Comparison of mortality prediction performance among the four models of AKI patients.

NIAID Data Ecosystem2026-03-12 收录

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https://figshare.com/articles/dataset/Comparison_of_mortality_prediction_performance_among_the_four_models_of_AKI_patients_/13716319 数据链接链接失效反馈

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Comparison of mortality prediction performance among the four models of AKI patients.

创建时间：

2021-02-04

Supplementary Material for: A MARKED EOSINOPHILIC INFILTRATION IN MUCOSA COULD BE A BETTER PREDICTIVE FACTOR FOR INTRACTABLE NON-ESOPHAGEAL EOSINOPHILIC GASTROINTESTINAL DISORDERS.

嗜酸性粒细胞性胃肠道疾病

临床预测模型

Introduction：Non-esophageal eosinophilic gastrointestinal disorders (non-EoE EGIDs) are rare, but their prevalence has recently increased. Although it has been reported that one-half of patients with

Figshare2023-04-21 更新40

Data Sheet 1_Development and validation of a risk prediction model for painful diabetic peripheral neuropathy in type 2 diabetes mellitus: a multicenter retrospective study.pdf

痛性糖尿病周围神经病变风险预测

临床预测模型

ObjectiveTo construct and validate a clinical model to predict painful diabetic peripheral neuropathy (PDPN) risk in type 2 diabetes mellitus (T2DM) patients for early identification and intervention

NIAID Data Ecosystem00

Utilization of lactate trajectory models for predicting acute kidney injury and mortality in patients with hyperlactatemia: insights across three independent cohorts

临床预测模型

急性肾损伤风险评估

This study aims to investigate the association between lactate trajectories and the risk of acute kidney injury (AKI) and hospital mortality in patients with hyperlactatemia. We conducted a multicente

NIAID Data Ecosystem00

Table 1_Machine learning-based prediction of intensive care unit admission in COVID-19 patients presenting with mild respiratory failure.docx

COVID-19重症监护预测

临床预测模型

IntroductionPrevious studies applying machine learning to predict severe respiratory failure in COVID-19 patients have shown inconsistent results due to variations in study populations and predictor v

NIAID Data Ecosystem00

Supplementary Material for: Associations Between Carvedilol Use and Outcomes in Critically Ill Patients with Acute Kidney Injury: A Multicenter Retrospective Cohort Study

急性肾损伤

重症监护药物

Background: Acute kidney injury (AKI) is one of the leading causes of in-hospital mortality in critically ill patients, with few treatment options other than supportive care. While preclinical studies

NIAID Data Ecosystem00

Comparison of mortality prediction performance among the four models of AKI patients.

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