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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

Neuroprognostication: a conceptual framework.

David Fischer^1,2, Brian L Edlow^3,4, Joseph T Giacino⁵

¹Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. d.b.fisch@gmail.com.

Nature Reviews. Neurology

|March 30, 2022

Summary

This summary is machine-generated.

Predicting recovery from brain injury (neuroprognostication) is complex. This study presents a structured framework to improve clinical decision-making for patients with disorders of consciousness, aiding treatment choices.

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Area of Science:

Neurology
Critical Care Medicine
Medical Ethics

Background:

Neuroprognostication, predicting recovery from disorders of consciousness after severe brain injury, is critical but complex.
Current clinical approaches are often unsystematic, leading to variability and errors in patient care.
Factors influencing neuroprognostication include biomedical, probabilistic, psychosocial, and ethical considerations.

Purpose of the Study:

To introduce a stepwise conceptual framework for systematic neuroprognostic reasoning.
To provide guidance for evaluating neurological function and recovery trajectories.
To develop a clinically actionable approach for weighing treatment risks and benefits.

Main Methods:

Developing a structured framework for neuroprognostic determinations.
Integrating neurological assessment, recovery trajectory estimation, goals of care, and patient values.
Formulating a method for assessing risks and benefits of life-sustaining treatments.

Main Results:

A stepwise conceptual framework is proposed to enhance clinical judgment in neuroprognostication.
The framework aims to standardize the evaluation process for disorders of consciousness.
It offers a structured approach to complement clinical decision-making.

Conclusions:

A systematic approach can provide structure and guidance to the complex process of neuroprognostication.
This framework can supplement clinical judgment and reduce errors in predicting recovery from brain injury.
Further investigation is directed towards refining this structured approach for improved patient outcomes.