肝素结合蛋白辅助临床血流感染诊断的价值

doi:10.16150/j.1671-2870.2023.02.007

摘要/Abstract

摘要：

目的：研究肝素结合蛋白（heparin-binding protein，HBP）检测在辅助诊断血流感染中的价值。方法：选取上海交通大学医学院附属瑞金医院2021年1月至2022年1月期间收治的207例血培养阳性住院患者及94例血培养阴性住院患者。检测血培养标本采集当日患者的HBP、降钙素原（procalcitonin, PCT）、C反应蛋白（C-reactive protein, CRP）水平及白细胞计数（white blood cell count, WBC）、中性粒细胞计数（absolute neutrophil count, ANC）、中性粒细胞/淋巴细胞计数比值（neutrophil-lymphocyte count ratio, NLCR）。比较血培养阳性组与阴性组间各指标水平的差异，并比较不同病原菌血流感染患者的HBP水平差异，用受试者操作特征曲线（receiver operator characteristic curve， ROC曲线）评估上述指标单独及联合检测对血流感染的辅助诊断价值。结果：血培养阳性患者的所有指标水平均显著高于血培养阴性患者。革兰阳性菌组血流感染患者的HBP水平与革兰阴性菌组患者相比，差异无统计学意义（中位数，70.26 ng/mL比89.15 ng/mL）,但二者均显著高于真菌感染患者（中位数22.90 ng/mL）（P<0.05）。诊断血流感染的ROC曲线显示，HBP的曲线下面积最大（0.742)，灵敏度为66.80%，特异度为74.40%，诊断效能显著优于WBC（0.622，灵敏度64.70%，特异度59.80%）、ANC（0.651，灵敏度51.60%，特异度75.60%）和NLCR（0.618，灵敏度72.10%，特异度48.80%）（P<0.05），且在排除恶性肿瘤或造血系统疾病患者后，HBP仍有相近的诊断效能（0.708，灵敏度60.50%，特异度78.70%）。HBP联合PCT检测是辅助诊断血流感染的最优组合，曲线下面积达0.751。结论：HBP检测对血流感染诊断有较好的参考价值。PCT是HBP联合检测诊断血流感染的优选项。

关键词: 血流感染, 肝素结合蛋白, 降钙素原, C反应蛋白

Abstract:

Objective: To investigate the diagnostic value of heparin-binding protein (HBP) in bloodstream infections. Methods: Two hundred and seven inpatients with positive blood culture results and 94 inpatients with negative results admitted to Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from January 2021 to January 2022 were enrolled. The levels of HBP, procalcitonin (PCT), C-reactive protein (CRP), white blood cell count (WBC), absolute neutrophil count (ANC), and neutrophil-lymphocyte count ratio (NLCR) were detected on the day of blood culture specimens were collected. The levels of each biomarker between the blood culture positive group and the negative group were compared. The comparison of HBP levels in patients with bloodstream infection between different pathogens was also conducted. The receiver operator characteristic curve (ROC curve) were used to evaluate the diagnostic effectiveness of the above biomarkers and combined detection for bloodstream infection. Results: The levels of all the biomarkers were significantly elevated in patients with positive blood culture compared with those with negative results. Moreover, HBP levels in patients infected with Gram-positive bacterial were not significantly different from those infected with Gram-negative bacterial (median 70.26 ng/mL vs 89.15 ng/mL), but both of them were significantly higher than those in patients infected with fungi (median 22.90 ng/mL). The ROC curves for the diagnosis of bloodstream infections showed that HBP demonstrated a higher area under the curve (0.742, sensitivity 66.80%, specificity 74.40%), compared with WBC (0.622, sensitivity 64.70%, specificity 59.80%), ANC (0.651, sensitivity 51.60%, specificity 75.60%) and NLCR (0.618, sensitivity 72.10%, specificity 48.80%) significantly (P<0.05). After excluding patients with malignancies or hematopoietic disorders, the diagnostic value of HBP showed a similar result (0.708, sensitivity 60.50%, specificity 78.70%). The detection of combined HBP and PCT was an optimal choose for bloodstream infection, with an area under the curve of 0.751. Conclusions: HBP possesses a significant diagnostic value for bloodstream infections, and combination of HBP and PCT may be the preferred approach for accurate diagnosis.

