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1.
BMC Med Educ ; 24(1): 319, 2024 Mar 20.
Artigo em Inglês | MEDLINE | ID: mdl-38509539

RESUMO

BACKGROUND: The Students Training in Academia, Health, and Research (STAHR) Program at the University of Missouri-Kansas City (UMKC) strives to help students from low-income families that have experienced educational challenges due to poverty and prepare them to enter, persist, and graduate from a health sciences degree program at UMKC. Students in the program participated in fuzzy cognitive mapping (FCM) sessions to ensure that all voices of the program were heard to improve program implementation, and student success, and contribute to an equitable educational environment. METHODS: Fuzzy Cognitive Mapping sessions for the 2020-2021 cohort of students (n = 52) were conducted to assess the strengths and weaknesses in program implementation, especially through the beginning of the COVID-19 pandemic. Students' maps were coded by a team of researchers and then confirmed using confirmatory factor analysis. RESULTS: Statistical analyses reveal that mentorship, workshops, and social support helped students to work toward their goal of obtaining a professional health sciences degree, while a lack of time, remote learning, and outside stressors inhibited their opportunities for success. CONCLUSIONS: The findings from a multipronged analysis of mapping data demonstrate the value of this innovative approach to the field, especially when looking to incorporate student voices.


Assuntos
Pandemias , Estudantes , Humanos , Avaliação de Programas e Projetos de Saúde , Mentores , Cognição
2.
Brain ; 145(5): 1668-1683, 2022 06 03.
Artigo em Inglês | MEDLINE | ID: mdl-35190816

RESUMO

Disease-causing variants in STXBP1 are among the most common genetic causes of neurodevelopmental disorders. However, the phenotypic spectrum in STXBP1-related disorders is wide and clear correlations between variant type and clinical features have not been observed so far. Here, we harmonized clinical data across 534 individuals with STXBP1-related disorders and analysed 19 973 derived phenotypic terms, including phenotypes of 253 individuals previously unreported in the scientific literature. The overall phenotypic landscape in STXBP1-related disorders is characterized by neurodevelopmental abnormalities in 95% and seizures in 89% of individuals, including focal-onset seizures as the most common seizure type (47%). More than 88% of individuals with STXBP1-related disorders have seizure onset in the first year of life, including neonatal seizure onset in 47%. Individuals with protein-truncating variants and deletions in STXBP1 (n = 261) were almost twice as likely to present with West syndrome and were more phenotypically similar than expected by chance. Five genetic hotspots with recurrent variants were identified in more than 10 individuals, including p.Arg406Cys/His (n = 40), p.Arg292Cys/His/Leu/Pro (n = 30), p.Arg551Cys/Gly/His/Leu (n = 24), p.Pro139Leu (n = 12), and p.Arg190Trp (n = 11). None of the recurrent variants were significantly associated with distinct electroclinical syndromes, single phenotypic features, or showed overall clinical similarity, indicating that the baseline variability in STXBP1-related disorders is too high for discrete phenotypic subgroups to emerge. We then reconstructed the seizure history in 62 individuals with STXBP1-related disorders in detail, retrospectively assigning seizure type and seizure frequency monthly across 4433 time intervals, and retrieved 251 anti-seizure medication prescriptions from the electronic medical records. We demonstrate a dynamic pattern of seizure control and complex interplay with response to specific medications particularly in the first year of life when seizures in STXBP1-related disorders are the most prominent. Adrenocorticotropic hormone and phenobarbital were more likely to initially reduce seizure frequency in infantile spasms and focal seizures compared to other treatment options, while the ketogenic diet was most effective in maintaining seizure freedom. In summary, we demonstrate how the multidimensional spectrum of phenotypic features in STXBP1-related disorders can be assessed using a computational phenotype framework to facilitate the development of future precision-medicine approaches.


Assuntos
Epilepsia , Espasmos Infantis , Eletroencefalografia , Epilepsia/genética , Humanos , Lactente , Proteínas Munc18/genética , Estudos Retrospectivos , Convulsões/genética , Espasmos Infantis/tratamento farmacológico , Espasmos Infantis/genética
4.
JAMA Netw Open ; 6(7): e2324380, 2023 07 03.
Artigo em Inglês | MEDLINE | ID: mdl-37471090

RESUMO

Importance: Genomic advances inform our understanding of epilepsy and can be translated to patients as precision diagnoses that influence clinical treatment, prognosis, and counseling. Objective: To delineate the genetic landscape of pediatric epilepsy and clinical utility of genetic diagnoses for patients with epilepsy. Design, Setting, and Participants: This cohort study used phenotypic data from medical records and treating clinicians at a pediatric hospital to identify patients with unexplained pediatric-onset epilepsy. Exome sequencing was performed for 522 patients and available biological parents, and sequencing data were analyzed for single nucleotide variants (SNVs) and copy number variants (CNVs). Variant pathogenicity was assessed, patients were provided with their diagnostic results, and clinical utility was evaluated. Patients were enrolled from August 2018 to October 2021, and data were analyzed through December 2022. Exposures: Phenotypic features associated with diagnostic genetic results. Main Outcomes and Measures: Main outcomes included diagnostic yield and clinical utility. Diagnostic findings included variants curated as pathogenic, likely pathogenic (PLP), or diagnostic variants of uncertain significance (VUS) with clinical features consistent with the involved gene's associated phenotype. The proportion of the cohort with diagnostic findings, the genes involved, and their clinical utility, defined as impact on clinical treatment, prognosis, or surveillance, are reported. Results: A total of 522 children (269 [51.5%] male; mean [SD] age at seizure onset, 1.2 [1.4] years) were enrolled, including 142 children (27%) with developmental epileptic encephalopathy and 263 children (50.4%) with intellectual disability. Of these, 100 participants (19.2%) had identifiable genetic explanations for their seizures: 89 participants had SNVs (87 germline, 2 somatic mosaic) involving 69 genes, and 11 participants had CNVs. The likelihood of identifying a genetic diagnosis was highest in patients with intellectual disability (adjusted odds ratio [aOR], 2.44; 95% CI, 1.40-4.26), early onset seizures (aOR, 0.93; 95% CI, 0.88-0.98), and motor impairment (aOR, 2.19; 95% CI 1.34-3.58). Among 43 patients with apparently de novo variants, 2 were subsequently determined to have asymptomatic parents harboring mosaic variants. Of 71 patients who received diagnostic results and were followed clinically, 29 (41%) had documented clinical utility resulting from their genetic diagnoses. Conclusions and Relevance: These findings suggest that pediatric-onset epilepsy is genetically heterogeneous and that some patients with previously unexplained pediatric-onset epilepsy had genetic diagnoses with direct clinical implications.


