The Scoring Model to Predict ICU Stay and Mortality After Emergency Admissions in Atrial Fibrillation: A Retrospective Study of 30 366 Patients

We derived and validated novel simplified scoring models with good discriminative performance to predict the likelihood of ICU stay, 3-day, 7-day, and 30-day death in AF patients after ED admission.

Authors

Institutions

Publication Details

Journal
Clinical Cardiology
Published
2025-02-01
DOI
https://doi.org/10.1002/clc.70101
Citations
1
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
2.25

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Scoring Model to Predict ICU Stay and Mortality After Emergency Admissions in Atrial Fibrillation: A Retrospective Study of 30 366 Patients

Jian Huang, Huishan Wang, Jikai Zhao, Xiaozhu Liu et al.
1 citations
Clinical Cardiology
Emergency and Acute Care Studies
2.25
article

The Scoring Model to Predict ICU Stay and Mortality After Emergency Admissions in Atrial Fibrillation: A Retrospective Study of 30 366 Patients

Jian Huang, Huishan Wang, Jikai Zhao, Xiaozhu Liu, Lirong Kuang, Tao Hong, Qianqian Wang, Mengyan Sun, Chao Luo, Jiewen Deng
article en
1 citations

Abstract

We derived and validated novel simplified scoring models with good discriminative performance to predict the likelihood of ICU stay, 3-day, 7-day, and 30-day death in AF patients after ED admission.

Clinical CardiologyVol. 48(2)
Capital Medical University (CN), Dalian Medical University (CN), Sir Run Run Shaw Hospital (CN), First People’s Hospital of Jingmen (CN), Wuchang University of Technology (CN), General Hospital of Shenyang Military Region (CN), Manchester College (GB), Beijing Shijitan Hospital (CN), Wuhan University of Science and Technology (CN), Zhejiang University (CN), Chongqing Medical University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Liaoning Province
Reduced inequalities
Openalex Percentile: Top 17%
Emergency and Acute Care Studies
2.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The Scoring Model to Predict ICU Stay and Mortality After Emergency Admissions in Atrial Fibrillation: A Retrospective Study of 30 366 Patients — Jian Huang, Huishan Wang, et al. · Clinical Cardiology (2025) | TGRS Research Map | TGRS