cm H20 positive end-expiratory pressures for ≥ 1 calendar-day.

SETTING

15 Paediatric Intensive Care Units.

MAIN OUTCOME MEASURES

Mechanical ventilation duration, intensive care and hospital length of stay; (LOS) and mortality.

RESULTS

A cohort of 391 ventilated children with an age (median, [Interquartile Ranges]) of 1 year[0.2-5.3] and 7 days[5-10] of mechanical ventilation were included. Intensive care and hospital stays were 11 [7-19] and 21 [14-39] days, respectively. Mortality was 5.9 %. Fifty-eight ventilator-associated respiratory infections were documented among 57 patients: Seventeen (29.3 %) qualified as ventilator-associated pneumonia (VAP) and 41 (70.7 %) as ventilator-associated tracheobronchitis (VAT). Eight pneumonias and 16 tracheobronchitis (47 % vs 39 %,P = 0.571) required positive end-expiratory pressure or oxygen increases consistent with ventilator-associated criteria. Pneumonias did not significantly impact on outcomes when compared to tracheobronchitis. In contrast, infections (pneumonia or tracheobronchitis) following VAEs criteria were associated with > 6, 8 and 15 extra-days of ventilation (16 vs 9.5, P = 0.001), intensive care stay (23.5 vs 15; P = 0.004) and hospital stay (39 vs 24; P = 0.015), respectively.

CONCLUSION

When assessing ventilated children with respiratory infections, VAE apparently is associated with higher ventilator-dependency and LOS compared with pneumonia or tracheobronchitis.

IMPLICATIONS FOR PRACTICE

Incorporating the modification of ventilatory settings for further categorization of the respiratory infections may facilitate therapeutic management among ventilated patients.

Early prediction of ventilator-associated pneumonia with machine learning models: A systematic review and meta-analysis of prediction model performance✰

BACKGROUND

Machine learning-based prediction models can catalog, classify, and correlate large amounts of multimodal data to aid clinicians at diagnostic, prognostic, and therapeutic levels. Early prediction of ventilator-associated pneumonia (VAP) may accelerate the diagnosis and guide preventive interventions. The performance of a variety of machine learning-based prediction models were analyzed among adults undergoing invasive mechanical ventilation.

METHODS

This systematic review and meta-analysis was conducted in accordance with the Cochrane Collaboration. Machine learning-based prediction models were identified from a search of nine multi-disciplinary databases. Two authors independently selected and extracted data using predefined criteria and data extraction forms. The predictive performance, the interpretability, the technological readiness level, and the risk of bias of the included studies were evaluated.

RESULTS

Final analysis included 10 static prediction models using supervised learning. The pooled area under the receiver operating characteristics curve, sensitivity, and specificity for VAP were 0.88 (95 % CI 0.82-0.94, I2 98.4 %), 0.72 (95 % CI 0.45-0.98, I2 97.4 %) and 0.90 (95 % CI 0.85-0.94, I2 97.9 %), respectively. All included studies had either a high or unclear risk of bias without significant improvements in applicability. The care-related risk factors for the best performing models were the duration of mechanical ventilation, the length of ICU stay, blood transfusion, nutrition strategy, and the presence of antibiotics.

CONCLUSION

A variety of the prediction models, prediction intervals, and prediction windows were identified to facilitate timely diagnosis. In addition, care-related risk factors susceptible for preventive interventions were identified. In future, there is a need for dynamic machine learning models using time-depended predictors in conjunction with feature importance of the models to predict real-time risk of VAP and related outcomes to optimize bundled care.

Hospital-Acquired Pneumonia and Ventilator-Associated Pneumonia: A Literature Review

Hospital-acquired pneumonia (HAP) and its subtype, ventilator-associated pneumonia (VAP), remain two significant causes of morbidity and mortality worldwide, despite the better understanding of pathophysiological mechanisms, etiology, risk factors, preventive methods (bundle of care principles) and supportive care. Prior detection of the risk factors combined with a clear clinical judgement based on clinical scores and dosage of different inflammatory biomarkers (procalcitonin, soluble triggering receptor expressed on myelloid cells type 1, C-reactive protein, mid-regional pro-adrenomedullin, mid-regional pro-atrial natriuretic peptide) represent the cornerstones of a well-established management plan by improving patient's outcome. This review article provides an overview of the newly approved terminology considering nosocomial pneumonia, as well as the risk factors, biomarkers, diagnostic methods and new treatment options that can guide the management of this spectrum of infections.

