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中华实验和临床感染病杂志(电子版) ›› 2024, Vol. 18 ›› Issue (04) : 222 -228. doi: 10.3877/cma.j.issn.1674-1358.2024.04.005

论 著

急性胰腺炎患者血清微小RNA-142-3p和磷脂酰肌醇3-激酶水平变化及对并发腹腔感染风险预测
白香妮, 孙巨军, 谢鹤, 李宏斌()   
  1. 710077 西安市,西电集团医院医学检验科
  • 收稿日期:2024-03-03 出版日期:2024-08-08
  • 通信作者: 李宏斌
  • 基金资助:
    西安市科技计划项目(No. 22YXYJ0120)

Changes of serum microRNA-142-3p and phosphoinositide 3-kinase levels in patients with acute pancreatitis and predictive analysis of the risk of concurrent abdominal infection

Xiangni Bai, Jujun Sun, He, Xie, Hongbin Li()   

  1. Medical Laboratory Department, Xidian Group Hospital, Xi’an 710077, China
  • Received:2024-03-03 Published:2024-08-08
  • Corresponding author: Hongbin Li
引用本文:

白香妮, 孙巨军, 谢鹤, 李宏斌. 急性胰腺炎患者血清微小RNA-142-3p和磷脂酰肌醇3-激酶水平变化及对并发腹腔感染风险预测[J]. 中华实验和临床感染病杂志(电子版), 2024, 18(04): 222-228.

Xiangni Bai, Jujun Sun, He, Xie, Hongbin Li. Changes of serum microRNA-142-3p and phosphoinositide 3-kinase levels in patients with acute pancreatitis and predictive analysis of the risk of concurrent abdominal infection[J]. Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition), 2024, 18(04): 222-228.

目的

探讨急性胰腺炎(AP)患者血清微小RNA-142-3p(miR-142-3p)和磷脂酰肌醇3-激酶(PI3K)水平变化,并采用列线图分析二者评估并发腹腔感染(IAI)的价值。

方法

选取2021年7月至2023年12月西电集团医院医学检验科收治的AP患者186例为观察组,并选取同期健康体检者93例为健康对照组。两组研究对象均检测血清miR-142-3p和PI3K水平。应用Logistic回归模型分析AP患者并发IAI的危险因素,绘制列线图分析miR-142-3p、PI3K对AP并发IAI的评估价值并进行决策曲线分析(DCA)。

结果

观察组患者血清miR-142-3p水平低于健康对照组(t = 8.181、P < 0.001),PI3K水平高于健康对照组(t = 16.605、P < 0.001),差异均有统计学意义。并发IAI患者白细胞计数(t = 2.265、P = 0.026)、C-反应蛋白(t = 3.239、P = 0.002)、降钙素原(t = 2.780、P = 0.007)和PI3K水平(t = 5.073、P < 0.001)显著高于非IAI患者,miR-142-3p(t = 3.693、P < 0.001)显着低于非IAI患者,差异均有统计学意义。C-反应蛋白(OR = 2.831、95%CI:1.563~5.127、P =0.022)、降钙素原(OR = 2.845、95%CI:1.472~5.498、P = 0.016)和PI3K(OR = 3.210、95%CI:1.708~6.032、P < 0.001)均为AP并发IAI的独立危险因素,miR-142-3p(OR = 0.350、95%CI:0.162~0.757、P < 0.001)为AP并发IAI的独立保护因素。列线图预测模型显示,PI3K和miR-142-3p对AP并发IAI具有较高预测价值,一致性指数分别为0.743和0.707;校正曲线分析显示,预测模型预测AP并发IAI风险与实际发生风险吻合度较高,平均绝对误差为0.026,在可接受范围;在阈值0.1~0.5范围内,联合评估AP并发IAI的净受益率优于PI3K、miR-142-3p单独检测。

结论

AP患者miR-142-3p呈低表达,PI3K呈高表达,二者表达水平是其并发IAI的独立影响因素,可通过检测二者水平评估患者并发IAI的风险。

Objective

To investigate the changes of serum microRNA-142-3p (miR-142-3p) and phosphoinositide 3-kinase (PI3K) levels in patients with acute pancreatitis (AP), and to evaluate the value in the assessment of intrabitoneal infection (IAI) by nomogram analysis.

Methods

Total of 186 patients with AP admitted to the Medical Laboratory Department, Xidian Group Hospital from July 2021 to December 2023 were selected as observation group, and 93 healthy subjects during the same period were selected as control group. Serum miR-142-3p and PI3K levels were detected for research objects in both groups. The risk factors of AP patients complicated with IAI were analyzed by Logistic regression model. The evaluation value of miR-142-3p and PI3K in AP complicated with IAI was analyzed by nomogram, and decision curve analysis (DCA) was performed.

