Driving Pressure and Mortality: in the Pediatric Intensive Care Unit (PICU)

NCT ID: NCT04419376

Last Updated: 2020-06-05

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

116 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-03-30

Study Completion Date

2020-04-15

Brief Summary

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Respiratory failure is one of the most common causes of both hospitalization and mortality in patients in the pediatric intensive care unit (PICU). Recently, it is recommended to target driving pressure (ΔP) in patients with ARDS to achieve better results with the administration of optimal mechanical ventilation. In many studies, higher ΔP was associated with mortality in adult ARDS patients; non-ARDS patients' studies showing the relationship between driving pressure and mortality are few, but contradictory results have come out.

This study aimed to determine whether ΔP was associated with mortality in pediatric patients diagnosed as pARDS and non-pARDS who received mechanical ventilation support due to respiratory failure. Patients who received invasive mechanical ventilation support due to respiratory failure in the pediatric intensive care unit over 1 month and under 18 years were included in our study Driving pressure was significantly associated with an increased risk of mortality among mechanically ventilated both pARDS and non-pARDS patients. Future prospective randomized clinical trials are needed to determine a protocol targeting DP can be developed and defining optimum cutoff values.

Detailed Description

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Respiratory failure is one of the most common causes of both hospitalization and mortality in patients in the pediatric intensive care unit (PICU). Recently, it is recommended to target driving pressure (ΔP) in patients with ARDS to achieve better results with the administration of optimal mechanical ventilation. ΔP is calculated as the difference between Plateau pressure (Pplat) and positive end-expiratory pressure (PEEP) and is determined by the ratio of the tidal volume to the compliance of the respiratory system (ΔP = Pplat - PEEP = VT/CRS). ΔP estimates how much mechanical strain (dynamic strain) the tidal volume causes in the lung. It is a non-invasive and simple method and can be easily calculated at the bedside. In many studies, higher ΔP was associated with mortality in adult ARDS patients; non-ARDS patients' studies showing the relationship between driving pressure and mortality are few, but contradictory results have come out.

This study aimed to determine whether ΔP was associated with mortality in pediatric patients diagnosed as pARDS and non-pARDS who received mechanical ventilation support due to respiratory failure.

Single-center, prospective, observational study of patients admitted to pediatric intensive care units (PICU) in Turkey. In our study, the ethics committee was approved by The Health Sciences University Izmir Behcet Uz Child Health and Diseases education and research hospital ethics committee (protocol no: 2019-344).In our study, patients who received invasive mechanical ventilation support due to respiratory failure in the pediatric intensive care unit over 1 month and under 18 years were included in the study between March 2018 and April 2020. Mechanically ventilated patients (via ETT or trachestomy) were recorded for patients whose ventilation duration lasted at least 24 hours. We divided the patients into two groups by calculating the oxygenation index (OI): \[mean airway pressure(MAP) × fraction of inspired oxygen (FiO2) \]/ partial pressure of oxygen in arterial blood (PaO2) × 100) used in the classification of PALICC, including ARDS and non-ARDS. PARDS definition was also identified based on the PALICC criteria. Data were prospectively recorded on day 1 including patient demographics, ventilator settings (VT, VT / ideal body weight (IBW), respiratory rate (RR), peak inspiratory pressure (PIP), plateau pressure (Pplat), mean airway pressure (Pmean), minute volume (VE), end-expiratory pressure (PEEP), static compliance (Cstat), fraction of inspired oxygen FIO2, inspiratory time ( IT), expiratory time (ET) and we calculated oxygenation index (OI), cstat (VT/∆P), partial pressure of oxygen in arterial blood (PaO2) /FiO2, driving pressure (ΔP), the pediatric index of mortality (PRISM) III scores and pediatric sequential organ failure assessment (pSOFA) scores.

All patients were ventilated with volume control (VCV) or pressure control (PCV) mode during the hospitalization. İn order to measure the driving pressure of patients, Pplat was measured in the mechanical ventilator every 12 hours using an inspiratory hold maneuver. The average Pplat was calculated using the mean of 2 measurements within 24 hours. Then, the total PEEP was measured by expiratory hold maneuver and ΔP was calculated with the Pplat-PEEP formula. Patients were followed for 30 days until hospital discharge. We used ΔP compared to other mechanic ventilator parameters between survivors and non-survivors at day 30. Besides, ΔP and other parameters of patients in the ARDS and non-ARDS groups were compared with their 30-day mortality.

Statistical Analyses Primarily, we evaluated the relationship between ΔP and mortality in patients with ARDS and non-ARDS. Our second target was to evaluate the relationship between mortality and ΔP and other mechanical ventilator parameters.

