白细胞群落参数在血流感染脓毒症患者中的诊断价值
Diagnostic Value of Cell Population Data for Sepsis in Patients with Bloodstream Infection
DOI: 10.12677/acm.2026.162400, PDF,   
作者: 贾凯迎:青岛大学青岛医学院,山东 青岛;淄博市市立医院检验科,山东 淄博;于谨铭, 王效淦:淄博市市立医院检验科,山东 淄博;王 清*, 李 静*:青岛大学青岛医学院,山东 青岛;青岛大学附属医院检验科,山东 青岛
关键词: 血流感染脓毒症白细胞群落参数联合检测Bloodstream Infection Sepsis Cell Population Data Combined Detection
摘要: 目的:探讨白细胞群落参数(cell population data, CPD)在血流感染脓毒症中的诊断价值。方法:选取2020年8月~2023年9月淄博市市立医院收治的血流感染脓毒症患者73例,选择同期在该院进行健康体检者60例作为健康对照。比较两组间CPD差异,通过二元Logistic回归分析影响血流感染脓毒症诊断的因素,绘制受试者工作特征(receiver operator characteristic, ROC)曲线,评估相关变量在血流感染脓毒症中的诊断效能,各指标间的相关性采用Spearman相关性分析。根据血培养结果比较革兰阳性菌和革兰阴性菌血流感染脓毒症组间相关指标的差异。根据药敏结果分为耐药菌68例,非耐药菌34例,比较两组间CPD差异。结果:对CPD进行单因素及二元Logistic回归分析,发现单核细胞细胞复杂性(MO-X) (OR = 1.563, P = 0.030)、中性粒细胞侧向散射光分布宽度(NE-WX) (OR = 1.063, P = 0.019)、中性粒细胞的荧光强度分布宽度(NE-WY) (OR = 1.044, P = 0.003)是血流感染脓毒症发生的独立危险因素。对上述独立危险因素进行ROC曲线分析,发现MO-X、NE-WX、NE-WY三指标联合检测对血流感染脓毒症的诊断性能AUC (95% CI)为0.918 (0.874~0.963),特异度0.933,敏感度为0.781。MO-X和NE-WY与SOFA评分之间存在正相关性(rs = 0.242, 0.305, P = 0.040, 0.009)。PCT在革兰阴性菌血流感染脓毒症组中较革兰阳性菌血流感染脓毒症组显著升高(P < 0.05)。革兰阳性菌血流感染脓毒症组的淋巴细胞荧光分布宽度(LY-WY)比革兰阴性菌血流感染脓毒症组高(P < 0.05)。耐药菌感染组和非耐药菌感染组两组间CPD差异无统计学意义。结论:CPD参数在血流感染脓毒症的诊断方面具有一定价值,在区分革兰阳性菌和革兰阴性菌感染方面也存在一定潜力。
Abstract: Objective: To investigate the diagnostic value of cell population data (CPD) in patients with sepsis caused by bloodstream infection. Methods: A total of 73 patients with bloodstream infection-associated sepsis admitted to Zibo Municipal Hospital between August 2020 and September 2023 were enrolled. Sixty healthy individuals who underwent physical examinations during the same period were included as controls. Differences in CPD parameters between the two groups were compared. Binary Logistic regression analysis was performed to identify factors associated with the diagnosis of bloodstream infection sepsis. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance of relevant variables of bloodstream infection sepsis. Correlations among various indicators were analyzed using Spearman correlation analysis. According to blood culture results, differences in related parameters between Gram-positive and Gram-negative bacterial bloodstream infection sepsis were compared. Based on antimicrobial susceptibility testing, patients were classified into 68 drug-resistant and 34 non-drug-resistant bacterial infection groups, and differences in CPD were compared between the two groups. Results: Univariate and binary Logistic regression analyses of CPD identified MO-X (OR = 1.563, P = 0.030), NE-WX (OR = 1.063, P = 0.019), and NE-WY (OR = 1.044, P = 0.003) as independent risk factors for bloodstream infection sepsis. ROC curve analysis of the above independent risk factors revealed that the combined detection of MO-X, NE-WX, and NE-WY for the diagnosis of bloodstream infection-associated sepsis had an AUC (95% CI) of 0.918 (0.874~0.963), with a specificity of 0.933 and sensitivity of 0.781. MO-X and NE-WY were positively correlated with the SOFA score (rs = 0.242 and 0.305, respectively; P = 0.040 and 0.009). Procalcitonin (PCT) levels were significantly higher in patients with Gram-negative bacterial bloodstream infection sepsis than in those with Gram-positive bacterial bloodstream infection sepsis (P < 0.05). LY-WY was significantly higher in the Gram-positive bacterial group than in the Gram-negative bacterial group (P < 0.05). No significant differences in CPD parameters were observed between the drug-resistant and non-drug-resistant bacterial infection groups. Conclusion: CPD parameters have diagnostic value in bloodstream infection sepsis and show potential utility in differentiating between Gram-positive and Gram-negative bacterial infections.
文章引用:贾凯迎, 于谨铭, 王效淦, 王清, 李静. 白细胞群落参数在血流感染脓毒症患者中的诊断价值[J]. 临床医学进展, 2026, 16(2): 349-359. https://doi.org/10.12677/acm.2026.162400

参考文献

[1] 周梦兰, 杨启文, 于淑颖, 等. 血流感染流行病学研究进展[J]. 中国感染与化疗杂志, 2019, 19(2): 212-217.
