Antibiotic-Resistant Septicemia in Pediatric Oncology Patients Associated with Post-Therapeutic Neutropenic Fever
Rosalino Vázquez-López,
Omar Rivero Rojas,
Andrea Ibarra Moreno,
José Erik Urrutia Favila,
Adan Peña Barreto,
Guadalupe Lizeth Ortega Ortuño,
Jorge Andrés Abello Vaamonde,
Ivanka Alejandra Aguilar Velazco,
José Marcos Félix Castro,
Sandra Georgina Solano-Gálvez,
Tomás Barrientos Fortes,
Juan Antonio González-Barrios
Affiliations
Rosalino Vázquez-López
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Omar Rivero Rojas
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Andrea Ibarra Moreno
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
José Erik Urrutia Favila
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Adan Peña Barreto
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Guadalupe Lizeth Ortega Ortuño
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Jorge Andrés Abello Vaamonde
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Ivanka Alejandra Aguilar Velazco
Departamento de Microbiología del Centro de Investigación en Ciencias de la Salud (CICSA), FCS, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
José Marcos Félix Castro
Coordinación Ciclos Clínicos, Facultad de Ciencias de la Salud, Universidad Anáhuac México Campus Norte, Cuidad de México 52786, Mexico
Sandra Georgina Solano-Gálvez
Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico
Tomás Barrientos Fortes
Director Facultad de Ciencias de la Salud, Universidad Anáhuac México, Cuidad de México 52786, Mexico
Juan Antonio González-Barrios
Laboratorio de Medicina Genómica, Hospital Regional “Primero de Octubre”, ISSSTE, Av. Instituto Politécnico Nacional 1669, Lindavista, Gustavo A. Madero, Ciudad de Mexico 07300, Mexico
Death in cancer patients can be caused by the progression of tumors, their malignity, or other associated conditions such as sepsis, which is a multiphasic host response to a pathogen that can be significantly amplified by endogenous factors. Its incidence is continuously rising, which reflects the increasing number of sick patients at a higher risk of infection, especially those that are elderly, pediatric, or immunosuppressed. Sepsis appears to be directly associated with oncological treatment and fatal septic shock. Patients with a cancer diagnosis face a much higher risk of infections after being immunosuppressed by chemotherapy, radiotherapy, or anti-inflammatory therapy, especially caused by non-pathogenic, Gram-negative, and multidrug-resistant pathogens. There is a notorious difference between the incidence and mortality rates related to sepsis in pediatric oncologic patients between developed and developing countries: they are much higher in developing countries, where investment for diagnosis and treatment resources, infrastructure, medical specialists, cancer-related control programs, and post-therapeutic care is insufficient. This situation not only limits but also reduces the life expectancy of treated pediatric oncologic patients, and demands higher costs from the healthcare systems. Therefore, efforts must aim to limit the progression of sepsis conditions, applying the most recommended therapeutic regimens as soon as the initial risk factors are clinically evident—or even before they are, as when taking advantage of machine learning prediction systems to analyze data.