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OBJECTIVES: to evaluate software technical quality for collecting data from patients under palliative care. METHODS: this is methodological technology evaluation research, according to the technical standard International Organization for Standardization/International Electrotechnical Commission 25040-2011, developed from August 2021 to August 2023. Eight nurses and eight information technology professionals participated as judges, who evaluated six quality characteristics and 23 subcharacteristics. Items that reached a percentage of agreement greater than 70% were considered suitable. RESULTS: the characteristics evaluated by nurses/information technology professionals received the following percentages of agreement, respectively: functional suitability (94%-84%); reliability (100-70%); usability (89.9-66.8%); performance efficiency (95.8%-86.1%); compatibility (95.8-79.6%); and safety (96%-83.4%). CONCLUSIONS: the software was considered suitable in quality evaluation to offer support to nurses in collecting patient data under palliative care, with the potential to operationalize the first Nursing Process stage.

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The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging crisis affecting the public health system. The clinical features of COVID-19 can range from an asymptomatic state to acute respiratory syndrome and multiple organ dysfunction. Although some hematological and biochemical parameters are altered during moderate and severe COVID-19, there is still a lack of tools to combine these parameters to predict the clinical outcome of a patient with COVID-19. Thus, this study aimed at employing hematological and biochemical parameters of patients diagnosed with COVID-19 in order to build machine learning algorithms for predicting COVID mortality or survival. Patients included in the study had a diagnosis of SARS-CoV-2 infection confirmed by RT-PCR and biochemical and hematological measurements were performed in three different time points upon hospital admission. Among the parameters evaluated, the ones that stand out the most are the important features of the T1 time point (urea, lymphocytes, glucose, basophils and age), which could be possible biomarkers for the severity of COVID-19 patients. This study shows that urea is the parameter that best classifies patient severity and rises over time, making it a crucial analyte to be used in machine learning algorithms to predict patient outcome. In this study optimal and medically interpretable machine learning algorithms for outcome prediction are presented for each time point. It was found that urea is the most paramount variable for outcome prediction over all three time points. However, the order of importance of other variables changes for each time point, demonstrating the importance of a dynamic approach for an effective patient's outcome prediction. All in all, the use of machine learning algorithms can be a defining tool for laboratory monitoring and clinical outcome prediction, which may bring benefits to public health in future pandemics with newly emerging and reemerging SARS-CoV-2 variants of concern.

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Several potential risk factors have been identified in the etiopathogenesis of febrile seizures (FS), including the type and extent of breastfeeding (BF). Given the lack of conclusive data, this study aims to systematically evaluate the evidence on the association between BF and FS. We conducted a systematic review and meta-analysis according to PRISMA guidelines. The search was conducted using descriptors for FS, BF, and formula feeding in MEDLINE, Embase, and Web of Science databases. We included observational studies that compared the incidence of FS between those who had ever breastfed and those who were formula fed. The study protocol was registered on the PROSPERO platform under the number CRD42023474906. A total of 1,893,079 participants from 8 datasets were included. Our main analysis showed no significant association of any type of BF on the incidence of FS compared with formula-fed children (OR: 0.84; CI: 0.67-1.04; I2 = 78%; Cochran's Q = 0.0001), although meta-regression showed that BF was associated with a lower incidence of FS in preterm infants. Our secondary outcome showed a significantly reduced incidence of FS in children who received BF exclusively (OR: 0.80; CI: 0.65-0.99; I2 = 70%; Cochran's Q = 0.02).    Conclusion: There was no significant reduction in the incidence of FS in those who were breastfed compared to formula feeding. However, our meta-regression analysis indicated an association between BF and a lower incidence of FS in preterm infants. Additionally, children who exclusively received BF had a significantly reduced incidence of FS. These findings should be further investigated in prospective cohorts. What is Known: • Breastfeeding can modify risk factors for febrile seizures, such as susceptibility to viral and bacterial infections, micronutrient deficiencies, and low birth weight. • However, studies have shown conflicting results regarding the impact of breastfeeding on febrile seizures. What is New: • When comparing any breastfeeding pattern with no breastfeeding, there is no significant difference in the incidence of febrile seizures. • When comparing exclusive breastfeeding with no breastfeeding, there may be a decrease in the occurrence of febrile seizures.

