Qing Liang , Tao Qie, Yinglei Li
Abstract
This research presents a novel visual predictive model aimed at the early identification of patients at elevated risk of poor prognosis following intravenous thrombolysis, assessed six months post-acute ischemic stroke.
Introduction
Stroke is a cerebrovascular disease with a high mortality rate, divided into haemorrhagic and ischaemic strokes [1,2]. Ischaemic stroke is the most common cerebrovascular disease and has a major impact on health, with increased morbidity and mortality.
Materials and methods
Our data came from a retrospective study of Baoding First Central Hospital (National Advanced Stroke Centre) from January 2017 to February 2023. Data were used for research purposes from 07/05/2023.
Results
During the study period from January 2017 to February 2023, 938 patients met the inclusion criteria. The 117 patients who met the exclusion criteria were subsequently excluded from the study, leaving 821 patients eligible for data analysis, including 574 in the training group and 247 in the validation group (Fig 1).
Discussion
This study primarily identified that the five factors—door-to-needle time (DNT), homocysteine (HCY), lactate dehydrogenase (LDH), post-thrombolysis National Institutes of Health Stroke Scale (NIHSS) score, and monocyte-to-high-density lipoprotein ratio (MHR)—are instrumental in constructing nomograms that can predict poor prognosis in patients with acute ischemic stroke six months following intravenous thrombolysis.
Conclusion
A dependable visual nomogram incorporating DNT, HCY, LDH, PNIHSS, and MHR can effectively predict the poor prognosis of patients with acute ischemic stroke (AIS) undergoing intravenous thrombolytic therapy with alteplase over a six-month period.
Citation: Liang Q, Qie T, Li Y (2025) Visual prediction of outcomes in patients undergoing intravenous thrombolysis. PLoS One 20(12): e0336226. https://doi.org/10.1371/journal.pone.0336226
Editor: Aldobrando Broccolini, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, ITALY
Received: November 14, 2024; Accepted: October 14, 2025; Published: December 18, 2025
Copyright: © 2025 Liang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by Medical Science Research Project of Hebei, Grant/Award Number: 20241053. The funders provided support in research design.
Competing interests: The authors have declared that no competing interests exist.
