Evidence map›Paper›PMID 35845963›Full record

ArticleBioMed research international2022

Evaluation Value of Serum miR-4299 and miR-16-5p in Risk Stratification of Sepsis-Induced Acute Kidney Injury.

Weiwei Pan, Junfeng Zhang, Luqi Hu, Zhiping Huang

RetractedAbstract readRetracted Publication
In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Urinary microRNAs in sepsis function as a novel prognostic marker.Experimental and therapeutic medicine · 2023
    Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Weiwei PanIntensive Care Unit, Beilun People's Hospital, No. 1288 Lushan East Road, Beilun District, Ningbo, Zhejiang, China.
Junfeng ZhangIntensive Care Unit, Beilun People's Hospital, No. 1288 Lushan East Road, Beilun District, Ningbo, Zhejiang, China.
Luqi HuIntensive Care Unit, Beilun People's Hospital, No. 1288 Lushan East Road, Beilun District, Ningbo, Zhejiang, China.
Zhiping HuangIntensive Care Unit, Beilun People's Hospital, No. 1288 Lushan East Road, Beilun District, Ningbo, Zhejiang, China.ORCID https://orcid.org/0000-0002-3475-7744

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study was designed to determine the evaluation value of serum miR-4299 and miR-16-5p in risk stratification of sepsis-induced acute kidney injury (SI-AKI). Methods: A total of 115 sepsis patients were enrolled and assigned to the SI-AKI group ( Results: Cases with sepsis, especially SI-AKI, presented significantly downregulated serum miR-4299 and miR-16-5p. After therapy, the expression in them increased. The area under curve (AUC) of serum miR-4299 and miR-16-5p in the prediction value for early diagnosis of SI-AKI was 0.895 (95% CI: 0.839-0.951, cutoff value: 0.780) and 0.838 (95% CI: 0.767-0.909, cutoff value: 0.775), respectively, and the AUC of them in the prediction value for clinical efficacy on the disease were 0.733 (95% CI: 0.645-0.820, cutoff value: 1.115) and 0.776 (95% CI: 0.698-0.855, cutoff value: 1.125), respectively. Serum miR-16-5p and mIR-4299 were negatively correlated with Scr, Cys-C, and KIM-1, separately. Conclusion: Both miR-16-5p and mIR-4299 are promising factors for early diagnosis of SI-AKI and dynamic evaluation of the efficacy on it.

Indexed as

Acute Kidney InjuryMicroRNAsSepsisHumansRisk AssessmentROC CurveMicroRNAsMIR4299 microRNA, humanMIRN16 microRNA, human

Identifiers

PMID35845963
PMCPMC9286879

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.