Evidence map›Paper›PMID 36337077›Full record

ArticleNeurotrauma reports2022

Prediction of Intracranial Hypertension and Brain Tissue Hypoxia Utilizing High-Resolution Data from the BOOST-II Clinical Trial.

Christos Lazaridis, Aswathy Ajith, Ali Mansour, David O Okonkwo, Ramon Diaz-Arrastia, Anoop Mayampurath

Open access · goldAbstract read
In one paragraph

Article in Neurotrauma reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Management Strategies Based on Multi-Modality Neuromonitoring in Severe Traumatic Brain Injury.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Review
  6. 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

6 authors at 5 institutions in 1 country.

Christos LazaridisDepartments of Neurology and Neurosurgery, University of Chicago Medical Center, University of Chicago, Chicago, Illinois, USA.
Aswathy AjithDepartment of Computer Science, University of Chicago, Chicago, Illinois, USA.
Ali MansourDepartments of Neurology and Neurosurgery, University of Chicago Medical Center, University of Chicago, Chicago, Illinois, USA.
David O OkonkwoDepartment of Neurosurgery, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Ramon Diaz-ArrastiaDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Anoop MayampurathDepartment of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA.
University of Pittsburgh · USUniversity of Chicago Medical Center · USUniversity of Pennsylvania · USUniversity of Chicago · USUniversity of Wisconsin–Madison · US

Funding

Using Machine Learning to Predict Clinical Deterioration in Hospitalized ChildrenK01HL148390 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI MAYAMPURATH, ANOOP · 2019 to 2023
$738k
NHLBI NIH HHS K01 HL148390
6 · The paper itself

Abstract

The current approach to intracranial hypertension and brain tissue hypoxia is reactive, based on fixed thresholds. We used statistical machine learning on high-frequency intracranial pressure (ICP) and partial brain tissue oxygen tension (PbtO

Indexed as

brain hypoxiaintracranial hypertensionpredictionsecondary brain injurytraumatic brain injury

Identifiers

PMID36337077
PMCPMC9622207
OpenAlexW4307720433

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.