Evidence map›Paper›PMID 37491259›Full record

Observational studyJournal of neuroengineering and rehabilitation2023

Neural coding of autonomic functions in different states of consciousness.

Piergiuseppe Liuzzi, Bahia Hakiki, Maenia Scarpino, Rachele Burali, Antonio Maiorelli, Francesca Draghi, Anna Maria Romoli, Antonello Grippo, Francesca Cecchi, Andrea Mannini

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of neuroengineering and rehabilitation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Piergiuseppe LiuzziSant'Anna School of Advanced Studies, The BioRobotics Institute, Viale Rinaldo Piaggio 69, 56025, Pontedera, PI, Italy.
Bahia HakikiIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy. bhakiki@dongnocchi.it.
Maenia ScarpinoIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Rachele BuraliIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Antonio MaiorelliIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Francesca DraghiIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Anna Maria RomoliIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Antonello GrippoIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Francesca CecchiIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Andrea ManniniIRCSS Fondazione Don Carlo Gnocchi ONLUS, Via di Scandicci 269, FI, 50143, Florence, Italy.
Don Carlo Gnocchi Foundation · ITPiaggio (Italy) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS -: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS -). EEG-ECG MI, besides clearly discriminating patients in an MCS - and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions.

Indexed as

BrainConsciousnessAdultElectroencephalographyFemaleHumansPersistent Vegetative StateProspective StudiesWakefulnessYoung AdultBrain–heart interactionDisorders of consciousnessEEG-ECG mutual informationMinimally Consciousness StateQuantitative Correlates of Consciousness

Identifiers

PMID37491259
PMCPMC10369699
OpenAlexW4385264710

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.