ROSSANA PULCINELI VIEIRA FRANCISCO
Projetos de Pesquisa
Unidades Organizacionais
Departamento de Obstetrícia e Ginecologia, Faculdade de Medicina - Docente
Instituto Central, Hospital das Clínicas, Faculdade de Medicina
LIM/57 - Laboratório de Fisiologia Obstétrica, Hospital das Clínicas, Faculdade de Medicina - Líder
Instituto Central, Hospital das Clínicas, Faculdade de Medicina
LIM/57 - Laboratório de Fisiologia Obstétrica, Hospital das Clínicas, Faculdade de Medicina - Líder
2 resultados
Resultados de Busca
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- Low back pain, pelvic pain, and associated factors in type 1 diabetic pregnant women(2024) BATISTA, Patricia Andrade; OLIVEIRA, Claudia de; COSTA, Rafaela Alkmin da; FRANCISCO, Rossana Pulcineli Vieira; CABAR, Fabio RobertoIntroduction: Pregnancy and diabetes mellitus promote several musculoskeletal changes predisposing this population to complaints of Lower Back (LB) and Pelvic Pain (PP). Objective: To assess the frequency of LB and PP and associated factors in type 1 Diabetic (DM1) pregnant women. Method: An observational analytical cross-sectional study. Thirty-six pregnant women with DM1 were evaluated through a postural assessment with a focus on pelvic positioning and what patients reported. The associated factors were assessed using the State-Trait Anxiety Inventory (STAI), the International Consultation on Incontinence Questionnaire Short Form (ICIQ-SF), and the Female Sexual Function Index (FSFI). Results: The frequency of LB and PP was 55.6 % and 30.6 %, respectively. The presence of anxiety was not associated with a higher prevalence of pain. The incidence of sexual dysfunctions was higher in the GD. DM1 duration had a mean of 14.9 years (+/- 8.2 SD) in the GD and 9.0 years (+/- 6.9 SD) in the GSD, which was statistically significant (p <= 0.050). In the multiple binary regression analysis for the occurrence of pain, the independent factor was DM1 duration >= 17 years (OR = 11.2; 95 % CI = 1.02-124.75). The association between DM1 duration >= 17 years and being overweight showed a probability of 95 % for the studied population in the analysis of the probabilities of occurrence of the pain event. Conclusion: There was a high frequency of LB and PP related to pregnancy in DM1 pregnant women in the second trimester of pregnancy. The incidence of sexual dysfunction and DM1 duration >= 17 years increases the chance that DM1 pregnant women will experience pain. There was no association between anxiety. urinary incontinence and pain in DM1 pregnant women.
- Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic(2024) RITTO, Ana Paula; ARAUJO, Adriana Ladeira de; CARVALHO, Carlos Roberto Ribeiro de; SOUZA, Heraldo Possolo De; FAVARETTO, Patricia Manga e Silva; SABOYA, Vivian Renata Boldrim; GARCIA, Michelle Louvaes; KULIKOWSKI, Leslie Domenici; KALLAS, Esper Georges; PEREIRA, Antonio Jose Rodrigues; COBELLO JUNIOR, Vilson; SILVA, Katia Regina; ABDALLA, Eidi Raquel Franco; SEGURADO, Aluisio Augusto Cotrim; SABINO, Ester Cerdeira; RIBEIRO JUNIOR, Ulysses; FRANCISCO, Rossana Pulcineli Vieira; MIETHKE-MORAIS, Anna; LEVIN, Anna Sara Shafferman; SAWAMURA, Marcio Valente Yamada; FERREIRA, Juliana Carvalho; SILVA, Clovis Artur; MAUAD, Thais; GOUVEIA, Nelson da Cruz; LETAIF, Leila Suemi Harima; BEGO, Marco Antonio; BATTISTELLA, Linamara Rizzo; DUARTE, Alberto Jose da Silva; SEELAENDER, Marilia Cerqueira Leite; MARCHINI, Julio; FORLENZA, Orestes Vicente; ROCHA, Vanderson Geraldo; MENDES-CORREA, Maria Cassia; COSTA, Silvia Figueiredo; CERRI, Giovanni Guido; BONFA, Eloisa Silva Dutra de Oliveira; CHAMMAS, Roger; BARROS FILHO, Tarcisio Eloy Pessoa de; BUSATTO FILHO, GeraldoIntroduction The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency.Methods At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output.Results Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19.Discussion Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.