Assuntos
Epilepsia , Deficiência Intelectual , Masculino , Feminino , Humanos , Estudos de Coortes , Sequenciamento do Exoma , Deficiência Intelectual/epidemiologia , Epilepsia/diagnóstico , Epilepsia/genética , Convulsões
5.
Hosp Pediatr ; 11(8): 871-877, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34301718

RESUMO

OBJECTIVES: In this study, we assessed the knowledge and experience of pediatric pharmacists and nurses at a US tertiary-care pediatric center regarding the risk factors for, recognition of, and best practices for managing an acute kidney injury (AKI) in children. METHODS: The authors developed a survey to assess the attitudes and knowledge of nurses and pharmacists regarding AKI in hospitalized children, which was reviewed by a small multidisciplinary group for content and length. The final 16-item survey consisted of demographic, self-assessment and attitude, and knowledge questions. All pediatric pharmacists and nurses at the study site received a voluntary online survey via e-mail. Data were analyzed by using descriptive statistics. RESULTS: A survey was sent to 620 nurses and 50 pharmacists; 148 (25%) and 22 (44%), respectively, completed it. Most respondents were <35 years old and had ≤10 years of experience in both their professions and pediatrics. A total of 72% of pediatric nurses felt identification of AKI was within their scope of practice, and ∼60% felt confident in their ability to do so. More than 80% of pediatric pharmacists felt confident in their abilities to adjust medication doses in pediatric patients with AKI, but <60% felt confident in their ability to estimate the glomerular filtration rate in these patients. Nurses and pharmacists were able to correctly identify specific AKI criteria 60% to 70% and 70% to 90% of the time, respectively. CONCLUSIONS: Although pediatric nurses and pharmacists have knowledge of AKI prevention and mitigation, gaps exist, and there is a desire for education in recognition of their key roles in the clinical team.


Assuntos
Injúria Renal Aguda , Enfermeiros Pediátricos , Injúria Renal Aguda/induzido quimicamente , Injúria Renal Aguda/diagnóstico , Adulto , Criança , Conhecimentos, Atitudes e Prática em Saúde , Humanos , Farmacêuticos , Inquéritos e Questionários
6.
J Pediatr Health Care ; 34(2): 145-160, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31836355

RESUMO

INTRODUCTION: Pediatric patients who develop acute kidney injury (AKI) while hospitalized have longer hospital stays, increased morbidity and mortality, and are at an increased risk for developing chronic kidney disease. Early recognition of AKI is becoming a major clinical focus. There is little research focusing on nursing interventions that may affect a pediatric patient's risk for developing AKI. The purpose of this review is to summarize reported predictors of AKI to improve its early recognition and treatment among hospitalized pediatric patients. METHODS: A review of research was conducted to further identify risk factors of AKI among noncritically ill hospitalized pediatric patients. RESULTS: The current literature demonstrated inconsistent findings in early recognition of AKI among hospitalized pediatric patients. DISCUSSION: Interventions for early recognition and treatment of AKI should consider other variables, such as previous history of AKI and fluid status as risk factors, warranting additional research.


Assuntos
Injúria Renal Aguda/etiologia , Injúria Renal Aguda/diagnóstico , Injúria Renal Aguda/terapia , Pesquisa Biomédica , Criança , Hospitalização , Humanos , Fatores de Risco
7.
NPJ Genom Med ; 5: 29, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32655885

RESUMO

While genomic data is frequently collected under distinct research protocols and disparate clinical and research regimes, there is a benefit in streamlining sequencing strategies to create harmonized databases, particularly in the area of pediatric rare disease. Research hospitals seeking to implement unified genomics workflows for research and clinical practice face numerous challenges, as they need to address the unique requirements and goals of the distinct environments and many stakeholders, including clinicians, researchers and sequencing providers. Here, we present outcomes of the first phase of the Children's Rare Disease Cohorts initiative (CRDC) that was completed at Boston Children's Hospital (BCH). We have developed a broadly sharable database of 2441 exomes from 15 pediatric rare disease cohorts, with major contributions from early onset epilepsy and early onset inflammatory bowel disease. All sequencing data is integrated and combined with phenotypic and research data in a genomics learning system (GLS). Phenotypes were both manually annotated and pulled automatically from patient medical records. Deployment of a genomically-ordered relational database allowed us to provide a modular and robust platform for centralized storage and analysis of research and clinical data, currently totaling 8516 exomes and 112 genomes. The GLS integrates analytical systems, including machine learning algorithms for automated variant classification and prioritization, as well as phenotype extraction via natural language processing (NLP) of clinical notes. This GLS is extensible to additional analytic systems and growing research and clinical collections of genomic and other types of data.

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