Leticia Rodrigues Goulart de Souza

@.incor.usp.br

Faculdade de Medicina da USP
Instituto do Coração do Hospital das Clínicas

Leticia Rodrigues Goulart de Souza


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https://researchid.co/leticia.goulart

EDUCATION

Enfermeira formada pela Universidade Anhembi Morumbi. Pós-graduada em Centro Cirúrgico, Recuperação Anestésica e Central de Material e Esterilização pela Faculdade de Ciências Médicas da Santa Casa de São Paulo, aprimoramento em Controle de Infecção Hospitalar no Hospital Clínicas da Faculdade de Medicina da Universidade de São Paulo e doutoranda pela Faculdade de Medicina da Universidade de São Paulo.

RESEARCH, TEACHING, or OTHER INTERESTS

Multidisciplinary, Health Professions

FUTURE PROJECTS

Fatores de risco pré-operatório para infecções de sítio cirúrgico em cirurgias de revascularização miocárdica

Diante do aumento constante do número de procedimentos cirúrgicos cardíacos e da relevância das ISC como principais complicações relacionadas à assistência à saúde, seria útil um instrumento capaz de predizer o risco de infecção no período pós-operatório. Tal modelo facilitaria uma avaliação de risco/benefício da intervenção cirúrgica cardíaca, bem como a identificação de fatores passíveis de intervenção para otimização dos desfechos.


Applications Invited
Centros de cuidados ao paciente cirúrgico cardíaco.
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Scopus Publications

Scopus Publications

  • Early prediction of 30-day mortality in patients with surgical wound infections following cardiothoracic surgery: Development and validation of the SWICS-30 score utilizing conventional logistic regression and artificial neural network
    Julio Alejandro Cedeno, Tania Mara Varejão Strabelli, Bruno Adler Maccagnan Pinheiro Besen, Rafael de Freitas Souza, Denise Blini Sierra, Leticia Rodrigues Goulart de Souza, Samuel Terra Gallafrio, Cely Saad Abboud, Diego Feriani, Rinaldo Focaccia Siciliano
    Brazilian Journal of Infectious Diseases, 2025
    • Creation an score that can predict early mortality in patients with surgical wound infection after cardio thoracic surgery. • Use an artificial intelligence (deep learning with artificial neural network) for validation. • 8.3 % of mortality due to infection in patients with surgical wound infection after cardio thoracic surgery. We aimed to create and validate the 30-day prognostic score for mortality in patients with surgical wound infection (SWICS-30) after cardiothoracic surgery. This retrospective study enrolled patients with surgical wound infection following cardiothoracic surgery admitted to a Cardiologic Reference Center Hospital between January 2006 and January 2023. Clinical data and commonly used blood tests were analyzed at the time of diagnosis. An independent scoring system was developed through logistic regression analysis and validated using Artificial intelligence. From 1713 patients evaluated (mean age of 60 years (18–89), 55 % female), 143 (8.4 %) experienced 30-day mortality. The SWICS-30 logistic regression score comprised the following variables: age over 65 years, undergoing valve heart surgery, combined coronary and valve heart surgery, heart transplantation, time from surgery to infection diagnosis exceeding 21 days, leukocyte count over 13,000/mm3, lymphocyte count below 1000/mm3, platelet count below 150,000/mm3, and creatinine level exceeding 1.5 mg/dL. These patients were stratified into low (2.7 %), moderate (14.2 %), and high (47.1 %) in-hospital mortality risk categories. Artificial intelligence confirmed accuracy at 90 %.