Orientador: Renato Passini Junior / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciencias Medicas / Made available in DSpace on 2018-11-27T10:57:27Z (GMT). No. of bitstreams: 1 Pinto_GiulianeJesusLajos_M.pdf: 245675 bytes, checksum: 71fd93a1854439989a54c4faa89da2dc (MD5) Previous issue date: 2005 / Resumo: Objetivo: estudar a colonização bacteriana endocervical em gestantes com trabalho de parto prematuro e/ou ruptura prematura de membranas (termo e pré-termo). Método: 212 gestantes com trabalho de parto prematuro (TPP) e/ou ruptura prematura de membranas (RPM), internadas no Hospital Estadual Sumaré (Unicamp), foram avaliadas no período de julho de 2002 a janeiro de 2004. Na admissão hospitalar foram coletadas duas amostras do conteúdo endocervical, realizadas bacterioscopia e cultura em meios ágar-sangue ou ágar-chocolate. Foram analisadas associações da colonização endocervical com infecção de trato urinário materno, corioamnionite, uso de antibióticos, dados de parto, sofrimento fetal, prematuridade, infecção e óbito neonatais. Resultados: entre as mulheres estudadas, 74 (35%) tinham TPP e 138 (65%), RPM. A prevalência de colonização endocervical foi de 14,2% (IC=9,5%-18,9%), com resultados similares em TPP e RPM. Na população estudada, o microorganismo mais encontrado foi o estreptococo do grupo B (EGB) (9,4%), sendo também isolados Candida sp (5 casos), Streptococcus sp (2 casos), Streptococcus pneumoniae, Escherichia coli e Enterococcus sp (1 caso de cada). Das bacterioscopias analisadas, os achados mais freqüentes foram baixa prevalência de bacilos de Dodërlein e elevado número de leucócitos. Em mulheres colonizadas houve maior prevalência de infecção de trato urinário (23,8% versus 5,4%; p<0,01), infecção neonatal (25,0% versus 7,3%; p<0,01) e óbito neonatal (dois casos entre as colonizadas; p<0,02), quando comparadas às não-colonizadas. Conclusões: observou-se alta prevalência de colonização endocervical, sem a utilização de meios de cultura seletivos. O EGB foi o principal microorganismo isolado, reforçando a necessidade de triagem deste agente durante a gestação e nas situações de risco estudadas. Um terço das culturas positivas ocorreram por outros agentes. Estudos complementares são necessários para esclarecer a importância destes achados bacteriológicos no canal endocervical e sua associação com complicações gestacionais, sepse e mortalidade neonatais / Abstract: Objective: to study cervical colonization in women with preterm labor and/or premature rupture of membranes. Method: 212 pregnant women with preterm labor and/or premature rupture of membranes (PROM), admitted at Hospital Estadual Sumaré, during the period between July 2002 and January 2004, were studied. Two cervical samples from each woman were collected and bacterioscopy and culture in blood-agar or chocolate-agar plates were performed. Association of cervical microorganisms and urinary infection, chorioamnionitis, antibiotics use, prematurity, neonatal infection and neonatal death were evaluated. Results: the population evaluated consisted of 74 women with preterm labor (35%) and 138 women with PROM (preterm and term). The prevalence of cervical colonization was 14.2% (CI=9.5-18.9%), with similar results in preterm labor or PROM. Group B streptococcus was the most prevalent organism in this population (9.4%). Other organisms isolated were Candida sp, Streptococcus sp, Streptococcus pneumoniae, Escherichia coli and Enterococcus sp. The most common findings of bacterioscopy were a reduced number of lactobacilli and a great number of leukocytes. Endocervical colonization was associated with a higher occurrence of urinary tract infection (23.8% versus 5.4%; p<0.01), early-onset of neonatal infection (25.0% versus 7.3%; p<0.01) and neonatal mortality (2 cases in colonizated women; p<0.02) when compared with a negative culture of endocervical mucus. Conclusions: this study showed high prevalence of endocervical colonization despite of the use of a nonselective culture media. The main microorganism isolated was Group B streptococcus but other organisms were present in one third of studied population. More studies are needed to evaluate the influence of endocervical colonization in obstetrical outcome and in neonatal sepsis and mortality / Mestrado / Tocoginecologia / Mestre em Tocoginecologia

