在加拿大三个省份验证被动监测脑卒中严重程度评分。

IF 2.9 4区 医学 Q2 CLINICAL NEUROLOGY
Canadian Journal of Neurological Sciences Pub Date : 2025-01-01 Epub Date: 2024-03-06 DOI:10.1017/cjn.2024.36
Amy Y X Yu, Peter C Austin, Alison L Park, Jiming Fang, Michael D Hill, Noreen Kamal, Thalia S Field, Raed A Joundi, Sandra Peterson, Yinshan Zhao, Moira K Kapral
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引用次数: 0

摘要

背景:脑卒中预后研究需要对脑卒中严重程度进行风险调整,但这一指标往往无法获得。被动监测卒中严重程度(PaSSV)评分是加拿大安大略省开发的一种基于行政数据的卒中严重程度测量方法。我们评估了 PaSSV 在加拿大不列颠哥伦比亚省(BC)、新斯科舍省(NS)和安大略省的地理和时间外部有效性:我们使用各省的关联行政数据来识别 2014-2019 年间患有缺血性卒中或脑内出血的成年患者,并计算他们的 PaSSV 得分。我们使用 Cox 比例危险模型评估了 PaSSV 评分与 30 天内死亡危险和 365 天内入住长期护理机构的特定病因危险之间的关联。我们使用 Uno's c 统计量评估了模型的判别值,比较了有 PaSSV 和无 PaSSV 的模型:我们纳入了 86,142 名患者(不列颠哥伦比亚省 n = 18,387 人,安大略省 n = 65,082 人,新南威尔士州 n = 2,673 人)。各省的 PaSSV 平均值和中位数相似。PaSSV 分数越高,代表卒中严重程度越低,死亡风险越低(不列颠哥伦比亚省的风险比和 95% 置信区间为 0.70 [0.68,0.71],安大略省为 0.69 [0.68,0.69],新南威尔士州为 0.72 [0.68,0.75]),入住长期护理机构的风险越低(不列颠哥伦比亚省为 0.77 [0.76,0.79],安大略省为 0.84 [0.83,0.85],新南威尔士州为 0.86 [0.79,0.93])。与不包含该变量的模型相比,将 PaSSV 纳入多变量模型可提高 c 统计量:PaSSV具有地理和时间有效性,因此可用于卒中结局研究中的风险调整,包括多辖区分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validation of the Passive Surveillance Stroke Severity Score in Three Canadian Provinces.

Background: Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada.

Methods: We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models' discriminative values using Uno's c-statistic, comparing models with versus without PaSSV.

Results: We included 86,142 patients (n = 18,387 in BC, n = 65,082 in Ontario, n = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable.

Conclusion: PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

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来源期刊
CiteScore
4.30
自引率
3.30%
发文量
330
审稿时长
4-8 weeks
期刊介绍: Canadian Neurological Sciences Federation The Canadian Journal of Neurological Sciences is the official publication of the four member societies of the Canadian Neurological Sciences Federation -- Canadian Neurological Society (CNS), Canadian Association of Child Neurology (CACN), Canadian Neurosurgical Society (CNSS), Canadian Society of Clinical Neurophysiologists (CSCN). The Journal is a widely circulated internationally recognized medical journal that publishes peer-reviewed articles. The Journal is published in January, March, May, July, September, and November in an online only format. The first Canadian Journal of Neurological Sciences (the Journal) was published in 1974 in Winnipeg. In 1981, the Journal became the official publication of the member societies of the CNSF.
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