Evidence map›Paper›PMID 37512155›Full record

ArticleMedicina (Kaunas, Lithuania)2023

A New Neurological Screening Approach for Diagnosing Brainstem Infarction Using the Calling Method and Familiar Voices.

Yuzuru Ohshiro

Open access · goldAbstract readCase Reports
In one paragraph

Article in Medicina (Kaunas, Lithuania), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 81% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Yuzuru OhshiroDepartment of Internal Medcine, Omoromachi Medical Center, Naha City 900-0011, Okinawa, Japan.ORCID 0000-0002-9345-3759
Nagara Medical Center · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This report proposes a new approach to assess dysarthria in patients with brainstem infarction by involving familiar individuals. Collaboration provides valuable insights compared to subjective traditional methods. A man in his 70s presented with resolved positional vertigo. Standard neurological tests showed no abnormalities, and inquiries with the patient's friend did not reveal voice changes. While inquiring about voice changes with family, friends, and acquaintances is a common practice in clinical settings, our approach involved the patient calling out to his friend from a distance. Despite the physician detecting no abnormalities, the friend noticed a lower voice. Subsequent magnetic resonance imaging (MRI) confirmed brainstem infarction. Early and subtle symptoms of brainstem infarction pose a detection challenge and can lead to serious outcomes if overlooked. This report provides the first evidence that distance calling can detect subtle voice changes associated with brainstem infarction potentially overlooked by conventional neurological examinations, including inquiries with individuals familiar with the patient's voice. Detecting brainstem infarction in emergency department cases is often missed, but conducting MRIs on every patient is not feasible. This simple method may identify patients overlooked by conventional screening who should undergo neuroimaging such as MRI. Further research is needed, and involving non-professionals in assessments could significantly advance the diagnostic process.

Indexed as

Brain Stem InfarctionsEmergency Service, HospitalHumansMagnetic Resonance ImagingMaleMass ScreeningNeurologic Examinationbrainstem infarctioncase reportdysarthriastroke screenings

Identifiers

PMID37512155
PMCPMC10383907
OpenAlexW4385201916

What OpenQuestion holds

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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.