posted on 2021-10-06, 13:21authored bySara-Azhari Mohamed, Navian Lee Viknaswaran, Jonathan Doran, Clara Sanz-Nogués, Khalid Ahmed, Linda Howard, Muhammad Tubassam, Timothy O'Brien, Stewart R. Walsh
Background: The ERICVA score was derived to predict amputation-free survival in patients with
critical limb ischemia (CLI). It may be a useful tool to stratify patients in trials of novel interventions
to treat CLI but, as yet, it has not been externally validated.
Methods: A prospective database of CLI patients was developed during prescreening of patients
for a phase 1 stem cell therapy clinical trial. The primary outcome was amputation free survival
(AFS) at 1 year. Both the full ERICVA scale (11 parameters) and simplified ERICVA scale (5
parameters) were validated. Data analysis was performed by calculation of the area under the
receiver operating characteristic (ROC) curve examining the predictive value of the scores. The
Chi-square test was used to examine the association between risk group and one-year AFS
and the cumulative survival of the three risk groups was compared using Kaplan Meier survival
curves.
Results: A series of 179 CLI patients were included in the analysis. The Chi-square test of
independence showed a significant association between the risk group (high, medium and
low) and one-year AFS outcome (P = 0.0007). Kaplan-Meier survival curve showed significant
difference in one-year AFS between the three risk groups (log-rank P < 0.001). The area under
the curve (AUC) was found to be 0.63 and 0.61 for the full and simplified score, respectively. The
sensitivity of the full score was 0.44 with specificity of 0.84. The simplified score had a sensitivity
of 0.28 and specificity of 0.92.
Conclusion: The ERICVA risk score system was found to have a fair validity but cannot be
considered reliable as a single predictor of one year AFS of CLI patients. The simplified score
had an AUC almost identical to the full score and can accordingly replace the full score.
Funding
Development of a structure identification methodology for nonlinear dynamic systems