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Record W4320857743 · doi:10.1017/cjn.2023.23

Factors Predicting Prolonged Mechanical Ventilation in Guillain–Barré Syndrome

2023· article· en· W4320857743 on OpenAlexvenueno aff
Juan Carlos López‐Hernández, Edwin Steven Vargas-Cañas, Javier Andrés Galnares‐Olalde, Jorge Alberto López-Alderete, Alejandro López-Pizano, Mijail Adán Rivas-Cruz, Jesús Arturo Violante-Villanueva, Elma Paredes‐Aragón

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2023
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMechanical ventilationMedicineGuillain-Barre syndromeVentilation (architecture)AnesthesiaCompound muscle action potentialRisk factorMedian nerveInternal medicineSurgeryElectrophysiologyPediatrics

Abstract

fetched live from OpenAlex

ABSTRACT: Background: Up to 30% of patients with Guillain–Barré syndrome require mechanical ventilation and 5% die due to acute complications of mechanical ventilation. There is a considerable group of patients that will need prolonged mechanical ventilation (considered as >14 days) and should be considered for early tracheostomy. The objective of this study is to identify risk factors for prolonged mechanical ventilation. Methods: We prospectively analyzed patients with Guillain–Barré diagnosis with versus without prolonged mechanical ventilation. We considered clinical and electrophysiological characteristics and analyzed factors associated with prolonged mechanical ventilation. Results: Three hundred and three patients were included; 29% required mechanical ventilation. When comparing the groups, patients with prolonged invasive mechanical ventilation (IMV) have a lower score on the Medical Research Council score (19.5 ± 16.2 vs 27.4 ± 17.5, p = 0.03) and a higher frequency of dysautonomia (42.3% vs 19.4%, p = 0.037), as well as lower amplitudes of the distal compound muscle action potential (CMAP) of the median nerve [0.37 (RIQ 0.07–2.25) vs. 3.9 (RIQ1.2–6.4), p = <0.001] and ulnar nerve [0.37 (RIQ0.0–3.72) vs 1.5 (RIQ0.3–6.6), p = <0.001], and higher frequency of severe axonal damage in these nerves (distal CMAP ≤ 1.0 mV). Through binary logistic regression, severe axonal degeneration of the median nerve is an independent risk factor for prolonged IMV OR 4.9 (95%CI 1.1–21.5) p = 0.03, AUC of 0.774, (95%CI 0.66–0.88), p = < 0.001. Conclusions: Severe median nerve damage is an independent risk factor for prolonged mechanical ventilation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.284
Teacher spread0.232 · 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 teacher head, not a consensus.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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