@article{ref1,
title="Development of a nomogram based on diffusion-weighted imaging and clinical information to predict delayed encephalopathy after acute carbon monoxide poisoning",
journal="Journal of integrative neuroscience",
year="2023",
author="Wang, Shenghai and Han, Wenxuan and Sun, Tianze and Wang, Hui and Zhang, Zhenxian and Li, Haining",
volume="22",
number="6",
pages="e165-e165",
abstract="BACKGROUND: Delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) is a severe complication that can arise from acute carbon monoxide poisoning (ACOP). This study aims to identify the independent risk factors associated with DEACMP and to develop a nomogram to predict the probability of developing DEACMP. <br><br>METHODS: The data of patients diagnosed with ACOP between September 2015 and June 2021 were analyzed retrospectively. The patients were divided into the two groups: the DEACMP group and the non-DEACMP group. Univariate analysis and multivariate logistic regression analysis were conducted to identify the independent risk factors for DEACMP. Subsequently, a nomogram was constructed to predict the probability of DEACMP. <br><br>RESULTS: The study included 122 patients, out of whom 30 (24.6%) developed DEACMP. The multivariate logistic regression analysis revealed that acute high-signal lesions on diffusion-weighted imaging (DWI), duration of carbon monoxide (CO) exposure, and Glasgow Coma Scale (GCS) score were independent risk factors for DEACMP (Odds Ratio = 6.230, 1.323, 0.714, p < 0.05). Based on these indicators, a predictive nomogram was constructed. <br><br>CONCLUSIONS: This study constructed a nomogram for predicting DEACMP using high-signal lesions on DWI and clinical indicators. The nomogram may serve as a dependable tool to differentiate high-risk patients and enable the provision of personalized treatment to lower the incidence of DEACMP.<p /> <p>Language: en</p>",
language="en",
issn="0219-6352",
doi="10.31083/j.jin2206165",
url="http://dx.doi.org/10.31083/j.jin2206165"
}