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. 2022 Apr 26;22:156. doi: 10.1186/s12883-022-02678-2

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — The nomogram prediction model. To use, mark an individual’s DM, draw a vertical line up to the points axis to establish the score associated with DM. Repeat this process for the other six predictors. Add the scores for each predictor together and mark the total score on the total points axis. A vertical line is drawn down to the risk of the HT axis to obtain the probability. DM = diabetes mellitus. AF = atrial fibrillation. TC = total cholesterol. Fib = fibrous protein. CIA = cerebral infarction area. NIHSS = National Institutes of Health Stroke Scale score. OTT = onset-to-treatment