女性特异性因素和心理社会因素对 50 岁以下女性卒中风险的预测价值。
Added Predictive Value of Female-Specific Factors and Psychosocial Factors for the Risk of Stroke in Women Under 50.
机构信息
From the Department of Neurology (H.J.A.v.O., M.D.F., M.J.H.W.), National eHealth Living Lab (H.J.A.v.O.), Departments of Public Health & Primary Care/Health Campus The Hague (H.J.v.A.O., T.N.B., J.M.K., H.M.M.V., R.C.V.), Clinical Epidemiology (R.H.H.G.), and Biomedical Data Sciences (H.P., R.H.H.G.), Leiden University Medical Center; Department of Neurology (J.P.K.), University Medical Center Utrecht; and Department of Neurology (M.J.H.W.), University Medical Center Groningen, the Netherlands.
出版信息
Neurology. 2023 Aug 22;101(8):e805-e814. doi: 10.1212/WNL.0000000000207513. Epub 2023 Jul 21.
BACKGROUND AND OBJECTIVES
Female-specific factors and psychosocial factors may be important in the prediction of stroke but are not included in prediction models that are currently used. We investigated whether addition of these factors would improve the performance of prediction models for the risk of stroke in women younger than 50 years.
METHODS
We used data from the Stichting Informatievoorziening voor Zorg en Onderzoek, population-based, primary care database of women aged 20-49 years without a history of cardiovascular disease. Analyses were stratified by 10-year age intervals at cohort entry. Cox proportional hazards models to predict stroke risk were developed, including traditional cardiovascular factors, and compared with models that additionally included female-specific and psychosocial factors. We compared the risk models using the -statistic and slope of the calibration curve at a follow-up of 10 years. We developed an age-specific stroke risk prediction tool that may help communicating the risk of stroke in clinical practice.
RESULTS
We included 409,026 women with a total of 3,990,185 person-years of follow-up. Stroke occurred in 2,751 women (incidence rate 6.9 [95% CI 6.6-7.2] per 10,000 person-years). Models with only traditional cardiovascular factors performed poorly to moderately in all age groups: 20-29 years: -statistic: 0.617 (95% CI 0.592-0.639); 30-39 years: -statistic: 0.615 (95% CI 0.596-0.634); and 40-49 years: -statistic: 0.585 (95% CI 0.573-0.597). After adding the female-specific and psychosocial risk factors to the reference models, the model discrimination increased moderately, especially in the age groups 30-39 (Δ-statistic: 0.019) and 40-49 years (Δ-statistic: 0.029) compared with the reference models, respectively.
DISCUSSION
The addition of female-specific factors and psychosocial risk factors improves the discriminatory performance of prediction models for stroke in women younger than 50 years.
背景与目的
女性特有的因素和心理社会因素可能对预测中风很重要，但目前使用的预测模型并未包含这些因素。我们研究了这些因素的加入是否会提高预测年轻女性（<50 岁）中风风险的模型性能。
方法
我们使用了 Stichting Informatievoorziening voor Zorg en Onderzoek 的数据，该数据库基于人群，涵盖了无心血管疾病史的 20-49 岁女性初级保健数据库。分析按队列入组时的 10 年年龄间隔进行分层。我们建立了预测中风风险的 Cox 比例风险模型，包括传统心血管因素，并与额外包含女性特定因素和心理社会因素的模型进行了比较。我们使用 -统计量和校准曲线的斜率比较了风险模型，随访时间为 10 年。我们开发了一种年龄特异性的中风风险预测工具，有助于在临床实践中沟通中风风险。
结果
我们纳入了 409026 名女性，总随访时间为 3990185 人年。共有 2751 名女性发生中风（发病率为 6.9 [95%CI 6.6-7.2] / 10000 人年）。仅包含传统心血管因素的模型在所有年龄组中的表现均较差至中等：20-29 岁：-统计量：0.617（95%CI 0.592-0.639）；30-39 岁：-统计量：0.615（95%CI 0.596-0.634）；40-49 岁：-统计量：0.585（95%CI 0.573-0.597）。将女性特定和心理社会风险因素添加到参考模型后，模型的区分度略有提高，尤其是在 30-39 岁（Δ-统计量：0.019）和 40-49 岁（Δ-统计量：0.029）年龄组与参考模型相比。
讨论
女性特有的因素和心理社会风险因素的加入提高了预测年轻女性（<50 岁）中风风险的模型性能。
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