FELIPE YU MATSUSHITA

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Instituto da Criança, Hospital das Clínicas, Faculdade de Medicina - Médico
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina - Médico
LIM/36 - Laboratório de Pediatria Clínica, Hospital das Clínicas, Faculdade de Medicina

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  • article 0 Citação(ões) na Scopus
    Association between Serum Lactate and Morbidity and Mortality in Neonates: A Systematic Review and Meta-Analysis
    (2023) MATSUSHITA, Felipe Yu; KREBS, Vera Lucia Jornada; CARVALHO, Werther Brunow De
    Objective: Lactate is a marker of hypoperfusion in critically ill patients. Whether lactate is useful for identifying and stratifying neonates with a higher risk of adverse outcomes remains unknown. This study aimed to investigate the association between lactate and morbidity and mortality in neonates. Methods: A meta-analysis was performed to determine the association between blood lactate levels and outcomes in neonates. Ovid MEDLINE, EMBASE, Cochrane Library, and ClinicalTrials.gov were searched from inception to 1 May 2021. A total of 49 observational studies and 14 data accuracy test studies were included. The risk of bias was assessed using the Newcastle-Ottawa Scale for observational studies and the QUADAS-2 tool for data accuracy test studies. The primary outcome was mortality, while the secondary outcomes included acute kidney injury, necessity for renal replacement therapy, neurological outcomes, respiratory morbidities, hemodynamic instability, and retinopathy of prematurity. Results: Of the 3184 articles screened, 63 studies fulfilled all eligibility criteria, comprising 46,069 neonates. Higher lactate levels are associated with mortality (standard mean difference, -1.09 [95% CI, -1.46 to -0.73]). Using the estimated sensitivity (0.769) and specificity (0.791) and assuming a prevalence of 15% for adverse outcomes (median of prevalence among studies) in a hypothetical cohort of 10,000 neonates, assessing the lactate level alone would miss 346 (3.46%) cases (false negative) and wrongly diagnose 1776 (17.76%) cases (false positive). Conclusions: Higher lactate levels are associated with a greater risk of mortality and morbidities in neonates. However, our results do not support the use of lactate as a screening test to identify adverse outcomes in newborns. Research efforts should focus on analyzing serial lactate measurements, rather than a single measurement.
  • article 1 Citação(ões) na Scopus
    Reassessing the role of milrinone in the treatment of heart failure and pulmonary hypertension in neonates and children: a systematic review and meta-analysis
    (2024) MATSUSHITA, Felipe Yu; KREBS, Vera Lucia Jornada; CAMPOS, Carolina Vieira de; GAIOLLA, Paula Vieira de Vincenzi; CARVALHO, Werther Brunow de
    To evaluate milrinone's impact on pediatric cardiac function, focusing on its specific role as an inotrope and lusitrope, while considering its systemic and pulmonary vasodilatory effects. Search of PubMed, EMBASE, and the Cochrane Library up to August 2023. We included all studies that evaluated milrinone in children under 18 years old in neonatal, pediatric, or cardiac intensive care units. We excluded case reports, studies that did not provide tabular information on milrinone's outcomes, and studies focused on non-intensive care populations. We extracted data on the research design, objectives, study sample, and results of each study, including the impact of milrinone and any associated factors. We screened a total of 9423 abstracts and 41 studies were ultimately included. Milrinone significantly improved left ventricular ejection fraction (WMD 3.41 [95% CI 0.61 - 6.21]), left ventricle shortening fraction (WMD 4.25 [95% CI 3.43 - 5.08]), cardiac index (WMD 0.50 [95% CI 0.32 to 0.68]), left ventricle output (WMD 55.81 [95% CI 4.91 to 106.72]), serum lactate (WMD -0.59 [95% CI -1.15 to -0.02]), and stroke volume index (WMD 2.95 [95% CI 0.09 - 5.82]). However, milrinone was not associated with improvements in ventricular myocardial performance index (WMD -0.01 [95% CI -0.06 to 0.04]) and ventricular longitudinal strain (WMD -2.14 [95% CI -4.56 to 0.28]). Furthermore, milrinone was not associated with isovolumetric relaxation time reduction (WMD -8.87 [95% CI -21.40 to 3.66]).Conclusion: Our meta-analysis suggests potential clinical benefits of milrinone by improving cardiac function, likely driven by its systemic vasodilatory effects. However, questions arise about its inotropic influence and the presence of a lusitropic effect. Moreover, milrinone's pulmonary vasodilatory effect appears relatively weaker compared to its systemic actions. Further research is needed to elucidate milrinone's precise mechanisms and refine its clinical applications in pediatric practice.What is Known:center dot Milrinone is a phosphodiesterase III inhibitor that has been used to treat a variety of pediatric and neonatal conditions.center dot Milrinone is believed to exert its therapeutic effects by enhancing cardiac contractility and promoting vascular relaxation.What is New:center dot Milrinone may not have a significant inotropic effect.center dot Milrinone's pulmonary vasodilatory effect is less robust than its systemic vasodilatory effect.
