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术后脑膜炎预测规则的制定:一项横断面研究。

Development of a prediction rule for diagnosing postoperative meningitis: a cross-sectional study.

机构信息

1Academic Group of Clinical Epidemiology (GRAEPIC), School of Medicine, Universidad de Antioquia.

2Instituto Neurológico deColombia.

出版信息

J Neurosurg. 2018 Jan;128(1):262-271. doi: 10.3171/2016.10.JNS16379. Epub 2017 Mar 10.

DOI:10.3171/2016.10.JNS16379
PMID:28298047
Abstract

OBJECTIVE Diagnosing nosocomial meningitis (NM) in neurosurgical patients is difficult. The standard CSF test is not optimal and when it is obtained, CSF cultures are negative in as many as 70% of cases. The goal of this study was to develop a diagnostic prediction rule for postoperative meningitis using a combination of clinical, laboratory, and CSF variables, as well as risk factors (RFs) for CNS infection. METHODS A cross-sectional study was performed in 4 intensive care units in Medellín, Colombia. Patients with a history of neurosurgical procedures were selected at the onset of febrile symptoms and/or after an increase in acute-phase reactants. Their CSF was studied for suspicion of infection and a bivariate analysis was performed between the dependent variable (confirmed/probable NM) and the identified independent variables. Those variables with a p value ≤ 0.2 were fitted in a multiple logistic regression analysis with the same dependent variable. After determining the best model according to its discrimination and calibration, the β coefficient for each selected dichotomized variable obtained from the logistic regression model was used to construct the score for the prediction rule. RESULTS Among 320 patients recruited for the study, 154 had confirmed or probable NM. Using bivariate analysis, 15 variables had statistical associations with the outcome: aneurysmal subarachnoid hemorrhage (aSAH), traumatic brain injury, CSF leak, positioning of external ventricular drains (EVDs), daily CSF draining via EVDs, intraventricular hemorrhage, neurological deterioration, age ≥ 50 years, surgical duration ≥ 220 minutes, blood loss during surgery ≥ 200 ml, C-reactive protein (CRP) ≥ 6 mg/dl, CSF/serum glucose ratio ≤ 0.4 mmol/L, CSF lactate ≥ 4 mmol/L, CSF leukocytes ≥ 250 cells, and CSF polymorphonuclear (PMN) neutrophils ≥ 50%. The multivariate analysis fitted a final model with 6 variables for the prediction rule (aSAH diagnosis: 1 point; CRP ≥ 6 mg/dl: 1 point; CSF/serum glucose ratio ≤ 0.4 mmol/L: 1 point; CSF leak: 1.5 points; CSF PMN neutrophils ≥ 50%: 1.5 points; and CSF lactate ≥ 4 mmol/L: 4 points) with good calibration (Hosmer-Lemeshow goodness of fit = 0.71) and discrimination (area under the receiver operating characteristic curve = 0.94). CONCLUSIONS The prediction rule for diagnosing NM improves the diagnostic accuracy in neurosurgical patients with suspicion of infection. A score ≥ 6 points suggests a high probability of neuroinfection, for which antibiotic treatment should be considered. An independent validation of the rule in a different group of patients is warranted.

摘要

目的

神经外科患者的医院获得性脑膜炎(NM)诊断较为困难。标准的脑脊液(CSF)检测并不理想,且获得 CSF 时,多达 70%的病例 CSF 培养为阴性。本研究的目的是建立一种使用临床、实验室和 CSF 变量以及中枢神经系统(CNS)感染的危险因素(RFs)的术后脑膜炎诊断预测规则。

方法

在哥伦比亚麦德林的 4 个重症监护病房进行了一项横断面研究。在出现发热症状和/或急性反应蛋白升高时,选择有神经外科手术史的患者。对其 CSF 进行感染疑似检测,并对因变量(确诊/可能 NM)与鉴定出的独立变量进行双变量分析。p 值≤0.2 的变量进行多元逻辑回归分析,采用相同的因变量。根据其区分度和校准确定最佳模型后,从逻辑回归模型中获得的每个选定二分类变量的β系数用于构建预测规则的评分。

结果

在为研究招募的 320 名患者中,有 154 名患有确诊或可能 NM。通过双变量分析,有 15 个变量与结果有统计学关联:蛛网膜下腔出血(aSAH)、创伤性脑损伤、CSF 漏、外部脑室引流管(EVD)定位、EVD 每日引流 CSF、脑室内出血、神经功能恶化、年龄≥50 岁、手术时间≥220 分钟、术中失血≥200ml、C 反应蛋白(CRP)≥6mg/dl、CSF/血清葡萄糖比值≤0.4mmol/L、CSF 乳酸≥4mmol/L、CSF 白细胞≥250 个、CSF 多形核(PMN)中性粒细胞≥50%。多变量分析拟合了一个具有 6 个变量的预测规则的最终模型(aSAH 诊断:1 分;CRP≥6mg/dl:1 分;CSF/血清葡萄糖比值≤0.4mmol/L:1 分;CSF 漏:1.5 分;CSF PMN 中性粒细胞≥50%:1.5 分;CSF 乳酸≥4mmol/L:4 分),校准良好(Hosmer-Lemeshow 拟合优度检验=0.71),区分度高(受试者工作特征曲线下面积=0.94)。

结论

NM 诊断预测规则可提高疑似感染神经外科患者的诊断准确性。评分≥6 分提示神经感染的可能性较大,应考虑使用抗生素治疗。需要在另一组患者中对该规则进行独立验证。

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