Evidence map›Paper›PMID 29157229›Full record

ArticleBMC medical education2017

Computer model for the cardiovascular system: development of an e-learning tool for teaching of medical students.

David Roy Warriner, Martin Bayley, Yubing Shi, Patricia Victoria Lawford, Andrew Narracott, John Fenner

Abstract read
In one paragraph

Article in BMC medical education, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

6 authors.

David Roy WarrinerMathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK. d.r.warriner@sheffield.ac.uk.
Martin BayleyDepartment of Scientific Computing, Royal Hallamshire Hospital, Sheffield Teaching Hospitals, Glossop Road, Sheffield, S10 2JF, UK.
Yubing ShiMathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
Patricia Victoria LawfordMathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
Andrew NarracottMathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
John FennerMathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.

Funding

Engineering and Physical Sciences Research Council R/125661-1.Virtual Physiological Human (Network of Excellence) 223920
6 · The paper itself

Abstract

backgroundThis study combined themes in cardiovascular modelling, clinical cardiology and e-learning to create an on-line environment that would assist undergraduate medical students in understanding key physiological and pathophysiological processes in the cardiovascular system.

methodsAn interactive on-line environment was developed incorporating a lumped-parameter mathematical model of the human cardiovascular system. The model outputs were used to characterise the progression of key disease processes and allowed students to classify disease severity with the aim of improving their understanding of abnormal physiology in a clinical context. Access to the on-line environment was offered to students at all stages of undergraduate training as an adjunct to routine lectures and tutorials in cardiac pathophysiology. Student feedback was collected on this novel on-line material in the course of routine audits of teaching delivery.

resultsMedical students, irrespective of their stage of undergraduate training, reported that they found the models and the environment interesting and a positive experience. After exposure to the environment, there was a statistically significant improvement in student performance on a series of 6 questions based on cardiovascular medicine, with a 33% and 22% increase in the number of questions answered correctly, p < 0.0001 and p < 0.001 respectively.

conclusionsConsiderable improvement was found in students' knowledge and understanding during assessment after exposure to the e-learning environment. Opportunities exist for development of similar environments in other fields of medicine, refinement of the existing environment and further engagement with student cohorts. This work combines some exciting and developing fields in medical education, but routine adoption of these types of tool will be possible only with the engagement of all stake-holders, from educationalists, clinicians, modellers to, most importantly, medical students.

Indexed as

Computer-Assisted InstructionComputer SimulationEducation, DistanceModels, CardiovascularCardiologyCardiovascular DiseasesCardiovascular SystemEducation, Medical, UndergraduateHumansLearningStudents, MedicalTeachingUnited KingdomCardiologyCardiovascular scienceE-learningVirtual patients

Identifiers

PMID29157229
PMCPMC5697416

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.