Evidence map›Paper›PMID 35807150›Full record

ArticleJournal of clinical medicine2022

Construction of a Glycaemia-Based Signature for Predicting Acute Kidney Injury in Ischaemic Stroke Patients after Endovascular Treatment.

Chengfang Liu, Xiaohui Li, Zhaohan Xu, Yishan Wang, Teng Jiang, Meng Wang, Qiwen Deng, Junshan Zhou

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 26% 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, 7 citations in OpenAlex.

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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 1 institution in 1 country.

Chengfang LiuDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Xiaohui LiDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Zhaohan XuDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Yishan WangDepartment of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Teng JiangDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Meng WangDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Qiwen DengDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.ORCID 0000-0003-4324-8009
Junshan ZhouDepartment of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China.
Nanjing Medical University · CN

Funding

Health China BuChang ZhiYuan Public welfare projects for Heart and brain health No. HIGHER202102Medical Scientific Research Project of Jiangsu Commission of Health ZDA2020019National Science and Technology Innovation 2030 - Major Program of Brain Science and Brain-Inspired Intelligence Research 2021ZD0201807Stroke Prevention Project of the National Health Commission of the People's Republic of China GN-2020R0013
6 · The paper itself

Abstract

Background: Hyperglycaemia is thought to be connected to worse functional outcomes after ischaemic stroke. However, the association between hyperglycaemia and acute kidney injury (AKI) after endovascular treatment (EVT) remains elusive. The purpose of this study was to investigate the influence of glycaemic on AKI after EVT. Methods: We retrospectively collected the clinical information of patients who underwent EVT from April 2015 to August 2021. Blood glucose after EVT was recorded as acute glycaemia. Chronic glucose levels were estimated by glycosylated haemoglobin (HbA1c) using the following formula: chronic glucose levels (mg/dL) = 28.7 × HbA1c (%) − 46.7. AKI was defined as an increase in maximum serum creatinine to ≥1.5 baseline. We evaluated the association of AKI with blood glucose. A nomogram was established to predict the risk of AKI, and its diagnostic efficiency was determined by decision curve analysis. Results: We enrolled 717 acute ischaemic stroke patients who underwent EVT. Of them, 205 (28.6%) experienced AKI. Acute glycaemia (OR: 1.007, 95% CI: 1.003−1.011, p < 0.001), the acute/chronic glycaemic ratio (OR: 4.455, 95% CI: 2.237−8.871, p < 0.001) and the difference between acute and chronic glycaemia (ΔA-C) (OR: 1.008, 95% CI: 1.004−1.013, p < 0.001) were associated with the incidence of AKI. Additionally, age, atrial fibrillation, ASITN/SIR collateral grading, postoperative mTICI scale, and admission NIHSS were also significantly correlated with AKI. We then created a glycaemia-based nomogram, and its concordance index was 0.743. The net benefit of the nomogram was further confirmed by decision curve analysis. Conclusions: The glycaemia-based nomogram may be used to predict AKI in ischaemic stroke patients receiving EVT.

Indexed as

acute kidney injuryendovascular treatmentglycaemiaischaemic strokenomogram

Identifiers

PMID35807150
PMCPMC9267863
OpenAlexW4283803427

What Socratic 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 Socratic graph.