A predictive model for 28-day mortality after discharge in patients with sepsis associated with cerebrovascular disease

The proposed prediction model allows clinicians to promptly assess the mortality risk in patients with cerebrovascular disease complicated by sepsis within 28 days after discharge, facilitating early intervention strategies. Consequently, clinicians can implement additional advantageous medical interventions for individuals with cerebrovascular disease and sepsis.

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Publication Details

Journal
Technology and Health Care
Published
2024-08-20
DOI
https://doi.org/10.3233/thc-241150
Primary Topic
Acute Ischemic Stroke Management
Type
article
Field-Weighted Citation Impact
0.00
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article

A predictive model for 28-day mortality after discharge in patients with sepsis associated with cerebrovascular disease

Defeng Hua, Yan Chen
Technology and Health Care
Acute Ischemic Stroke Management
article

A predictive model for 28-day mortality after discharge in patients with sepsis associated with cerebrovascular disease

Defeng Hua, Yan Chen
article en

Abstract

The proposed prediction model allows clinicians to promptly assess the mortality risk in patients with cerebrovascular disease complicated by sepsis within 28 days after discharge, facilitating early intervention strategies. Consequently, clinicians can implement additional advantageous medical interventions for individuals with cerebrovascular disease and sepsis.

Technology and Health CareVol. 33(1)
Weifang People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 79%
Acute Ischemic Stroke Management
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A predictive model for 28-day mortality after discharge in patients with sepsis associated with cerebrovascular disease — Defeng Hua, Yan Chen · Technology and Health Care (2024) | TGRS Research Map | TGRS