Trial Review

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Trial registered on ANZCTR


Registration number
ACTRN12613001006730
Ethics application status
Approved
Date submitted
9/09/2013
Date registered
10/09/2013
Date last updated
13/07/2017
Type of registration
Retrospectively registered

Titles & IDs
Public title
Optimising positive end expiratory pressure (PEEP) in mechanically ventilated patients with acute respiratory distress syndrome (ARDS)
Scientific title
The investigation of model based methods to provide an optimal level of positive end expiratory pressure (PEEP) to mechanically ventilated patients with acute respiratory distress syndrome (ARDS)
Secondary ID [1] 283150 0
Nil
Universal Trial Number (UTN)
U111111429939
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Acute Respiratory Distress Syndrome (ARDS) 290009 0
Condition category
Condition code
Respiratory 290394 290394 0 0
Other respiratory disorders / diseases

Intervention/exposure
Study type
Interventional
Description of intervention(s) / exposure
The planned interventions will test the response of patient lung when it is ventilated at different positive end expiratory pressure (PEEP) to determine the best PEEP settings specific to each patient at a particular time.

The best PEEP is found to occur during minimal elastance. Minimal elastance PEEP is able to maximise lung recruitment and avoid overdistension. It is important ventilation is optimised as soon as possible when the patient is admitted to the ICU. Delayed proxy consent will be sought for these reasons.

The intervention tests a mathematical model (Time-varying elastance model) to better inform intensive care clinicians about the lung condition, and select a PEEP at minimal elastance during a PEEP titration protocol. Patients whose PEEP selected by the mathematical model, implemented by the clinician, will be compared with the outcomes of patients who have had their PEEP determined solely by clinical judgement.

Details of PEEP titration protocol
1. A staircase recruitment manoeuvre (RM) is performed (C.L. Hodgson et al., 2011). During RM, PEEP is increased in steps of 5cmH2O from a base level of 5cmH2O PEEP.
2. PEEP is increased until peak airway pressure (PIP) reaches a limit of 55cmH2O (or lower, if clinician feels this is too high for the patient)
3. Each PEEP is maintained for 10-15 breathing cycles before a subsequent increase.
4. Elastance is calculated at each PEEP
5. The minimum elastance PEEP is determined
6. This PEEP is recommended to the attending clinician
7. If the clinician feels this PEEP is appropriate, they will re-perform steps 1 and 2. The purpose of this increase is to re-recruit the lung after decremented portion of RM. On the decremented portion of the RM, the clinician will end the PEEP decrease on the recommended PEEP.
8. Otherwise the clinician will set the PEEP to a PEEP they feel is more appropriate. If the clinician chooses to ignore the model suggestion, this will be recorded. Further the data from the patient will still be recorded.

Every 3 hours or when the patient is turned in the bed the following adjustments are to be made:

1. PEEP is increased in 3 steps of 2cmH2O with 10~15 breathing cycles at each step.
2. If the Elastance shows an increase at each and every step, then revert back to the original PEEP setting minus 1cmH2O.
3. If the Elastance shows a decrease at each and every step, then set to the final PEEP setting (a total of 6cmH2O increase in PEEP).
4. If the Elastance decreases at the first step and then increases at any subsequent step, then set to the PEEP that yielded the minimum Elastance value during the adjustment procedure.
5. If the Elastance increases at the first step and then decreases at any subsequent step, then leave PEEP at original setting. This instance is cause for the clinician to consider a full recruitment manoeuvre.

The study will run for at least 48 hours, and until there has been significant resolution of their lung condition. Following each intervention, clinical staff in the ICU will be given the option of following the recommended settings as determined by the mathematical model.

Data regarding clinician compliance with the protocol, the number of low oxygen recordings (using standard pulse oximetry monitoring), length of mechanical ventilation and ICU stay, total oxygen “dose” and ICU mortality will be collected and compared with a matched cohort.
Intervention code [1] 287887 0
Treatment: Devices
Comparator / control treatment
The comparator cohort for this study includes patients that are not enrolled for the actual trial. Their treatment will not be in any way affected of altered as a result of this trial. They will receive normal care from ICU professionals as per usual hospital routine. These data were obtained in previous observational trial (Feb 2010 to Dec 2011) ACTRN12611001179921.
Control group
Historical

Outcomes
Primary outcome [1] 290414 0
Number of desaturation events (measured by continuous pulse oximetry, where SpO2 is less than 88%)
Timepoint [1] 290414 0
The occurance of desaturation events of a patient is recorded throughout the trial or for at least 48 hours.
Primary outcome [2] 290439 0
Length of mechanical ventilation
Timepoint [2] 290439 0
The length of MV is recorded as the duration from start of the trial until the discontinuation of mechanical ventilation.
Secondary outcome [1] 304472 0
PEEP selection based on minimal elastance has been suggested in some clinical and experimental trials [1-3]. However, there is yet confirmation of the PEEP selected at this elastance is optimal. The primary outcome the study will further verify and validate the benefit of minimal elastance selected PEEP during mechanical ventilation.

