Vanderbilt University School of Medicine, Nashville, TN, USA; Surgical Outcomes Center for Kids, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN, USA.
Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA; Surgical Outcomes Center for Kids, Monroe Carell Jr. Children's Hospital at Vanderbilt, Nashville, TN, USA.
J Stroke Cerebrovasc Dis. 2021 Apr;30(4):105658. doi: 10.1016/j.jstrokecerebrovasdis.2021.105658. Epub 2021 Feb 12.
The National Inpatient Sample (NIS) has led to several breakthroughs via large sample size. However, utility of NIS is limited by the lack of admission NIHSS and 90-day modified Rankin score (mRS). This study creates estimates for stroke severity at admission and 90-day mRS using NIS data for acute ischemic stroke (AIS) patients treated with mechanical thrombectomy (MT).
Three patient cohorts undergoing MT for AIS were utilized: Cohort 1 (N = 3729) and Cohort 3 (N = 1642) were derived from NIS data. Cohort 2 (N=293) was derived from a prospectively-maintained clinical registry. Using Cohort 1, Administrative Stroke Outcome Variable (ASOV) was created using disposition and mortality. Factors reflective of stroke severity were entered into a stepwise logistic regression predicting poor ASOV. Odds ratios were used to create the Administrative Data Stroke Scale (ADSS). Performances of ADSS and ASOV were tested using Cohort 2 and compared with admission NIHSS and 90-day mRS, respectively. ADSS performance was compared with All Patient Refined-Diagnosis Related Group (APR-DRG) severity score using Cohort 3.
Agreement of ASOV with 90-day mRS > 2 was fair (κ = 0.473). Agreement with 90-day mRS > 3 was substantial (κ = 0.687). ADSS significantly correlated (p < 0.001) with clinically-significant admission NIHSS > 15. ADSS performed comparably (AUC = 0.749) to admission NIHSS (AUC = 0.697) in predicting 90-day mRS > 2 and mRS > 3 (AUC = 0.767, 0.685, respectively). ADSS outperformed APR-DRG severity score in predicting poor ASOV (AUC = 0.698, 0.682, respectively).
We developed and validated measures of stroke severity at admission (ADSS) and outcome (ASOV, estimate for 90-day mRS > 3) to increase utility of NIS data in stroke research.
国家住院患者样本(NIS)通过大样本量取得了多项突破。然而,由于缺乏入院 NIHSS 和 90 天改良 Rankin 评分(mRS),其应用受到限制。本研究利用 NIS 数据,针对接受机械取栓治疗的急性缺血性脑卒中(AIS)患者,建立入院时及 90 天 mRS 的脑卒中严重程度预测模型。
本研究利用了接受机械取栓治疗的 AIS 患者的三个患者队列:队列 1(N=3729)和队列 3(N=1642)来自 NIS 数据,队列 2(N=293)来自前瞻性维护的临床登记处。利用队列 1,通过结局和死亡率,创建行政性脑卒中结局变量(ASOV)。将反映脑卒中严重程度的因素纳入逐步逻辑回归模型,以预测不良 ASOV。比值比用于创建行政数据脑卒中量表(ADSS)。利用队列 2 对 ADSS 和 ASOV 的性能进行了测试,并分别与入院 NIHSS 和 90 天 mRS 进行了比较。利用队列 3 对 ADSS 与所有患者修正诊断相关组(APR-DRG)严重程度评分的性能进行了比较。
ASOV 与 90 天 mRS>2 的一致性为中度(κ=0.473),与 90 天 mRS>3 的一致性为高度(κ=0.687)。ADSS 与有临床意义的入院 NIHSS>15 显著相关(p<0.001)。ADSS 在预测 90 天 mRS>2 和 mRS>3 方面的表现与入院 NIHSS 相当(AUC=0.749,0.697)(AUC=0.767,0.685)。ADSS 在预测不良 ASOV 方面优于 APR-DRG 严重程度评分(AUC=0.698,0.682)。
本研究开发并验证了入院时脑卒中严重程度(ADSS)和结局(ASOV,90 天 mRS>3 的估计值)的测量方法,以提高 NIS 数据在脑卒中研究中的应用价值。