Prognostic Nomogram for Predicting Lower Extremity Deep Venous Thrombosis in Neurointensive Care Unit Patients: A Prospective Observational Study.

Abstract

BACKGROUND:

Deep venous thrombosis (DVT) of the lower extremities is one of the common complications for neurointensive care unit patients, which leads to increased morbidity and mortality. The purpose of our study was to explore risk factors and develop a prognostic nomogram for lower extremity DVT in neurointensive care unit patients.

METHODS:

We prospectively collected and analyzed the clinical data of 420 neurointensive care unit patients who received treatment in our institution between January 2018 and September 2019. Stepwise logistic regression was used to select predictors. R software was used to develop the prognostic nomogram. The performance of the nomogram was validated using a validation cohort of patients with data collected between October 2019 and March 2020.

RESULTS:

Among 420 patients, 153 (36.4%) had lower extremity DVT and five (1.2%) had both DVT and pulmonary embolism (PE) in our study. Logistic regression analysis indicated that age [odds ratio (OR): 1.050; 95% confidence interval (CI): 1.029-1.071; P < 0.001], Glasgow Coma Scale (GCS) score (OR: 0.889; 95% CI: 0.825-0.959; P = 0.002), D-dimer level (OR: 1.040; 95% CI: 1.008-1.074; P = 0.014), muscle strength (OR: 2.424; 95% CI: 1.346-4.366; P = 0.003), and infection (OR: 1.778; 95% CI: 1.034-3.055; P = 0.037) were independent predictors for lower extremity DVT. These predictors were selected to be included in the nomogram model. The area under the curve values in the primary cohort and validation cohort were 0.817 (95% CI: 0.776-0.858) and 0.778 (95% CI: 0.688-0.868), respectively, and respective Brier scores were 0.167 and 0.183.

CONCLUSION:

Age, GCS score, D-dimer level, muscle strength, and infection are independent predictors for lower extremity DVT. The nomogram is a reliable and convenient model to predict the development of lower extremity DVT in neurointensive care unit patients.

• Authors: Rongqing Li, Jinxia Jiang, Yu Song, Jianan Zhang, Yawen Wu, Lingzhi Wu, Xiaoping Zhu, Li Zeng
• Journal: Frontiers in neurology (Front Neurol) Vol. 12 Pg. 761029 ( 2021) ISSN: 1664-2295 [Print] Switzerland
• PMID: 35153974 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Li, Jiang, Song, Zhang, Wu, Wu, Zhu and Zeng.