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ABSTRACT Objectives: to evaluate software technical quality for collecting data from patients under palliative care. Methods: this is methodological technology evaluation research, according to the technical standard International Organization for Standardization/International Electrotechnical Commission 25040-2011, developed from August 2021 to August 2023. Eight nurses and eight information technology professionals participated as judges, who evaluated six quality characteristics and 23 subcharacteristics. Items that reached a percentage of agreement greater than 70% were considered suitable. Results: the characteristics evaluated by nurses/information technology professionals received the following percentages of agreement, respectively: functional suitability (94%-84%); reliability (100-70%); usability (89.9-66.8%); performance efficiency (95.8%-86.1%); compatibility (95.8-79.6%); and safety (96%-83.4%). Conclusions: the software was considered suitable in quality evaluation to offer support to nurses in collecting patient data under palliative care, with the potential to operationalize the first Nursing Process stage.

RESUMEN Objetivos: evaluar la calidad técnica del software para la recolección de datos de pacientes en cuidados paliativos. Métodos: se trata de una investigación metodológica de evaluación de tecnología, según la norma técnica International Organization for Standardization/International Electrotechnical Comission 25040-2011, desarrollada de agosto de 2021 a agosto de 2023. Participaron como jueces ocho enfermeros y ocho profesionales de tecnologías de la información, quienes evaluaron seis características de calidad y 23 subcaracterísticas. Se consideraron adecuados los ítems que alcanzaron un porcentaje de acuerdo superior al 70%. Resultados: las características evaluadas por enfermeros/profesionales de tecnologías de la información recibieron los siguientes porcentajes de acuerdo, respectivamente: adecuación funcional (94%-84%); confiabilidad (100-70%); usabilidad (89,9-66,8%); eficiencia del desempeño (95,8%-86,1%); compatibilidad (95,8-79,6%); y seguridad (96%-83,4%). Conclusiones: el software fue considerado adecuado en la evaluación de calidad para ofrecer apoyo a los enfermeros en la recolección de datos de los pacientes en cuidados paliativos, con potencial para operacionalizar la primera etapa del Proceso de Enfermería.

RESUMO Objetivos: avaliar a qualidade técnica de software para coleta de dados de pacientes sob cuidados paliativos. Métodos: trata-se de pesquisa metodológica de avaliação de tecnologia, conforme norma técnica International Organization for Standardization/International Electrotechnical Comission 25040-2011, desenvolvida de agosto de 2021 a agosto de 2023. Participaram oito enfermeiros e oito profissionais de tecnologia da informação como juízes, os quais avaliaram seis características e 23 subcaracterísticas de qualidade. Consideraram-se adequados os itens que atingiram porcentual de concordância superior a 70%. Resultados: as características avaliadas pelos enfermeiros/profissionais de tecnologia da informação receberam os seguintes porcentuais de concordância, respectivamente: adequação funcional (94%-84%); confiabilidade (100-70%); usabilidade (89,9-66,8%); eficiência de desempenho (95,8%-86,1%); compatibilidade (95,8-79,6%); e segurança (96%-83,4%). Conclusões: o software foi considerado adequado na avaliação de qualidade para oferecer suporte ao enfermeiro na coleta de dados do paciente em cuidados paliativos, com potencial para operacionalizar a primeira etapa do Processo de Enfermagem.

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OBJECTIVE: To develop digital technology for patient and family integration into the Intensive Care Unit care team, aiming to subsidize decision-making for the prevention of infections related to healthcare. METHOD: Methodological research of technological production in three phases: pre-production, production, and post-production in a teaching hospital in southern Brazil. Sixteen intensive care unit nurses participated. RESULTS: The research produced six videos: general guidelines on the Intensive Care Unit, Preventing infections: hand hygiene; Pneumonia associated with mechanical ventilation; Catheter-associated primary bloodstream infection; Catheter-related urinary tract infection. FINAL CONSIDERATIONS: The proposed technology was developed and aims to assist nurses in bringing patients and families closer to the routines of the intensive care environment to provide safety in the contact of the patient of intensive care units with family members and in the active participation for the prevention of infections related to healthcare.

