Related Experiment Video
Updated: Nov 2, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
An algorithm combining VVSYmQ® and VCSS scores may help to predict disease severity in C2 patients
Mikel Sadek1, Matthew Pergamo1, Jose I Almeida2
1NYU Langone Health, New York, NY, USA.
Objectives:
The purpose was to assess whether combining patient reported scores (VVSymQ®) and physician reported scores (VCSS) stratifies disease severity in C2 patients.
Methods:
Consecutive patients were pooled from the VANISH-1 and VANISH-2 cohorts. VCSS and VVSymQ® were calculated for each patient. The relationship between scoring systems was evaluated using Pearson's correlation and frequency distribution analysis.
Results:
Two-hundred and ten C2 limbs were included. Scoring systems demonstrated: VVSymQ®: mean = 8.72; VCSS: mean = 6.32; correlation (r = 0.22, p = 0.05). Frequency distribution analysis demonstrated 61.4% of patients had low VVSymQ® and low VCSS; 31.3% had elevated VVSymQ® and increased VCSS; 7.3% were inconsistent with C2 disease. Strict concordance analysis revealed 40.5% had VVSymQ® (< 9)/VCSS (0-6), 18.6% had VVSymQ® (≥ 9)/VCSS (7-9), and 2.9% had VVSymQ® (≥9)/VCSS (≥10).
Conclusions:
For combined elevated VVSymQ® and VCSS, moderate/severe disease is corroborated, and intervention may be indicated. For combined lower scores, the disease severity is mild and conservative therapy is more appropriate.
Related Concept Videos
Classification of Illness
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

