The development of a novel knowledge-based weaning algorithm using pulmonary parameters: a simulation study.

Weaning is important for patients and clinicians who have to determine correct weaning time so that patients do not become addicted to the ventilator. There are already some predictors developed, such as the rapid shallow breathing index (RSBI), the pressure time index (PTI), and Jabour weaning inde...

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Publicado en:Medical & Biological Engineering & Computing Vol. 56; no. 3; pp. 373 - 385
Autores principales: Guler, Hasan, Kilic, Ugur
Formato: algorithm equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Mar2018
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2018
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-017-1698-7
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        atl: The development of a novel knowledge-based weaning algorithm using pulmonary parameters: a simulation study.
      aug:
        au:
          Guler, Hasan
          Kilic, Ugur
        affil: Electrical-Electronics Engineering Department, Firat University, Elazig, Turkey
      sug:
        subj:
          Lung Physiology
          Ventilator Weaning
          Computer Simulation
          Knowledge
          Algorithms
          Hydrogen-Ion Concentration
          Blood Pressure
          Glasgow Coma Scale
          Body Temperature
          Hemodynamics
          Logic
          Oxygen Metabolism
          Respiratory Function Tests
          Carbon Dioxide Metabolism
          Blood Gas Analysis
          Hemoglobins Metabolism
          Human
      ab: Weaning is important for patients and clinicians who have to determine correct weaning time so that patients do not become addicted to the ventilator. There are already some predictors developed, such as the rapid shallow breathing index (RSBI), the pressure time index (PTI), and Jabour weaning index. Many important dimensions of weaning are sometimes ignored by these predictors. This is an attempt to develop a knowledge-based weaning process via fuzzy logic that eliminates the disadvantages of the present predictors. Sixteen vital parameters listed in published literature have been used to determine the weaning decisions in the developed system. Since there are considered to be too many individual parameters in it, related parameters were grouped together to determine acid-base balance, adequate oxygenation, adequate pulmonary function, hemodynamic stability, and the psychological status of the patients. To test the performance of the developed algorithm, 20 clinical scenarios were generated using Monte Carlo simulations and the Gaussian distribution method. The developed knowledge-based algorithm and RSBI predictor were applied to the generated scenarios. Finally, a clinician evaluated each clinical scenario independently. The Student's t test was used to show the statistical differences between the developed weaning algorithm, RSBI, and the clinician's evaluation. According to the results obtained, there were no statistical differences between the proposed methods and the clinician evaluations.
      pubtype: Academic Journal
      doctype:
        algorithm
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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