Bayesian prediction of treatment outcome in anorexia nervosa: a preliminary study.

Autor: Pohjolainen V; Veera Pohjolainen, Hospital District of Helsinki and Uusimaa, Department of Psychiatry, Helsinki, Health Centre, Department of Psychiatry, Helsinki, and University of Helsinki , Helsinki , Finland., Ryynänen OP, Räsänen P, Roine RP, Koponen S, Karlsson H
Jazyk: angličtina
Zdroj: Nordic journal of psychiatry [Nord J Psychiatry] 2015 Apr; Vol. 69 (3), pp. 210-5. Date of Electronic Publication: 2014 Oct 07.
DOI: 10.3109/08039488.2014.962612
Abstrakt: Background: Knowledge of the prognostic factors predicting treatment outcome in anorexia nervosa (AN) measured with health-related quality of life (HRQoL) is limited.
Aims: We performed a novel statistical analysis to identify factors predicting treatment outcome in AN.
Methods: 39 patients entering treatment of an ICD-10-defined AN completed the 15D HRQoL survey, the Eating Disorder Inventory (EDI) and a questionnaire evaluating self reported health status and eating habits before and 2 years after the start of treatment. The analysis was based on a Bayesian approach, which allows analyses of small data sets, and was performed using a naïve Bayes classifier.
Results: An impaired follow-up HRQoL score was associated with three baseline risk factors: low self-reported vitality, high scores in eating control and a poor reported health status. Low baseline body mass index (BMI) and a high score in the eating dimension of the 15D predicted low follow-up BMI.
Conclusions: In our preliminary study, we identified a set of variables predicting poor HRQoL in AN. An effort to treat these symptoms effectively in the beginning of AN treatment may influence the outcome.
Databáze: MEDLINE
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