Fever may be the only sign of an underlying infection in neutropenic cancer patients. Unrecognized fever and untreated infections can lead to progressive sepsis and possibly death. The importance of early recognition, timely antibiotics, and treatment is crucial to favorable outcomes. The primary objective of this study was to evaluate the treatment of adult cancer patients with febrile neutropenia for compliance with National Comprehensive Cancer Network (NCCN) febrile neutropenia guidelines at our institution, UCHealth Memorial Hospital. Secondary objectives were to examine antibiotic selection, culture results, time to antibiotics, all-cause mortality, and length of hospital stay. This was a single-center, retrospective chart review of hospitalized neutropenic patients undergoing active chemotherapy. Neutropenia and fever were defined based on NCCN Guidelines. A total of 223 neutropenic patients were hospitalized between October 15, 2015, and December 31, 2016. Overall, 16 patients met the inclusion criteria for chemotherapy-induced neutropenia with fever. Compliance with the NCCN guideline standards was seen in seven (43.8%) patients. Antibiotics administered within 60 minutes of presentation was the lowest standard with adherence in eight (50%) patients. Empiric monotherapy antibiotic regimens were initiated in 11 (68.8%) patients; eight (50%) received cefepime and three (18.8%) received meropenem. At our institution, full compliance with the NCCN febrile neutropenia guidelines is not optimal. This study demonstrates the need for process improvement initiatives, including the addition of an electronic health record alert to flag patients undergoing active chemotherapy. It also warrants promoting the use of our institution's emergency department febrile neutropenia treatment pathway to providers to improve overall compliance.
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December 2024
Department of Infectious Diseases, Hospital Clinic of Barcelona-IDIBAPS, 08036 Barcelona, Spain.
The rise of multidrug-resistant (MDR) infections demands personalized antibiotic strategies for febrile neutropenia (FN) in hematological malignancies. This study investigates machine learning (ML) for identifying patient profiles with increased susceptibility to bloodstream infections (BSI) during FN onset, aiming to tailor treatment approaches. From January 2020 to June 2022, we used the unsupervised ML algorithm KAMILA to analyze data from hospitalized hematological malignancy patients.
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MVR Cancer Centre and Research Institute, Calicut, Kerala, India.
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Division of Medical Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON M4N 3M5, Canada.
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January 2025
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