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DOI 10.3390/toxins14080508

Медицинская библиотека · Toxins · 2022

Individual Response to Botulinum Toxin Therapy in Movement Disorders: A Time Series Analysis Approach.

Leplow Bernd, Pohl Johannes, Wöllner Julia, Weise David

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

On a group level, satisfaction with botulinum neurotoxin (BoNT) treatment in neurological indications is high. However, it is well known that a relevant amount of patients may not respond as expected. The aim of this study is to evaluate the BoNT treatment outcome on an individual level using a statistical single-case analysis as an adjunct to traditional group statistics. The course of the daily perceived severity of symptoms across a BoNT cycle was analyzed in 20 cervical dystonia (CD) and 15 hemifacial spasm (HFS) patients. A parametric single-case autoregressive integrated moving average (ARIMA) time series analysis was used to detect individual responsiveness to BoNT treatment. Overall, both CD and HFS patients significantly responded to BoNT treatment with a gradual worsening of symptom intensities towards BoNT reinjection. However, only 8/20 CD patients (40%) and 5/15 HFS patients (33.3%) displayed the expected U-shaped curve of BoNT efficacy across a single treatment cycle. CD (but not HFS) patients who followed the expected outcome course had longer BoNT injection intervals, showed a better match to objective symptom assessments, and were characterized by a stronger certainty to control their somatic symptoms (i.e., internal medical locus of control). In addition to standard evaluation procedures, patients should be identified who do not follow the mean course-of-treatment effect. Thus, the ARIMA single-case time series analysis seems to be an appropriate addition to clinical treatment studies in order to detect individual courses of subjective symptom intensities.

Для цитирования: Leplow Bernd, Pohl Johannes, Wöllner Julia, Weise David. Individual Response to Botulinum Toxin Therapy in Movement Disorders: A Time Series Analysis Approach.. Toxins. 2022. DOI: 10.3390/toxins14080508.

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