ArticleCurrent medical science2019
A Diagnostic Tool for Identification of Etiologies of Fever of Unknown Origin in Adult Patients.
Article in Current medical science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04661085 (A Descriptive Study of Patients Suspected With Infection in the Emergency Department, With a Special Focus on Infection With Unknown Origin.), which is not on this map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
A Descriptive Study of Patients Suspected With Infection in the Emergency Department, With a Special Focus on Infection With Unknown Origin.
Who cites it
8 citing papers in PubMed.
- Development of a Machine Learning-Based Prediction Model to Differentiate Infectious and Non-Infectious Diseases in Patients with Undiagnosed Fever: A Single Hospital-Based Retrospective Study.Journal of clinical medicine · 2026Article
- Epidemiology and genotypic profiling of hepatitis B virus among febrile individuals in a high-endemic Ghanaian setting.BMC infectious diseases · 2026Article
- Clinical and Laboratory Discriminators for Tuberculosis and Lymphoma in Adults Presenting with Fever of Unknown Origin: A Prospective Cohort Study.International journal of general medicine · 2026Article
- Interest ofJournal of clinical medicine · 2025Article
- Neutrophil-to-ferritin ratio can predict hematological causes of fever of unknown origin.Scientific reports · 2024Article
- Differential diagnosis of lymphoma withJournal of cancer research and clinical oncology · 2023Observational
- Diagnostic models for fever of unknown origin based onEJNMMI research · 2022Article
- Application of Machine Learning for the Prediction of Etiological Types of Classic Fever of Unknown Origin.Frontiers in public health · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The diagnosis and treatment of fever of unknown origin (FUO) are huge challenges to clinicians. Separating the etiologies of FUO into infectious and non-infectious disease is conducive to clinical physicians not only on making decisions rapidly concerning the prescription of suitable antibiotics but also on further analysis of the final diagnosis. In order to develop and validate a diagnostic tool to efficiently distinguish the etiologies of adult FUO patients as infectious or non-infectious disease, FUO patients from the departments of infectious disease and internal medicine in three Chinese tertiary hospitals were enrolled retrospectively and prospectively. By using polynomial logistic regression analysis, the diagnostic formula and the associated scoring system were developed. The variables included in this diagnostic formula were from clinical evaluations and common laboratory examinations. The proposed tool could discriminate infectious and non-infectious causes of FUO with an area under receiver operating characteristic curve (AUC) of 0.83, sensitivity of 0.80 and specificity of 0.75. This diagnosis tool could predict the infectious and non-infectious causes of FUO in the validation cohort with an AUC of 0.79, sensitivity of 0.79 and specificity of 0.70. The results suggested that this diagnostic tool could be a reliable tool to discriminate between infectious and non-infectious causes of FUO.
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