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Record W3091499839 · doi:10.1097/cce.0000000000000238

Quantification of Neurological Blood-Based Biomarkers in Critically Ill Patients With Coronavirus Disease 2019

2020· article· en· W3091499839 on OpenAlexafffund
Jennifer Cooper, Sophie Stukas, Ryan L. Hoiland, Nicholas A. Fergusson, Sonny Thiara, Denise Foster, Anish R. Mitra, A. Jon Stoessl, William J. Panenka, Mypinder S. Sekhon, Cheryl L. Wellington

Bibliographic record

VenueCritical Care Explorations · 2020
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsInternational Collaboration On Repair DiscoveriesCanadian Sport Centre PacificUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersVancouver Coastal Health Research Institute
KeywordsMedicineDeliriumIntensive careInternal medicineGlial fibrillary acidic proteinCoronavirusGastroenterologyRespiratory failurePathologyDiseaseImmunologyIntensive care medicineCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Objectives: To provide an objective characterization of acute neurologic injury in critically ill patients with coronavirus disease 2019. Design: Prospective observational study. Demographics, comorbidities, and daily clinical physiologic and laboratory data were collected. Plasma levels of neurofilament-light chain, total tau, ubiquitin carboxy-terminal hydrolase L1, and glial fibrillary acidic protein were measured. The primary neurologic outcome was delirium defined by the Intensive Care Delirium Screening Checklist (scale 1–8). Associations among plasma biomarkers, respiratory failure, and inflammation were analyzed. Setting: Multicenter study in ICUs. Patients: Critically ill patients with respiratory failure, with coronavirus disease 2019, or without (ICU control). Measurements and Main Results: A total of 27 patients with coronavirus disease 2019 and 19 ICU controls were enrolled. Compared with ICU controls with pneumonia of other etiology, patients with coronavirus disease 2019 had significantly higher glial fibrillary acidic protein (272 pg/mL [150–555 pg/mL] vs 118 pg/mL [78.5–168 pg/mL]; p = 0.0009). In coronavirus disease 2019 patients, glial fibrillary acidic protein (rho = 0.5115, p = 0.0064), ubiquitin carboxy-terminal hydrolase L1 (rho = 0.4056, p = 0.0358), and neurofilament-light chain (rho = 0.6223, p = 0.0005) positively correlated with Intensive Care Delirium Screening Checklist score and were increased in patients with delirium (Intensive Care Delirium Screening Checklist ≥ 4) in the coronavirus disease 2019 group but not in ICU controls. There were no associations between the measures of respiratory function or cytokines with glial fibrillary acidic protein, total tau, ubiquitin carboxy-terminal hydrolase L1, or neurofilament-light chain levels in patients with coronavirus disease 2019. Conclusions: Plasma glial fibrillary acidic protein is two-fold higher in critically ill patients with coronavirus disease 2019 compared with ICU controls. Higher levels of glial fibrillary acidic protein, ubiquitin carboxy-terminal hydrolase L1, and neurofilament-light chain associate with delirium in patients with coronavirus disease 2019. Elevated plasma glial fibrillary acidic protein, ubiquitin carboxy-terminal hydrolase L1, and neurofilament-light chain are independent of respiratory function and peripheral cytokines.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.055
GPT teacher head0.323
Teacher spread0.268 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations51
Published2020
Admission routes2
Has abstractyes

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