Evidence map›Paper›PMID 30119071›Full record

ArticleCritical care medicine2018

Intracranial Pressure Trajectories: A Novel Approach to Informing Severe Traumatic Brain Injury Phenotypes.

Ruchira M Jha, Jonathan Elmer, Benjamin E Zusman, Shashvat Desai, Ava M Puccio, David O Okonkwo, Seo Young Park, Lori A Shutter, Jessica S Wallisch, Yvette P Conley and 1 more

Abstract read
In one paragraph

Article in Critical care medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 64 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025
    Review
  10. Article
  11. Article
  12. Article
  13. Computational Prognostic Modeling in Traumatic Brain Injury.Advances in experimental medicine and biology · 2024
    Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 1 institution in 1 country.

Ruchira M Jha
Jonathan ElmerDepartment of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Benjamin E ZusmanDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Shashvat DesaiDepartment of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Ava M PuccioDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
David O OkonkwoDepartment of Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Seo Young ParkDepartment of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Lori A Shutter
Jessica S WallischDepartment of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Yvette P ConleyClinical and Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Patrick M KochanekDepartment of Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
University of Pittsburgh · US

Funding

Institutional Career Development CoreKL2TR001856 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI RAY, KRISTIN N, RUBIO, DORIS M · 2016 to 2025
$13.8M
University of Pittsburgh Clinical and Translational Science InstitutionKL2TR000146 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$8.7M
Genomic Variability and Symptomatology After Traumatic Brain InjuryR01NR013342 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CONLEY, YVETTE P · 2011 to 2013
$1.2M
Quantitative electroencephalography after cardiac arrestK23NS097629 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ELMER, JONATHAN · 2017 to 2021
$945k
Translational assessment of sulfonylurea receptor-1 as a biomarker and therapeutic target for cerebral edema in traumatic brain injuryK23NS101036 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI JHA, RUCHIRA MENKA · 2017 to 2021
$944k
Transcriptomics in Traumatic Brain Injury: Relationship to Brain Oxygenation and OutcomesR00NR013176 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PUCCIO, AVA M. · 2014 to 2016
$724k
NCATS NIH HHS KL2 TR000146NCATS NIH HHS KL2 TR001856NINDS NIH HHS K23 NS097629NINDS NIH HHS K23 NS101036NINR NIH HHS R00 NR013176NINR NIH HHS R01 NR013342
6 · The paper itself

Abstract

objectivesIntracranial pressure in traumatic brain injury is dynamic and influenced by factors like injury patterns, treatments, and genetics. Existing studies use time invariant summary intracranial pressure measures thus potentially losing critical information about temporal trends. We identified longitudinal intracranial pressure trajectories in severe traumatic brain injury and evaluated whether they predicted outcome. We further interrogated the model to explore whether ABCC8 polymorphisms (a known cerebraledema regulator) differed across trajectory groups.

designProspective observational cohort.

settingSingle-center academic medical center. PATIENTS: Four-hundred four severe traumatic brain injury patients.

interventionsNone. MEASUREMENTS AND MAIN

resultsWe used group-based trajectory modeling to identify hourly intracranial pressure trajectories in days 0-5 post traumatic brain injury incorporating risk factor adjustment (age, sex, Glasgow Coma Scale 6score, craniectomy, primary hemorrhage pattern). We compared 6-month outcomes (Glasgow Outcome Scale, Disability Rating Scale, mortality) and ABCC8 tag-single-nucleotide polymorphisms associated with cerebral edema (rs2237982, rs7105832) across groups. Regression models determined whether trajectory groups predicted outcome. A six trajectory group model best fit the data, identifying cohorts differing in initial intracranial pressure, evolution, and number/proportion of spikes greater than 20 mm Hg. There were pattern differences in age, hemorrhage type, and craniectomy rates. ABCC8 polymorphisms differed across groups. GOS (p = 0.006), Disability Rating Scale (p = 0.001), mortality (p < 0.0001), and rs2237982 (p = 0.035) differed across groups. Unfavorable outcomes were surprisingly predicted by both low intracranial pressure trajectories and sustained intracranial hypertension. Intracranial pressure variability differed across groups (p < 0.001) and may reflect preserved/impaired intracranial elastance/compliance.

conclusionsWe employed a novel approach investigating longitudinal/dynamic intracranial pressure patterns in traumatic brain injury. In a risk adjusted model, six groups were identified and predicted outcomes. If validated, trajectory modeling may be a first step toward developing a new, granular approach for intracranial pressure phenotyping in conjunction with other phenotyping tools like biomarkers and neuroimaging. This may be particularly relevant in light of changing traumatic brain injury demographics toward the elderly.

Indexed as

AdultAgedBrain Injuries, TraumaticFemaleHumansIntracranial HypertensionIntracranial PressureMaleMiddle AgedOutcome Assessment, Health CareRisk FactorsSeverity of Illness IndexSulfonylurea ReceptorsABCC8 protein, humanSulfonylurea Receptors

Identifiers

PMID30119071
PMCPMC6185785
OpenAlexW2887702453

What OpenQuestion holds

Textmetadata
LicenceTDM
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.