Evidence map›Paper›PMID 36934333›Full record

ReviewExpert review of neurotherapeutics2023

Current perspectives on the clinical management of cryptogenic stroke.

Dixon Yang, Mitchell S V Elkind

Open access · greenAbstract readReview
In one paragraph

Review in Expert review of neurotherapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 7% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
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  6. Review
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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 at 2 institutions in 1 country.

Dixon YangDepartment of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Mitchell S V ElkindDepartment of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
American Heart Association · USColumbia University · US

Funding

NEUROEPIDEMIOLOGY TRAINING PROGRAMT32NS007153 · NINDS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI GU, YIAN, WILLEY, JOSHUA ZEBADIAH · 1987 to 2023
$6.2M
NINDS NIH HHS T32 NS007153
6 · The paper itself

Abstract

introductionCryptogenic stroke is a heterogeneous entity defined as an ischemic stroke for which no probable cause is identified despite thorough diagnostic evaluation. Since about a quarter of all ischemic strokes are classified as cryptogenic, it is a commonly encountered problem for providers as secondary stroke prevention is guided by stroke etiology. AREAS COVERED: In this review, the authors provide an overview of stroke subtype classification schemes and diagnostic evaluation in cryptogenic stroke. They then detail putative cryptogenic stroke mechanisms, their therapeutic implications, and ongoing research. This review synthesizes the available evidence on PubMed up to December 2022. EXPERT OPINION: Cryptogenic stroke is an evolving concept that changes with ongoing research. Investigations are focused on improving our diagnostic capabilities and solidifying useful constructs within cryptogenic stroke that could become therapeutically targetable subgroups within an otherwise nonspecific entity. Advances in technology may help move specific proposed cryptogenic stroke mechanisms from undetermined to known source of ischemic stroke.

Indexed as

Ischemic StrokeStrokeHumansSecondary PreventionatherosclerosisAtrial cardiopathyatrial fibrillationcryptogenic strokeembolic stroke of undetermined sourcepatent foramen ovalestroke

Identifiers

PMID36934333
PMCPMC10166643
OpenAlexW4327857167

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.