Cargando…

A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage

OBJECTIVE: The aim of this study was to examine the predictive value of the multiplication of neutrophil and monocyte counts (MNM) in peripheral blood, and develop a new predictive model for the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS: This is a retrospective an...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhuang, Dongzhou, Ren, Zhihui, Sheng, Jiangtao, Zheng, Zenan, Peng, Hui, Ou, Xurong, Zhong, Yuan, Li, Tian, Wang, Shousen, Li, Kangsheng, Chen, Weiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10351672/
https://www.ncbi.nlm.nih.gov/pubmed/37198730
http://dx.doi.org/10.1002/acn3.51789
_version_ 1785074380681773056
author Zhuang, Dongzhou
Ren, Zhihui
Sheng, Jiangtao
Zheng, Zenan
Peng, Hui
Ou, Xurong
Zhong, Yuan
Li, Tian
Wang, Shousen
Li, Kangsheng
Chen, Weiqiang
author_facet Zhuang, Dongzhou
Ren, Zhihui
Sheng, Jiangtao
Zheng, Zenan
Peng, Hui
Ou, Xurong
Zhong, Yuan
Li, Tian
Wang, Shousen
Li, Kangsheng
Chen, Weiqiang
author_sort Zhuang, Dongzhou
collection PubMed
description OBJECTIVE: The aim of this study was to examine the predictive value of the multiplication of neutrophil and monocyte counts (MNM) in peripheral blood, and develop a new predictive model for the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS: This is a retrospective analysis that included 2 separate cohorts of patients undergoing endovascular coiling for aSAH. The training cohort consisted of 687 patients in the First Affiliated Hospital of Shantou University Medical College; the validation cohort consisted of 299 patients from Sun Yat‐sen University's Affiliated Jieyang People's Hospital. The training cohort was used to develop 2 models to predict unfavorable prognosis (modified Rankin scale of 3–6 at 3 months): one was based on traditional factors (e.g., age, modified Fisher grade, NIHSS score, and blood glucose), and another model that included traditional factors as well as MNM on admission. RESULTS: In the training cohort, MNM upon admission was independently associated with unfavorable prognosis (odds ratio after adjustment, 1.06; 95% confidence interval [CI], 1.03–1.10). In the validation cohort, the basic model that included only traditional factors had 70.99% sensitivity, 84.36% specificity, and 0.859 (95% CI, 0.817–0.901) area under the receiver operating characteristic curve (AUC). Adding MNM increased model sensitivity (from 70.99% to 76.48%), specificity (from 84.36% to 88.63%), and overall performance (AUC 0.859 [95% CI, 0.817–0.901] to 0.879 [95% CI, 0.841–0.917]). INTERPRETATION: MNM upon admission is associated with unfavorable prognosis in patients undergoing endovascular embolization for aSAH. The nomogram including MNM is a user‐friendly tool to help clinicians quickly predict the outcome of patients with aSAH.
format Online
Article
Text
id pubmed-10351672
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-103516722023-07-18 A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage Zhuang, Dongzhou Ren, Zhihui Sheng, Jiangtao Zheng, Zenan Peng, Hui Ou, Xurong Zhong, Yuan Li, Tian Wang, Shousen Li, Kangsheng Chen, Weiqiang Ann Clin Transl Neurol Research Articles OBJECTIVE: The aim of this study was to examine the predictive value of the multiplication of neutrophil and monocyte counts (MNM) in peripheral blood, and develop a new predictive model for the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS: This is a retrospective analysis that included 2 separate cohorts of patients undergoing endovascular coiling for aSAH. The training cohort consisted of 687 patients in the First Affiliated Hospital of Shantou University Medical College; the validation cohort consisted of 299 patients from Sun Yat‐sen University's Affiliated Jieyang People's Hospital. The training cohort was used to develop 2 models to predict unfavorable prognosis (modified Rankin scale of 3–6 at 3 months): one was based on traditional factors (e.g., age, modified Fisher grade, NIHSS score, and blood glucose), and another model that included traditional factors as well as MNM on admission. RESULTS: In the training cohort, MNM upon admission was independently associated with unfavorable prognosis (odds ratio after adjustment, 1.06; 95% confidence interval [CI], 1.03–1.10). In the validation cohort, the basic model that included only traditional factors had 70.99% sensitivity, 84.36% specificity, and 0.859 (95% CI, 0.817–0.901) area under the receiver operating characteristic curve (AUC). Adding MNM increased model sensitivity (from 70.99% to 76.48%), specificity (from 84.36% to 88.63%), and overall performance (AUC 0.859 [95% CI, 0.817–0.901] to 0.879 [95% CI, 0.841–0.917]). INTERPRETATION: MNM upon admission is associated with unfavorable prognosis in patients undergoing endovascular embolization for aSAH. The nomogram including MNM is a user‐friendly tool to help clinicians quickly predict the outcome of patients with aSAH. John Wiley and Sons Inc. 2023-05-17 /pmc/articles/PMC10351672/ /pubmed/37198730 http://dx.doi.org/10.1002/acn3.51789 Text en © 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Zhuang, Dongzhou
Ren, Zhihui
Sheng, Jiangtao
Zheng, Zenan
Peng, Hui
Ou, Xurong
Zhong, Yuan
Li, Tian
Wang, Shousen
Li, Kangsheng
Chen, Weiqiang
A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
title A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
title_full A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
title_fullStr A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
title_full_unstemmed A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
title_short A dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
title_sort dynamic nomogram for predicting unfavorable prognosis after aneurysmal subarachnoid hemorrhage
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10351672/
https://www.ncbi.nlm.nih.gov/pubmed/37198730
http://dx.doi.org/10.1002/acn3.51789
work_keys_str_mv AT zhuangdongzhou adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT renzhihui adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT shengjiangtao adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT zhengzenan adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT penghui adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT ouxurong adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT zhongyuan adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT litian adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT wangshousen adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT likangsheng adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT chenweiqiang adynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT zhuangdongzhou dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT renzhihui dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT shengjiangtao dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT zhengzenan dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT penghui dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT ouxurong dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT zhongyuan dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT litian dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT wangshousen dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT likangsheng dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage
AT chenweiqiang dynamicnomogramforpredictingunfavorableprognosisafteraneurysmalsubarachnoidhemorrhage