Baseline characteristics of patients in 3 month mortality.

NIAID Data Ecosystem2026-03-13 收录

患者死亡率预测

医疗预后分析

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资源简介：

Baseline characteristics of patients in 3 month mortality.

创建时间：

2022-03-14

Cox proportional hazard model for prognosis of HD patients at a four-year follow-up.

医疗预后分析

药物效果评估

aValues are expressed as mean ± SD or percent. bACE, angiotensin converting enzyme; ARB, angiotensin receptor blocker. cCI, confidence interval. dHR, hazard ratio. *p<0.10 in univariate Cox regression

NIAID Data Ecosystem60

Multivariate analysis of prognostic factors associated with hospital mortality in patients with HFNC failure.

医疗预后分析

高流量疗效

Multivariate analysis of prognostic factors associated with hospital mortality in patients with HFNC failure.

Figshare2022-06-29 更新10

Supplementary Material for: Pre-End-Stage Renal Disease Hemoglobin Variability Predicts Post-End-Stage Renal Disease Mortality in Patients Transitioning to Dialysis

慢性肾脏病

患者死亡率预测

Background: Hemoglobin variability (Hb-var) has been associated with increased mortality both in non-dialysis dependent chronic kidney disease (NDD-CKD) and end-stage renal disease (ESRD) patients. Ho

Figshare2017-11-07 更新10

Table_5_Machine Learning for Prediction of Outcomes in Cardiogenic Shock.DOCX

心源性休克预后

患者死亡率预测

ObjectiveThe management of cardiogenic shock (CS) in the elderly remains a major clinical challenge. Existing clinical prediction models have not performed well in assessing the prognosis of elderly p

NIAID Data Ecosystem20

Cox proportional hazards modeling.

医疗预后分析

脓毒性休克风险因素

BackgroundPrevious studies have shown that both age and hemoglobin are closely associated with the prognosis of septic shock. A recent study found that hemoglobin may change with age. Hemoglobin-to-Ag

Figshare2024-12-06 更新10

Baseline characteristics of patients in 3 month mortality.

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