From the Anesthesia and Critical Care Department, Hôtel Dieu, University Hospital of Nantes, Nantes, France (R.C., A.G., K.A.) Anesthesia and Critical Care Department, Hôpital La Timone, University Hospital of Marseille, Marseille, France (N.B., T.T.) Anesthesia and Critical Care Department, Hôpital Pierre-Paul Ricquet, University Toulouse 3-Paul Sabatier, Toulouse, France (M.S., T.G., V.A.) Anesthesia and Critical Care Department, Hôpital Beaujon, Assistance Publique des Hôpitaux de Paris, Clichy, France (C.P.-B., J.J.) Anesthesia and Critical Care Department, Hôpital Pontchaillou, University Hospital of Rennes, and University of Rennes 1, Rennes, France (H.B., S.V., M.G.) Anesthesia and Critical Care Department, Hôpital de Hautepierre, University Hospital of Strasbourg, Strasbourg, France (J.P., D.V.) Anesthesia and Critical Care Department, Hôpital Laennec, University Hospital of Nantes, Saint-Herblain, France (K.L., Y.B., B.R.) Institut du Thorax, Institut National de la Santé et de la Recherche Médicale, UMR1087, Institut de Recherche en Santé, University Hospital of Nantes, Nantes, France (B.R.) Plateforme de Méthodologie et de Biostatistique, Cellule de Promotion de la Recherche Clinique, University Hospital of Nantes, Nantes, France (A.L.T., F.F.) Institut National de la Santé et de la Recherche Médicale MethodS for Patients-centered outcomes and HEalth REsearch U1246, Unité de Formation de Recherche des Sciences Pharmaceutiques, University of Nantes, University of Tours, Nantes, France (F.F.) Laboratoire Unité propre de l'enseignement supérieur et de recherche EA 3826, University Hospital of Nantes, Nantes, France (K.A.). Anesthesia and Critical Care Department, Hôpital Cochin, Paris, France Anesthesia and Critical Care Department, Hôpital Foch, Suresnes, France Anesthesia and Critical Care Department, Hôpital Raymond Poincaré, Garches, France Anesthesia and Critical Care Department, Hôpital Européen Georges Pompidou, Paris, France. Anesthesia and Critical Care Department, Hôpital Européen Georges Pompidou, Paris, France.
Anesthesiology. 2018 Dec;129(6):1111-1120. doi: 10.1097/ALN.0000000000002426.
WHAT THIS ARTICLE TELLS US THAT IS NEW: BACKGROUND:: Craniotomy for brain tumor displays significant morbidity and mortality, and no score is available to discriminate high-risk patients. Our objective was to validate a prediction score for postoperative neurosurgical complications in this setting.
Creation of a score in a learning cohort from a prospective specific database of 1,094 patients undergoing elective brain tumor craniotomy in one center from 2008 to 2012. The validation cohort was validated in a prospective multicenter independent cohort of 830 patients from 2013 to 2015 in six university hospitals in France. The primary outcome variable was postoperative neurologic complications requiring in-intensive care unit management (intracranial hypertension, intracranial bleeding, status epilepticus, respiratory failure, impaired consciousness, unexpected motor deficit). The least absolute shrinkage and selection operator method was used for potential risk factor selection with logistic regression.
Severe complications occurred in 125 (11.4%) and 90 (10.8%) patients in the learning and validation cohorts, respectively. The independent risk factors for severe complications were related to the patient (Glasgow Coma Score before surgery at or below 14, history of brain tumor surgery), tumor characteristics (greatest diameter, cerebral midline shift at least 3 mm), and perioperative management (transfusion of blood products, maximum and minimal systolic arterial pressure, duration of surgery). The positive predictive value of the score at or below 3% was 12.1%, and the negative predictive value was 100% in the learning cohort. In-intensive care unit mortality was observed in eight (0.7%) and six (0.7%) patients in the learning and validation cohorts, respectively.
The validation of prediction scores is the first step toward on-demand intensive care unit admission. Further research is needed to improve the score's performance before routine use.
这篇文章主要介绍了什么：背景：开颅手术治疗脑肿瘤会带来显著的发病率和死亡率，目前还没有评分系统能够区分高危患者。我们的目标是验证该手术环境下术后神经外科并发症的预测评分。
方法：在一家中心的 2008 年至 2012 年期间接受择期脑肿瘤开颅手术的 1094 名患者前瞻性特定数据库中创建评分。验证队列在法国六家大学医院的 2013 年至 2015 年期间的前瞻性多中心独立队列中进行验证，该队列中共有 830 名患者。主要结局变量是需要在重症监护病房治疗的术后神经并发症（颅内高压、颅内出血、癫痫持续状态、呼吸衰竭、意识障碍、意外运动障碍）。采用最小绝对收缩和选择算子方法进行逻辑回归的潜在风险因素选择。
结果：学习队列中有 125 例（11.4%）和验证队列中有 90 例（10.8%）患者发生严重并发症。严重并发症的独立危险因素与患者（术前格拉斯哥昏迷评分≤14 分、脑肿瘤手术史）、肿瘤特征（最大直径、中线移位至少 3 毫米）和围手术期管理（输血、最大和最小收缩压、手术持续时间）有关。该评分在学习队列中等于或低于 3%的阳性预测值为 12.1%，阴性预测值为 100%。学习和验证队列中分别有 8 例（0.7%）和 6 例（0.7%）患者发生 ICU 死亡。
结论：预测评分的验证是按需入住 ICU 的第一步。在常规使用之前，需要进一步研究来提高评分的性能。
