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1.
Cancer Nurs ; 2024 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-38949311

RESUMO

BACKGROUND: Management of chemotherapy-induced mucosal barrier damage and oral/anal mucositis in leukemia is challenging. OBJECTIVE: The aim of this study was to investigate the effect of mucositis care training given to children receiving leukemia treatment and their caregivers on caregiver knowledge and skills, the development of gastrointestinal mucositis in children, the mean oral mucositis area in children, and the mucosal barrier injury laboratory-confirmed bloodstream infection in the clinic. METHODS: A stepped-wedge, quasi-experimental, unpaired control group design was used. The participants in the control group were given routine training, and the intervention group members were given mucositis care training in accordance with the guideline recommendations. RESULTS: No significant difference was found between groups in developing anal mucositis, but a significant difference in developing oral mucositis was documented, with the mean mucositis area of children being 8.36 ± 3.97 cm2 in the control group and 4.66 ± 2.90 cm2 in the intervention group. The mucosal barrier injury laboratory-confirmed bloodstream infection ratio was 4 per 1000 catheter days in the control group and 3 per 1000 catheter days in the intervention group. CONCLUSION: Mucositis care training had a significant positive effect on caregivers' knowledge and skills, the development of oral mucositis, and the mean oral mucositis area in children. However, the training had no effect on the development of anal mucositis or the infection rate in the clinic. IMPLICATIONS FOR PRACTICE: Nurses might increase the knowledge and skill levels of caregivers with training on mucositis care, prevent the development of mucositis, and reduce the mean mucositis area. Training might also contribute to the reduction in the infection rate of the clinic.

2.
Pediatr Res ; 93(2): 390-395, 2023 01.
Artigo em Inglês | MEDLINE | ID: mdl-36302858

RESUMO

Although the overall incidence of pediatric oncological diseases tends to increase over the years, it is among the rare diseases of the pediatric population. The diagnosis, treatment, and healthcare management of this group of diseases are important. Prevention of treatment-related complications is vital for patients, particularly in the pediatric population. Nowadays, the use of artificial intelligence and machine learning technologies in the management of oncological diseases is becoming increasingly important. With the advancement of software technologies, improvements have been made in the early diagnosis of risk groups in oncological diseases, in radiology, pathology, and imaging technologies, in cancer staging and management. In addition, these technologies can be used to predict the outcome in chemotherapy treatment of oncological diseases. In this context, this study identifies artificial intelligence and machine learning methods used in the prediction of complications due to chemotherapeutic agents used in childhood cancer treatment. For this purpose, the concepts of artificial intelligence and machine learning are explained in this review. A general framework for the use of machine learning in healthcare and pediatric oncology has been drawn and examples of studies conducted on this topic in pediatric oncology have been given. IMPACT: Artificial intelligence and machine learning are advanced tools that can be used to predict chemotherapy-related complications. Algorithms can assist clinicians' decision-making processes in the management of complications. Although studies are using these methods, there is a need to increase the number of studies on artificial intelligence applications in pediatric clinics.


Assuntos
Inteligência Artificial , Neoplasias , Humanos , Criança , Aprendizado de Máquina , Algoritmos , Oncologia
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