神经外科术后细菌性脑膜炎多指标联合诊断模型的建立
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摘要
目的建立神经外科术后细菌性脑膜炎诊断的多指标线性判别模型。方法回顾性分析2012—2016年某院细菌性脑膜炎(226例)和无菌性脑膜炎患者(255例)的14项实验室检查,将有意义的指标绘制受试者工作曲线(ROC曲线),曲线下面积(AUC)> 0. 7的项目进行线性回归拟合,建立多指标联合诊断线性判别模型。选取26例脑膜炎患者的数据,验证判别模型的判别能力。结果两组脑膜炎患者11项指标比较,差异有统计学意义(均P <0. 05),其中脑脊液白细胞计数(C-WBC)、脑脊液葡萄糖浓度(C-Glu)、血葡萄糖浓度(B-Glu)、脑脊液血糖比例(C/B-Glu)及脑脊液乳酸(C-Lac) 5项指标的AUC均>0. 7。通过线性拟合获得判别模型:Y=-0. 268×C-Glu+0. 127×B-Glu+0. 24×C-Lac-0. 722×C/B-Glu+0. 00000638×C-WBC-0. 866,拟合5项指标诊断细菌性脑膜炎的ROC曲线AUC为0. 907,灵敏度、特异度、阳性预测值与阴性预测值均> 80. 0%。26例脑膜炎患者的数据验证判别模型效果,结果显示,模型判别的准确率与特异度均较高(90. 0%、81. 2%),一致率达84. 6%。结论利用多指标联合诊断可以有效地区分细菌性脑膜炎与无菌性脑膜炎,更好地解决细菌性脑膜炎的诊断问题。
Objective To establish a multi-index linear discriminant model for the diagnosis of bacterial meningitis after neurosurgery operation. Methods A retrospective analysis was performed on 14 laboratory examinations of bacterial meningitis( n = 226) and aseptic meningitis( n = 255) in patients in a hospital from 2012 to 2016. Receiver operating characteristic( ROC) curve for significant variables was drawn,items with area under the curve( AUC) >0. 7 were conducted linear regression fitting,and a linear discriminant model for combined multi-index diagnosis was established,data of 26 patients with meningitis were selected to verify the discriminant capacity of the discriminant model. Results There were significant differences in 11 indexes between two groups of patients with meningitis( all P< 0. 05). AUC of cerebrospinal fluid( CSF) white blood cell count( C-WBC),CSF glucose concentration( C-Glu),blood glucose concentration( B-Glu),CSF blood glucose ratio( C/B-Glu) and CSF lactic acid( C-Lac) were all> 0. 7. The discriminant model was obtained by linear fitting: Y =-0. 268 × C-Glu + 0. 127 × B-Glu + 0. 24 × CLac-0. 722 × C/B-Glu + 0. 00000638 × C-WBC-0. 866,AUC of ROC curve of five indexes for diagnosis of bacterial meningitis was 0. 907,sensitivity,specificity,positive predictive value,and negative predictive value were all >80. 0 %. Data of 26 patients with meningitis validated the discriminant capacity of discriminant model,the accuracy and specificity discriminated by the model were high( 90. 0 %,81. 2 %),consistency rate was 84. 6 %. Conclusion The combined diagnosis of multiple indexes can effectively distinguish bacterial meningitis from aseptic meningitis,and promote the diagnosis of bacterial meningitis.
