Evidence map›Paper›PMID 21207039›Full record

ArticleHeart and vessels2011

Clinical analysis of the risk factors of slow coronary flow.

Shuang Xia, Song-Bai Deng, Yang Wang, Jun Xiao, Jian-Lin Du, Yu Zhang, Xi-Chun Wang, Ye-Qing Li, Rui Zhao, Li He and 2 more

Abstract read
PubMed Publisher
In one paragraph

Article in Heart and vessels, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
3.1field-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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 64 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Prevalence and predictors of slow coronary flow phenomenon in Kermanshah province.Journal of cardiovascular and thoracic research · 2021
    Article
  19. Article
  20. 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

12 authors at 4 institutions in 1 country.

Shuang XiaDepartment of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, 74 Lingjiang Road, Chongqing, China.
Song-Bai Deng
Yang Wang
Jun Xiao
Jian-Lin Du
Yu Zhang
Xi-Chun Wang
Ye-Qing Li
Rui Zhao
Li He
Yu-Luan Xiang
Qiang She
Chongqing Medical University · CNSecond Affiliated Hospital of Chongqing Medical University · CNChongqing Emergency Medical Center · CNDalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Slow coronary flow (SCF) phenomenon is a coronary microvascular disorder characterized by the delayed passage of contrast in the absence of obstructive epicardial coronary disease, and is an important clinical entity because it may be the cause of precordial pain when the body is at rest and/or during exercise. Although clinical and pathological features of SCF have been previously described, its etiopathogenesis remains unclear. The present study aims to investigate the risk factors of slow coronary flow, in order to provide the foundation for further exploration of potential mechanisms of SCF. A total of 47 consecutive patients with documented slow coronary flow, and 33 patients with normal coronary flow--as defined by TIMI frame count (TFC)--were recruited for this study. Clinical information was collected, and biochemical indicators including high-sensitivity C-reactive protein (hs-CRP), and a marker of systemic inflammation were detected. Logistic regression analysis was performed for statistical analysis. SCF patients had a higher level of serum uric acid (323.2 ± 79.3 vs. 282.8 ± 82.4 μmol/l, p = 0.03), 2-h postprandial blood glucose (8.6 ± 2.7 vs. 7.5 ± 1.8 mmol/l, p = 0.04), platelet count (165.9 ± 51.6 × 10(3) vs. 127.0 ± 32.0 × 10(3) cells/μl, p = 0.0003) and hs-CRP (3.4 ± 0.8 vs. 2.0 ± 0.9 mg/l, p < 0.0001) than those of patients in the control group. No marked differences in other variables were observed between the two groups. Logistic regression showed serum uric acid level (χ(2) = 3.84, β = 0.007, p = 0.049), 2-h postprandial blood glucose (χ(2) = 5.02, β = 0.277, p = 0.025) and blood platelet count (χ(2) = 12.16, β = 0.026, p = 0.001) were independent predictors of SCF. When hs-CRP was included in the multivariate model, hs-CRP (χ(2) = 21.19, β = 1.90, p < 0.0001) was the only independent predictor of SCF. These findings suggested that an elevation of serum uric acid level, 2-h postprandial blood glucose, and blood platelet count might be the causes of SCF, and inflammation was likely to be implicated in the causal pathway leading to SCF.

Indexed as

Coronary CirculationMicrocirculationBiomarkersBlood GlucoseCase-Control StudiesChinaChi-Square DistributionCoronary AngiographyC-Reactive ProteinHumansInflammation MediatorsLogistic ModelsNo-Reflow PhenomenonObserver VariationPlatelet CountPostprandial PeriodBiomarkersBlood GlucoseC-Reactive ProteinInflammation MediatorsUric Acid

Identifiers

PMID21207039
OpenAlexW2004575044

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.