1. Carvalho, A., et al. (2007). "Positive end-expiratory pressure at minimal respiratory elastance represents the best compromise between mechanical stress and lung aeration in oleic acid induced lung injury." Critical Care 11(4): R86.
2. Lambermont, B., et al. (2008). "Comparison of functional residual capacity and static compliance of the respiratory system during a positive end-expiratory pressure (PEEP) ramp procedure in an experimental model of acute respiratory distress syndrome." Critical Care 12(4): R91.
3. Chiew, Y. S., et al. (2011). "Model-based PEEP Optimisation in Mechanical Ventilation." BioMedical Engineering OnLine 10(1): 111.
Timepoint [1] 304472 0
The assessment is conducted after completion of the clinical trials.
Secondary outcome [2] 304529 0
The study also aims to give clinicians the confidence to allow clinical staff to adjust PEEP levels, which may enable the clinicians more time to look at other aspects of the patient’s health and improve the standard of care in the intensive care unit.

This assessment will be conducted by using qualitative questionaires and feedback of clinical staffs that were involde during the trial
Timepoint [2] 304529 0
The assessment is conducted after completion of the clinical trials.

Eligibility
Key inclusion criteria
1. Patient on mechanical ventilation.
2. Patients diagnosed with all degrees of ARDS (PF ratio <300) as per the Berlin Definition (2012) (The ARDS Definition Task Force, A. 2012), by intensive care clinicians.
3. Arterial line in situ.
Minimum age
16 Years
Maximum age
No limit
Sex
Both males and females
Can healthy volunteers participate?
No
Key exclusion criteria
1. Patients who are likely to be discontinued from MV within 24 hours.
2. Patients aged less than 16.
4. Patients who are moribund and/or not expected to survive for more than 72 hours.
5. Patients whose care could be compromised if given increased sedation and/or muscle relaxants for the purpose of assessing lung recruitment.
6. Lack of clinical equipoise by ICU medical staff managing the patient.

Study design
Purpose of the study
Treatment
Allocation to intervention
Non-randomised trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Mechanically ventilated patients are unable to communicate due to their requirements for analgesia (opioids, such as morphine) and sedation (hypnotic drugs, such as diazepam or “valium”). They also frequently have metabolic or septic encephalopathies, or brain injury. Thus, virtually no patient will ever be competent to provide informed consent or desire to participate. Patients on MV who meet the inclusion criteria will be enrolled in the trial, once proper consents are obtained form family or whanau.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
No randomising will occur in this trial.
Masking / blinding
Who is / are masked / blinded?



Intervention assignment
Other design features
Phase
Not Applicable
Type of endpoint/s
Statistical methods / analysis

Recruitment
Recruitment status
Stopped early
Data analysis
Data collected is being analysed
Reason for early stopping/withdrawal
Lack of funding/staff/facilities
Other reasons/comments
Other reasons
The trial has collected sufficient data for analysis and testing. The clinical protocol requires additional changes.
Date of first participant enrolment
Anticipated
6/09/2013
Actual
9/09/2013
Date of last participant enrolment
Anticipated
Actual
19/11/2014
Date of last data collection
Anticipated
Actual
19/11/2014
Sample size
Target
60
Accrual to date
Final
13
Recruitment outside Australia
Country [1] 5392 0
New Zealand
State/province [1] 5392 0
Canterbury

Funding & Sponsors
Funding source category [1] 287907 0
Self funded/Unfunded
Name [1] 287907 0
Country [1] 287907 0
Primary sponsor type
Government body
Name
Canterbury District Health Board
Address
Level 2
H Block
The Princess Margaret Hospital
Cashmere Road
Cashmere
PO Box 1600
Christchurch 8140
Country
New Zealand
Secondary sponsor category [1] 286633 0
University
Name [1] 286633 0
University of Canterbury
Address [1] 286633 0
Private Bag 4800
Christchurch 8140
Country [1] 286633 0
New Zealand

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 289842 0
Health and Disability Ethics Comittee (Southern)
Ethics committee address [1] 289842 0
Health and Disability Ethics Committees
1 the Terrace
PO Box 5013
Wellington
6011
Ethics committee country [1] 289842 0
New Zealand
Date submitted for ethics approval [1] 289842 0
10/05/2013
Approval date [1] 289842 0
08/06/2013
Ethics approval number [1] 289842 0
13/STH/84

Summary
Brief summary
Intensive care clinicians use Mechanical Ventilation on a daily basis in the ICU to treat patients with injured lungs. An important setting on the ventilator machines is known as positive end expiratory pressure or PEEP. This controls the pressure in the lung at the end of the breath, and its accuracy is critical in the successful treatment of injured lungs.