Objective To establish a multi-index linear discriminant model for the diagnosis of bacterial meningitis after neurosurgery operation. Methods A retrospective analysis was performed on 14 laboratory examinations of bacterial meningitis( n = 226) and aseptic meningitis( n = 255) in patients in a hospital from 2012 to 2016. Receiver operating characteristic( ROC) curve for significant variables was drawn,items with area under the curve( AUC) >0. 7 were conducted linear regression fitting,and a linear discriminant model for combined multi-index diagnosis was established,data of 26 patients with meningitis were selected to verify the discriminant capacity of the discriminant model. Results There were significant differences in 11 indexes between two groups of patients with meningitis( all P< 0. 05). AUC of cerebrospinal fluid( CSF) white blood cell count( C-WBC),CSF glucose concentration( C-Glu),blood glucose concentration( B-Glu),CSF blood glucose ratio( C/B-Glu) and CSF lactic acid( C-Lac) were all> 0. 7. The discriminant model was obtained by linear fitting: Y =-0. 268 × C-Glu + 0. 127 × B-Glu + 0. 24 × CLac-0. 722 × C/B-Glu + 0. 00000638 × C-WBC-0. 866,AUC of ROC curve of five indexes for diagnosis of bacterial meningitis was 0. 907,sensitivity,specificity,positive predictive value,and negative predictive value were all >80. 0 %. Data of 26 patients with meningitis validated the discriminant capacity of discriminant model,the accuracy and specificity discriminated by the model were high( 90. 0 %,81. 2 %),consistency rate was 84. 6 %. Conclusion The combined diagnosis of multiple indexes can effectively distinguish bacterial meningitis from aseptic meningitis,and promote the diagnosis of bacterial meningitis.
引文
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[5]王玉芳,王凌雁,李静超,等.脑脊液乳酸对颅脑手术后血性脑脊液患者细菌性脑膜炎的诊断价值[J].中华危重病急救医学,2017,29(5):425-430.
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[7] Li Y,Zhang G,Ma R,et al. The diagnostic value of cerebrospinal fluids procalcitonin and lactate for the differential diagnosis of post-neurosurgical bacterial meningitis and aseptic meningitis[J].Clin Biochem,2015,48(1-2):50-54.
[8] Tavares WM,Machado AG,Matushita H,et al. CSF markers for diagnosis of bacterial meningitis in neurosurgical postoperative patients[J]. Arq Neuropsiquiatr,2006,64(3A):592-595.
[9] Bonsu BK,Harper MB. Differentiating acute bacterial meningitis from acute viral meningitis among children with cerebrospinal fluid pleocytosis:a multivariable regression model[J]. Pediatr Infect Dis J,2004,23(6):511-517.
[10] Spanos A,Harrell FE Jr,Durack DT. Differential diagnosis of acute meningitis. An analysis of the predictive value of initial observations[J]. JAMA,1989,262(19):2700-2707.
[11] Mount HR,Boyle SD. Aseptic and bacterial meningitis:eva-luation,treatment,and prevention[J]. Am Fam Physician,2017,96(5):314-322.
[12] Bal ZS,Yazici P,Sen S,et al. A fatal case of tuberculous meningitis in a child with juvenile idiopathic arthritis:a diagnostic challenge[J]. Rev Soc Bras Med Trop,2017,50(5):709-711.
[13] Lee JY,Son M,Kang JH,et al. Serum interleukin-6 levels as an indicator of aseptic meningitis among children with enterovirus 71-induced hand,foot and mouth disease[J]. Postgrad Med,2018,130(2):258-263.
[14] Zhang Y,Xiao X,Zhang J,et al. Diagnostic accuracy of routine blood examinations and CSF lactate level for post-neurosurgical bacterial meningitis[J]. Int J Infect Dis,2017,59:50-54.
[15] Shokrollahi MR,Shabanzadeh K,Noorbakhsh S,et al. Diagnostic value of CRP,procalcitonin,and ferritin levels in cerebrospinal fluid of children with meningitis[J]. Cent Nerv Syst Agents Med Chem,2018,26,18(1):58-62.
[16] Gowin E,Wysocki J,Avonts D,et al. Usefulness of inflammatory biomarkers in discriminating between bacterial and aseptic meningitis in hospitalized children from a population with low vaccination coverage[J]. Arch Med Sci,2016,12(2):408-414.
[17] Srifuengfung S,Chokephaibulkit K. Detection of bacterial antigen in cerebrospinal fluid in patients with bacterial meningitis:a literature review[J]. J Med Assoc Thai,2010,93(Suppl 5):S71-S75.
[18] Cunha BA. Distinguishing bacterial from viral meningitis:the critical importance of the CSF lactic acid levels[J]. Intensive Care Med,2006,32(8):1272-1273.
[19] Wootton SH,Aguilera E,Salazar L,et al. Enhancing pathogen identification in patients with meningitis and a negative Gram stain()R using the BioFire Film Array Meningitis/Ence-phalitis panel[J]. Ann Clin Microbiol Antimicrob,2016,15:26.
