Evidence map›Paper›PMID 36104517›Full record

ArticleInflammation2023

Diagnostic and Prognostic Value of Deregulated Circulating Long Non-coding RNA TUG1 in Elderly Patients with Severe Pneumonia.

Kai Gong, Jiao Xu, Jianlei Tang

Abstract read
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In one paragraph

Article in Inflammation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 60% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Review
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

3 authors at 1 institution in 1 country.

Kai Gong *Department of Respiratory Medicine, Wu-Jin Hospital Affiliated to Jiangsu University, Wu-Jin Clinical College of Xuzhou Medical University, No. 2 Yongning North Road, Chang Zhou, Jiangsu, 213017, China.
Jiao Xu *Department of Respiratory Medicine, Wu-Jin Hospital Affiliated to Jiangsu University, Wu-Jin Clinical College of Xuzhou Medical University, No. 2 Yongning North Road, Chang Zhou, Jiangsu, 213017, China.
Jianlei TangDepartment of Intensive Care Unit, Wu-Jin Hospital Affiliated to Jiangsu University, Wu-Jin Clinical College of Xuzhou Medical University, No. 2 Yongning North Road, Chang Zhou, Jiangsu, 213017, China. tangjianlei_icu@163.com.
Jiangsu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To investigate the expression pattern of long non-coding RNA TUG1 in elderly patients with severe community-acquired pneumonia (sCAP) and evaluate its diagnostic and prognostic value for sCAP. Serum TUG1 levels were detected in 130 sCAP patients and 122 healthy volunteers via qRT-PCR method. The receiver operating characteristic (ROC) curve and k-M plot were drawn for the diagnostic and prognostic value evaluation. A diminished trend of TUG1 was detected in the serum of sCAP cases, and negatively correlated with the concentration of TNF-α, CRP, suPAR and sTREM-1. Among the 130 cases, 30 cases died from sCAP within 30 days after admission. Serum TUG1 had the diagnostic value for 30-day mortality prediction with the AUC of 0.823. In the non-survival group, more cases had old age, high CURB score and PSI score. K-M plot demonstrated that cases with low TUG1 levels showed poor survival than those carrying high TUG1 levels. Serum TUG1 was an independent risk factor for death in elderly patients with sCAP within 30 days after admission. Serum TUG1 was at low expression in sCAP patients, and it had the predictive value for the clinical prognosis of elderly sCAP patients.

Indexed as

Community-Acquired InfectionsPneumoniaRNA, Long NoncodingAgedHumansPrognosisSeverity of Illness IndexRNA, Long NoncodingInflammationSevere community-acquired pneumoniaSurvivalTUG1

Identifiers

PMID36104517
OpenAlexW4295789397

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.