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作者信息

Amato Alexandre Campos Moraes, Parga José Rodrigues, Stolf Noedir Antônio Groppo

机构信息

Instituto de Medicina Avançada - AMATO, Cirurgia Vascular e Endovascular, São Paulo, SP, Brasil.

Universidade de Santo Amaro - UNISA, Disciplina de Cirurgia Vascular, São Paulo, SP, Brasil.

出版信息

J Vasc Bras. 2018 Jan-Mar;17(1):19-25. doi: 10.1590/1677-5449.006317.

Abstract

BACKGROUND

There are clinically important morphological differences in the Adamkiewicz artery (AKA) between populations that do and do not have aortic disease and they have an influence on the neuroischemic complications involving the spinal cord during surgical operations. It is not yet known whether clinical parameters correlate with the predictability of identification of the artery using angiotomography.

OBJECTIVE

To develop a mathematical model that by correlating clinical parameters with atherosclerosis enables prediction of the probability of identification of the AKA in patients examined with angiotomography.

METHOD

This is a cross-sectional, observational study using a patient database and image bank. A multivariate statistical analysis was conducted and a logit mathematical model was constructed to predict AKA identification. Significant variables were used to build a formula for calculation of the probability of identification. This model was calibrated and its power of discrimination was assessed using receiver operating characteristic (ROC) curves. Selection of explanatory variables was based on largest area under the ROC curve (p = 0.041) and combined significance of variables.

RESULTS

A total of 110 cases were analyzed (54.5% were male, mean age was 60.97 years, and ethnicity coefficients were white -2.471, brown -1.297, and black -0.971) and the AKA was identified in 60.9%. Body mass index: 27.06 ± 0.98 (coef. -0.101); smokers: 55.5% (coef. -1.614/-1.439); diabetes: 13.6%; hypertension: 65.5% (coef. -1.469); dyslipidemia: 58.2%; aortic aneurysm: 38.2%; aortic dissection: 12.7%; and mural thrombus: 24.5%. The constant was 6.262. The formula for calculating the probability of detection is as follows: . The prediction model was constructed and made available at: https://vascular.pro/aka-model .

CONCLUSIONS

Using the covariates ethnicity, body mass index, smoking, arterial hypertension, and dyslipidemia, it proved possible to create a mathematical model for predicting identification of the AKA with a combined significance of nine coefficients (p = 0.042).

摘要

背景

患有和未患有主动脉疾病的人群,其Adamkiewicz动脉(AKA)在临床上存在重要的形态学差异,这些差异会影响手术过程中涉及脊髓的神经缺血性并发症。目前尚不清楚临床参数是否与血管造影识别该动脉的可预测性相关。

目的

建立一个数学模型,通过将临床参数与动脉粥样硬化相关联,预测血管造影检查患者中AKA被识别的概率。

方法

这是一项使用患者数据库和图像库的横断面观察性研究。进行了多变量统计分析,并构建了一个逻辑数学模型来预测AKA的识别。使用显著变量构建计算识别概率的公式。该模型经过校准,并使用受试者工作特征(ROC)曲线评估其判别能力。解释变量的选择基于ROC曲线下的最大面积(p = 0.041)和变量的综合显著性。

结果

共分析了110例病例(54.5%为男性,平均年龄60.97岁,种族系数为白人 -2.471,棕色人种 -1.297,黑人 -0.971),60.9%的病例识别出了AKA。体重指数:27.06 ± 0.98(系数 -0.101);吸烟者:55.5%(系数 -1.614/-1.439);糖尿病:13.6%;高血压:65.5%(系数 -1.469);血脂异常:58.2%;主动脉瘤:38.2%;主动脉夹层:12.7%;壁血栓:24.5%。常数为6.262。计算检测概率的公式如下: 。预测模型已构建并可在以下网址获取:https://vascular.pro/aka-model

结论

利用种族、体重指数、吸烟、动脉高血压和血脂异常等协变量,证明可以创建一个预测AKA识别的数学模型,九个系数的综合显著性为(p = 0.042)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a04e/5990262/f8f03bd37cb8/jvb-17-01-019-g01.jpg

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