| Literature DB >> 29463949 |
Shuying Huang1,2, Kejian Qian3, Yuanfang Zhu4, Zikun Huang5, Qing Luo5, Cheng Qing3.
Abstract
BACKGROUND: This study aims to evaluate the diagnostic value of nuclear-enriched abundant transcript 1 (NEAT1) expression in peripheral blood mononuclear cells (PBMCs) for the early diagnosis of sepsis.Entities:
Mesh:
Substances:
Year: 2017 PMID: 29463949 PMCID: PMC5804381 DOI: 10.1155/2017/7962836
Source DB: PubMed Journal: Dis Markers ISSN: 0278-0240 Impact factor: 3.434
Baseline characteristics of the study population.
| Sepsis | SIRS | Healthy controls |
| |
|---|---|---|---|---|
| Number | 59 | 52 | 56 | — |
| Age (years) | 58.7 ± 14.6 | 54.9 ± 15.9 | 52.6 ± 17.7 | 0.19 |
| Sex (male/female) | 35/24 | 30/22 | 33/23 | 0.73 |
| WBC (×109/L) | 13.57 ± 6.63∗ | 8.21 ± 3.85 | 6.57 ± 1.36 | <0.01 |
| PCT (ng/mL) | 8.9 ± 1.87 | 0.6 ± 0.12 | — | <0.01 |
| SOFA score | 8.7 ± 3.2 | 4.6 ± 2.3 | — | <0.01 |
| APACHEII score | 17.8 ± 5.7 | 8.7 ± 3.5 | — | <0.01 |
| Lac (mmol/L) | 3.98 ± 2.13∗ | 0.65 ± 0.01 | 0.51 ± 0.00 | <0.01 |
| CRP ( | 17.59 ± 4.87∗ | 2.75 ± 1.24 | 2.08 ± 1.01 | <0.01 |
| Survival at 28 d, | 35 (59.3%)∗ | 47 (90.3%) | 0 | <0.01 |
∗ P < 0.05, versus SIRS.
Clinical data for survivors and nonsurvivors based on a 28-day survival.
| Survivors ( | Nonsurvivors ( |
| |
|---|---|---|---|
| Age (years) | 53.6 ± 17.1 | 50.1 ± 15.3 | 0.242 |
| SOFA score | 6.1 ± 2.3 | 10.4 ± 3.5 | <0.001 |
| APACHE II score | 13.1 ± 5.5 | 19.7 ± 7.8 | <0.001 |
| WBC (×109/L) | 13.57 ± 6.63 | 16.57 ± 1.36 | 0.158 |
| PCT (ng/mL) | 3.2 ± 2.64 | 7.8 ± 2.93 | <0.001 |
| Lac (mmol/L) | 2.58 ± 1.01 | 4.01 ± 1.90 | <0.001 |
| CRP ( | 12.33 ± 4.67 | 20.68 ± 5.94 | <0.001 |
Figure 1NEAT1 expression is increased in patients with sepsis and SIRS. (a) Expression of NEAT1 in PBMCs of patients with SIRS (n = 52), sepsis (n = 59), and normal controls (n = 56). (b) NEAT1 expression in PBMCs of patients with sepsis who survived (n = 35) or who died (n = 24). ∗P < 0.05 and ∗∗P < 0.01.
Figure 2ROC curve analysis of NEAT1 concentrations for the prediction of sepsis and SIRS.