A dynamic online nomogram for predicting death in hospital after aneurysmal subarachnoid hemorrhage

Author:

Li Tian,Zhuang Dongzhou,Xiao Yong,Chen Xiaoxuan,Zhong Yuan,Ou Xurong,Peng Hui,Wang Shousen,Chen Weiqiang,Sheng Jiangtao

Abstract

Abstract Background This study aimed to validate the efficacy the multiplication of neutrophils and monocytes (MNM) and a novel dynamic nomogram for predicting in-hospital death in patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods Retrospective study was done on 986 patients with endovascular coiling for aSAH. Independent risk factors associated with in-hospital death were identified using both univariate and multivariate logistic regression analysis. In the development cohort, a dynamic nomogram of in-hospital deaths was introduced and made available online as a straightforward calculator. To predict the in-hospital death from the external validation cohort by nomogram, calibration analysis, decision curve analysis, and receiver operating characteristic analysis were carried out. Results 72/687 patients (10.5%) in the development cohort and 31/299 patients (10.4%) in the validation cohort died. MNM was linked to in-hospital death in univariate and multivariate regression studies. In the development cohort, a unique nomogram demonstrated a high prediction ability for in-hospital death. According to the calibration curves, the nomogram has a reliable degree of consistency and calibration. With threshold probabilities between 10% and 90%, the nomogram’s net benefit was superior to the basic model. The MNM and nomogram also exhibited good predictive values for in-hospital death in the validation cohort. Conclusions MNM is a novel predictor of in-hospital mortality in patients with aSAH. For aSAH patients, a dynamic nomogram is a useful technique for predicting in-hospital death.

Funder

Fujian Provincial Science and Technology Innovation Joint Fund

Natural Science Foundation of Guangdong Province

China Postdoctoral Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

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