Evidence map›Paper›PMID 35813727›Full record

ArticleJournal of thoracic disease2022

A Nomogram model for predicting the occurrence of no-reflow phenomenon after percutaneous coronary intervention using the lncRNA

Chen-Kai Hu, Ru-Ping Cai, Lei He, Shi-Rong He, Jun-Yu Liao, Qiang Su

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2022. 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 47% 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. Article
  3. Review
  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

6 authors at 2 institutions in 1 country.

Chen-Kai Hu *Department of Cardiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Ru-Ping Cai *Department of Cardiology, Affiliated Hospital of Guilin Medical University, Guilin, China.
Lei HeDepartment of Cardiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Shi-Rong HeDepartment of Cardiology, Affiliated Hospital of Guilin Medical University, Guilin, China.
Jun-Yu LiaoDepartment of Cardiology, Affiliated Hospital of Guilin Medical University, Guilin, China.
Qiang SuDepartment of Cardiology, Affiliated Hospital of Guilin Medical University, Guilin, China.
Guilin Medical University · CNNanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Studies have shown that percutaneous coronary intervention (PCI) is considered as the essential therapeutic strategy for the patients with ST-segment elevation myocardial infarction (STEMI). However; no-reflow could still occur in a few patients after PCI. Studies have reported that biomarkers related to no-reflow pathogenetic components could play a prognostic role in the prediction phenomenon. Hence, this study explored the establishment of nomogram model for predicting the occurrence of no-reflow phenomenon after PCI using the lncRNA Methods: In this observational study, a total of 76 STEMI patients who underwent emergency PCI between January 2018 and December 2021were included. The patients after PCI, were divided into reflow (n=44) and no-reflow groups (n=32). The demographic, environmental and clinical risk factors were assessed and analysed between the groups. Quantitative RT-PCR was used to detect Results: Plasma lncRNA Conclusions:

Indexed as

No-reflowpercutaneous coronary intervention (PCI)ST-segment elevation myocardial infarction (STEMI)

Identifiers

PMID35813727
PMCPMC9264104
OpenAlexW4283720588

What Socratic 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 Socratic graph.