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OBJECTIVE: To describe the use of the Fugulin scale to classify pediatric patients hospitalized in a respiratory unit as a subsidy for the allocation of human resources given the increase in cases of Severe Acute Respiratory Syndrome. METHOD: Experience report conducted in a children's hospital in the Metropolitan Region of Curitiba with data collection from medical records and approved by the Institution and by the Research Ethics Committee. RESULTS: Between February and May 2022, the percentage of patients categorized in minimal and intermediate care decreased by 53 and 11.4%, respectively, while those in high dependency and semi-intensive care expanded by 31.2 and 84.2%. In addition, in just four months, there was a considerable increase in the positivity of virologies compared to the twelve months of 2021. The susceptibility of children to the development of severe respiratory infection was proven through the decrease in virologies with undetectable results. CONCLUSION: The results obtained allowed us to conclude there was a significant increase in the complexity of patients admitted to the respiratory unit, showing it is essential to provide a nursing team compatible with the care needs.

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OBJECTIVE: To describe the implementation of Modified Seldinger Technology for percutaneous catheterization in critically ill newborns. METHOD: A quasi-experimental before- and-after study, carried out with neonatologist nurses in a Neonatal Intensive Care Unit. RESULTS: Seven nurses participated in the research. Catheter pre-insertion, insertion and maintenance were assessed using the conventional and modified Seldinger technique. Reliability was satisfactory in pre-test, 5.40 (Md = 6.00), and post-test, 5.94 (Md = 7.00), and perfect in the items about device insertion and maintenance. There was low assertiveness in the items on indication, microintroduction procedure via ultrasound, limb repositioning and disinfection of connections/connectors. CONCLUSION: Despite the Modified Seldinger Technique expanding some stages of execution over the traditional method of percutaneous catheterization, nurses were more assertive after theoretical-practical training. The technology was implemented and is in the process of being implemented in the health service.

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Platforms based on impedimetric electronic tongue (nonselective sensor) and machine learning are promising to bring disease screening biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point-of-care, thus contributing to rationalize and decentralize laboratory tests with social and economic impacts being achieved. By combining a low-cost and scalable electronic tongue with machine learning, in this chapter, we describe the simultaneous determination of two extracellular vesicle (EV) biomarkers, i.e., the concentrations of EV and carried proteins, in mice blood with Ehrlich tumor from a single impedance spectrum without using biorecognizing elements. This tumor shows primary features of mammary tumor cells. Pencil HB core electrodes are integrated into polydimethylsiloxane (PDMS) microfluidic chip. The platform shows the highest throughput in comparison with the methods addressed in the literature to determine EV biomarkers.

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Despite all efforts to combat the pandemic of COVID-19, we are still living with high numbers of infected persons, an overburdened health care system, and the lack of an effective and definitive treatment. Understanding the pathophysiology of the disease is crucial for the development of new technologies and therapies for the best clinical management of patients. Since the manipulation of the whole virus requires a structure with an adequate level of biosafety, the development of alternative technologies, such as the synthesis of peptides from viral proteins, is a possible solution to circumvent this problem. In addition, the use and validation of animal models is of extreme importance to screen new drugs and to compress the organism's response to the disease. Peptides derived from recombinant S protein from SARS-CoV-2 were synthesized and validated by in silico, in vitro and in vivo methodologies. Macrophages and neutrophils were challenged with the peptides and the production of inflammatory mediators and activation profile were evaluated. These peptides were also inoculated into the swim bladder of transgenic zebrafish larvae at 6 days post fertilization (dpf) to mimic the inflammatory process triggered by the virus, which was evaluated by confocal microscopy. In addition, toxicity and oxidative stress assays were also developed. In silico and molecular dynamics assays revealed that the peptides bind to the ACE2 receptor stably and interact with receptors and adhesion molecules, such as MHC and TCR, from humans and zebrafish. Macrophages stimulated with one of the peptides showed increased production of NO, TNF-α and CXCL2. Inoculation of the peptides in zebrafish larvae triggered an inflammatory process marked by macrophage recruitment and increased mortality, as well as histopathological changes, similarly to what is observed in individuals with COVID-19. The use of peptides is a valuable alternative for the study of host immune response in the context of COVID-19. The use of zebrafish as an animal model also proved to be appropriate and effective in evaluating the inflammatory process, comparable to humans.

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