Evidence map›Paper›PMID 27051514›Full record

ArticleInterface focus2016

Requirements for the formal representation of pathophysiology mechanisms by clinicians.

B de Bono, M Helvensteijn, N Kokash, I Martorelli, D Sarwar, S Islam, P Grenon, P Hunter

Abstract read
In one paragraph

Article in Interface focus, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

8 authors.

B de BonoAuckland Bioengineering Institute (ABI), University of Auckland, Auckland, New Zealand; Farr Institute, University College London, 222 Euston Road, London, UK.ORCID 0000-0003-0638-5274
M HelvensteijnLeiden Institute of Advanced Computer Science , University of Leiden , Leiden , The Netherlands.
N KokashLeiden Institute of Advanced Computer Science , University of Leiden , Leiden , The Netherlands.
I MartorelliLeiden Institute of Advanced Computer Science , University of Leiden , Leiden , The Netherlands.
D SarwarAuckland Bioengineering Institute (ABI) , University of Auckland , Auckland , New Zealand.
S IslamUniversity of East London , University Way, London , UK.
P GrenonFarr Institute , University College London , 222 Euston Road, London , UK.
P HunterAuckland Bioengineering Institute (ABI), University of Auckland, Auckland, New Zealand; Department of Physiology, Anatomy and Genetics (DPAG), University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge of multiscale mechanisms in pathophysiology is the bedrock of clinical practice. If quantitative methods, predicting patient-specific behaviour of these pathophysiology mechanisms, are to be brought to bear on clinical decision-making, the Human Physiome community and Clinical community must share a common computational blueprint for pathophysiology mechanisms. A number of obstacles stand in the way of this sharing-not least the technical and operational challenges that must be overcome to ensure that (i) the explicit biological meanings of the Physiome's quantitative methods to represent mechanisms are open to articulation, verification and study by clinicians, and that (ii) clinicians are given the tools and training to explicitly express disease manifestations in direct contribution to modelling. To this end, the Physiome and Clinical communities must co-develop a common computational toolkit, based on this blueprint, to bridge the representation of knowledge of pathophysiology mechanisms (a) that is implicitly depicted in electronic health records and the literature, with (b) that found in mathematical models explicitly describing mechanisms. In particular, this paper makes use of a step-wise description of a specific disease mechanism as a means to elicit the requirements of representing pathophysiological meaning explicitly. The computational blueprint developed from these requirements addresses the Clinical community goals to (i) organize and manage healthcare resources in terms of relevant disease-related knowledge of mechanisms and (ii) train the next generation of physicians in the application of quantitative methods relevant to their research and practice.

Indexed as

clinical communitydisease mechanism modellingknowledge managementpathophysiologyphysiome community

Identifiers

PMID27051514
PMCPMC4759753

What OpenQuestion holds

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Registered trials

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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.