  • article 1 Citação(ões) na Scopus
    Complete blood count and C-reactive protein to predict positive blood culture among neonates using machine learning algorithms
    (2023) MATSUSHITA, Felipe Yu; KREBS, Vera Lucia Jornada; CARVALHO, Werther Brunow de
    Purpose: The authors aimed to develop a Machine-Learning (ML) algorithm that can predict positive blood culture in the neonatal intensive care unit, using complete blood count and C-reactive protein values.Methods: The study was based on patients' electronic health records at a tertiary neonatal intensive care unit in Sao Paulo, Brazil. All blood cultures that had paired complete blood count and C-reactive protein measurements taken at the same time were included. To evaluate the machine learning model's performance, the authors used accuracy, Area Under the Receiver Operating Characteristics (AUROC), recall, precision, and F1-score.Results: The dataset included 1181 blood cultures with paired complete blood count plus c-reactive protein and 1911 blood cultures with paired complete blood count only. The f1-score ranged from 0.14 to 0.43, recall ranged from 0.08 to 0.59, precision ranged from 0.29 to 1.00, and accuracy ranged from 0.688 to 0.864.Conclusion: Complete blood count parameters and C-reactive protein levels cannot be used in ML models to pre-dict bacteremia in newborns.
  • article 1 Citação(ões) na Scopus
    Identifying two distinct subphenotypes of patent ductus arteriosus in preterm infants using machine learning
    (2023) MATSUSHITA, Felipe Yu; KREBS, Vera Lucia Jornada; CARVALHO, Werther Brunow de
    To use unsupervised machine learning to identify potential subphenotypes of preterm infants with patent ductus arteriosus (PDA). The study was conducted retrospectively at a neonatal intensive care unit in Brazil. Patients with a gestational age < 28 weeks who had undergone at least one echocardiogram within the first two weeks of life and had PDA size > 1.5 or LA/AO ratio > 1.5 were included. Agglomerative hierarchical clustering on principal components was used to divide the data into different clusters based on common characteristics. Two distinct subphenotypes of preterm infants with hemodynamically significant PDA were identified: ""inflamed,"" characterized by high leukocyte, neutrophil, and neutrophil-to-lymphocyte ratio, and ""respiratory acidosis,"" characterized by low pH and high pCO(2) levels. Conclusions: This study suggests that there may be two distinct subphenotypes of preterm infants with hemodynamically significant PDA: ""inflamed"" and ""respiratory acidosis."" By dividing the population into different subgroups based on common characteristics, it is possible to get a more nuanced understanding of the effectiveness of PDA interventions. What is Known: Treatment of PDA in preterm infants has been controversial. Stratification of preterm infants with PDA into subgroups is important in order to determine the best treatment. What is New: Unsupervised machine learning was used to identify two subphenotypes of preterm infants with hemodynamically significant PDA. The 'inflamed' cluster was characterized by higher values of leukocyte, neutrophil, and neutrophil-to-lymphocyte ratio. The 'respiratory acidosis' cluster was characterized by lower pH values and higher pCO2 values.