Key words: Bloodstream infection, Heparin-binding protein, Procalcitonin, C-reactive protein

中图分类号:

R515.3

林瀚, 祖拜热古丽·麦麦提阿卜拉, 苏同轩. 肝素结合蛋白辅助临床血流感染诊断的价值[J]. 诊断学理论与实践, 2023, 22(02): 147-153.

LIN Han, ZUBAIREGULI Maimaitiabula, SU Tongxuan. Value of heparin-binding protein in diagnosis of bloodstream infection[J]. Journal of Diagnostics Concepts & Practice, 2023, 22(02): 147-153.

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参考文献 23

[1]	XIE J, WANG H, KANG Y, et al. The Epidemiology of Sepsis in Chinese ICUs: A National Cross-Sectional Survey[J]. Crit Care Med, 2020, 48(3):e209-e218. doi: 10.1097/CCM.0000000000004155 URL
[2]	BAUER M, GERLACH H, VOGELMANN T, et al. Mortality in sepsis and septic shock in Europe, North America and Australia between 2009 and 2019- results from a systematic review and meta-analysis[J]. Crit Care, 2020, 24(1):239. doi: 10.1186/s13054-020-02950-2
[3]	GOTO M, AL-HASAN M N. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe[J]. Clin Microbiol Infect, 2013, 19(6):501-509. doi: 10.1111/1469-0691.12195 URL
[4]	PAOLI C J, REYNOLDS M A, SINHA M, et al. Epidemio-logy and Costs of Sepsis in the United States-An Analysis Based on Timing of Diagnosis and Severity Level[J]. Crit Care Med, 2018, 46(12):1889-1897. doi: 10.1097/CCM.0000000000003342 URL
[5]	PIERRAKOS C, VINCENT J L. Sepsis biomarkers: a review[J]. Crit Care, 2010, 14(1):R15. doi: 10.1186/cc8872 URL
[6]	SHAFER W M, MARTIN L E, SPITZNAGEL J K. Catio-nic antimicrobial proteins isolated from human neutrophil granulocytes in the presence of diisopropyl fluorophosphate[J]. Infect Immun, 1984, 45(1):29-35. doi: 10.1128/iai.45.1.29-35.1984 URL
[7]	GAUTAM N, OLOFSSON A M, HERWALD H, et al. Heparin-binding protein (HBP/CAP37): a missing link in neutrophil-evoked alteration of vascular permeability[J]. Nat Med, 2001, 7(10):1123-1127. doi: 10.1038/nm1001-1123 pmid: 11590435
[8]	FISHER J, LINDER A. Heparin-binding protein: a key player in the pathophysiology of organ dysfunction in sepsis[J]. J Intern Med, 2017, 281(6):562-574. doi: 10.1111/joim.12604 pmid: 28370601
[9]	刘珍, 王峰, 高晖, 等. 血浆肝素结合蛋白联合降钙素原及C-反应蛋白对脓毒症及脓毒性休克患者诊断价值的研究[J]. 中国卫生检验杂志, 2021, 31(22):2696-2701.
	LIU Z, WANG F, GAO H, et al. A study on the diagnostic value of plasma heparin binding protein combined with procalcitonin and C-reactive protein for patients with sepsis and septic shock[J]. Chin J Health Lab Technol, 2021, 31(22):2696-2701.
[10]	李磊, 郑传明, 夏群, 等. 肝素结合蛋白联合降钙素原在评估急性胰腺炎合并感染中的预测价值[J]. 中华全科医学, 2020, 18(6):927-929,1068.
	LI L, ZHENG C M, XIA Q, et al. Predictive value of heparin-binding protein combined with procalcitonin in the assessment of acute pancreatitis co-infection[J]. Chin J Gen Pract, 2020, 18(6):927-929,1068.
[11]	张晓彤, 国世星, 邵青, 等. 多因子联合检测在诊断血流感染和指导抗菌药物早期合理使用中的应用价值[J]. 实用检验医师杂志, 2020, 12(1):37-41.
