Evidence map›Paper›PMID 27583179›Full record

ArticleSurgical neurology international2016

Clinical outcome prediction in aneurysmal subarachnoid hemorrhage - Alterations in brain-body interface.

Benjamin W Y Lo, Hitoshi Fukuda, Mark Angle, Jeanne Teitelbaum, R Loch Macdonald, Forough Farrokhyar, Lehana Thabane, Mitchell A H Levine

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Surgical neurology international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 87% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Observational
  2. Article
  3. 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

8 authors at 4 institutions in 1 country.

Benjamin W Y LoDepartment of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
Hitoshi FukudaDepartment of Neurosurgery, Kurashiki Central Hospital, Kyoto University, Okayama, Japan.
Mark AngleDepartment of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
Jeanne TeitelbaumDepartment of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada.
R Loch MacdonaldDivision of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
Forough FarrokhyarDepartment of Surgery, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada.
Lehana ThabaneDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada.
Mitchell A H LevineDepartment of Medicine, Division of Clinical Pharmacology, Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada.
McGill University · CAMcMaster University · CAMontreal Neurological Institute and Hospital · CASt. Michael's Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBrain-body associations are essential in influencing outcome in patients with ruptured brain aneurysms. Thus far, there is scarce literature on such important relationships.

methodsThe multicenter Tirilazad database (3551 patients) was used to create this clinical outcome prediction model in order to elucidate significant brain-body associations. Traditional binary logistic regression models were used.

resultsBinary logistic regression main effects model included four statistically significant single prognostic variables, namely, neurological grade, age, stroke, and time to surgery. Logistic regression models demonstrated the significance of hypertension and liver disease in development of brain swelling, as well as the negative consequences of seizures in patients with a history of myocardial infarction and post-admission fever worsening neurological outcome.

conclusionsUsing the aforementioned results generated from binary logistic regression models, we can identify potential patients who are in the high risk group of neurological deterioration. Specific therapies can be tailored to prevent these detriments, including treatment of hypertension, seizures, early detection and treatment of myocardial infarction, and prevention of hepatic encephalopathy.

Indexed as

Aneurysmal subarachnoid hemorrhagebrain-body interactionsclinical outcome prediction model

Identifiers

PMID27583179
PMCPMC4982352
OpenAlexW2522612301

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.