Currently, doctors have no standard way of selecting the PEEP for each patient, and use their clinical intuition, or their “gut-feeling”. Different patients have different lungs and as such, selecting PEEP this way might lead to an incorrect PEEP setting for that patient. This might cause the patient to require longer stays in the ICU and/or or further lung injury.

This study aims to evaluate a computer based method of PEEP selection and is based on prior research conducted here in the Christchurch ICU. Because this method of PEEP selection is specific to each patient, it is anticipated ventilation better matched to their lungs. This could lead to healthier lungs and as a result, require the patient to spend less time in the ICU.

Trial website
Trial related presentations / publications
1.. Kannangara DO, Newberry F, Howe S, Major V, Redmond D, Szlavecz A, Chiew YS, Pretty C, Benyo B, Shaw GM, Chase JG, Estimating the True Respiratory Mechanics during Asynchronous Pressure Controlled Ventilation, Biomedical Signal Processing and Control, 30: 70-78, 2016.
2. Damanhuri NS, Chiew YS, Othman NA, Docherty PD, Pretty C, Shaw, GM, Desaive T, Chase JG, “Assessing Respiratory Mechanics Using Pressure Reconstruction Method in Mechanically Ventilated Spontaneous Breathing Patient,” Computer Methods and Programs in Biomedicine, 2016, Vol 130, pp. 175-185
4.. Major V, Corbett S, Redmond R, Beatson A, Glassenbury D, Chiew YS, Pretty C, Desaive T, Szlavecz A, Benyo B, Shaw GM, and Chase JG, Respiratory mechanics assessment for reverse-triggered breathing cycles using pressure reconstruction. Biomedical Signal Processing and Control 2016, 23:1-9.
5. Szlavecz A, Chiew YS, Redmond D, A Beatson A, Glassenbury D, Corbett S, Major V, Pretty C, Shaw GM, Benyo B, Desaive T, Chase JG, The Clinical Utilisation of Respiratory Elastance Software (CURE Soft): a bedside software for real-time respiratory mechanics monitoring and mechanical ventilation management. BioMedical Engineering OnLine 2014, 13:140.
Public notes

Contacts
Principal investigator
Name 42710 0
Dr Geoffery Shaw
Address 42710 0
Department of Intensive Care
Christchurch Hospital
Private Bag 4710
Christchurch 8140
Country 42710 0
New Zealand
Phone 42710 0
+643364 1077
Fax 42710 0
Email 42710 0
[email protected]
Contact person for public queries
Name 42711 0
Dr Geoffery Shaw
Address 42711 0
Department of Intensive Care
Christchurch Hospital
Private Bag 4710
Christchurch 8140
Country 42711 0
New Zealand
Phone 42711 0
+643364 1077
Fax 42711 0
Email 42711 0
[email protected]
Contact person for scientific queries
Name 42712 0
Dr J Geoffrey Chase
Address 42712 0
University of Canterbury Department of Mechanical Engineering Private Bag 4800 Christchurch 8140
Country 42712 0
New Zealand
Phone 42712 0
+6421342743
Fax 42712 0
Email 42712 0
[email protected]

No information has been provided regarding IPD availability


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
SourceTitleYear of PublicationDOI
EmbaseA virtual patient model for mechanical ventilation.2018https://dx.doi.org/10.1016/j.cmpb.2018.08.004
EmbaseRespiratory mechanics assessment for reverse-triggered breathing cycles using pressure reconstruction.2016https://dx.doi.org/10.1016/j.bspc.2015.07.007
EmbasePredictive Virtual Patient Modelling of Mechanical Ventilation: Impact of Recruitment Function.2019https://dx.doi.org/10.1007/s10439-019-02253-w
Dimensions AIModel-based PEEP titration versus standard practice in mechanical ventilation: a randomised controlled trial2020https://doi.org/10.1186/s13063-019-4035-7
Dimensions AIBasis function identification of lung mechanics in mechanical ventilation for predicting outcomes of therapy changes: A first virtual patient2018https://doi.org/10.1016/j.ifacol.2018.09.151
Dimensions AINegative Lung Elastance in Mechanically Ventilated Spontaneously Breathing Patient2017https://doi.org/10.1016/j.ifacol.2017.08.2269
Dimensions AIValidation of a Model-based Method for Estimating Functional Volume Gains during Recruitment Manoeuvres in Mechanical Ventilation2018https://doi.org/10.1016/j.ifacol.2018.11.637
N.B. These documents automatically identified may not have been verified by the study sponsor.