	ZHANG X T, GUO S X, SHAO Q, et al. Application value of multi-factor combined detection in diagnosis of bloodstream infection and guidance for early rational use of antibacterial drugs[J]. Chin J Clin Pathol, 2020, 12(1):37-41.
[12]	潘晓微, 李克诚. 血浆肝素结合蛋白和降钙素原对血流感染的诊断价值[J]. 检验医学, 2017, 32(11):999-1003.
	PAN X W, LI K C. Plasma heparin binding protein and procalcitonin in the diagnosis of bloodstream infection[J]. Lab Med, 2017, 32(11):999-1003.
[13]	MELLHAMMAR L, THELAUS L, ELÉN S, et al. Heparin binding protein in severe COVID-19-A prospective observational cohort study[J]. PLoS One, 2021, 16(4):e0249570. doi: 10.1371/journal.pone.0249570 URL
[14]	LINDER A, ÅKESSON P, INGHAMMAR M, et al. Ele-vated plasma levels of heparin-binding protein in intensive care unit patients with severe sepsis and septic shock[J]. Crit Care, 2012, 16(3):R90. doi: 10.1186/cc11353 URL
[15]	WU Y L, YO C H, HSU W T, et al. Accuracy of Heparin-Binding Protein in Diagnosing Sepsis: A Systematic Review and Meta-Analysis[J]. Crit Care Med, 2021, 49(1):e80-e90. doi: 10.1097/CCM.0000000000004738 URL
[16]	ANSAR W, GHOSH S. C-reactive protein and the bio-logy of disease[J]. Immunol Res, 2013, 56(1):131-142. doi: 10.1007/s12026-013-8384-0 URL
[17]	LI S, RONG H, GUO Q, et al. Serum procalcitonin levels distinguish Gram-negative bacterial sepsis from Gram-positive bacterial and fungal sepsis[J]. J Res Med Sci, 2016, 21:39. pmid: 27904585
[18]	WACKER C, PRKNO A, BRUNKHORST F M, et al. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis[J]. Lancet Infect Dis, 2013, 13(5):426-435. doi: 10.1016/S1473-3099(12)70323-7 pmid: 23375419
[19]	KERN W V, RIEG S. Burden of bacterial bloodstream infection-a brief update on epidemiology and significance of multidrug-resistant pathogens[J]. Clin Microbiol Infect, 2020, 26(2):151-157. doi: 10.1016/j.cmi.2019.10.031 URL
[20]	万会林, 孔德华, 周万青, 等. 降钙素原、C-反应蛋白、白细胞和中性粒细胞在鉴别血流感染中的应用价值[J]. 世界复合医学, 2019, 5(12):41-43.
	WAN H L, KONG D H, ZHOU W Q, et al. The Application Value of Procalcitonin, C-reactive Protein, Leukocytes and Neutrophils in Differential Bloodstream Infection[J]. World J Complex Med, 2019, 5(12):41-43.
[21]	OBERHOFFER M, STONANS I, RUSSWURM S, et al. Procalcitonin expression in human peripheral blood mononuclear cells and its modulation by lipopolysaccharides and sepsis-related cytokines in vitro[J]. J Lab Clin Med, 1999, 134(1):49-55. pmid: 10402059
[22]	BERAN O, POTMĚŠIL R, HOLUB M. Differences in Toll-like receptor expression and cytokine production after stimulation with heat-killed Gram-positive and Gram-negative bacteria[J]. Folia Microbiol (Praha), 2011, 56(3):283-287. doi: 10.1007/s12223-011-0025-1 URL
[23]	SNÄLL J, LINNÉR A, UHLMANN J, et al. Differential neutrophil responses to bacterial stimuli: Streptococcal strains are potent inducers of heparin-binding protein and resistin-release[J]. Sci Rep, 2016, 6:21288. doi: 10.1038/srep21288 pmid: 26887258

