Literature DB >> 28763355

Regulatory Considerations for Physiological Closed-Loop Controlled Medical Devices Used for Automated Critical Care: Food and Drug Administration Workshop Discussion Topics.

Bahram Parvinian1,2, Christopher Scully2, Hanniebey Wiyor1, Allison Kumar3, Sandy Weininger2.   

Abstract

Part of the mission of the Center for Devices and Radiological Health (CDRH) at the US Food and Drug Administration is to facilitate medical device innovation. Therefore, CDRH plays an important role in helping its stakeholders such as manufacturers, health care professionals, patients, patient advocates, academia, and other government agencies navigate the regulatory landscape for medical devices. This is particularly important for innovative physiological closed-loop controlled (PCLC) devices used in critical care environments, such as intensive care units, emergency settings, and battlefield environments. CDRH's current working definition of a PCLC medical device is a medical device that incorporates physiological sensor(s) for automatic manipulation of a physiological variable through actuation of therapy that is conventionally made by a clinician. These emerging devices enable automatic therapy delivery and may have the potential to revolutionize the standard of care by ensuring adequate and timely therapy delivery with improved performance in high workload and high-stress environments. For emergency response and military applications, automatic PCLC devices may play an important role in reducing cognitive overload, minimizing human error, and enhancing medical care during surge scenarios (ie, events that exceed the capability of the normal medical infrastructure). CDRH held an open public workshop on October 13 and 14, 2015 with the aim of fostering an open discussion on design, implementation, and evaluation considerations associated with PCLC devices used in critical care environments. CDRH is currently developing regulatory recommendations and guidelines that will facilitate innovation for PCLC devices. This article highlights the contents of the white paper that was central to the workshop and focuses on the ensuing discussions regarding the engineering, clinical, and human factors considerations.

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Mesh:

Year:  2018        PMID: 28763355      PMCID: PMC6233305          DOI: 10.1213/ANE.0000000000002329

Source DB:  PubMed          Journal:  Anesth Analg        ISSN: 0003-2999            Impact factor:   5.108


  18 in total

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Review 2.  Trust in automation: designing for appropriate reliance.

Authors:  John D Lee; Katrina A See
Journal:  Hum Factors       Date:  2004       Impact factor: 2.888

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Authors:  A Palladino; G Fiengo; D Lanzo
Journal:  ISA Trans       Date:  2011-11-08       Impact factor: 5.468

4.  A direct dynamic dose-response model of propofol for individualized anesthesia care.

Authors:  Jin-Oh Hahn; Guy A Dumont; J Mark Ansermino
Journal:  IEEE Trans Biomed Eng       Date:  2011-11-24       Impact factor: 4.538

Review 5.  Complacency and bias in human use of automation: an attentional integration.

Authors:  Raja Parasuraman; Dietrich H Manzey
Journal:  Hum Factors       Date:  2010-06       Impact factor: 2.888

6.  Closed-loop systems in anesthesia: reality or fantasy?

Authors:  Timothy E Miller; Tong J Gan
Journal:  Anesth Analg       Date:  2013-11       Impact factor: 5.108

Review 7.  Automation bias: a systematic review of frequency, effect mediators, and mitigators.

Authors:  Kate Goddard; Abdul Roudsari; Jeremy C Wyatt
Journal:  J Am Med Inform Assoc       Date:  2011-06-16       Impact factor: 4.497

Review 8.  Review article: closed-loop systems in anesthesia: is there a potential for closed-loop fluid management and hemodynamic optimization?

Authors:  Joseph Rinehart; Ngai Liu; Brenton Alexander; Maxime Cannesson
Journal:  Anesth Analg       Date:  2011-09-29       Impact factor: 5.108

Review 9.  Automated respiratory support in newborn infants.

Authors:  Nelson Claure; Eduardo Bancalari
Journal:  Semin Fetal Neonatal Med       Date:  2008-10-01       Impact factor: 3.926

10.  Platform for real-time simulation of dynamic systems and hardware-in-the-loop for control algorithms.

Authors:  Isaac D T de Souza; Sergio N Silva; Rafael M Teles; Marcelo A C Fernandes
Journal:  Sensors (Basel)       Date:  2014-10-15       Impact factor: 3.576

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  9 in total

1.  Evaluation of Fluid Resuscitation Control Algorithms via a Hardware-in-the-Loop Test Bed.

Authors:  Hossein Mirinejad; Bahram Parvinian; Margo Ricks; Yi Zhang; Sandy Weininger; Jin-Oh Hahn; Christopher G Scully
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-08       Impact factor: 4.538

2.  A Century of Technology in Anesthesia & Analgesia.

Authors:  Jane S Moon; Maxime Cannesson
Journal:  Anesth Analg       Date:  2022-07-15       Impact factor: 6.627

3.  Practical Use of Regularization in Individualizing a Mathematical Model of Cardiovascular Hemodynamics Using Scarce Data.

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Journal:  Front Physiol       Date:  2020-05-26       Impact factor: 4.566

Review 4.  Artificial intelligence and anesthesia: A narrative review.

Authors:  Madhavi Singh; Gita Nath
Journal:  Saudi J Anaesth       Date:  2022-01-04

Review 5.  Closed-Loop Controlled Fluid Administration Systems: A Comprehensive Scoping Review.

Authors:  Guy Avital; Eric J Snider; David Berard; Saul J Vega; Sofia I Hernandez Torres; Victor A Convertino; Jose Salinas; Emily N Boice
Journal:  J Pers Med       Date:  2022-07-18

6.  Advancing Regulatory Science With Computational Modeling for Medical Devices at the FDA's Office of Science and Engineering Laboratories.

Authors:  Tina M Morrison; Pras Pathmanathan; Mariam Adwan; Edward Margerrison
Journal:  Front Med (Lausanne)       Date:  2018-09-25

7.  Variability in pharmacologically-induced coma for treatment of refractory status epilepticus.

Authors:  Jingzhi An; Durga Jonnalagadda; Valdery Moura; Patrick L Purdon; Emery N Brown; M Brandon Westover
Journal:  PLoS One       Date:  2018-10-31       Impact factor: 3.240

Review 8.  The dawn of physiological closed-loop ventilation-a review.

Authors:  Philip von Platen; Anake Pomprapa; Burkhard Lachmann; Steffen Leonhardt
Journal:  Crit Care       Date:  2020-03-29       Impact factor: 9.097

Review 9.  Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs).

Authors:  Jennifer C Goldsack; Andrea Coravos; Jessie P Bakker; Brinnae Bent; Ariel V Dowling; Cheryl Fitzer-Attas; Alan Godfrey; Job G Godino; Ninad Gujar; Elena Izmailova; Christine Manta; Barry Peterson; Benjamin Vandendriessche; William A Wood; Ke Will Wang; Jessilyn Dunn
Journal:  NPJ Digit Med       Date:  2020-04-14
  9 in total

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