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DOI 10.1515/cclm-2016-0442

Медицинская библиотека · Clinical chemistry and laboratory medicine · 2017

Retrospective validation of a β-trace protein interpretation algorithm for the diagnosis of cerebrospinal fluid leakage.

Bernasconi Luca, Pötzl Theresa, Steuer Christian, Dellweg Alexander, Metternich Frank, Huber Andreas R

СтатьяВалидационное исследованиеПеревод пока не подготовлен

Аннотация

BACKGROUND

Cerebrospinal fluid (CSF) leakage is a rare condition that can potentially lead to the development of serious complications. In the last decade, β-trace protein (β-TP) has been shown to be a valuable immunological biomarker that allows prompt and non-invasive identification of CSF leakage. At our institution, the measurement of β-TP has been included in the diagnostic work-up of CSF leakage for more than 10 years. According to our diagnostic algorithm, the presence of CSF in secretion is excluded when β-TP values are <0.7 mg/L, whereas β-TP values ≥1.3 mg/L indicate the presence of CSF in secretion. β-TP values between 0.7 and 1.29 mg/L indicate the presence of CSF if the β-TP ratio (β-TP secretion/β-TP serum) is ≥2. This study aimed to validate this diagnostic algorithm using clinically defined nasal/ear secretions.

METHODS

We performed a retrospective statistical analysis of three β-TP interpretation strategies using data of 236 samples originating from 121 patients with suspect CSF leakage received at our laboratory between 2004 and 2012.

RESULTS

The highest odds ratio was obtained when the proposed algorithm has been used for the interpretation of β-TP results, showing a sensitivity of 98.3% and a specificity of 96%. Positive and negative predictive values were 89.2% and 99.4%, respectively.

CONCLUSIONS

Our data suggest that the proposed β-TP interpretation algorithm is a valuable tool for the diagnosis of CSF leakage in the clinical practice.

Для цитирования: Bernasconi Luca, Pötzl Theresa, Steuer Christian, Dellweg Alexander, Metternich Frank, Huber Andreas R. Retrospective validation of a β-trace protein interpretation algorithm for the diagnosis of cerebrospinal fluid leakage.. Clinical chemistry and laboratory medicine. 2017. DOI: 10.1515/cclm-2016-0442.

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