Biomarkers	Patients with blood culture positive （n=207）	Patients with blood culture negative （n=94）	P
HBP（ng/mL）	76.13（22.90, 148.27）	15.29（7.15, 44.46）	<0.001
PCT（ng/mL）	1.01（0.33, 4.92）	0.27（0.11, 1.33）	<0.001
CRP（ng/mL）	120.80（52.00, 178.1）	52.50（13.95, 120.45）	<0.001
WBC（10⁹/L）	10.28（5.80, 14.36）	7.40（3.69, 12.43）	0.001
ANC（10⁹/L）	8.99（4.78, 12.39）	5.65（2.50, 8.96）	<0.001
NLCR	11.30（6.27, 19.04）	7.45（3.98, 13.19）	0.001

Biomarkers	Gram-negative Bacteria（n=136）	Gram-positive Bacteria（n=53）	Fungi（n=18）
HBP（ng/mL）	89.15（37.85, 168.46）^*	70.26（17.37, 141.87）^Δ	22.90（11.10, 34.64）^*Δ
PCT（ng/mL）	1.47（0.45, 7.12）^*#	0.40（0.19, 1.36）^#	0.66（0.29, 1.82）^*
CRP（mg/L）	134.40（69.18, 186.18）^*#	84.90（18.40, 150.00）^#	60.00（52.00,100.00）^*
WBC（10⁹/L）	11.48（7.13, 15.28）^*#	8.76（5.56, 13.08）^#	5.97（3.55, 11.63）^*
ANC（10⁹/L）	9.56（5.63, 13.08）^*#	7.08（4.02, 11.12）^#	4.60（2.69, 9.99）^*
NLCR	12.40（7.52, 20.91）^*#	8.79（4.50, 14.78）^#	5.34（3.80, 12.45）^*

Species	Number	Percent	HBP (ng/mL) [Median（P25, P75）]
Gram-negative bacteria
Klebsiella Pneumoniae	66	31.89%	100.77（49.09, 186.47）
Acinetobacter baumannii	23	11.11%	106.31（20.88, 149.04）
Pseudomonas aeruginosa	17	8.21%	112.07（46.35, 162.37）
Escherichia coli	16	7.73%	57.05（17.80, 113.95）
other	14	6.76%	70.99（22.92,142.62）
Gram-positive bacteria
Staphylococcus epidermidis	14	6.76%	125.04（43.53, 242.84）
Enterococcus faecalis	10	4.83%	102.44（16.45, 175.84）
Staphylococcus aureus	7	3.38%	24.59（17.00, 141.87）
Staphylococcus hominis	4	1.93%	40.79（12.94, 111.50）
other	18	8.70%	64;45（13.87, 112.43）
Fungi
Candida parapsilosis	9	4.35%	22.90（7.15, 62.23）
Candida tropicalis	4	1.93%	23.19（11.65, 156.98）
other	5	2.42%	22.90（<5.90, 45.11）

Biomarkers	AUC	Asymptotic significance	95% Confidence interval	Cut-off	Sensitivity	Specificity
HBP（ng/mL）	0.742	<0.001	0.676-0.808	38.30	66.80%	74.40%
PCT（ng/mL）	0.685	<0.001	0.614-0.757	0.24	84.70%	47.60%
CRP（mg/L）	0.680	<0.001	0.610-0.750	103.50	54.70%	74.40%
WBC（10⁹/L）	0.622^*	0.001	0.548-0.697	8.25	64.70%	59.80%
ANC	0.651^*	<0.001	0.578-0.723	8.61	51.60%	75.60%
NLCR	0.618^*	0.002	0.545-0.692	6.86	72.10%	48.80%

Biomarkers	AUC	Asymptotic significance	95% Confidence interval	Cut-off	Sensitivity	Specificity
HBP	0.708	<0.001	0.622-0.794	59.03	60.50%	78.70%
PCT	0.598	0.039	0.503-0.694	0.24	85.50%	33.40%
CRP	0.602	0.033	0.511-0.692	103.50	55.80%	66.00%
WBC	0.527	0.57	0.433-0.621	10.16	53.50%	61.70%
ANC	0.559	0.212	0.467-0.651	8.61	52.90%	66.00%
NLCR	0.554	0.257	0.461-0.647	9.93	58.70%	55.30%