Results

The serum level of miR-142-3p of patients in observation group was lower than that of control group (t = 8.181, P < 0.001), and the level of PI3K in observation group was higher than that of control group (t = 16.605, P < 0.001), both with significant differences. The levels of white blood cell count (t = 2.265, P = 0.026), C-reactive protein (t = 3.239, P = 0.002), procalcitonin (t = 2.780,P = 0.007) and PI3K (t = 5.073, P < 0.001) of patients complicated with IAI were higher than those of non-IAI patients, and miR-142-3p was lower than that of non-IAI patients (t = 3.693, P < 0.001), all with significant differences. C-reactive protein (OR = 2.831, 95%CI: 1.563-5.127, P = 0.022), procalcitonin (OR = 2.845, 95%CI:1.472-5.498, P = 0.016) and PI3K (OR = 3.210, 95%CI: 1.708-6.032, P < 0.001) were all independent risk factors for AP complicated with IAI and miR-142-3p was an independent protective factor for AP complicated with IAI(OR = 0.350, 95%CI: 0.162-0.757, P < 0.001). The results of the nomogram prediction model showed that PI3K and miR-142-3p had high predictive value for AP complicated with IAI, and the consistency indexes were 0.743 and 0.707,respectively. The calibration curve analysis showed that the prediction model predicted risks of AP complicated with IAI and actual risk of occurrence, and the mean absolute error was 0.026, and it was within the acceptable range.Within the threshold range of 0.1-0.5, the net benefit rate of combined assessment of AP complicated with IAI was superior to that of PI3K and miR-142-3p alone.

Conclusions

AP patients show low expression of miR-142-3p and high expression of PI3K, and the expression levels are independent influencing factors for concurrent IAI. Clinically,the risk of AP patients with IAI can be evaluated by detecting the levels of the two indexes.

表1 观察组和健康对照组血清miR-142-3p 和PI3K 水平(± s
表2 倾向性评分匹配前IAI 患者和非IAI 患者的基线临床特征
续表3
临床特征 IAI患者(52例) 非IAI患者(52例) 统计量 P
年龄(x¯±s,岁) 57.02±5.12 56.29±5.03 t=0.733 0.465
性别[例(%)] χ 2=0.040a 0.841
32(61.54) 31(59.62)
20(38.46) 21(40.38)
体质量指数(x¯±s,kg/m2 24.29±2.13 24.14±2.20 t=0.353 0.725
病因[例(%)] χ 2=0.909b 0.823
胆源性 8(15.38) 10(19.23)
乙醇性 3(5.77) 4(7.69)
高脂血症 40(76.92) 36(69.23)
特发性 1(1.92) 2(3.85)
并发症[例(%)]
低氧血症 43(82.69) 38(73.08) χ 2=1.396a 0.238
高血压 16(30.77) 13(25.00) χ 2=0.430a 0.512
糖尿病 10(19.23) 8(15.38) χ 2=0.269a 0.604
病情程度[例(%)] Z=0.957 0.339
MAP 26(50.00) 31(59.62)
MSAP 17(32.69) 15(28.85)
SAP 9(17.31) 6(11.54)
临床特征 IAI患者(52例) 非IAI患者(52例) 统计量 P
发病类型[例(%)] χ 2=1.077a 0.300
初发型 32(61.54) 37(71.15)
复发型 20(38.46) 15(28.85)
发病至入院时间(x¯±s,h) 11.09±3.34 10.06±3.42 t=1.554 0.123
禁食时间(x¯±s,d) 10.25±3.69 9.27±3.82 t=1.331 0.186
生化指标(x¯±s)
白细胞计数(×109/L) 15.42±3.88 13.76±3.59 t=2.265 0.026
C-反应蛋白(mg/L) 92.62±10.02 86.29±9.91 t=3.239 0.002
降钙素原(μg/L) 4.85±0.91 4.37±0.85 t=2.780 0.007
血淀粉酶(U/L) 675.64±98.67 639.88±90.82 t=1.923 0.057
血钙(mmol/L) 1.65±0.43 1.71±0.40 t=0.737 0.463
白蛋白(g/L) 27.87±5.73 25.76±6.02 t=1.831 0.070
血肌酐(μmol/L) 102.34±25.13 98.82±27.48 t=0.682 0.497
miR-142-3p 0.74±0.12 0.82±0.10 t=3.693 <0.001
PI3K(pmol/L) 202.04±40.87 160.67±42.29 t=5.073 <0.001
表4 AP 并发IAI 的影响因素
图1 AP并发IAI列线图预测模型
图2 AP并发IAI列线图预测模型的校正曲线
图3 列线图模型评估AP并发IAI的决策曲线
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