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Record W2415999633 · doi:10.5935/0103-507x.20150036

A guided approach to diagnose severe muscle weakness in the intensive care unit

2015· article· en· W2415999633 on OpenAlexaff
Nicola Latronico, Rik Gosselink

Bibliographic record

VenueRevista Brasileira de Terapia Intensiva · 2015
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineIntensive care unitWeaknessIntensive care medicineMuscle weaknessPhysical medicine and rehabilitationInternal medicineSurgery

Abstract

fetched live from OpenAlex

A guided approach to diagnose severe muscle weakness in the intensive care unit COMMENTARY Intensive care unit (ICU) acquired muscle weakness (ICUAW) is a clinically detected condition characterized by diffuse, symmetric weakness involving the limbs and respiratory muscles.(1) Patients have different degrees of limb muscle weakness and are dependent on a ventilator, while the facial muscles are spared.Diagnosis of ICUAW requires that no plausible etiology other than critical illness be identified, and thus, other causes of acute muscle weakness are excluded.One major diagnostic criterion is that ICUAW is detected after the onset of critical illness; therefore, it is important to differentiate ICUAW from Guillain-Barrè syndrome or other acute neuromuscular disorders that may cause respiratory failure and ICU admission (Figure 1).(1) The use of neuromuscular blocking agents for long periods of time, the use of some antibiotics and electrolyte abnormalities, such as hypermagnesemia, hypokalemia, hypercalcemia, and hypophosphatemia, and prolonged immobilization are common in the ICU and should be appropriately treated before a diagnosis of ICUAW is posed.(2) A diagnosis of ICUAW is achieved by manually testing the muscle strength using the Medical Research Council (MRC) scale or by measuring handgrip strength using a dynamometer.MRC muscle strength is assessed in 12 muscle groups (Figure 2): a summed score below 48/60 designates ICUAW or significant weakness, and an MRC score below 36/48 indicates severe weakness.(3) Recently, a simplified version of the scale with only four categories and improved clinimetric properties was proposed (Figure 2).(4) To date, this version has been validated in a small cohort of 60 critically ill patients with excellent inter-rater reliability and high sensitivity and specificity in diagnosing ICUAW compared to complete full MRC.(5) Handgrip dynamometry measures isometric muscle strength and can be used as a quick diagnostic test.Cut-off scores of less than 11kg (IQR 10 -40) in males and less than 7kg (IQR 0 -7.3) in females are considered to be indicative of ICUAW (Figure 1).( 5) Both MRC and handgrip dynamometry are volitional tests and require the patients to be alert, cooperative, and motivated.Sedation, delirium and coma often interfere with the early evaluation of muscle strength in the ICU.However, voluntary muscle strength using the MRC sum score or handgrip dynamometry can be reliably assessed if adequate clinical experience is gained with manual muscle testing in ICU patients and strict guidelines and the use of standardized test procedures and positions are followed to accurately select patients.(6) Common causes of ICUAW include critical illness polyneuropathy (CIP) and myopathy (CIM), which are revealed by appropriate nerve

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)0.002
metaresearch head score (Gemma)0.008
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: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.064
GPT teacher head0.329
Teacher spread0.264 · 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
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

Citations65
Published2015
Admission routes1
Has abstractyes

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