Clinical Trial Details
— Status: Not yet recruiting
Administrative data
NCT number |
NCT06298435 |
Other study ID # |
17536 |
Secondary ID |
|
Status |
Not yet recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
March 1, 2024 |
Est. completion date |
April 1, 2025 |
Study information
Verified date |
February 2024 |
Source |
University Medical Center Groningen |
Contact |
Clemens Barends, phd |
Phone |
+31-503616161 |
Email |
c.r.m.barends[@]umcg.nl |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
• Background Intermittent Positive Pressure Ventilation is used during general anesthesia but
can lead to serious complications. Respiratory parameter settings can be adjusted to minimize
the detrimental effects of this unphysiological artificial respiration. Determining optimal
ventilator settings is a multifactorial problem with many possible realisations. Knowledge of
the relationship of patient outcomes with mathematically identifiable integer sets of
ventilator setting parameters may help to understand which effects ventilator settings have
on patient outcomes. An exploratory database study can provide a basis for further,
prospective, interventional studies to find the optimal combination of ventilator settings.
Main research question
- To determine the relationship between the use of mathematically identifiable integer
ventilator parameter sets and patient outcomes
- Design (including population, confounders/outcomes) Retrospective database study of all
cases of adult patients undergoing procedures in the UMCG under general anesthesia with
IPPV between 01-01-2018 and 01-04-2023. Multivariate and mixed-model analyses, where
appropriate, will be corrections for patient specific characteristics such as ASA PS,
age, BMI, sex.
- Expected results Using mathematically identifiable integer ventilatory parameter sets
improves respiratory and/or hemodynamic patient outcomes.
Description:
• Introduction and rationale
Intermittent Positive Pressure Ventilation (IPPV) is required for almost every patient under
general anesthesia. It is recognized that IPPV is an unphysiological way of breathing and it
can have serious complications when instituted incorrectly. 1 Known complications of IPPV
include (but are not limited to) desaturation, atelectasis and baro-/volutrauma.
Many studies have tried to determine the optimal settings for ventilatory parameters during
IPPV. 2 Currently, however, it is unknown whether the use of specific ventilatory parameter
sets is related to improved outcomes for patients undergoing procedures under general
anesthesia.
IPPV is commonly instituted using a set of parameters which determine respiratory
characteristics among which are Peak Inspiratory Pressure (PIP), Positive End Expiratory
Pressure (PEEP), Plateau Pressure (PlatP) and the Fraction of Inspired Oxygen(FiO2). 3
Adjustment of these parameters allows the clinician to optimize the mechanical
characteristics of the artificial respiration of the patient.
IPPV changes intrathoracic pressure in a cyclic way. Pressure increases during inspiration
and decreases during expiration. The influence of increased intrathoracic pressure, caused by
IPPV, on hemodynamic parameters is well known and is one of the factors used by
anesthesiologists when instituting IPPV. IPPV-pressures may both increase or decrease
hemodynamic parameters such as cardiac preload and left ventricular wall tension, thus
influencing not only oxygenation and decarbonization, but also cardiac output, myocardial
oxygen consumption and direct cerebral oxygenation. The relationship between respiration and
circulation exhibits complex dynamics and understanding this may help to promote more natural
and physiologic breathing patterns, leading to improved oxygenation and reduced respiratory
distress.
In addition to direct influence of positive ventilatory pressures on hemodynamic factors the
cyclic nature of both IPPV and hemodynamic factors needs to be taken into account when
investigating the relationship between IPPV and patient outcomes. When changes in respiratory
pressures coincide with related physiological phenomena, each cycle may pose an additive
influence on both parameters. Furthermore, coinciding physiological cycles may lead to
"respiratory entrainment," where the ventilator-induced breaths becomes asynchronizous with
the patient's intrinsic respiratory rhythm, leading to ineffective ventilation and increased
risk of lung injury. Additionally, reducing respiratory entrainment may help to reduce the
likelihood of mechanical fatigue and stress on the lung tissue, as it avoids repetitive or
periodic stress on the respiratory system. Using mathematically identified integer sets as
ventilatory parameter settings may reduce the coinciding of respiratory cycles with recurring
physiological phenomena. Furthermore, the role of mathematical identification of optimal
integer sets for use in ventilator parameters can help find optimal settings to reduce
complications from Intermittent Positive Pressure Ventilation
Research question To determine the relationship between the use of mathematically
identifiable integer ventilator parameter sets and patient outcomes
METHOD Description study design
This is a retrospective database study. A database search of all cases of adult patients
undergoing procedures in the UMCG under general anesthesia with IPPV between 01-01-2018 and
01-04-2023 will be conducted. Researchers will use anonymized data only from the existing
patient data records.
This study will investigate the relationship of mathematically identifiable integer sets of
ventilator setting parameters during surgery performed under general anesthesia with IPPV.
Data will be extracted from the Electronic Patient Database and all data will be handled
anonymously.
Parameter integer sets will be identified using probabilistic (or Monte Carlo) algorithms and
sieve methods. Non-multifactorial and multifactorial sets will be compared and only
non-negative integers will be considered for analysis
Univariate, multivariate regression methods and mixed-model analyses, where appropriate, will
be used to determine which integer sets in ventilatory parameter settings during surgery
performed under general anesthesia and IPPV are related to patient outcomes such as SpO2 and
FiO2/ SpO2-ratio