Evidence map›Paper›PMID 27214704›Full record

ReviewSeminars in neurology2016

Stages of the Inflammatory Response in Pathology and Tissue Repair after Intracerebral Hemorrhage.

Michael H Askenase, Lauren H Sansing

Abstract readReview
In one paragraph

Review in Seminars in neurology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

72 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  7. Cytokine markers in intracerebral hemorrhage are linked to ventricular imaging and outcomes.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2026
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  16. Review
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12 more citing papers are in PubMed but not listed here.

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

2 authors.

Michael H AskenaseDepartment of Neurology, Yale School of Medicine, New Haven, Connecticut.
Lauren H SansingDepartment of Neurology, Yale School of Medicine, New Haven, Connecticut.

Funding

Targeting Myeloid Populations to Reduce Injury after Intracerebral HemorrhageK08NS078110 · NINDS · YALE UNIVERSITY · PI SANSING, LAUREN H · 2012 to 2016
$938k
NINDS NIH HHS K08 NS078110
6 · The paper itself

Abstract

Intracerebral hemorrhage (ICH) is a major health concern, with high rates of mortality and morbidity and no highly effective clinical interventions. Basic research in animal models of ICH has provided insight into its complex pathology, in particular revealing the role of inflammation in driving neuronal death and neurologic deficits after hemorrhage. The response to ICH occurs in four distinct phases: (1) initial tissue damage and local activation of inflammatory factors, (2) inflammation-driven breakdown of the blood-brain barrier, (3) recruitment of circulating inflammatory cells and subsequent secondary immunopathology, and (4) engagement of tissue repair responses that promote tissue repair and restoration of neurologic function. The development of CNS inflammation occurs over many days after initial hemorrhage and thus may represent an ideal target for treatment of the disease, but further research is required to identify the mechanisms that promote engagement of inflammatory versus anti-inflammatory pathways. In this review, the authors examine how experimental models of ICH have uncovered critical mediators of pathology in each of the four stages of the inflammatory response, and focus on the role of the immune system in these processes.

Indexed as

InflammationAnimalsAnti-Inflammatory AgentsBlood-Brain BarrierCerebral HemorrhageHumansAnti-Inflammatory Agents

Identifiers

PMID27214704
PMCPMC4956485

What OpenQuestion holds

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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.