Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT05353127 |
| Other study ID # |
2022_053 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
April 12, 2022 |
| Est. completion date |
October 1, 2022 |
Study information
| Verified date |
April 2022 |
| Source |
VieCuri Medical Centre |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Cardiopulmonary exercise testing (CPET) is used for preoperative risk assessment in patients
with colorectal cancer who need to undergo surgery. For presentation and interpretation
purposes, CPET data are averaged by using a time- or breath-based average. It is uncertain to
what extent differences in data averaging methods influence the numerical value of
preoperative CPET-derived variables used for risk assessment. Therefore, the primary aim of
this study is to investigate the influence of different CPET data averaging intervals on the
numerical values of CPET-derived variables used for preoperative risk assessment in patients
scheduled for elective colorectal cancer surgery. The secondary aim is to elucidate the
impact of data-averaging intervals on classification of patients into a low- or high-risk
category for postoperative complications based on known risk assessment thresholds.
Description:
Surgery for colorectal cancer is associated with a high incidence of postoperative
complications. Risk assessment by means of a cardiopulmonary exercise test (CPET) is an
essential part of the preoperative diagnostic work-up of colorectal cancer patients. During
CPET, a patient exercises against a progressively increasing work rate until volitional
exhaustion, while breath-by-breath respiratory gasses are analyzed. The large number of data
points that are collected by the breath-by-breath sampling rate can be a burden for data
visualization, as they can be noisy. Therefore, data averaging is performed to optimize
graphical data display and to aid CPET interpretation. To date, there are no studies
quantifying the extent to which differences in data averaging influence the numerical value
of preoperative CPET-derived variables for risk assessment based on aerobic fitness, such as
the the oxygen uptake (VO2) at the ventilatory anaerobic threshold (VAT), VO2 at peak
exercise (VO2peak), and the oxygen uptake efficiency slope (OUES), and of preoperative
CPET-derived variables for risk assessment based on ventilatory efficiency, such as the
ventilatory equivalent for carbon dioxide production at the VAT (VE/VCO2VAT) and the slope of
the relationship between the minute ventilation and carbon dioxide production
(VE/VCO2-slope). Therefore, the primary aim of this study is to investigate the influence of
different CPET data averaging intervals on the numerical values of CPET-derived variables
used for preoperative risk assessment in patients scheduled for elective colorectal cancer
surgery. The secondary aim is to elucidate the impact of data-averaging intervals on the
classification of patients into a low- or high-risk category for postoperative complications
based on known risk assessment thresholds.
Participants Data from patients considered for colorectal cancer surgery who are ≥18 years of
age, have a score ≤7 metabolic equivalents of task on the veterans-specific activity
questionnaire, and therefore performed preoperative CPET as a part of a prehabilitation study
will be collected. Preoperative CPET was conducted before any intervention was initiated.
Procedures Preoperative CPET data will be anonymized and patient characteristics other than
anthropometric measures will be concealed. A medical physiologist and a clinical exercise
physiologist will determine the CPET variables VO2VAT, VO2peak, respiratory exchange ratio at
peak exercise (RERpeak), VE/VCO2VAT, VE/VCO2-slope, and the OUES in all 20 CPETs using a
predefined set of guidelines Final determination of each parameter will be based on consensus
between the two observers. In case of disagreement between observers, a third observer will
be consulted. Determination of the aforementioned CPET variables will be repeated using each
of the five different data-averaging intervals. Data averaging-intervals consists of a
stationary time-based average over 10, 20, and 30 seconds, and of a rolling average over 3
and 7 breaths that were defined as follows. The stationary time-based average will be
calculated by averaging the breath-by-breath data over 10, 20, or 30 seconds. A rolling
average is defined as averaging a fixed number of single breath measurements (i.e., 3 and 7),
then discarding the first breath and adding a new breath to obtain a new breath averaging
block.
CPET interpretation will be performed using Blue Cherry software version 1.3.3.3 (Geratherm
Respiratory GmbH, Bad Kissingen, Germany).
Apart from the CPET data, the preoperative patient characteristics age, sex, body mass index,
smoking status (never, former, current), age-adjusted Charlson comorbidity index,
comorbidities, American Society of Anesthesiologists classification, veterans-specific
activity questionnaire score, hemoglobin levels (mmol/L), and tumor location will be
recorded.
To assess the influence of different CPET data averaging intervals on the numerical values of
CPET-derived variables, mean differences of the numerical values of VO2VAT, VO2peak, RERpeak,
VE/VCO2VAT, VE/VCO2-slope, and OUES between different data-averaging intervals will be
analyzed by means of within factors repeated measures analysis of variance (ANOVA). In case
of a statistically significant difference between methods (p<0.05), post-hoc testing will be
performed using the Bonferroni test to identify the exact differences. To evaluate the
influence of data-averaging intervals on risk assessment, participants will be classified as
being at low or high risk for postoperative complications based on their VO2VAT, VO2peak,
VE/VCO2VAT, and OUES. For each CPET-derived variable, numerical values will be determined for
each of the five data-averaging will be compared with known preoperative risk assessment
thresholds (patients will be classified as high-risk when having a VO2VAT <11.1 mL/kg/min, a
VO2peak <18.2 mL/kg/min, a VE/VCO2VAT >30.9, and/or an OUES/kg <20.6). Friedman's test will
be used to determine whether differences in risk assessment exist between data-averaging
methods. Differences between data-averaging methods will be assumed statistically significant
when p<0.05.