Orientador: Renato Passini Júnior / Tese (Doutorado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas / Made available in DSpace on 2018-11-27T12:42:05Z (GMT). No. of bitstreams: 1 MachadoJunior_LuisCarlos_D.pdf: 2512679 bytes, checksum: 24dd4c071dfcdc0f3d90247ac2b8cd08 (MD5) Previous issue date: 2013 / Resumo: INTRODUÇÃO: A idade gestacional ao nascimento é um dos principais fatores associados com complicações e mortes neonatais. Crianças nascidas entre 34 semanas e 36 semanas e seis dias de idade gestacional, denominadas prematuros tardios, são, tradicionalmente, considerados como de risco e prognóstico muito semelhantes aos dos recém-nascidos a termo. Estudos mais recentes, porém, têm mostrado que tanto prematuros tardios, quanto aqueles nascidos entre 37 e 38 semanas, apresentam resultados neonatais e no primeiro ano de vida, significativamente piores que os dos recém-nascidos a partir de 39 semanas. OBJETIVOS: revisar a literatura sobre o tema, analisar a prevalência de nascimento de prematuros tardios no tempo e comparar a frequência de mortes e complicações neonatais nos prematuros tardios e nos nascidos entre 37 e 38 semanas, com as mortes e complicações neonatais dos recém-nascidos a partir de 39 semanas. MÉTODO: revisão de literatura englobando os bancos de dados Medline, Lilacs e Biblioteca Cochrane. Realizado estudo de coorte retrospectiva com os dados de recém-nascidos vivos atendidos no Centro de Atenção Integral à Saúde da Mulher (CAISM) da Universidade Estadual de Campinas (UNICAMP), de janeiro de 2004 a dezembro de 2010. Os dados foram extraídos a partir do arquivo eletrônico da instituição. Foram excluídos os casos sem informação sobre a idade gestacional, as malformações e doenças congênitas fetais e as gestações múltiplas. Além das mortes neonatais, foram estudadas as seguintes complicações: hemorragia do sistema nervoso central, convulsões, índice de Apgar menor que sete no primeiro e quinto minutos, pneumonia, atelectasia, displasia broncopulmonar, pneumotórax, laringite pós entubação, síndrome de aspiração de mecônio, hipotermia, hipocalcemia e icterícia. As variáveis de controle foram: idade materna, estado civil, tabagismo, realização de pré-natal, hipertensão arterial (pré eclampsia ou crônica), diabetes, infecção urinária, outras morbidades maternas, primiparidade, cinco ou mais partos anteriores, tipo de parto, crescimento fetal restrito e sexo do recém-nascido. Para análise estatística foi aplicado o teste de qui-quadrado e o teste exato de Fisher, quando indicado. Assumiu-se o valor de p menor que 0,05 como significâncias estatísticas. Foi utilizado odds ratio (OR) como medida de efeito e a regressão logística múltipla para a análise multivariada. RESULTADOS: Foram estudados 18.032 nascimentos únicos, sendo 1.653 prematuros tardios e 16.379 recém nascidos de termo. Houve mais mortes neonatais (OR ajustado = 5.30; IC 95%: 2,61?10,74) nos prematuros tardios em comparação com os recém-nascidos a termo (nascidos entre 37 e 42 semanas). Também houve mais mortes neonatais (OR ajustado = 2,44; IC 95% 1,05-5,63) nos recém-nascidos de termo precoce comparados aos de termo tardio. Houve associação significativa para todas as complicações estudadas com a prematuridade tardia, exceto para síndrome de aspiração de mecônio. Encontrou-se tendência significativa de aumento na proporção de prematuros tardios em relação ao total dos partos ao longo do período estudado. CONCLUSÃO: Conclui-se que tanto os prematuros tardios quanto os nascidos entre 37 e 38 semanas são uma população de maior risco se comparados aos recém-nascidos a partir de 39 semanas / Abstract: INTRODUCTION: Gestational age at birth is a major determinant of neonatal mortality and complications. The risk of death and complications in infants born at 34 to 36 weeks of pregnancy (named late preterm infants) has been traditionally considered to be very similar to that of term infants. Some recent studies, however, have shown that late preterm infants, as well as those