scholarly journals Relationships between Causes of Fever of Unknown Origin and Inflammatory Markers: A Multicenter Collaborative Retrospective Study

2015 ◽  
Vol 54 (16) ◽  
pp. 1989-1994 ◽  
Author(s):  
Toshio Naito ◽  
Keito Torikai ◽  
Masafumi Mizooka ◽  
Fujiko Mitsumoto ◽  
Kenji Kanazawa ◽  
...  
2008 ◽  
Vol 38 (4) ◽  
pp. 221-222 ◽  
Author(s):  
Minghua Zheng ◽  
Hailong Lin ◽  
Sheng Luo ◽  
Lihua Xu ◽  
Yanjun Zeng ◽  
...  

This is a retrospective study of older patients admitted to the First and Second Affiliated Hospitals of Wenzhou Medical College, China, with a diagnosis of fever of unknown origin. The study took place from January 1998 to December 2006 among 102 patients who fulfilled the criteria. Infections were responsible for 50 cases (49.1%), followed by no diagnosis in 27 (26.5%), miscellaneous in nine (8.8%), neoplasms in eight (7.8%) and connective tissue disease in another eight (7.8%). Mycobacterium TB was the most frequent type of infection diagnosed.


2020 ◽  
Vol 71 (Supplement_4) ◽  
pp. S409-S415
Author(s):  
Teng Xu ◽  
Li Wang ◽  
Shi Wu ◽  
Fenfen Zhou ◽  
Haihui Huang

Abstract Background Infectious disease is the leading cause of fever of unknown origin (FUO). Serum inflammatory markers historically used to diagnose bacterial infection have sufficient diagnostic sensitivity but low specificity. This study aimed to develop a simple scoring system for differentiating bacterial infections from other causes of early-stage FUO. Methods This study included a retrospective cohort of patients presenting with FUO at the Huashan Hospital (January 2014 to June 2017). The diagnostic utility of serum inflammatory markers for bacterial infection was evaluated using the receiver operating characteristic (ROC) curve analysis. Relevant markers were subsequently measured prospectively in a separate cohort of FUO patients (December 2017 to May 2019). A scoring system was based on inflammatory markers and other test results. Results Bacterial infection was identified in 34% of patients in the retrospective cohort. The area under the ROC curve (AUC) was 0.644 (95% confidence interval [CI], .595–.693) for C-reactive protein, 0.624 (95% CI, .573–.675) for procalcitonin, and 0.646 (95% CI, .595–.697) for serum ferritin (SF) in diagnosing bacterial infection. Bacterial infection was found in 29% of cases in the prospective cohort. A model based on serum amyloid A (SAA) and SF levels and neutrophil percentage yielded an AUC of 0.775 (95% CI, .695–.854). Validation analysis indicated lower probability (<15%) of bacterial infection for patients with a score <16.5 points. Conclusions A scoring system based on SAA and SF levels and neutrophil percentage can help distinguish bacterial infection from other causes of FUO, potentially reducing antibiotic use.


1990 ◽  
Vol 64 (3) ◽  
pp. 335-341 ◽  
Author(s):  
Hiroshi FUKUHARA ◽  
Kazunori TAMAKI ◽  
Hiroaki NAKAMURA ◽  
Hiroshi KANESIMA ◽  
Yuei IRABU ◽  
...  

BMJ Open ◽  
2013 ◽  
Vol 3 (12) ◽  
pp. e003971 ◽  
Author(s):  
Toshio Naito ◽  
Masafumi Mizooka ◽  
Fujiko Mitsumoto ◽  
Kenji Kanazawa ◽  
Keito Torikai ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Anoshirwan Andrej Tavakoli ◽  
Miriam Reichert ◽  
Tanja Blank ◽  
Dietmar Dinter ◽  
Sabine Weckbach ◽  
...  

2011 ◽  
Vol 44 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Thomas Ingemann Pedersen ◽  
Casper Roed ◽  
Lene Surland Knudsen ◽  
Annika Loft ◽  
Peter Skinhoj ◽  
...  

2009 ◽  
Vol 30 (1) ◽  
pp. 41-47 ◽  
Author(s):  
Catherine Castaigne ◽  
Marianne Tondeur ◽  
Stéphane De Wit ◽  
Marc Hildebrand ◽  
Nathan Clumeck ◽  
...  

2008 ◽  
Vol 56 (1) ◽  
pp. 182-184 ◽  
Author(s):  
Yongping Chen ◽  
Minghua Zheng ◽  
Xiang Hu ◽  
Yu Li ◽  
Yanjun Zeng ◽  
...  

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