Clinical Risk Score for Prediction of Urgency in Carotid Cavernous Sinus Fistulas.

IF 1.8 Q3 OPHTHALMOLOGY
Pawasoot Supasai, Kanwasee Kanjana, Yosanan Yospaiboon
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引用次数: 0

Abstract

Purpose: To develop a clinical risk score for the prediction of urgency in patients with carotid cavernous sinus fistulas (CCFs) and test for the discriminative ability of the diagnostic prediction.

Methods: The medical charts of 60 patients with CCFs were retrospectively reviewed. The clinical characteristics of direct and dural CCFs were analyzed by logistic regression. The clinical risk score was developed from the coefficient in the multivariable regression model and used to predict direct CCFs which were more urgent than the dural type. The score prediction was reported as an area under the receiver operating characteristic (AuROC) curve and 95% confidence interval (95% CI).

Results: In a univariable analysis, the clinical characteristics which increased the risk of direct CCFs were age, gender, trauma, underlying diseases, visual acuity (VA) at presentation, bruit, chemosis, and dilated retinal vessels. However, in multivariable analysis, the significant predictors were limited to age, trauma, bruit, underlying diseases and logMAR VA. Regression coefficient of each predictor was converted to a risk score and summation of scores from these predictors for each patient was calculated. The total risk score predicted the urgent direct CCFs correctly with AuROC of 97.77% (95% CI; 93.57, 100).

Conclusion: The clinical risk score for the prediction of urgent direct CCFs has been developed and used in the patients with CCFs in our setting. The discriminative ability of the score prediction is high. This simple clinical risk score may help clinicians suspect direct CCFs and urgently refer the patients to have prompt angiography and treatment.

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Abstract Image

预测颈动脉海绵窦瘘急症的临床风险评分。
目的:建立预测颈动脉海绵窦瘘(CCFs)患者急症的临床风险评分,并检验其诊断预测的判别能力。方法:回顾性分析60例CCFs患者的病历资料。采用logistic回归分析直接和硬脑膜CCFs的临床特点。临床风险评分由多变量回归模型中的系数得出,用于预测直接CCFs,后者比硬脑膜型更为紧急。评分预测报告为受试者工作特征(AuROC)曲线下的面积和95%置信区间(95% CI)。结果:在一项单变量分析中,增加直接CCFs风险的临床特征是年龄、性别、创伤、基础疾病、就诊时视力(VA)、瘀伤、化脓和视网膜血管扩张。然而,在多变量分析中,显著的预测因子仅限于年龄、创伤、bruit、基础疾病和logMAR VA。每个预测因子的回归系数转换为风险评分,并计算每个患者这些预测因子的评分总和。总风险评分正确预测紧急直接CCFs, AuROC为97.77% (95% CI;93.57, 100)。结论:用于预测急迫性直接CCFs的临床风险评分已被开发并应用于本院CCFs患者。分数预测的判别能力较高。这个简单的临床风险评分可以帮助临床医生怀疑直接CCFs,并紧急推荐患者及时进行血管造影和治疗。
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来源期刊
Clinical ophthalmology
Clinical ophthalmology OPHTHALMOLOGY-
CiteScore
3.50
自引率
9.10%
发文量
499
审稿时长
16 weeks
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