Evidence map›Paper›PMID 31126255›Full record

Observational studyBMC nephrology2019

Impact of blood glucose levels on the accuracy of urinary N-acety-β-D-glucosaminidase for acute kidney injury detection in critically ill adults: a multicenter, prospective, observational study.

Lin Wang, Yujun Deng, Yiling Zhai, Feng Xu, Jinghua Li, Danqing Zhang, Lu Gao, Yating Hou, Xin OuYang, Linhui Hu and 4 more

Open access · goldAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in BMC nephrology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. 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

14 authors at 4 institutions in 1 country.

Lin WangDepartment of Intensive Care Unit of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong Province, China.
Yujun DengDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Yiling ZhaiDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Feng XuDepartment of Emergency Medicine, Shandong University Qilu Hospital, Jinan, 250012, Shandong Province, China.
Jinghua LiDepartment of Clinical Laboratory, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong Province, China.
Danqing ZhangDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Lu GaoDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Yating HouDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Xin OuYangDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Linhui HuDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Jie YuanDepartment of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 96 Dongchuan Road, Guangzhou, 510080, Guangdong Province, China.
Heng YeDepartment of Critical Care Medicine, Guangzhou Nansha Central Hospital, Guangzhou, 511400, Guangdong Province, China.
Ruibin ChiDepartment of Critical Care Medicine, Xiaolan Hospital of Southern Medical University, Zhongshan, 528415, Guangdong Province, China.
Chunbo ChenDepartment of Intensive Care Unit of Cardiovascular Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong Province, China. gghccm@163.com.ORCID 0000-0001-5662-497X
Guangdong Academy of Medical Sciences · CNPanyu District Central Hospital · CNQilu Hospital of Shandong University · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe performance of urinary N-acetyl-β-D-glucosaminidase (uNAG) for the detection of acute kidney injury (AKI) was controversial. uNAG is positively correlated with blood glucose levels. Hyperglycemia is common in the critically ill adults. The influence of blood glucose levels on the accuracy of uNAG in AKI detection has not yet been reported. The present study evaluated the effect of blood glucose levels on the diagnostic accuracy of uNAG to detect AKI.

methodsA total of 1585 critically ill adults in intensive care units at three university hospitals were recruited in this prospective observational study. uNAG, serum glucose, and glycosylated hemoglobin (HbA1c) were measured at ICU admission. Patients were categorized based on the history of diabetes and blood glucose levels. The performance of uNAG to detect AKI in different groups was assessed by the area under the receiver operator characteristic curve.

resultsFour hundred and twelve patients developed AKI, of which 109 patients were severe AKI. uNAG was significantly correlated with the levels of serum glucose (P < 0.001) and HbA1c (P < 0.001). After stratification based on the serum glucose levels, no significant difference was observed in the AUC of uNAG in detecting AKI between any two groups (P > 0.05). Stratification for stress hyperglycemic demonstrated similar results.However, among non-diabetic patients, the optimal cut-off value of uNAG for detecting AKI was higher in stress hyperglycemic patients as compared to those without stress hyperglycemia.

conclusionsThe blood glucose levels did not significantly affect the performance of uNAG for AKI detection in critically ill adults. However, the optimal cut-off value of uNAG to detect AKIwas affected by stress hyperglycemia in non-diabetic patients.

Indexed as

Critical IllnessAcetylglucosaminidaseAcute Kidney InjuryAdultAgedBiomarkersBlood GlucoseFemaleHumansMaleMiddle AgedProspective StudiesAcetylglucosaminidaseBiomarkersBlood GlucoseAcute kidney injuryBlood glucose levelsCritically ill patientsN-acetyl-β-D-glucosaminidase

Identifiers

PMID31126255
PMCPMC6534873
OpenAlexW2945750097

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.