Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
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 ā„18 years of age, have a score ā¤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.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| PatiĆ«nts who underwent a CPET prior to elective colorectal surgery investigate fitness level. | Patients considered for colorectal cancer surgery who were ā„18 years of age, had a score ā¤7 metabolic equivalents of task on the veterans-specific activity questionnaire. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| CPET/Cardiopulmonary Exercise Test | Diagnostic Test | During CPET, a patient exercises against a progressively increasing work rate until volitional exhaustion, while breath-by-breath respiratory gasses are analyzed. |
| Measure | Description | Time Frame |
|---|---|---|
| Influence of different CPET data averaging intervals on the numerical values of CPET-derived variables. | To assess the influence of different CPET data averaging intervals on the numerical the numerical values of VO2VAT, | Baseline, pre surgery |
| Influence of different CPET data averaging intervals on the numerical values of CPET- | To assess the influence of different CPET data averaging intervals on the numerical the numerical values of VO2peak. | Baseline, pre surgery |
| Influence of different CPET data averaging intervals on the numerical values of CPET- | To assess the influence of different CPET data averaging intervals on the numerical the numerical values of VE/VCO2-slope. | Baseline, pre surgery |
| Influence of different CPET data averaging intervals on the numerical values of CPET- | To assess the influence of different CPET data averaging intervals on the numerical the numerical values of RERpeak. | Baseline, pre surgery |
| Influence of different CPET data averaging intervals on the numerical values of CPET- | To assess the influence of different CPET data averaging intervals on the numerical the numerical values of VE/VCO2VAT. | Baseline, pre surgery |
| Influence of different CPET data averaging intervals on the numerical values of CPET- | To assess the influence of different CPET data averaging intervals on the numerical the numerical values of the OUES. | Baseline, pre surgery |
| Measure | Description | Time Frame |
|---|---|---|
| High- or Low-risk for postoperative complications | Patients are 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 [12], and/or an OUES/kg <20.6 | Baseline, pre surgery |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Patients considered for colorectal cancer surgery at the VieCuri Medical Centre Venlo, who had undergone a preoperative CPET before colorectal surgery as a part of a prehabilitation study.
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Viecuri Medical Center | Venlo | Limburg | 5912BL | Netherlands |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36928094 | Derived | Franssen RFW, Sanders BHE, Takken T, Vogelaar FJ, Janssen-Heijnen MLG, Bongers BC. Influence of different data-averaging methods on mean values of selected variables derived from preoperative cardiopulmonary exercise testing in patients scheduled for colorectal surgery. PLoS One. 2023 Mar 16;18(3):e0283129. doi: 10.1371/journal.pone.0283129. eCollection 2023. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D015179 | Colorectal Neoplasms |
| D003110 | Colonic Neoplasms |
| ID | Term |
|---|---|
| D007414 | Intestinal Neoplasms |
| D005770 | Gastrointestinal Neoplasms |
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
Not provided
Not provided
Not provided
Not provided
Not provided
| D009369 | Neoplasms |
| D004066 | Digestive System Diseases |
| D005767 | Gastrointestinal Diseases |
| D003108 | Colonic Diseases |
| D007410 | Intestinal Diseases |
| D012002 | Rectal Diseases |