Evidence map›Paper›PMID 36601217›Full record

ArticleCureus2022

Relationships Between Resting Energy Expenditure and Transcranial Doppler Measurements in Patients With and Without Brain Death.

Ellada Kiourtzieva, Vasilios Grosomanidis, Ekaterini Amaniti, Dimitrios Matamis, Chryssa Pourzitaki

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Technical Considerations in the TCD Evaluation of Cerebral Circulatory Arrest in Death by Neurological Criteria.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    Review
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

5 authors at 4 institutions in 3 countries.

Ellada KiourtzievaDepartment of Anesthesiology and Intensive Care, Aristotle University of Thessaloniki, Thessaloniki, GRC.
Vasilios GrosomanidisDepartment of Anesthesiology and Intensive Care, Aristotle University of Thessaloniki, Thessaloniki, GRC.
Ekaterini AmanitiDepartment of Anesthesiology and Intensive Care, Aristotle University of Thessaloniki, Thessaloniki, GRC.
Dimitrios MatamisIntensive Care Unit, Papageorgiou General Hospital, Thessaloniki, GRC.
Chryssa PourzitakiDepartment of Clinical Pharmacology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, GRC.
Papageorgiou General Hospital · GRAHEPA University Hospital · GRAristotle University of Thessaloniki · GRCambridge School · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Brain metabolism deteriorates during brain death, suggesting that cerebral metabolic measurements could serve as a prognostic factor. The application of transcranial Doppler can be useful in evaluating patients evolving to brain death. Resting energy expenditure is lower than expected in patients with brain death, and this is caused by the decrease in cerebral blood flow and consequently lower oxygen supply. The primary aim of this retrospective study is to investigate the early metabolic changes in patients with clinical criteria of brain death and examine if these changes are related to a gradual decrease in blood flow velocities in the middle cerebral artery. Methods All consecutive patients from 1st June 2018 to 30th April 2022, admitted to the ICU with brain injury and a GCS ≤ 8, were included retrospectively in the study. Patients were allocated into two groups: Group A, patients without clinical signs of brain death (n = 32), and Group B, patients with brain death (n = 34). In each group, three sets of metabolic measurements were performed concomitantly with cerebral blood flow velocities using transcranial Doppler (a) upon admission to the ICU, (b) once hemodynamic stabilization was obtained, and (c) 48 hours after their hemodynamic stabilization or when brain death was confirmed by clinical criteria. Resting energy expenditure (REE) measurements were performed using a metabolic computer. Cerebral blood flow velocities were measured after a period of 30 min using a 2-MHZ 2D ultrasound probe. Results Brain-dead patients had a significant decrease in their metabolic parameters as the cerebral blood flow velocities recorded with the transcranial Doppler deteriorated, (REE Group A = 1667.65 ± 597 vs Group B = 1376.12 ± 615, p = 0.05 and REE predicted Group A = 113.19 ± 44.9 vs Group B = 93.29 ± 41.5, p = 0.066 for measurement 1; REE Group A = 1844 ± 530.9 vs Group B = 1219.97 ± 489, p < 0.001 and REE predicted Group A = 124.38 ± 39 vs Group B = 81.35 ± 30.4, p < 0.001 for measurement 2; REE Group A = 1750.97 ± 414, p < 0.001 and REE predicted Group A = 116.38 ± 19.2 vs Group B = 56.09 ± 19.6, p < 0.001 for measurement 3). Multiple stepwise regression analysis revealed a strong relationship between age, the worsening of the blood flow velocities pattern, and the decrease in REE (multiple R = 0.264, F = 5.55, p = 0.009). Furthermore, a statistically significant correlation was found between temperature and REE (correlation coefficient = 0.500, 0.674, 0.784 for measurements 1, 2, and 3, respectively, and p < 0.001 for all measures). Conclusions In brain-dead patients, the gradual decrease in cerebral blood flow leads to a decrease in REE as well as thermogenetic control. These changes can be detected early after the patient's admission to the ICU.

Indexed as

basal metabolic ratebrain deathbrain injuryresting energy expendituretranscranial doppler sonography

Identifiers

PMID36601217
PMCPMC9804031
OpenAlexW4310490804

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.