[2] Durand ML,Calderwood SB,Weber DJ,et al. Acute bacterial meningitis in adults. A review of 493 episodes[J]. N Engl J Med,1993,328(1):21-28.
[3] Aku FY,Lessa FC,Asiedu-Bekoe F,et al. Meningitis outbreak caused by vaccine-preventable bacterial pathogens-Northern Ghana,2016[J]. MMWR Morb Mortal Wkly Rep,2017,66(30):806-810.
[4] Tunkel AR,Hasbun R,Bhimraj A,et al. 2017 Infectious Diseases Society of America’s clinical practice guidelines for healthcare-associated ventriculitis and meningitis[J]. Clin Infect Dis,2017,doi:10. 1093/cid/ciw861.
[5]王玉芳,王凌雁,李静超,等.脑脊液乳酸对颅脑手术后血性脑脊液患者细菌性脑膜炎的诊断价值[J].中华危重病急救医学,2017,29(5):425-430.
[6] Carmel PW,Greif LK. The aseptic meningitis syndrome:a complication of posterior fossa surgery[J]. Pediatr Neurosurg,1993,19(5):276-280.
[7] Li Y,Zhang G,Ma R,et al. The diagnostic value of cerebrospinal fluids procalcitonin and lactate for the differential diagnosis of post-neurosurgical bacterial meningitis and aseptic meningitis[J].Clin Biochem,2015,48(1-2):50-54.
[8] Tavares WM,Machado AG,Matushita H,et al. CSF markers for diagnosis of bacterial meningitis in neurosurgical postoperative patients[J]. Arq Neuropsiquiatr,2006,64(3A):592-595.
[9] Bonsu BK,Harper MB. Differentiating acute bacterial meningitis from acute viral meningitis among children with cerebrospinal fluid pleocytosis:a multivariable regression model[J]. Pediatr Infect Dis J,2004,23(6):511-517.
[10] Spanos A,Harrell FE Jr,Durack DT. Differential diagnosis of acute meningitis. An analysis of the predictive value of initial observations[J]. JAMA,1989,262(19):2700-2707.
[11] Mount HR,Boyle SD. Aseptic and bacterial meningitis:eva-luation,treatment,and prevention[J]. Am Fam Physician,2017,96(5):314-322.
[12] Bal ZS,Yazici P,Sen S,et al. A fatal case of tuberculous meningitis in a child with juvenile idiopathic arthritis:a diagnostic challenge[J]. Rev Soc Bras Med Trop,2017,50(5):709-711.
[13] Lee JY,Son M,Kang JH,et al. Serum interleukin-6 levels as an indicator of aseptic meningitis among children with enterovirus 71-induced hand,foot and mouth disease[J]. Postgrad Med,2018,130(2):258-263.
[14] Zhang Y,Xiao X,Zhang J,et al. Diagnostic accuracy of routine blood examinations and CSF lactate level for post-neurosurgical bacterial meningitis[J]. Int J Infect Dis,2017,59:50-54.
[15] Shokrollahi MR,Shabanzadeh K,Noorbakhsh S,et al. Diagnostic value of CRP,procalcitonin,and ferritin levels in cerebrospinal fluid of children with meningitis[J]. Cent Nerv Syst Agents Med Chem,2018,26,18(1):58-62.
[16] Gowin E,Wysocki J,Avonts D,et al. Usefulness of inflammatory biomarkers in discriminating between bacterial and aseptic meningitis in hospitalized children from a population with low vaccination coverage[J]. Arch Med Sci,2016,12(2):408-414.
[17] Srifuengfung S,Chokephaibulkit K. Detection of bacterial antigen in cerebrospinal fluid in patients with bacterial meningitis:a literature review[J]. J Med Assoc Thai,2010,93(Suppl 5):S71-S75.
[18] Cunha BA. Distinguishing bacterial from viral meningitis:the critical importance of the CSF lactic acid levels[J]. Intensive Care Med,2006,32(8):1272-1273.
[19] Wootton SH,Aguilera E,Salazar L,et al. Enhancing pathogen identification in patients with meningitis and a negative Gram stain()R using the BioFire Film Array Meningitis/Ence-phalitis panel[J]. Ann Clin Microbiol Antimicrob,2016,15:26.