born at 37 and 38 weeks, have significantly worse outcomes in the neonatal period and in the first year of life than those born at 39 weeks or later. OBJECTIVE: to conduct a literature review on this issue; assess the prevalence and any temporal trend in late preterm births in the period that was studied; to compare neonatal deaths and complications in late preterm infants versus term infants, and compare neonatal deaths in infants born at 37 and 38 weeks (early term) versus those born at 39 to 42 weeks (late term). METHODS: A retrospective cohort study of live births was carried out in the Women's Integrated Healthcare Center (CAISM), State University of Campinas (UNICAMP), from January 2004 to December 2010. Data were extracted from an electronic database containing all medical records of the institution. Excluded from the study were congenital diseases and malformations, multiple pregnancies and cases without data on gestational age. Outcomes studied were neonatal deaths, length of hospital stay and the following complications: central nervous system hemorrhage, convulsions, Apgar score lower than seven at the first and fifth minute, pneumonia, atelectasis, pneumothorax, bronchopulmonary dysplasia, pulmonary hypertension, postintubation laryngitis, meconium aspiration syndrome, hypothermia, hypocalcemia and jaundice. Control variables were: maternal age, marital status, smoking habit, and absence of prenatal care, maternal hypertensive disease, maternal diabetes, urinary tract infection, other maternal morbid condition, primiparity, five or more previous births, fetal growth restriction, fetal gender, labor induction and pre labor cesarean section. It was used the chi square test and Fischer's exact test when indicated. The odds ratio (OR) was used as a measure of effect and multiple logistic regression was used for multivariate analysis. A significant level of 5% was adopted. RESULTS: After exclusions, there were 18,032 single births (1,653 late preterm births and 16,379 term births). An adjusted OR of 5.30; 95% confidence interval of 2.61--- 10.74 was found for neonatal death in late preterm births compared to term births (at 37 to 42 weeks), and an adjusted OR of 2.44; 95 confidence interval of 1.05-5.63 for neonatal death in early term births compared to late term births. A significantly higher risk was found in late preterm infants compared to term infants for all complications studied, except for meconium aspiration syndrome. There was a significantly growing trend in the proportion of late preterm births at the institution in the period studied. CONCLUSION: It was concluded that late preterm infants are at higher risk of undesirable outcomes than term infants. Furthermore, early term infants have a higher risk of death compared to late term infants and these differences are clinically relevant / Doutorado / Saúde Materna e Perinatal / Doutor em Ciências da Saúde

Un des marqueurs biophysique le plus prometteur pour la détection des accouchements prématurés (AP) est l'activité électrique de l'utérus, enregistrée sur l’abdomen des femmes enceintes, l’électrohystérogramme (EHG). Plusieurs outils de traitement du signal (linéaires, non linéaires) ont déjà été utilisés pour l'analyse de l'excitabilité et de la propagation de l’EHG, afin de différencier les contractions de grossesse, qui sont inefficaces, des contractions efficaces d’accouchement, qui pourraient provoquer un AP. Dans ces études nombreuses, les paramètres sont calculés sur des bases de données de signaux différentes, obtenus avec des protocoles d'enregistrement différents. Il est donc difficile de comparer les résultats afin de choisir les «meilleurs» paramètres pour la détection de l’AP. En outre, ce grand nombre de paramètres augmente la complexité de calcul dans un but de diagnostic. Par conséquent, l'objectif principal de cette thèse est de tester, sur une population de femmes donnée, quels outils de traitement du signal EHG permettent une discrimination entre les deux types de contractions (grossesse/accouchement). Dans ce but plusieurs méthodes de sélection de paramètres sont testées afin de sélectionner les paramètres les plus