Evidence mapPaperPMID 32640513Full record

ReviewGenes2020

Precision and Personalized Medicine: How Genomic Approach Improves the Management of Cardiovascular and Neurodegenerative Disease.

Oriana Strianese, Francesca Rizzo, Michele Ciccarelli, Gennaro Galasso, Ylenia D'Agostino, Annamaria Salvati, Carmine Del Giudice, Paola Tesorio, Maria Rosaria Rusciano

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 3 pooled it
8.5field-weighted citation impact, top 2% 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

84 citing papers in PubMed, 3 syntheses or guidelines pooled it, 216 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Review
  20. Review

24 more citing papers are in PubMed but not listed here.

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

9 authors at 1 institution in 1 country.

Oriana StrianeseClinical Research and Innovation, Clinica Montevergine S.p.A., 83013 Mercogliano, Italy.
Francesca RizzoLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84084 Baronissi, Italy.ORCID 0000-0003-1783-5015
Michele CiccarelliDepartment of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84084 Baronissi, Italy.ORCID 0000-0003-2379-1960
Gennaro GalassoDepartment of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84084 Baronissi, Italy.
Ylenia D'AgostinoLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84084 Baronissi, Italy.
Annamaria SalvatiLaboratory of Molecular Medicine and Genomics, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, 84084 Baronissi, Italy.ORCID 0000-0002-9601-2975
Carmine Del GiudiceClinical Research and Innovation, Clinica Montevergine S.p.A., 83013 Mercogliano, Italy.
Paola TesorioUnit of Cardiology, Clinica Montevergine S.p.A., 83013 Mercogliano, Italy.
Maria Rosaria RuscianoClinical Research and Innovation, Clinica Montevergine S.p.A., 83013 Mercogliano, Italy.ORCID 0000-0002-7112-6503
University of Salerno · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Life expectancy has gradually grown over the last century. This has deeply affected healthcare costs, since the growth of an aging population is correlated to the increasing burden of chronic diseases. This represents the interesting challenge of how to manage patients with chronic diseases in order to improve health care budgets. Effective primary prevention could represent a promising route. To this end, precision, together with personalized medicine, are useful instruments in order to investigate pathological processes before the appearance of clinical symptoms and to guide physicians to choose a targeted therapy to manage the patient. Cardiovascular and neurodegenerative diseases represent suitable models for taking full advantage of precision medicine technologies applied to all stages of disease development. The availability of high technology incorporating artificial intelligence and advancement progress made in the field of biomedical research have been substantial to understand how genes, epigenetic modifications, aging, nutrition, drugs, microbiome and other environmental factors can impact health and chronic disorders. The aim of the present review is to address how precision and personalized medicine can bring greater clarity to the clinical and biological complexity of these types of disorders associated with high mortality, involving tremendous health care costs, by describing in detail the methods that can be applied. This might offer precious tools for preventive strategies and possible clues on the evolution of the disease and could help in predicting morbidity, mortality and detecting chronic disease indicators much earlier in the disease course. This, of course, will have a major effect on both improving the quality of care and quality of life of the patients and reducing time efforts and healthcare costs.

Indexed as

AnimalsCardiovascular DiseasesGenetic TestingGenomicsHumansNeurodegenerative DiseasesPrecision Medicineclinical applicationgenomicspersonalized medicineprecision medicine

Identifiers

PMID32640513
PMCPMC7397223
OpenAlexW3040489902

What Socratic holds

Textmetadata
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 Socratic graph.