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Identifying Infected Emergency Department Patients Admitted to the Hospital Ward at Risk of Clinical Deterioration and Intensive Care Unit Transfer
Open accessAbstract
Objectives: An important challenge faced by emergency physicians (EPs) is determining which patients should be admitted to an intensive care unit (ICU) and which can be safely admitted to a regular ward. Understanding risk factors leading to undertriage would be useful, but these factors are not well characterized. Methods: The authors performed a secondary analysis of two prospective, observational studies of patients admitted to the hospital with clinically suspected infection from an urban university emergency department (ED). Inclusion criteria were as follows: adult ED patient (age 18 years or older), ward admission, and suspected infection. The primary outcome was transfer to an ICU within 48 hours of admission. Using multiple logistic regression, independent predictors of early ICU transfer were identified, and the area under the curve for the model was calculated. Results: Of 5,365 subjects, 93 (1.7%) were transferred to an ICU within 48 hours. Independent predictors of ICU transfer included respiratory compromise (odds ratio [OR] = 2.5, 95% confidence interval [CI] = 1.4 to 4.3), congestive heart failure (CHF; OR = 2.2, 95% CI = 1.4 to 3.6), peripheral vascular disease (OR = 2.0, 95% CI = 1.1 to 3.7), systolic blood pressure (sBP) < 100 mm Hg (OR = 1.9, 95% CI = 1.2 to 2.9), heart rate > 90 beats/min (OR = 1.8, 95% CI = 1.1 to 2.8), and creatinine > 2.0 (OR = 1.8, 95% CI = 1.1 to 2.8). Cellulitis was associated with a lower likelihood of ICU transfer (OR = 0.33, 95% CI = 0.15 to 0.72). The area under the curve for the model was 0.73, showing moderate discriminatory ability. Conclusions: In this preliminary study, independent predictors of ICU transfer within 48 hours of admission were identified. While somewhat intuitive, physicians should consider these factors when determining patient disposition. ACADEMIC EMERGENCY MEDICINE 2010; 17:1080–1085 © 2010 by the Society for Academic Emergency Medicine
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Sepsis clinical progression exhibits significant heterogeneity, with patients potentially experiencing rapid recovery, gradual improvement, or continued deterioration.
“The clinical progression of sepsis exhibits significant heterogeneity, with patients potentially experiencing rapid recovery, gradual improvement, or continued deterioration4.”
From Machine learning predicts sepsis deterioration trajectories. (2026) · cites this paper as [4]
The Discussion (page unavailable) reports that some ED patients with suspected infection deteriorated and required early ICU transfer, while cellulitis was associated with a better outcome. It does not describe rapid recovery or gradual improvement as distinct clinical courses, and its study population had suspected infection rather than confirmed sepsis. (LLM, conf=0.82)
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Machine learning predicts sepsis deterioration trajectories.
Zhang, R., Long, F., Zhao, Z., Wu, J., Tan, R., Xu, W., Li, L., Long, Y., & Qu, H. (2026) · NPJ Digital Medicine · doi:10.1038/s41746-026-02565-x · Cited by 6
Metadata
- Authors
- Kennedy, M., Joyce, N., Howell, M. D., Lawrence Mottley, J., & Shapiro, N. I.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Kennedy, Maura
- Venue
- Academic Emergency Medicine
- Publisher
- Wiley
- Published
- 2010-10
- Volume
- 17
- Issue
- 10
- Pages
- 1080-1085
- ISSN
- 1069-6563 (ISSN-L)
- 1553-2712
- PMC
- PMC3058807
- OpenAlex
- W1598817823
- Cited by
- 63
- References
- 0
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 5 · 2020: 5 · 2019: 4 · 2018: 4 · 2017: 8 · 2016: 6 · 2015: 4 · 2014: 6 · 2013: 4 · 2012: 5
- FWCI
- 2.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Academic Emergency Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL091757, HL091757)
- National Institute of General Medical Sciences (P50GM076659, GM076659)
- Topics
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Health Sciences › Medicine › Emergency Medicine › Trauma and Emergency Care Studies
- Keywords
- ICU transfer, clinical deterioration, emergency department admission, suspected infection, risk factors, respiratory compromise, congestive heart failure, peripheral vascular disease, hypotension, tachycardia, hyperbilirubinemia, cellulitis, patient disposition
- MeSH terms
- Adult, Age Factors, Aged, Aged, 80 and over, Decision Making, Emergency Medicine, Emergency Service, Hospital, Female, Hospital Units, Hospitals, University, Humans, Intensive Care Units, Length of Stay, Male, Middle Aged, Patient Admission, Patient Transfer, Prospective Studies, Risk Factors, Sex Factors, Time Factors, Cohort Studies, Confidence Intervals, Logistic Models, Odds Ratio, Survival Analysis, Bacteremia, Critical Illness, Hospital Mortality, Patient Selection, Kaplan-Meier Estimate
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