Medical-type peritoneal mesothelioma leading to death two months after onset of fever of unknown origin

Ishizuka, Kosuke; Uehara, Takanori; Arai, Makoto; Ikeda, Jun‐ichiro; Hirose, Yuta; Ikusaka, Masatomi

doi:10.1016/j.radcr.2021.11.064

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Given that FUO may be caused by infectious, inflammatory, malignant, and miscellaneous disorders, clinicians often order non-clue-based imaging and specific testing early at the onset of FUO, and this approach may be inefficient or misleading [28]. In recent years, serious complications and even deaths from many diseases associated with FUO have been reported [29][30][31]. FUO is a persistent clinical problem that often confuses clinicians to the point that physicians need to deal with different diseases characterized by FUO at a great cost.…”

Section: Discussionmentioning

confidence: 99%

Human brucellosis and fever of unknown origin

Song

Wang

et al. 2022

BMC Infect Dis

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Background Human brucellosis has become one of the major public health problems in China, and increases atypical manifestations, such as fever of unknown origin (FUO), and misdiagnosis rates has complicated the diagnosis of brucellosis. To date, no relevant study on the relationship between brucellosis and FUO has been conducted. Methods We retrospectively reviewed the medical charts of 35 patients with confirmed human brucellosis and prospectively recorded their outcomes by telephone interview. The patients were admitted to the Second Affiliated Hospital of Nanchang University between January 01, 2013 and October 31, 2019. Patient data were collected from hospital medical records. Results The percentage of males was significantly higher than that of female in FUO (78.95% vs. 21.05%, P < 0.05), and 80% of the patients had a clear history of exposure to cattle and sheep. Moreover, 19 (54%) cases were hospitalized with FUO, among which the patients with epidemiological histories were significantly more than those without (P < 0.05). The incidence of toxic hepatitis in FUO patients was higher than that in non-FUO patients (89% vs. 50%, P < 0.05). Meanwhile, the misdiagnosis rate was considerably higher in the FUO group than in the non-FUO group (100% vs. 63%; P < 0.05). Conclusion Brucellosis is predominantly FUO admission in a non-endemic area of China, accompanied by irregular fever and toxic hepatitis. Careful examination of the epidemiological history and timely improvement of blood and bone marrow cultures can facilitate early diagnosis and prevent misdiagnosis.

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Section: Discussionmentioning

confidence: 99%

Human brucellosis and fever of unknown origin

Song

Wang

et al. 2022

BMC Infect Dis

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A Pathological Diagnosis Method for FUO based on Multi-Path Hierarchical Classification: Model Design and Validation (Preprint)

Du,

Ding,

et al. 2024

Preprint

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BACKGROUND Fever of Unknown Origin (FUO) is a significant challenge for the medical community due to its association with a wide range of diseases, the complexity of diagnosis, and the likelihood of misdiagnosis. Machine learning can extract valuable information from the extensive data of patient indicators, aiding doctors in diagnosing the underlying cause of FUO. OBJECTIVE A hierarchical classification method based on multipath feature selection was proposed to address the problem that the causes of FUO are diverse and difficult to diagnose accurately. METHODS The dataset was obtained from the clinical diagnostic records of patients with FUO who were admitted to the First Affiliated Hospital of Xi'an Jiaotong University between the years 2011 and 2020. The dataset contains 564 samples, with 5 broad categories of etiologies and subcategories, totaling 16 precise etiologies. An intelligent diagnostic algorithm for FUO was constructed based on hierarchical classification to identify 16 precise etiologies and two improvements were made: (1) A multi-path prediction model to minimize the probability of error propagation; (2) A utilization of L1,2 regularization constraint to effectively identify the most suitable subset of features to eliminate redundancy and interference in the hierarchical classification process. To confirm the proposed method's validity, we conducted ablation experiments and compared it with other flat and hierarchical classification algorithms. RESULTS According to the ablation experiments, the proposed method achieves the optimal result when the intermediate path is 3, with an accuracy of 72.35%, FH of 85.01%, and FLCA of 83.29%. This performance is superior to the traditional single-path hierarchical classification, showing improvements of 5.69%, 2.89%, and 3.39%, respectively. The feature selection based on the L1,2 regularization constraint can further enhance the model's performance. The best results were achieved by filtering 25% of the features, with an accuracy of 76.08%, FH of 86.72%, and FLCA of 85.39%. Based on the comparison experiments, the proposed method outperforms the seven flat algorithms and four hierarchical classification algorithms that were compared. For example, the accuracy can be improved by at least 5.39% compared to ELM and up to 24.7% compared to KNN. CONCLUSIONS The proposed algorithm greatly improves the classification performance compared to existing machine learning algorithms. It can better predict the cause of FUO, assisting physicians in their work. CLINICALTRIAL

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Medical-type peritoneal mesothelioma leading to death two months after onset of fever of unknown origin

Cited by 2 publications

References 6 publications

Human brucellosis and fever of unknown origin

Human brucellosis and fever of unknown origin

A Pathological Diagnosis Method for FUO based on Multi-Path Hierarchical Classification: Model Design and Validation (Preprint)

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