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Pathophysiology and management of critical illness polyneuropathy and myopathy

2021· article· en· W3139372485 on OpenAlexaff
Kevin J. Cheung, Alasdair Timothy Llewelyn Rathbone, Michel Melanson, Jessica Trier, Benjamin Ritsma, Matti D. Allen

Bibliographic record

VenueJournal of Applied Physiology · 2021
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsCritical illness polyneuropathyMedicineIntensive care medicineMyopathyCritical illnessPsychological interventionIntensive care unitPathophysiologyWeaknessBioinformaticsCritically illPathologyPsychiatrySurgery

Abstract

fetched live from OpenAlex

Critical illness-associated weakness (CIAW) is an umbrella term used to describe a group of neuromuscular disorders caused by severe illness. It can be subdivided into three major classifications based on the component of the neuromuscular system (i.e. peripheral nerves or skeletal muscle or both) that are affected. This includes critical illness polyneuropathy (CIP), critical illness myopathy (CIM), and an overlap syndrome, critical illness polyneuromyopathy (CIPNM). It is a common complication observed in people with critical illness requiring intensive care unit (ICU) admission. Given CIAW is found in individuals experiencing grave illness, it can be challenging to study from a practical standpoint. However, over the past 2 decades, many insights into the pathophysiology of this condition have been made. Results from studies in both humans and animal models have found that a profound systemic inflammatory response and factors related to bioenergetic failure as well as microvascular, metabolic, and electrophysiological alterations underlie the development of CIAW. Current management strategies focus on early mobilization, achieving euglycemia, and nutritional optimization. Other interventions lack sufficient evidence, mainly due to a dearth of large trials. The goal of this Physiology in Medicine article is to highlight important aspects of the pathophysiology of these enigmatic conditions. It is hoped that improved understanding of the mechanisms underlying these disorders will lead to further study and new investigations for novel pharmacologic, nutritional, and exercise-based interventions to optimize patient outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.263
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations54
Published2021
Admission routes1
Has abstractyes

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