Evidence map›Paper›PMID 33209373›Full record

ArticleJournal of thoracic disease2020

Impact of increased inflammation biomarkers on periprocedural myocardial infarction in patients undergoing elective percutaneous coronary intervention: a cohort study.

Liding Zhao, Ya Li, Tian Xu, Yi Luan, Qingbo Lv, Yao Wang, Xue Lv, Guosheng Fu, Wenbin Zhang

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. 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

9 authors at 2 institutions in 1 country.

Liding ZhaoDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Ya LiDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Tian XuDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Yi LuanDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Qingbo LvDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Yao WangDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Xue LvDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Guosheng FuDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Wenbin ZhangDepartment of Cardiovascular Diseases, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Zhejiang University · CNSir Run Run Shaw Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe fact that each inflammatory indicator has a forecasting capacity on the occurrence of periprocedural myocardial infarction (PMI) has a controversial existence. The purpose of this study was to explore the role of inflammation biological indicators on PMI in a group of patients undergoing selective percutaneous coronary intervention (PCI).

methodsThe study was carried out both in a retrospective and prospective manner in 7,413 and 1,189 subjects, respectively. In the retrospective cohort study, the association between inflammation biomarkers and PMI was assessed by univariate and multivariate logistic regression. WBC, CRP, and NLR were distributed using k-means clustering into a virtual variable "Inflammatory Trend", and multivariate logistic regression and subgroup analysis were performed. In the prospective cohort study, the endpoints were PMI, cardiovascular death or cardiac arrest. The chi-square test was performed to calculate the relative risk (RR).

resultsIn the retrospective cohort study, except WBC, CRP, NLR and virtual variable "Inflammatory trend" were independent risk factors for PMI. The subgroup analysis revealed that CRP can serve as the most stable predictor. In the prospective cohort study, WBC (RR =1.134, P=0.416) has no effect on the incidence of PMI. However, an elevation in the incidence of PMI was observed with an increase of NLR (RR =1.354, P=0.041) and CRP (RR =1.412, P=0.025).

conclusionsIn patients with elective PCI for single-vessel lesions, high CRP increases the risk for PMI. The increase of NLR was an independent risk factor for PMI, especially for patients with hypertension and under the age of 70. WBC has no influence on the occurrence of PMI.

Indexed as

C-reactive proteinneutrophil to lymphocyte ratiopercutaneous coronary intervention (PCI)periprocedural myocardial infarction (PMI)White blood cell (WBC)

Identifiers

PMID33209373
PMCPMC7656373
OpenAlexW3093460890

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.