Evidence map›Paper›PMID 33719758›Full record

ArticleJournal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc2021

Visualization and application of disease diagnosis codes for population health management using porcine diseases as a model.

Giovani Trevisan, Kent J Schwartz, Eric R Burrough, Bailey Arruda, Rachel J Derscheid, Michael C Rahe, Edison de Souza Magalhães, Marcelo N Almeida, Rodger G Main, Daniel C L Linhares

Open access · greenAbstract read
In one paragraph

Article in Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

13 citing papers in PubMed, 15 citations in OpenAlex.

  1. AVeterinary sciences · 2026
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  2. Review
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  11. Editorial: Zoonotic emerging viral infectious diseases.Frontiers in veterinary science · 2023
    Article
  12. Article
  13. Leveraging and enhancing the value of veterinary diagnostic laboratory data.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2021
    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

10 authors at 1 institution in 1 country.

Giovani TrevisanVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.ORCID https://orcid.org/0000-0002-4980-526X
Kent J SchwartzVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
Eric R BurroughVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.ORCID https://orcid.org/0000-0003-4747-9189
Bailey ArrudaVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
Rachel J DerscheidVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.ORCID https://orcid.org/0000-0002-4402-5862
Michael C RaheVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.ORCID https://orcid.org/0000-0003-2123-4124
Edison de Souza MagalhãesVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
Marcelo N AlmeidaVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.ORCID https://orcid.org/0000-0003-3638-7721
Rodger G MainVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
Daniel C L LinharesVeterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
Iowa State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and timely results of diagnostic investigations and laboratory testing guide clinical interventions for the continuous improvement of animal health and welfare. Infectious diseases can severely limit the health, welfare, and productivity of populations of animals. Livestock veterinarians submit thousands of samples daily to veterinary diagnostic laboratories (VDLs) for disease diagnosis, pathogen monitoring, and surveillance. Individual diagnostic laboratory reports are immediately useful; however, aggregated historical laboratory data are increasingly valued by clinicians and decision-makers to identify changes in the health status of various animal populations over time and geographical space. The value of this historical information is enhanced by visualization of trends of agent detection, disease diagnosis, or both, which helps focus time and resources on the most significant pathogens and fosters more effective communication between livestock producers, veterinarians, and VDL professionals. Advances in data visualization tools allow quick, efficient, and often real-time scanning and analysis of databases to inform, guide, and modify animal health intervention algorithms. Value is derived at the farm, production system, or regional level. Visualization tools allow client-specific analyses, benchmarking, formulation of research questions, and monitoring the effects of disease management and precision farming practices. We present here the approach taken to visualize trends of disease occurrence using porcine disease diagnostic code data for the period 2010 to 2019. Our semi-automatic standardized creation of a visualization platform allowed the transformation of diagnostic report data into aggregated information to visualize and monitor disease diagnosis.

Indexed as

Population Health ManagementAnimalsClinical CodingSus scrofaSwineSwine DiseasesVeterinary Medicinedata visualizationdisease diagnosispopulation healthsyndromic surveillance

Identifiers

PMID33719758
PMCPMC8120091
OpenAlexW3135344633

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.