Evidence map›Paper›PMID 36505313›Full record

ArticleAmerican journal of translational research2022

Correlation of serum miR-127 level with severity and prognosis of sepsis.

Cheng Gao, Huan Chen

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

2 authors at 1 institution in 1 country.

Cheng GaoDepartment of Critical Care, Jingzhou Hospital Affiliated to Yangtze University Jingzhou 434020, Hubei, China.
Huan ChenDepartment of Obstetrics and Gynecology, Jingzhou Hospital Affiliated to Yangtze University Jingzhou 434020, Hubei, China.
Yangtze University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the relationship of serum miR-127 level with the severity of sepsis patients and its predictive efficacy for prognosis.

methodsA total of 205 healthy individuals who underwent physical examination in Jingzhou Hospital Affiliated to Yangtze University and 205 patients with sepsis who were hospitalized in ICU from January 2021 to March 2022 were recruited in this study, and their serum miR-127 level were measured. The patients were divided into a high-miR-127 group (110 cases) and a low-miR-127 group (95 cases) based on the optimal cut-off value of miR-127 to assess the prognosis. The clinical data and 28-day survival of the two groups were analyzed. The patients were further divided into a death group (57 cases) and a survival group (148 cases) based on their 28-day survival. Factors associated with poor prognosis of sepsis were analyzed by Cox regression.

resultsThere were statistically significant differences in heart rate, body temperature, white blood cells (WBC), hemoglobin (Hb), procalcitonin (PCT), C-reactive protein (CRP), alanine aminotransferase (ALT), total bilirubin (TBIL), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), cardiac troponin I (cTnI), blood urea nitrogen (BUN), Prothrombin time (PT), serum creatinine (Scr), fibrinogen (FIB) and miR-127 between sepsis patients and healthy controls (

conclusionSerum miR-127 is highly expressed in sepsis and related to the severity of sepsis. Those with high miR-127 level have a higher risk of poor prognosis.

Indexed as

correlationdisease severitymiR-127prognosisSepsis

Identifiers

PMID36505313
PMCPMC9730080
OpenAlexW4311282689

What OpenQuestion holds

Textmetadata
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.