Ventilator-associated events: From surveillance to optimizing management

Mechanical ventilation (MV) is a life-support therapy that may predispose to morbid and lethal complications, with ventilator-associated pneumonia (VAP) being the most prevalent. In 2013, the Center for Disease Control (CDC) defined criteria for ventilator-associated events (VAE). Ten years later, a growing number of studies assessing or validating its clinical applicability and the potential benefits of its inclusion have been published. Surveillance with VAE criteria is retrospective and the focus is often on a subset of patients with higher than lower severity. To date, it is estimated that around 30% of ventilated patients in the intensive care unit (ICU) develop VAE. While surveillance enhances the detection of infectious and non-infectious MV-related complications that are severe enough to impact the patient's outcomes, there are still many gaps in its classification and management. In this review, we provide an update by discussing VAE etiologies, epidemiology, and classification. Preventive strategies on optimizing ventilation, sedative and neuromuscular blockade therapy, and restrictive fluid management are warranted. An ideal VAE bundle is likely to minimize the period of intubation. We believe that it is time to progress from just surveillance to clinical care. Therefore, with this review, we have aimed to provide a roadmap for future research on the subject.

Infection-Related Ventilator-Associated Complications in Critically Ill Patients with Trauma: A Retrospective Analysis

BACKGROUND

Trauma is a leading cause of death and disability. Patients with trauma undergoing invasive mechanical ventilation (IMV) are at risk for ventilator-associated events (VAEs) potentially associated with a longer duration of IMV and increased stay in the intensive care unit (ICU).

METHODS

We conducted a retrospective cohort study aimed to evaluate the incidence of infection-related ventilator-associated complications (IVACs), possible ventilator-associated pneumonia (PVAP), and their characteristics among patients experiencing severe trauma that required ICU admission and IMV for at least four days. We also determined pathogens implicated in PVAP episodes and characterized the use of antimicrobial therapy.

RESULTS

In total, 88 adult patients were included in the main analysis. In this study, we observed that 29.5% of patients developed a respiratory infection during ICU stay. Among them, five patients (19.2%) suffered from respiratory infections due to multi-drug resistant bacteria. Patients who developed IVAC/PVAP presented lower total GCS (median value, 7; (IQR, 9) vs. 12.5, (IQR, 8); p = 0.068) than those who did not develop IVAC/PVAP.

CONCLUSIONS

We observed that less than one-third of trauma patients fulfilling criteria for ventilator associated events developed a respiratory infection during the ICU stay.

Relationship between ventilator bundle compliance and the occurrence of ventilator-associated events: a prospective cohort study

Background

Instead of ventilator-associated pneumonia (VAP), the modern definition of ventilator-associated events (VAEs) has been introduced to identify infectious and noninfectious respiratory complications. Some studies revealed that compliance to the ventilator bundle is associated with decreased occurrence of VAP, but little is known about its association with the decrease of VAEs occurrence.

Methods

A prospective cohort research design was used. Data were collected over eight months from May 2019 to February 2020 in five general intensive care units. The researchers assessed the compliance to ventilator care bundle using the Institute for Healthcare Improvement ventilation bundle checklist. Mechanically ventilated patients were prospectively assessed for the occurrence of VAEs using a pre-validated calculator from the Centers for Disease Control and Prevention. All are non-invasive tools and no intervention was done by the authors.

Results

A total of 141 mechanically ventilated patients completed the study. The odds ratio of having VAEs in patients who received ventilator bundle was -1.19 (95% CI, -2.01 to -0.38), a statistically significant effect, Wald χ2(1) = 8.18, p = 0.004.

Conclusion/ implications for practice

Ventilator bundle compliance was associated with a reduced risk for VAEs occurrence. Nurses should comply with the ventilator bundle because it is associated with decreased VAEs occurrence.

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.

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.