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Predicting Coma Trajectories: The Impact of Bias and Noise on Shared Decisions

Coma trajectories are characterized by quick awakening or protracted awakening. Outcome is bookended by restored functionality or permanent cognitively and physically debilitated states. Given the stakes, prognostication cannot be easily questioned as a judgment call, and a scientific underpinning i...

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Detalles Bibliográficos
Autores principales: Wijdicks, Eelco F. M., Hwang, David Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382106/
https://www.ncbi.nlm.nih.gov/pubmed/34426900
http://dx.doi.org/10.1007/s12028-021-01324-y
Descripción
Sumario:Coma trajectories are characterized by quick awakening or protracted awakening. Outcome is bookended by restored functionality or permanent cognitively and physically debilitated states. Given the stakes, prognostication cannot be easily questioned as a judgment call, and a scientific underpinning is elemental. Conventional wisdom in determining coma-outcome trajectories posits that (1) predictive models are better than personal experiences, (2) self-fulfilling prophesy is unchecked and driven by nihilism, with little regard for prior probability outcomes, and (3) recovery is impacted by patients’ prior wishes and preexisting medical conditions—but also by what families are told about the patient’s state and anticipated clinical course. Moreover, a predicted good outcome can be offset by a major subsequent complication, or a predicted poor outcome can be offset by aggressive care. This article examines some of these concepts, including how we decide on aggressiveness of care, how we judge quality of life, and the impact on outcome. Most patients who awaken quickly do well and can resume their pretrauma injury lives. In worse off, slow-to-awaken patients, outcomes are a mixed bag of limited innate resilience, depleted cognitive and physical reserves, and adjusted quality of life. Bias and noise are factors not easily measured in outcome prediction, but their influence on recovery trajectories raises some troubling issues.