Evidence map›Paper›PMID 32953824›Full record

ReviewAnnals of translational medicine2020

Applications and grants of National Natural Scientific Foundation of China's General Program in abnormalities and diseases of locomotor system: a ten-year review.

Dou Dou

Open access · diamondAbstract readReview
In one paragraph

Review in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 35% 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, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. 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

1 author at 1 institution in 1 country.

Dou DouDepartment of Health Sciences, National Natural Science Foundation of China, Beijing, China.
National Natural Science Foundation of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Translational medicine is a branch of medical research that attempts to establish a more direct link between basic research and clinical practice. The improvement of clinical management cannot be separated from the progress and breakthrough made in basic biomedical research. As one of the main funding agencies for basic research in China, National Natural Scientific Foundation of China (NSFC) plays an active role in promotion of the development of basic medical research and translational medicine. General Program mainly supports scientists to carry out basic research on bottom-up based topics within the funding scope of NSFC to conduct innovative research and promote a balanced, coordinated and sustained development of all disciplines. Musculoskeletal injury and disease is a major threat to human health worldwide and has become the major cause of disability in China. In this review, we aim to further promote the clinical transformation by summarizing the trends and hotspots of basic research in this field based on the analysis of the data of General Program in abnormalities and diseases of locomotor system over the last decade, including analyses of the number of applications received and projects funded, the distribution of the keywords in applications and grants, distribution of applications and grants of General Program in the secondary application code of H06 and in the host institution.

Indexed as

funding rategeneral programlocomotor systemNational Natural Scientific Foundation of China (NSFC)

Identifiers

PMID32953824
PMCPMC7475454
OpenAlexW3049650662

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.