| Autor: |
Ruoxuan Wang, Aimin Jiang, Rui Zhang, Chuchu Shi, Qianqian Ding, Shihan Liu, Fumei Zhao, Yuyan Ma, Junhui Liu, Xiao Fu, Xuan Liang, ZhiPing Ruan, Yu Yao, Tao Tian |
| Rok vydání: |
2023 |
| DOI: |
10.21203/rs.3.rs-2486032/v1 |
| Popis: |
(1) Background: Patients with malignancy are more vulnerable to developing nosocomial infections. Limited studies investigated cancer patients' clinical features and prognostic factors of fungi infections. Herein, this study was performed to explore the clinical characteristics of nosocomial infections due to fungi and develop a nomogram to predict the in-hospital death risk of these patients. (2) Methods: This retrospective observational study analyzed cancer patients with nosocomial infections caused by fungi from September 2013 to September 2021. The univariate and multivariate logistics regression analyses were utilized to identify the influencing factors of in-hospital death risk of nosocomial infections caused by fungi. A nomogram was developed to predict the in-hospital death risk of these individuals, with the receiver operating characteristics curve (ROC), calibration curve, and decision curve being generated to evaluate its performance. (3) Results: 216 patients with solid tumors developed fungal infections during hospitalization, of which 57 experienced in-hospital death. C.albicans is the most common fungal species(68.0%). The respiratory system was the most common site of infection(59.0%), followed by intra-abdominal infection (8.8%). The multivariate regression analysis revealed that ECOG-PS 3–4, pulmonary metastases, thrombocytopenia, hypoalbuminemia, and mechanical ventilation were independent risk factors of in-hospital death risk. A nomogram was constructed based on the identified risk factors to predict the in-hospital death risk of these patients. (4) Conclusions: Fungi-related nosocomial infections are common in solid tumors and have a bleak prognosis. The constructed nomogram could help oncologists make a timely and appropriate clinical decision with significant net clinical benefit to patients. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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