• JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
  • JoomlaWorks Simple Image Rotator
 
  Bookmark and Share
 
 
Doctoral Thesis
DOI
10.11606/T.6.2015.tde-03082015-122033
Document
Author
Full name
Cíntia Ginaid de Souza
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2015
Supervisor
Committee
Siqueira, Arnaldo Augusto Franco de (President)
Ceccon, Maria Esther Jurfest Rivero
Godoy, Moacir Fernandes de
Leone, Claudio
Raimundo, Rodrigo Daminello
Title in Portuguese
Variabilidade da frequência cardíaca na sepse neonatal
Keywords in Portuguese
Dinâmica Não Linear
Sepse Neonatal Precoce
Teoria do Caos
Variabilidade da Frequência Cardíaca
Abstract in Portuguese
Introdução: as infecções são responsáveis por mais de um terço das mortes neonatais, sendo a sepse a de maior expressão. A sepse neonatal precoce (SNP) aumenta em cinco vezes a taxa de mortalidade entre recém-nascidos (RN) de termo e pré-termos tardios e em vinte e cinco vezes a taxa de mortalidade entre pré-termos extremos. A Variabilidade da Frequência Cardíaca (VFC) vem se mostrando capaz de antecipar o diagnóstico, reduzindo em 22% o risco relativo de mortalidade entre os pré-termos de muito baixo peso com sepse. Objetivo: verificar a VFC de RN com suspeita de SNP; identificar medidas significantes e verificar se, associadas a variáveis clínico-laboratoriais, aumentam a chance de identificar pacientes passíveis de desenvolver a doença. Método: utilizou-se um frequencímetro portátil para aferir as medidas da VFC nos domínios do tempo, da frequência e do Caos. Dentre elas, elegeu-se aquelas com curva ROC > 0,75 para, com seus valores de cut-off, aplicar regressão logística e identificar as que melhor se adequassem ao modelo. As variáveis clínico-laboratoriais significantes que restaram da análise univariada foram submetidas à análise multivariada a fim de identificar, também, as que melhor se adequassem ao modelo. Resultados: foram identificadas quatro variáveis clínico-laboratoriais (sexo masculino, idade gestacional < 34 semanas, Score de Rodwell e proteína C-reativa), e nove medidas da VFC (RRmean, SDNN, RR tri index, LF, HF, SD2 do plot de Poincaré, ShaEnt, CorrDim D2 e SamAsy). Cinco apresentaram área sob a curva ROC > 0,75: SDNN, RR tri index, LF, SD2 e CorrDim D2. Depois de aplicada a regressão logística, restou apenas a CorrDim D2 com cut-off = 0,1164. Identificadas, as variáveis foram submetidas ao cálculo do logit para, com isso, quantificar a chance do paciente suspeito de evoluir para a doença, na dependência das três variáveis eleitas: CorrDim D2, idade gestacional < 34 semanas e score de Rodwell. Conclusão: o estudo mostrou que tanto o modelo preditivo clinico como a CorrDim D2 são capazes, de forma independente, de estimar a chance que um futuro paciente com sepse suspeitada tem de efetivamente confirmar o diagnóstico de sepse. E que, além disso, se a CorrDim D2 for agregada ao modelo preditivo clínico, esta chance aumenta consideravelmente.
Title in English
Heart Rate Variability in Neonatal Sepsis
Keywords in English
Chaos Theory
Early-Onset Neonatal Sepsis
Heart Rate Variability
Non-Linear Dynamics
Abstract in English
Introduction: infectious diseases are responsible for more than one-third of neonatal deaths, and sepsis is of great importance. Early Neonatal Sepsis (ENS) increases five times the mortality rate among term and late preterm newborns. Among extreme preterm babies the mortality rate increases by twenty-five times. Heart Rate Variability (HRV) has been showing to be capable of anticipating the diagnosis, thus reducing by 22 percent the relative risk of mortality of very low preterm babies with sepsis. Objective: to verify HRV of newborn babies suspects of having ENS; to identify significant measures of HRV and to verify if, associated to clinical-laboratorial variables, if they improve the chance of identifying patients exposed to developing ENS. Method: a portable frequencimeter was used to registering the measurements of HRV in the domains of time, of frequency and of chaos. Among them, only those with a ROC curve greater than 0.75 were chosen, with their cut-off values to enter a logistic regression with the aim of identifying those more suitable to the model. The clinical-laboratorial variables which were considered significant in a univariete analysis were also submitted to the multivariate analysis with the purpose of identifying those better fitted to the model. Results: four clinical-laboratorial variables (male sex, gestational age less than 34 weeks, the Rodwell Score and C-Reactive Protein); similarly, nine measures of HRV (RRmean, SDNN, RR tri index, LF, HF, SD2 of Poincaré plot, ShaEnt, CorrDimD2 and SamAsy). Five of them presented an area under the ROC curve greater than 0.75: SDNN, RR tri index, LF, SD2 and CorrDim D2. Once applied the logistic regression, only CorrDim D2 remained, with a cut-off value of 0.1164. The identified variables were, then, submitted to the calculation of the logit, with the purpose of quantifying the chance of a patient suspect of evolving to a sepsis, in the dependence of the three elected variables: CorrDim D2, gestational age under 34 weeks and the Score of Rodwell. Conclusion: the study showed that both, the predictive clinical model as CorrDim D2 are able, independently, to estimate the chance that a patient with suspected sepsis future has to effectively confirm the diagnosis of sepsis. And that, moreover, if the CorrDim D2 is aggregated to clinical predictive model, this chance increases considerably.
 
WARNING - Viewing this document is conditioned on your acceptance of the following terms of use:
This document is only for private use for research and teaching activities. Reproduction for commercial use is forbidden. This rights cover the whole data about this document as well as its contents. Any uses or copies of this document in whole or in part must include the author's name.
Publishing Date
2015-10-19
 
WARNING: Learn what derived works are clicking here.
All rights of the thesis/dissertation are from the authors
Centro de Informática de São Carlos
Digital Library of Theses and Dissertations of USP. Copyright © 2001-2022. All rights reserved.