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Dataset Information

Gut microbiome-based noninvasive diagnostic model to predict acute coronary syndromes.


ABSTRACT:

Background

Previous studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.

Methods

We recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and deci

SUBMITTER: Wang J 

PROVIDER: S-EPMC10829574 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature