AIMS: Alcohol withdrawal seizures (AWS) are among the most important possible complications during the detoxification treatment of alcohol-dependent patients. Pharmacological therapy is often used during detoxification, but can cause dangerous side effects [Eur Addict Res 2010;16:179-184]. In separate studies several biological markers have been described as being associated with AWS risk. We investigated the role of homocysteine (HCT), carbohydrate-deficient transferrin (CDT) and prolactin (PRL) as biological markers for the risk of developing AWS. METHODS: The present study included 189 alcohol-dependent patients of whom 51 had a history of AWS. We investigated the HCT, CDT and PRL levels of all patients and calculated sensitivity and specificity. Bayes' theorem was used to calculate positive (PPV) and negative (NPV) predictive values. RESULTS: The highest combined sensitivity and specificity for %CDT was reached at a plasma cutoff value of 3.75%. The combination of HCT at a cutoff value of 23.9 μmol/l and %CDT at a cutoff value of 3.75% showed the best predictive values (sensitivity 47.1%, specificity 88.4%, PPV 0.504, NPV 0.870). CONCLUSION: A combined assessment of HCT and CDT levels can be a useful method to identify patients at a higher risk of AWS, which may lead to a more individualized therapy.
AIMS: Alcohol withdrawal seizures (AWS) are among the most important possible complications during the detoxification treatment of alcohol-dependent patients. Pharmacological therapy is often used during detoxification, but can cause dangerous side effects [Eur Addict Res 2010;16:179-184]. In separate studies several biological markers have been described as being associated with AWS risk. We investigated the role of homocysteine (HCT), carbohydrate-deficient transferrin (CDT) and prolactin (PRL) as biological markers for the risk of developing AWS. METHODS: The present study included 189 alcohol-dependent patients of whom 51 had a history of AWS. We investigated the HCT, CDT and PRL levels of all patients and calculated sensitivity and specificity. Bayes' theorem was used to calculate positive (PPV) and negative (NPV) predictive values. RESULTS: The highest combined sensitivity and specificity for %CDT was reached at a plasma cutoff value of 3.75%. The combination of HCT at a cutoff value of 23.9 μmol/l and %CDT at a cutoff value of 3.75% showed the best predictive values (sensitivity 47.1%, specificity 88.4%, PPV 0.504, NPV 0.870). CONCLUSION: A combined assessment of HCT and CDT levels can be a useful method to identify patients at a higher risk of AWS, which may lead to a more individualized therapy.
Authors: S Jesse; G Bråthen; M Ferrara; M Keindl; E Ben-Menachem; R Tanasescu; E Brodtkorb; M Hillbom; M A Leone; A C Ludolph Journal: Acta Neurol Scand Date: 2016-09-01 Impact factor: 3.209