discriminants. La première méthode, développée dans cette thèse, est basée sur la mesure de la distance entre les histogrammes des paramètres pour les différentes classes (grossesse et accouchement) en utilisant la méthode « Jeffrey divergence (JD)». Les autres sont des méthodes de fouille de données existantes issues de la littérature. Les EHG ont été enregistrés en utilisant un système multivoies posé sur l'abdomen de la femme enceinte, pour l'enregistrement simultané de 16 voies d'EHG. Une approche monovariée (caractérisation d’une seule voie) et bivariée (couplage entre deux voies) sont utilisées dans notre travail. Utiliser toutes les voies, analyse monovariée, ou toutes les combinaisons de voies, analyse bivariée, conduit à une grande dimension des paramètres. Par conséquent, un autre objectif de notre thèse est la sélection des voies, ou des combinaisons de voies, qui fournissent l'information la plus utile pour distinguer entre les contractions de grossesse et d’accouchement. Cette étape de sélection de voie est suivie par la sélection des paramètres, sur les voies ou les combinaisons de voies sélectionnées. De plus, nous avons développé cette approche en utilisant des signaux monopolaires et bipolaires.Les résultats de ce travail nous permettent de mettre en évidence, lors du traitement de l’EHG, les paramètres et les voies qui donnent la meilleure discrimination entre les contractions de grossesse et celles d’accouchement. Ces résultats pourront ensuite être utilisés pour la détection des menaces d’accouchement prématuré. / One of the most promising biophysical markers of preterm labor is the electrical activity of the uterus, picked up on woman’s abdomen, the electrohysterogram (EHG). Several processing tools of the EHG signal (linear, nonlinear), allow the analysis of both excitability and propagation of the uterine electrical activity in order to differentiate between pregnancy contractions, which are ineffective, from labor effective contractions that might cause preterm birth. Therefore, on these multiple studies, the parameters being computed from different signal databases, obtained with different recording protocols, it is sometimes difficult to compare their results in order to choose the “best” parameter for preterm labor detection. Additionally, this large number of parameters increases the computational complexity for diagnostic purpose. Therefore, the main objective of this thesis is to select, among all the features of interest extracted from multiple studies, the most pertinent feature subsets in order to discriminate, on a given population, pregnancy and labor contractions. For this purpose, several methods for feature selection are tested. The first one, developed in this work, is based on the measurement of the Jeffrey divergence (JD) distance between the histograms of the parameters of the 2 classes, pregnancy and labor. The other are “Filter” and “Wrapper” Data Mining methods, extracted from the literature. In our work monovariate (in one given EHG channel) and bivariate analysis (propagation of EHG by measuring the coupling between channels) are used. The EHG signals are recorded using a multichannel system positioned on the woman’s abdomen for the simultaneous recording of 16 channels of EHG. Using all channels, for the monovariate, or all combinations of channels for the bivariate analysis, leads to a large dimension of parameters for each contraction. Therefore, another objective of our thesis is the selection of the best channels, for the monovariate, or best channel combinations, for the bivariate analysis, that provide the most useful information to discriminate between pregnancy and labor classes. This channel selection step is then followed by the feature selection for the channels or channel combinations selected. Additionally, we tested all our work using monopolar and bipolar signals.The results of this thesis permits us to evidence, when processing the EHG, which channels and features can be used with the best chance of success as inputs of a diagnosis system for discrimination between pregnancy and labor contractions. This could be further used for preterm labor diagnosis.

