Evidence map›Paper›PMID 36946052›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2023

[Effect of co-morbid chronic kidney disease on the accuracy of cardiac troponin levels for diagnosis of acute myocardial infarction].

Y Deng, H Chen, G Li, L Chen, Q Fu

Open access · greenAbstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Y DengDepartment of Cardiovascular Disease, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China.
H ChenDepartment of Endocrinology and Metabolism, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China.
G LiDepartment of Cardiovascular Disease, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China.
L ChenDepartment of Cardiovascular Disease, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China.
Q FuDepartment of Cardiovascular Disease, Shenzhen Hospital, Southern Medical University, Shenzhen 518101, China.
Southern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the accuracy of cardiac troponin (cTn) levels in the diagnosis of acute myocardial infarction (AMI) in patients with chronic kidney disease (CKD) and explore a potential strategy for improving the diagnostic accuracy.

methodsWe retrospectively analyzed the data from patients with high-risk chest pain admitted in Zhujiang Hospital from January, 2018 to December, 2020, including 126 patients with and 272 patients without CKD, and 122 patients diagnosed to have AMI and 276 patients without AMI. The baseline clinical data of the patients and blood test results within 12 h after admission were collected.

resultsIn patients without AMI, cTnT level was significantly higher in those with co-morbid CKD than in those without CKD (

conclusionIn CKD patients, the cutoff level of cTn is increased for diagnosing AMI, and cTnI has a higher diagnostic specificity than cTnT. The combination of cTnT and cTnI levels may further improve diagnostic efficacy for AMI.

Indexed as

Myocardial InfarctionRenal Insufficiency, ChronicBiomarkersComorbidityHumansRetrospective StudiesTroponin ITroponin TBiomarkersTroponin ITroponin Tacute myocardial infarctionchronic kidney diseasetroponin Itroponin T

Identifiers

PMID36946052
PMCPMC10034548
OpenAlexW4353016743

What OpenQuestion holds

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Registered trials

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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.