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大数据中的小洞察:颅底手术后的脑脊液漏和数据库研究的局限性。

Little Insights from Big Data: Cerebrospinal Fluid Leak After Skull Base Surgery and the Limitations of Database Research.

机构信息

Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota, USA.

Department of Neurologic Surgery, Mayo Clinic, Rochester, Minnesota, USA; Mayo Clinic Neuro-Informatics Laboratory, Mayo Clinic, Rochester, Minnesota, USA.

出版信息

World Neurosurg. 2019 Jul;127:e561-e569. doi: 10.1016/j.wneu.2019.03.207. Epub 2019 Mar 28.

Abstract

BACKGROUND

Cerebrospinal fluid (CSF) leak is a frustrating complication of skull base surgery. Published methodologies using national surgical databases to assess CSF leak have not accounted for variability between skull base operations.

OBJECTIVE

Our goal was to attempt the development of a novel framework for adapting big data techniques to skull base surgery and assess the reliability of corresponding data manipulations.

METHODS

A retrospective nested case-control analysis was performed using patients from the National Surgical Quality Improvement Program (NSQIP) registry, 2012-2015. Current Procedural Terminology and International Classification of Diseases, Ninth Revision codes identified possible skull base operations, which were systematically grouped by anatomic location. Meningioma, schwannoma, pituitary adenoma, and trigeminal neuralgia (TN) were included.

RESULTS

Of 2918 patients, 84 (2.9%) were readmitted/reoperated on within 30 days for CSF leak. Operations involving the anterior fossa, both middle/posterior fossas in 1 approach, or the orbitocranial zygomatic approach were significantly associated with CSF leak, as were schwannomas and meningiomas in any location (8.5%, 3.1%, 10.2%, 4.1%, and 3.0%; all P < 0.0001). Multivariate analysis of only middle/posterior fossa lesions identified schwannoma (odds ratio [OR], 2.7; 95% confidence interval [CI], 1.3-5.6; P = 0.008), TN (OR, 5.4; 95% CI, 2-14.7; P = 0.008), chronic obstructive pulmonary disease (OR, 3.9; 95% CI, 1.1-14; P = 0.03), and increased operative time (OR, 4.0; 95% CI, 1.7-9.5; P = 0.009) as significant CSF leak risk factors.

CONCLUSIONS

Based on NSQIP data analyzed using a rational skull base/anatomic framework, risk factors for postoperative CSF leak include chronic obstructive pulmonary disease, operative time, anterior fossa meningioma, and middle/posterior fossa schwannoma or TN. Although databases such as NSQIP can be extensively manipulated to generate surrogate results that may provide limited insight, applications beyond their design should be approached carefully.

摘要

背景

脑脊液(CSF)漏是颅底手术令人沮丧的并发症。使用国家外科数据库发表的方法来评估 CSF 漏,并未考虑到颅底手术之间的差异。

目的

我们的目标是尝试开发一种将大数据技术应用于颅底手术的新框架,并评估相应数据操作的可靠性。

方法

对 2012-2015 年国家外科质量改进计划(NSQIP)登记处的患者进行回顾性嵌套病例对照分析。使用当前的手术程序术语和国际疾病分类,第九版代码确定可能的颅底手术,并根据解剖位置对其进行系统分组。纳入脑膜瘤、神经鞘瘤、垂体腺瘤和三叉神经痛(TN)。

结果

在 2918 名患者中,有 84 名(2.9%)在 30 天内因 CSF 漏而再次住院/再次手术。涉及前颅窝、中/后颅窝在 1 个入路中或眶颅颧入路的手术与 CSF 漏显著相关,任何部位的神经鞘瘤和脑膜瘤也是如此(8.5%、3.1%、10.2%、4.1%和 3.0%;均 P < 0.0001)。仅对中/后颅窝病变进行的多变量分析确定了神经鞘瘤(比值比[OR],2.7;95%置信区间[CI],1.3-5.6;P = 0.008)、TN(OR,5.4;95% CI,2-14.7;P = 0.008)、慢性阻塞性肺疾病(OR,3.9;95% CI,1.1-14;P = 0.03)和手术时间延长(OR,4.0;95% CI,1.7-9.5;P = 0.009)是 CSF 漏的显著危险因素。

结论

根据使用合理的颅底/解剖框架对 NSQIP 数据进行的分析,术后 CSF 漏的危险因素包括慢性阻塞性肺疾病、手术时间、前颅窝脑膜瘤以及中/后颅窝神经鞘瘤或 TN。尽管像 NSQIP 这样的数据库可以进行广泛的操作以生成可能提供有限见解的替代结果,但应谨慎应用超出其设计的应用。

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