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Published on: November 28, 2018
Assessing the accuracy of algorithm-derived cardiorespiratory fitness in surgical patients: a prospective cohort
Fadi Hammal1, Tanis Quaife1, Kieran Purich1
1Department of Anesthesiology & Pain Medicine, University of Alberta, 2-150 Clinical Sciences Building, Edmonton, AB, T6G2G3, Canada.
Purpose:
To determine if a non-exercise algorithm-derived assessment of cardiorespiratory fitness (CRFA) accurately predicted estimated values obtained using a six-minute walk test (CRF6MWD) and the Duke Activity Status Index (CRFDASI).
Methods:
Following research ethics board approval, an observational cohort study was conducted in selected, consenting patients undergoing elective surgery. Participants completed questionnaires assessing their self-reported exercise capacity. Their height, weight, waist circumference, and vital signs were measured. A six-minute walk test was performed twice with a 45-min rest interval between tests. The correlation between CRFA and both CRF6MWD and CRFDASI was determined.
Results:
Two hundred forty-two participants were included. Mean age was 62 (range 45-88 yr); 150 (62%) were male, 87 (36%) self-reported walking or jogging > 16 km per week, and 49 (20%) were current smokers. The CRFA and CRF6MWD were highly correlated (Pearson r = 0.878; P < 0.001). CRFA and CRFDASI were less strongly correlated (Pearson r = 0.252; P < 0.001). Among patients capable of walking > 427 m in the six-minute walk test, CRFA, CRF6MWD, and CRFDASI were equivalent.
Conclusion:
A non-exercise algorithm can estimate cardiorespiratory fitness in patients presenting for elective surgery. The variables required to compute CRFA can be obtained in a clinic setting without the need to engage in formal exercise testing. Further evaluation of CRFA as a predictor of long-term outcome in patients is warranted.
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