[2] Chumbita, M., Puerta-Alcalde, P., Gudiol, C., Garcia-Pouton, N., Laporte-Amargós, J., Ladino, A., et al. (2022) Impact of Empirical Antibiotic Regimens on Mortality in Neutropenic Patients with Bloodstream Infection Presenting with Septic Shock. Antimicrobial Agents and Chemotherapy, 66, e0174421. [Google Scholar] [CrossRef] [PubMed]
[3] Urrechaga, E., Bóveda, O. and Aguirre, U. (2018) Improvement in Detecting Sepsis Using Leukocyte Cell Population Data (CPD). Clinical Chemistry and Laboratory Medicine, 57, 918-926. [Google Scholar] [CrossRef] [PubMed]
[4] Urrechaga, E. (2020) Reviewing the Value of Leukocytes Cell Population Data (CPD) in the Management of Sepsis. Annals of Translational Medicine, 8, 953-953. [Google Scholar] [CrossRef] [PubMed]
[5] Gyawali, B., Ramakrishna, K. and Dhamoon, A.S. (2019) Sepsis: The Evolution in Definition, Pathophysiology, and Management. SAGE Open Medicine, 7, 1-13. [Google Scholar] [CrossRef] [PubMed]
[6] Hassan, J., Khan, S., Zahra, R., Razaq, A., Zain, A., Razaq, L., et al. (2022) Role of Procalcitonin and C-Reactive Protein as Predictors of Sepsis and in Managing Sepsis in Postoperative Patients: A Systematic Review. Cureus, 14, e31067. [Google Scholar] [CrossRef] [PubMed]
[7] Park, S.H., Park, C.J., Lee, B.R., et al. (2015) Sepsis Affects Most Routine and Cell Population Data (CPD) Obtained Using the Sysmex XN-2000 Blood Cell Analyzer: Neutrophil-Related CPD NE-SFL and NE-WY Provide Useful Information for Detecting Sepsis. International Journal of Laboratory Hematology, 37, 190-198. [Google Scholar] [CrossRef] [PubMed]
[8] Urrechaga, E., Bóveda, O. and Aguirre, U. (2018) Role of Leucocytes Cell Population Data in the Early Detection of Sepsis. Journal of Clinical Pathology, 71, 259-266. [Google Scholar] [CrossRef] [PubMed]
[9] Manson, J., Thiemermann, C. and Brohi, K. (2011) Trauma Alarmins as Activators of Damage-Induced Inflammation. British Journal of Surgery, 99, 12-20. [Google Scholar] [CrossRef] [PubMed]
[10] Burn, G.L., Foti, A., Marsman, G., Patel, D.F. and Zychlinsky, A. (2021) The Neutrophil. Immunity, 54, 1377-1391. [Google Scholar] [CrossRef] [PubMed]
[11] Miyajima, Y., Niimi, H., Ueno, T., Matsui, A., Higashi, Y., Kojima, N., et al. (2023) Predictive Value of Cell Population Data with Sysmex XN-Series Hematology Analyzer for Culture-Proven Bacteremia. Frontiers in Medicine, 10, Article 1156889. [Google Scholar] [CrossRef] [PubMed]
[12] Buoro1, S., Seghezzi, M., Vavassori, M., Dominoni, P., Apassiti Esposito, S., Manenti, B., et al. (2016) Clinical Significance of Cell Population Data (CPD) on Sysmex XN-9000 in Septic Patients with Our without Liver Impairment. Annals of Translational Medicine, 4, 418-418. [Google Scholar] [CrossRef] [PubMed]
[13] Yan, S.T., Sun, L.C., Lian, R., Tao, Y.K., Zhang, H.B. and Zhang, G. (2018) Diagnostic and Predictive Values of Procalcitonin in Bloodstream Infections for Nosocomial Pneumonia. Journal of Critical Care, 44, 424-429. [Google Scholar] [CrossRef] [PubMed]
[14] Bilgili, B., Haliloğlu, M., Aslan, M.S., Sayan, İ., Kasapoğlu, U.S. and Cinel, İ. (2018) Diagnostic Accuracy of Procalcitonin for Differentiating Bacteraemic Gram-Negative Sepsis from Gram-Positive Sepsis. The Turkish Journal of Anaesthesiology and Reanimation, 46, 38-43.
[15] Luo, X., Chen, S., Zhang, J., Ren, J., Chen, M., Lin, K., et al. (2019) Procalcitonin as a Marker of Gram-Negative Bloodstream Infections in Hematological Patients with Febrile Neutropenia. Leukemia & Lymphoma, 60, 2441-2448. [Google Scholar] [CrossRef] [PubMed]
[16] 彭婷婷, 刘云红, 轩凯. 脓毒症患者炎症因子与内毒素变化和细菌类型及病情的关系研究[J]. 中华医院感染学杂志, 2020, 30(4): 487-491.
[17] 朱永, 李娜, 何振扬, 等. 降钙素原与C-反应蛋白联合检测在革兰阴性杆菌血流感染脓毒症患者中的临床分析[J]. 中华医院感染学杂志, 2016, 26(6): 1238-1240.
[18] 韩小娟, 伦瑞花, 张轩. 血清降钙素原对血流感染病原菌的鉴别诊断[J]. 中华医院感染学杂志, 2017, 27(10): 2186-2189.
[19] 何缘, 王然, 郝静, 等. 中性粒细胞与淋巴细胞比值在脓毒症中的应用进展[J]. 医学综述, 2017, 23(18): 3595-3598+3603.
[20] 刘英其, 李春梅, 叶晓燕, 等. 血流感染脓毒症患者炎症因子水平动态变化对病情严重程度及预后的预测分析[J]. 中华医院感染学杂志, 2018, 28(10): 1459-1462.