Evidence map›Paper›PMID 37532784›Full record

ReviewActa pharmacologica Sinica2023

Phenome-wide association study and precision medicine of cardiovascular diseases in the post-COVID-19 era.

Qian Cao, Xin Du, Xiao-Yan Jiang, Yuan Tian, Chen-Hao Gao, Zi-Yu Liu, Ting Xu, Xing-Xing Tao, Ming Lei, Xiao-Qiang Wang and 2 more

Open access · greenAbstract readReview
In one paragraph

Review in Acta pharmacologica Sinica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.2field-weighted citation impact, top 9% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
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

12 authors at 1 institution in 1 country.

Qian Cao *Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Xin Du *Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Xiao-Yan Jiang *Center for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Yuan TianCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Chen-Hao GaoCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Zi-Yu LiuCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Ting XuCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Xing-Xing TaoCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Ming LeiCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Xiao-Qiang WangCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.
Lingyu Linda YeCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China. lye@swmu.edu.cn.
Dayue Darrel DuanCenter for Phenomics of Traditional Chinese Medicine, the Affiliated Traditional Chinese Medicine Hospital, Southwest Medical University, Luzhou, 646000, China. dduan@swmu.edu.cn.
Southwest Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 infection causes injuries of not only the lungs but also the heart and endothelial cells in vasculature of multiple organs, and induces systemic inflammation and immune over-reactions, which makes COVID-19 a disease phenome that simultaneously affects multiple systems. Cardiovascular diseases (CVD) are intrinsic risk and causative factors for severe COVID-19 comorbidities and death. The wide-spread infection and reinfection of SARS-CoV-2 variants and the long-COVID may become a new common threat to human health and propose unprecedented impact on the risk factors, pathophysiology, and pharmacology of many diseases including CVD for a long time. COVID-19 has highlighted the urgent demand for precision medicine which needs new knowledge network to innovate disease taxonomy for more precise diagnosis, therapy, and prevention of disease. A deeper understanding of CVD in the setting of COVID-19 phenome requires a paradigm shift from the current phenotypic study that focuses on the virus or individual symptoms to phenomics of COVID-19 that addresses the inter-connectedness of clinical phenotypes, i.e., clinical phenome. Here, we summarize the CVD manifestations in the full clinical spectrum of COVID-19, and the phenome-wide association study of CVD interrelated to COVID-19. We discuss the underlying biology for CVD in the COVID-19 phenome and the concept of precision medicine with new phenomic taxonomy that addresses the overall pathophysiological responses of the body to the SARS-CoV-2 infection. We also briefly discuss the unique taxonomy of disease as Zheng-hou patterns in traditional Chinese medicine, and their potential implications in precision medicine of CVD in the post-COVID-19 era.

Indexed as

Cardiovascular DiseasesCOVID-19Endothelial CellsHumansPhenomicsPost-Acute COVID-19 SyndromePrecision MedicineSARS-CoV-2cardiovascular diseaseCOVID-19PheWASprecision medicineTraditional Chinese Medicine

Identifiers

PMID37532784
PMCPMC10692238
OpenAlexW4385497235

What Socratic 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 Socratic graph.