Evidence map›Paper›PMID 35146616›Full record

ArticleAdvances in experimental medicine and biology2022

Using Confocal Microscopy to Generate an Accurate Vascular Model for Use in Patient Education Animation.

Angela Douglass, Gillian Moffat, Craig Daly

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Article in Advances in experimental medicine and biology, 2022. 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 94% 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

3 authors at 2 institutions in 1 country.

Angela DouglassSchool of Life Sciences, College of Medical, Veterinary Sciences, University of Glasgow, Glasgow, UK. Angela.Douglas@glasgow.ac.uk.
Gillian MoffatSchool of Simulation and Visualisation, Glasgow School of Art, The Hub, Glasgow, UK.
Craig DalySchool of Life Sciences, College of Medical, Veterinary Sciences, University of Glasgow, Glasgow, UK.
University of Glasgow · GBGlasgow School of Art · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertension is a condition requiring lifelong medication, where patients often feel well with or without treatment. Uncontrolled hypertension, however, can lead to permanent remodelling processes that occur to the vascular structure, which are seldom understood by the public. As a result, a significant burden is placed on healthcare systems globally as a result of the effects of hypertension and lack of adherence to prescribed treatment.Improving patient education through well-designed interactive applications and animation is a known strategy that can improve adherence rates to medication. In the context of hypertension, little attention has been given to helping patients understand the unseen damage that occurs to vessels exposed to high blood pressure. However, generating an accurate representation of a vessel and the changes that occur can be challenging. Using microscopy data is one way for creating an anatomically correct model, but this often needs careful consideration as data cannot be directly imported. Here we describe methods for creating an accurate 3D model of a small artery using confocal microscopy data. This model can then be animated to demonstrate the substructures and pathological changes that occur in hypertensive conditions to better inform patients about the dangers of uncontrolled blood pressure.

Indexed as

HypertensionPatient Education as TopicAntihypertensive AgentsArteriesBlood PressureHumansMicroscopy, ConfocalAntihypertensive Agents3D modellingAnimationHypertensionPatient educationVascular remodelling

Identifiers

PMID35146616
OpenAlexW4211252862

What OpenQuestion holds

Textmetadata
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.