Individual dose-response models for levodopa infusion dose optimization.

Background and Objective: To achieve optimal effect with continuous infusion treatment in Parkinson's disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing sugges...

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Publicado en:International Journal of Medical Informatics Vol. 112; pp. 137 - 143
Autores principales: Thomas, Ilias, Alam, Moudud, Nyholm, Dag, Senek, Marina, Westin, Jerker
Formato: research Journal Article
Publicado: Elsevier B.V. Apr2018
Acceso en línea:Ver este registro en EBSCOhost
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      issn: 13865056
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      dt: Apr2018
      vid: 112
      pid: 467
      pub: Elsevier B.V.
      place: New York, New York
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        128227030
        128227030
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        10.1016/j.ijmedinf.2018.01.018
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        atl: Individual dose-response models for levodopa infusion dose optimization.
      aug:
        au:
          Thomas, Ilias
          Alam, Moudud
          Nyholm, Dag
          Senek, Marina
          Westin, Jerker
        affil: Department of Micro-data analysis, Dalarna University, Falun, 79 131, Sweden
      sug:
        subj:
          Parkinson Disease Drug Therapy
          Antiparkinson Agents Administration and Dosage
          Hospitalization Statistics and Numerical Data
          Levodopa Administration and Dosage
          Algorithms
          Computer Simulation
          Human
          Male
          Parkinson Disease Metabolism
          Levodopa Pharmacokinetics
          Antiparkinson Agents Pharmacokinetics
          Dose-Response Relationship, Drug
          Female
          Infusions, Parenteral
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Scales
          Male
          Female
      ab: Background and Objective: To achieve optimal effect with continuous infusion treatment in Parkinson's disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing suggestions for infusion treatment of PD, by fitting individual dose-response models. The feasibility of the proposed method was investigated using patient chart data.Methods: Patient records were collected at Uppsala University hospital which provided dosing information and dose-response evaluations. Mathematical optimization was used to fit individual patient models using the records' information, by minimizing an objective function. The individual models were passed to a dose optimization algorithm, which derived an optimized dosing suggestion for each patient model.Results: Using data from a single day's admission the algorithm showed great ability to fit appropriate individual patient models and derive optimized doses. The infusion rate dosing suggestions had 0.88 correlation and 10% absolute mean relative error compared to the optimal doses as determined by the hospital's treating team. The morning dose suggestions were consistency lower that the optimal morning doses, which could be attributed to different dosing strategies and/or lack of on-off evaluations in the morning.Conclusion: The proposed method showed promise and could be applied in clinical practice, to provide the hospital personnel with additional information when making dose adjustment decisions.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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