Thomas J Barton1, David A Low1, Esmee A Bakker2, Thomas Janssen3, Sonja de Groot4, Lucas van der Woude5, Dick H J Thijssen6. 1. Research Institute for Sports and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom. 2. Research Institute for Sports and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom; Radboud Institute for Health Sciences, Department of Physiology, Radboud University Medical Center, Nijmegen, the Netherlands. 3. Amsterdam Rehabilitation Research Center, Reade, Amsterdam, the Netherlands. 4. Amsterdam Rehabilitation Research Center, Reade, Amsterdam, the Netherlands; University of Groningen, University Medical Center Groningen, Center of Human Movement Sciences; Groningen, the Netherlands. 5. University of Groningen, University Medical Center Groningen, Center of Human Movement Sciences; Groningen, the Netherlands. 6. Research Institute for Sports and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom; Radboud Institute for Health Sciences, Department of Physiology, Radboud University Medical Center, Nijmegen, the Netherlands. Electronic address: D.Thijssen@ljmu.ac.uk.
Abstract
OBJECTIVES: To explore whether traditional models of cardiovascular disease (CVD) risk prediction correctly predict CVD events across a median 5.7-year follow-up period in individuals with spinal cord injury (SCI) and whether adding SCI-related characteristics (ie, lesion level) to the prediction model can improve the prognostic value. DESIGN: Retrospective analysis of patient records. SETTING: Observation at the start of active rehabilitation of participants in a multicenter cohort study, "Restoration of (Wheelchair) Mobility in SCI Rehabilitation," in the Netherlands. PARTICIPANTS: Patients with SCI (N=200) The patients were 74% men, aged 40±14 years, and with an American Spinal Injury Association (ASIA) impairment score of A through D. Forty percent had tetraplegia, and 69% were motor complete. INTERVENTIONS: Risk profiling/not applicable. MAIN OUTCOME MEASURES: Survival status and cardiovascular morbidity and mortality qwere obtained from medical records. Five-year Framingham Risk Scores (FRS) and the FRS ability to predict events assessed using receiver operating characteristic (ROC) curves with corresponding areas under the curve (AUC) and 95% confidence intervals (CI). Kaplan-Meier curves and the log-rank test were used to assess the difference in clinical outcome between participants with an FRS score lower or higher than the median FRS score for the cohort. SCI-related factors associated with CVD events, ASIA impairment, motor completeness, level of injury, and sports participation before injury were explored using univariate and multivariate Cox proportional hazard regression. RESULTS: The median 5-year FRS was 1.36%. Across a median follow-up period of 5.7 years, 39 developed a CVD event, including 10 fatalities. Although the FRS markedly underestimated the true occurrence of CVD events, the Kaplan-Meier curves and the log-rank test showed that the risk ratio for individuals with an FRS score less than the median FRS (eg, low risk) versus a score greater than the median FRS (high risk) was 3.2 (95% CI, 1.6-6.5; P=.001). Moreover, ROC with corresponding AUCs suggests acceptable accuracy of the FRS to identify individuals with increased risk for future CVD events (ROC AUC of 0.71; 95% CI, 0.62-0.82). Adding ASIA impairment (0.74; 95% CI, 0.66-0.82), motor impairment (0.74; 95% CI, 0.66-0.83), level of injury (0.72; 95% CI, 0.63-0.81), or active engagement in sport before injury (0.72; 95% CI, 0.63-0.88) to the FRS did not improve the level of discrimination. CONCLUSIONS: Our 5.7-year retrospective study reveals that cardiovascular risk factors and risk models markedly underestimate the true risk for CVD events in individuals with SCI. Nonetheless, these markers successfully distinguish between SCI individuals at high versus low risk for future CVD events. Our data may have future clinical implications, both related to (cutoff values of) CVD risk factors, but also for (earlier) prescription of (non)pharmacologic strategies against CVD in SCI individuals.
OBJECTIVES: To explore whether traditional models of cardiovascular disease (CVD) risk prediction correctly predict CVD events across a median 5.7-year follow-up period in individuals with spinal cord injury (SCI) and whether adding SCI-related characteristics (ie, lesion level) to the prediction model can improve the prognostic value. DESIGN: Retrospective analysis of patient records. SETTING: Observation at the start of active rehabilitation of participants in a multicenter cohort study, "Restoration of (Wheelchair) Mobility in SCI Rehabilitation," in the Netherlands. PARTICIPANTS: Patients with SCI (N=200) The patients were 74% men, aged 40±14 years, and with an American Spinal Injury Association (ASIA) impairment score of A through D. Forty percent had tetraplegia, and 69% were motor complete. INTERVENTIONS: Risk profiling/not applicable. MAIN OUTCOME MEASURES: Survival status and cardiovascular morbidity and mortality qwere obtained from medical records. Five-year Framingham Risk Scores (FRS) and the FRS ability to predict events assessed using receiver operating characteristic (ROC) curves with corresponding areas under the curve (AUC) and 95% confidence intervals (CI). Kaplan-Meier curves and the log-rank test were used to assess the difference in clinical outcome between participants with an FRS score lower or higher than the median FRS score for the cohort. SCI-related factors associated with CVD events, ASIA impairment, motor completeness, level of injury, and sports participation before injury were explored using univariate and multivariate Cox proportional hazard regression. RESULTS: The median 5-year FRS was 1.36%. Across a median follow-up period of 5.7 years, 39 developed a CVD event, including 10 fatalities. Although the FRS markedly underestimated the true occurrence of CVD events, the Kaplan-Meier curves and the log-rank test showed that the risk ratio for individuals with an FRS score less than the median FRS (eg, low risk) versus a score greater than the median FRS (high risk) was 3.2 (95% CI, 1.6-6.5; P=.001). Moreover, ROC with corresponding AUCs suggests acceptable accuracy of the FRS to identify individuals with increased risk for future CVD events (ROC AUC of 0.71; 95% CI, 0.62-0.82). Adding ASIA impairment (0.74; 95% CI, 0.66-0.82), motor impairment (0.74; 95% CI, 0.66-0.83), level of injury (0.72; 95% CI, 0.63-0.81), or active engagement in sport before injury (0.72; 95% CI, 0.63-0.88) to the FRS did not improve the level of discrimination. CONCLUSIONS: Our 5.7-year retrospective study reveals that cardiovascular risk factors and risk models markedly underestimate the true risk for CVD events in individuals with SCI. Nonetheless, these markers successfully distinguish between SCI individuals at high versus low risk for future CVD events. Our data may have future clinical implications, both related to (cutoff values of) CVD risk factors, but also for (earlier) prescription of (non)pharmacologic strategies against CVD in SCI individuals.