Validación de test diagnósticos (segunda parte). Test cuantitativos <span class="so-article-trans-title" dir="auto"> Translated title: Validation of diagnostic tests (part II). Quantitative tests </span>

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Abstract

Resumen En esta segunda parte sobre la validación de los test diagnósticos vamos a estudiar cómo analizar la bondad de los test diagnósticos cuantitativos. El análisis de estos test se realiza a partir de las curvas ROC (Receiver Operating characteristic Curve). Constituye un método para determinar la exactitud diagnóstica de test que utilizan escalas continuas. A partir de estas curvas analizaremos dos conceptos: la AUC (Area Under Curve) y el índice de Youden, que nos ayudará a una mejor interpretación de la validez de una prueba diagnóstica y su punto de corte.

Translated abstract

Abstract In this second part on the validation of diagnostic tests we are going to study how to analyze the goodness of quantitative diagnostic tests. The analysis of these tests is performed from the ROC curves (Receiver Operating characteristic Curve). It constitutes a method to determine the diagnostic accuracy of tests that use continuous scales. From these curves we will analyze two concepts: the AUC (Area Under Curve) and the Youden index, which will help us to better interpret the validity of a diagnostic test and its cut-off point.

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Is Open Access

D-Dimer Is a Diagnostic Biomarker of Abdominal Aortic Aneurysm in Patients With Peripheral Artery Disease

Huoying Cai, Baihong Pan, Jie Xu … (2022)

Background Etiology and risk factors of peripheral artery disease (PAD) include age, smoking, and hypertension, etc. , which are shared by an abdominal aortic aneurysm (AAA). Concomitance with AAA in patients with PAD is not rare but is easily overlooked in the clinical situation, though management strategies are altered totally. This study aims to investigate diagnostic biomarkers for the prediction of AAA in patients with PAD. Methods A total of 684 patients diagnosed with AAA and/or PAD were enrolled and analyzed retrospectively. Each patient with PAD and AAA was gender and age-matched. Demographic data, medical history, and serum laboratory test profiles were obtained. Statistical analysis was performed to determine diagnostic biomarkers of AAA in patients with PAD. Results Firstly, 320 patients with PAD-only and 320 patients with AAA-only were compared. Levels of bilirubin and D-Dimer were decreased, while the incidence of diabetes mellitus, levels of fibrinogen, and platelet count were increased significantly in patients with PAD-only compared with those in patients with AAA-only (P 0.675 mg/L, while only 3.55% patients were diagnosed AAA when D-dimer ≤ 0.675 mg/L. Conclusions PAD and AAA exert different clinical and serum profiles; D-dimer (>0.675 mg/L) is a reliable biomarker for the prediction of AAA in patients with PAD.