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Development of an HCV infection risk stratification algorithm for patients on chronic hemodialysis
Steven K Herrine1, Beckie Michael, Wai Li Ma
1Department of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, USA.
Insights
Hepatitis C virus (HCV) screening in hemodialysis (HD) patients is improved by a new algorithm. This strategy combines lower transaminase levels with clinical factors, enhancing detection accuracy for HCV infection in HD populations.
Area of Science:
- Nephrology
- Hepatology
- Clinical Chemistry
Background:
- Hepatitis C virus (HCV) affects approximately 9% of patients undergoing chronic hemodialysis (HD).
- Standard transaminase levels (AST, ALT) are often lower in HD patients, limiting their effectiveness for HCV screening.
- Accurate HCV detection is crucial in this vulnerable population to prevent disease progression and transmission.
Purpose of the Study:
- To develop an improved risk stratification strategy for HCV infection in chronic HD patients.
- To incorporate lowered aminotransferase levels and other clinical parameters into an effective screening algorithm.
- To enhance the sensitivity and specificity of HCV detection in the HD population.
Main Methods:
- Serum samples from 168 HD patients were analyzed for AST, ALT, ferritin, and hepatitis C antibody.
- Sensitivity, specificity, and predictive values were calculated for adjusted transaminase cutoff values.
- Multivariate classification and regression tree analysis identified key variables for predicting HCV risk.
Main Results:
- Lowered cutoff values for ALT (16 IU/L) and AST (18 IU/L) improved detection sensitivity and specificity.
- An algorithm combining patient age, months on HD, and AST achieved 97.2% sensitivity and 51.9% specificity for HCV detection.
- Median AST and ALT levels were significantly higher in anti-HCV antibody-positive patients.
Conclusions:
- Adjusted lower cutoff values for AST and ALT enhance HCV detection in HD patients.
- A novel algorithm integrating clinical parameters with transaminase levels significantly improves HCV screening accuracy.
- Prospective validation of this algorithm could lead to more targeted HCV testing in dialysis units, optimizing resource allocation.
Objective:
The prevalence of hepatitis C virus (HCV) in patients on chronic hemodialysis (HD) is near 9%. Transaminases, which are lower in HD patients, are not effective in screening for HCV. Our aim was to design an HCV risk stratification strategy incorporating lowered aminotransferase levels and other clinical parameters.
Methods:
Patient serum from 168 consecutive HD patients was analyzed for AST, ALT, ferritin, and hepatitis C antibody. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for lower transaminase values. Multivariate classification and regression tree analysis was used to determine the best combination of variables to predict risk for HCV infection.
Results:
Median AST and ALT levels were higher in anti-HCV Ab(+) patients (p < 0.05). Applying a lower cutoff value for ALT of 16 IU/L resulted in a sensitivity of 61.1%, a specificity of 66.7%, a positive predictive value of 33.9%, and a negative predictive value of 86.0% for detection of HCV infection. Multivariate classification and regression tree analysis derived an algorithm using patient age, months on HD, and AST, resulting in a 97.2% sensitivity and a 51.9% specificity for the detection of HCV(+) HD patients.
Conclusions:
A lower normal cutoff value of 18 IU/L for AST and 16 IU/L for ALT increased sensitivity and specificity for the detection of HCV infection in HD patients. An algorithm combining lower transaminases with clinical parameters improved both sensitivity and specificity in HCV detection. Prospective confirmation of this algorithm would allow more selective HCV enzyme immunoassay and polymerase chain reaction testing in dialysis units.