TY  - JOUR
PY  - 2023//
TI  - Development of a nomogram based on diffusion-weighted imaging and clinical information to predict delayed encephalopathy after acute carbon monoxide poisoning
JO  - Journal of integrative neuroscience
A1  - Wang, Shenghai
A1  - Han, Wenxuan
A1  - Sun, Tianze
A1  - Wang, Hui
A1  - Zhang, Zhenxian
A1  - Li, Haining
SP  - e165
EP  - e165
VL  - 22
IS  - 6
N2  - 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>
LA  - en
SN  - 0219-6352
UR  - http://dx.doi.org/10.31083/j.jin2206165
ID  - ref1
ER  -