Evidence map›Paper›PMID 29529072›Full record

Trial reportPloS one2018

Growth differentiation factor-15 levels and the risk of contrast induced acute kidney injury in acute myocardial infarction patients treated invasively: A propensity-score match analysis.

Ling Sun, Xuejun Zhou, Jianguang Jiang, Xuan Zang, Xin Chen, Haiyan Li, Haitao Cao, Qingjie Wang

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 20% 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, 9 citations in OpenAlex.

  1. Article
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  3. Review
  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

8 authors at 2 institutions in 1 country.

Ling SunDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Xuejun ZhouDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Jianguang JiangDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Xuan ZangDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Xin ChenDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Haiyan LiDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Haitao CaoDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Qingjie WangDepartment of Cardiology, Changzhou No.2 people's Hospital, Affiliated to Nanjing Medical University, Changzhou, China.
Changzhou No.2 People's Hospital · CNNanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGrowth differentiation factor-15 (GDF-15) is an emerging biomarker for risk stratification in cardiovascular disease. Contrast-induced acute kidney injury (AKI) is an important complication in patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI). In this retrospectively observational study, we aimed to determine the role of GDF-15 and the risk of AKI in acute myocardial infarction (AMI) patients.

methodsThe medical records of 1195 patients with AMI were reviewed. After exclusion criteria, a total of 751 eligible patients who underwent CAG or PCI were studied. Preoperative clinical parameters including GDF-15 levels were recorded. Multivariate logistic regression analysis was used to identify the risk factors of AKI. Subsequently, to reduce a potential selection bias and to balance differences between the two groups, a propensity score-matched analysis was performed. We recorded the 30-day all-cause mortality of the total study population. Kaplan-Meier analysis was performed to identify the association between short term survival in AMI patients and GDF-15 level.

resultsAmong 751 enrolled patients, 106 patients (14.1%) developed AKI. Patients were divided into two groups: AKI group (n = 106) and non-AKI group (n = 645). GDF-15 levels were significantly higher in AKI group compared to non-AKI group (1328.2 ± 349.7 ng/L vs. 1113.0 ± 371.3 ng/L, P <0.001). Multivariate logistic regression analyses showed GDF-15 was an independent risk factor of AKI (per 1000 ng/L increase of GDF-15, OR: 3.740, 95% CI: 1.940-7.207, P < 0.001). According to GDF-15 tertiles, patients were divided into three groups. Patients in middle (OR 2.93, 95% CI: 1.46-5.89, P = 0.003) and highest GDF-15 tertile (OR 3.72, 95% CI: 1.87-7.39, P <0.001) had higher risk of AKI compared to patients in the lowest GDF-15 tertile. The propensity score-matched group set comprised of 212 patients. Multivariate logistic regression revealed that GDF-15 is still an independent risk factor for AKI after matching (per 1000 ng/L increase of GDF-15, OR: 2.395, 95% CI: 1.020-5.626, P = 0.045). Based on the Kaplan-Meier analysis, the risk of 30-day all-cause mortality increased in higher GDF-15 tertiles log rank chi-square: 29.895, P <0.001).

conclusionThis suggests that preoperative plasma GDF-15 is an independent risk factor of AKI in AMI patients underwent CAG or PCI. GDF-15 and AKI are associated with poor short term survival of AMI patients.

Indexed as

Acute Kidney InjuryCoronary AngiographyMyocardial InfarctionPercutaneous Coronary InterventionAgedAged, 80 and overContrast MediaDisease-Free SurvivalFemaleGrowth Differentiation Factor 15HumansMaleMiddle AgedSurvival RateContrast MediaGDF15 protein, humanGrowth Differentiation Factor 15

Identifiers

PMID29529072
PMCPMC5846798
OpenAlexW2793321407

What OpenQuestion holds

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LicenceCC BY
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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.