Department of Pharmacy, Mayo Clinic, 200 1st St SW, Rochester, MN, 55902, USA.
Division of Neurology, Mayo Clinic, Rochester, MN, USA.
Neurocrit Care. 2022 Aug;37(1):73-80. doi: 10.1007/s12028-022-01442-1. Epub 2022 Feb 8.
Beta-lactam neurotoxicity is a relatively uncommon yet clinically significant adverse effect in critically ill patients. This study sought to define the incidence of neurotoxicity, derive a prediction model for beta-lactam neurotoxicity, and then validate the model in an independent cohort of critically ill adults.
This retrospective cohort study evaluated critically ill patients treated with ≥ 48 h of cefepime, piperacillin/tazobactam, or meropenem. Two separate cohorts were created: a derivation cohort and a validation cohort. Patients were screened for beta-lactam neurotoxicity by using search terms and diagnosis codes, followed by clinical adjudication using a standardized adverse event scoring tool. Multivariable regression models and least absolute shrinkage and selection operator were used to identify surrogates for neurotoxicity and develop a multivariable prediction model.
The overall incidence of beta-lactam neurotoxicity was 2.6% (n/N = 34/1323) in the derivation cohort and 2.1% in the validation cohort (n/N = 16/767). The final multivariable neurotoxicity assessment tool included weight, Charlson comorbidity score, age, and estimated creatinine clearance as predictors of neurotoxicity. Incidence of neurotoxicity reached 4% in those with a body mass index more than 30 kg/m. Use of the candidate variables in the neurotoxicity assessment tool suggested that a score more than 35 would identify a patient at high risk for neurotoxicity with 75% sensitivity and 54% specificity.
In this single center cohort of critically ill patients, beta-lactam neurotoxicity was demonstrated less frequently than previously reported. We identified obesity as a novel risk factor for the development of neurotoxicity. The prediction model needs to be further refined before it can be used in clinical practice as a tool to avoid drug-related harm.
β-内酰胺类神经毒性是危重症患者中一种相对罕见但具有临床重要意义的不良反应。本研究旨在确定神经毒性的发生率，为β-内酰胺类神经毒性建立预测模型，并在另一组独立的危重症成人患者中验证该模型。
本回顾性队列研究评估了接受≥48 小时头孢吡肟、哌拉西林/他唑巴坦或美罗培南治疗的危重症患者。创建了两个独立的队列：一个推导队列和一个验证队列。通过使用搜索词和诊断代码筛选出β-内酰胺类神经毒性患者，然后使用标准化不良事件评分工具进行临床判断。使用多变量回归模型和最小绝对收缩和选择算子（LASSO）来识别神经毒性的替代指标，并建立多变量预测模型。
在推导队列中，β-内酰胺类神经毒性的总发生率为 2.6%（n/N=34/1323），验证队列中为 2.1%（n/N=16/767）。最终的多变量神经毒性评估工具包括体重、Charlson 合并症评分、年龄和估计的肌酐清除率作为神经毒性的预测指标。体重指数（BMI）超过 30 kg/m2的患者，神经毒性发生率达到 4%。使用神经毒性评估工具中的候选变量提示，评分超过 35 分可识别出神经毒性高风险患者，其敏感性为 75%，特异性为 54%。
在本单中心危重症患者队列中，β-内酰胺类神经毒性的发生率低于先前报道。我们发现肥胖是神经毒性发生的一个新的危险因素。该预测模型需要进一步细化，才能在临床实践中作为避免药物相关伤害的工具使用。
