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Logistic regression analyses for the 0–30-day mortality.

Figshare2016-09-10 更新2026-04-29 收录

临床预后预测

医疗风险建模

数据链接：

https://figshare.com/articles/dataset/Logistic_regression_analyses_for_the_0_30-day_mortality_/3821526 数据链接链接失效反馈

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资源简介：

Logistic regression analyses for the 0–30-day mortality.

应用场景：

创建时间：

2016-09-10

COVID-19生物标志物

临床预后预测

HighlightsInnate immune activation during Covid-19 infection is associated with pernicious clinical outcome. BackgroundCoronavirus disease 2019 (Covid-19) is a worldwide threat that has already caused

NIAID Data Ecosystem40

Multivariate Cox proportional hazard models of independent predictors of all-cause mortality.

生存分析

临床预后预测

Values are shown as hazard ratio (95% confidence interval). Abbreviations. CVA, cerebrovascular accident; eGFR, estimated glomerular filtration rate; PAOD, peripheral arterial occlusive disease.* Adju

Figshare2015-12-03 更新30

Univariable logistic regression for death at one-year—factors available during hospitalization.

临床预后预测

医疗风险因素

Univariable logistic regression for death at one-year—factors available during hospitalization.

Figshare2023-08-09 更新20

Association between clustered subgroup membership at baseline and failing to achieve clinically meaningful improvement on outcome at 12 months.

患者亚组分析

临床预后预测

Association between clustered subgroup membership at baseline and failing to achieve clinically meaningful improvement on outcome at 12 months.

Figshare2020-11-05 更新40

Additional file 2 of PPP2R2B downregulation is associated with immune evasion and predicts poor clinical outcomes in triple-negative breast cancer