Driving pressure and other lung dynamics; according to the type and distribution of the data was compared with chi-square, Wilcoxon, Independent-T-test or Mann-Whitney-U test and p \<0.05 was considered statistically significant. The strength of the association between the two variables was measured using the correlation coefficient. We used Pearson correlation to parametric variable and Spearman correlation to the nonparametric variable to detect covariances before logistic regression analysis. We evaluated with spearman's correlation analysis to detect covariances before logistic regression analysis. Parameters found significant with mortality in univariate analyzes were evaluated by Logistic Regression analysis. (odds ratio \[OR\] and 95 % confidence intervals \[CI\]) Model fit was assessed using Hosmer-Lemeshow statistics.

For the multivariable analysis, we identified covariates that may be associated with mortality. VT /IBW, PaO2, OI, FiO2, PRISM III score, Days of ventilation and pSOFA score were not collinear with ΔP. We did not include Pplat, PIP, Pmean in logistic regression models containing ΔP given concerns for collinearity Individual covariates included age, gender, PRISM III score, PaO2, OI, FiO2, Days of ventilation and pSOFA score. We created 3 other modeling analyzes for Pplat, PIP, Pmean, because of collinearity with driving pressure. We evaluated this model to determine the best parameter related to mortality in whole patients under mechanical ventilation support due to respiratory failure. ΔP cut off (13 cmH2O) values in adult studies in the literature were categorized and mortality was estimated by a receiver operating characteristic (ROC). We performed all statistical analyses using IBM SPSS Statistics for Windows version 22 (Armonk, NY) for analysis.

Mechanical ventilation is one of the most common indications for admission to a pediatric intensive care unit (PICU), with up to 64% of admitted children requiring mechanical ventilation. Driving pressure (ΔP), which is calculated as end-inspiratory plateau pressure (Pplat) minus applied positive end-expiratory pressure (PEEP) and is equivalent to the ratio between the VT and compliance of the respiratory system, can reduce mortality with children who received mechanical ventilator support due to respiratory failure. ΔP is a non-invasive and simple method and can be easily calculated at the bedside.

Recent data in the adult ARDS population have shown that the ΔP is most related to mortality. Our study, we have shown that the ΔP on day 1 was associated with hospital mortality in with pARDS patients.

Conditions

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ARDS, Human Respiratory Failure

Study Design

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Observational Model Type

CASE_CROSSOVER

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients with pARDS

Within 7 days of known clinical insult Respiratory failure not fully explained by cardiac failure or fluid overload chest imaging findings of new infiltrate(s) consistent with acute pulmonary parenchymal disease patients with an oxygenation index (OI) (\[FIO2 × mean airway pressure × 100\]/PaO2) above 4

driving pressure

Intervention Type DEVICE

Mechanically ventilated patients (via ETT or trachestomy) were recorded for patients whose ventilation duration lasted at least 24 hours.We divided the patients into two groups by calculating the oxygenation index (OI): \[mean airway pressure(MAP) × fraction of inspired oxygen (FiO2) \]/ partial pressure of oxygen in arterial blood (PaO2) × 100) used in the classification of PALICC, including pARDS and non-pARDS.

Patients with non-pARDS

non-pARDS patients who received mechanical ventilation support due to respiratory failure.

driving pressure

Intervention Type DEVICE

Mechanically ventilated patients (via ETT or trachestomy) were recorded for patients whose ventilation duration lasted at least 24 hours.We divided the patients into two groups by calculating the oxygenation index (OI): \[mean airway pressure(MAP) × fraction of inspired oxygen (FiO2) \]/ partial pressure of oxygen in arterial blood (PaO2) × 100) used in the classification of PALICC, including pARDS and non-pARDS.

Interventions

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driving pressure

Mechanically ventilated patients (via ETT or trachestomy) were recorded for patients whose ventilation duration lasted at least 24 hours.We divided the patients into two groups by calculating the oxygenation index (OI): \[mean airway pressure(MAP) × fraction of inspired oxygen (FiO2) \]/ partial pressure of oxygen in arterial blood (PaO2) × 100) used in the classification of PALICC, including pARDS and non-pARDS.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* In our study, patients who received invasive mechanical ventilation support for at least 24 hours due to respiratory failure in the pediatric intensive care unit over 1 month and under 18 years were included in the study between March 2018 and April 2020.

Exclusion Criteria

* patients who died within the first 24 hours and patients whose desired respiratory mechanics were not measured and data deficiencies were detected
Minimum Eligible Age

1 Month

Maximum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Dr. Behcet Uz Children's Hospital

OTHER

Sponsor Role lead

Responsible Party

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Ekin soydan

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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ekin soydan

Role: PRINCIPAL_INVESTIGATOR

Investigator

Locations

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The Health Sciences University Izmir Behçet Uz Child Health and Diseases education and research hospital

Izmir, Turkey/izmir, Turkey (Türkiye)

Site Status

Countries

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Turkey (Türkiye)

References

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Other Identifiers

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2019-344

Identifier Type: -

Identifier Source: org_study_id

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