Introdução: Prematuridade é a principal causa de morbimortalidade perinatal. A aplicação de um instrumento que identifique o grupo de pacientes de risco para parto pré-termo (PPT) permitirá a aplicação de estratégias de prevenção e reduzirá essa complicação. Objetivos: validar a calculadora de risco para PPT espontâneo antes da 34ª semana de gestação, disponibilizada pela Fetal Medicine Foundation (FMF), em uma amostra de mulheres brasileiras. Métodos: Estudo retrospectivo, observacional que analisou 1325 gestantes admitidas para seguimento pré-natal. Variáveis maternas de interesse foram coletadas por meio da análise de questionários, prontuários e contato telefônico. Em seguida, os dados foram inseridos na calculadora para cálculo do risco de PPT. As gestantes foram divididas em dois grupos de acordo com a ocorrência de PPT antes da 34ª semana (Grupo 1) ou parto após 37 semanas de gestação (Grupo 2). Análise de regressão múltipla foi efetuada para avaliar os efeitos das variáveis estudadas sobre a ocorrência de parto pré-termo antes da 34ª semana e para a construção de um modelo de discriminação, que foi avaliado pelo índice c. Curva ROC foi utilizada para os cálculos de sensibilidade e especificidade e, com base nesses valores, do valor de corte acima do qual o risco de PPT antes de 34 semanas foi significativamente maior em nossa amostra de pacientes. Resultados: A prevalência de PPT espontâneo antes da 34ª semana foi de 1.3%. As variáveis que apresentaram diferenças significativas entre os Grupos 1 e 2 foram: tabagismo (p=0,0002), antecedente de prematuridade de prematuridade repetitiva entre 16 - 30 semanas sem parto prévios a termo e de prematuridade eletiva (p<0,0001 e p=0,0271, respectivamente) e risco calculado de PPT antes de 34 semana (1.32% X 0.78%, p<0,01). A regressão múltipla confirmou que o tabagismo e os antecedentes de PPT aumentaram o risco de PPT espontâneo em nossa amostra. Na avaliação do desempenho do teste índice para detectar PPT antes de 34 semanas, observou-se área sob a curva significante de 0.64 e o ponto de corte acima do qual o risco de PPT aumenta significativamente foi 0.7%. Conclusões: a calculadora de risco de PPT antes da 34ª semana da FMF é um bom instrumento para rastrear gestantes em nossa amostra populacional e o valor de corte acima do qual esse risco aumenta é 0.7%. / Introduction: Prematurity is the leading cause of perinatal morbidity and mortality. The use of an instrument to identify the group of patients at risk for preterm birth (PTB) will allow the implementation of prevention strategies, therefore reducing this complication. Objectives: To validate the calculator for assessment of risk for spontaneous delivery before 34 weeks of pregnancy, provided by the Fetal Medicine Foundation (FMF) for a group of Brazilian women. Methods: This retrospective and observational cohort study comprised 1,325 women undergoing routine antenatal care. Maternal variables were collected through the analysis of questionnaires, medical records and telephone calls. Then the data were inserted in the software to calculate the risk of PTB. The patients were divided in two groups according to the occurrence of PTB before 34 weeks (Group 1) or birth after 37 weeks of pregnancy (Group 2). Multilevel regression analysis was used to determine the effects of maternal characteristics on the occurrence of PTB before 34 weeks and to build a discrimination model which was evaluated by the index c. ROC curve was used to determine sensitivity and specificity, and the cutoff value above which it the risk of PTB before 34 weeks was significantly higher in our patient sample. Results: The prevalence of spontaneous PTB before 34 weeks was 1.3%. Variables that showed significant differences between groups 1 and 2 were: smoking (p=0.0002), history of repetitive PTB between 16-30 weeks without prior term and elective PTB (p<0.0001 and p=0.0271, respectively), and the risk of PTB before 34 week (1.32% vs. 0.78%, p<0.01). Multilevel regression analysis confirmed that smoking and history of PTB increased the risk of spontaneous PTB in our patient sample. On the assessment of performance index test to detect PPT before 34 weeks there was a significant area under the curve of 0.64 and the cutoff above which it the risk of PTB before 34 weeks was significantly higher was 0.7 %. Conclusions: the calculator for assessment of risk for spontaneous delivery before 34 weeks of pregnancy is a good tool for screening pregnant women in our population sample and the cutoff value above which it the risk increases is 0.7%.

L'EMG utérin appelé Electrohystérogramme (EHG) a été exploité depuis longtemps par ses caractéristiques temporelles, fréquentielles, et temps-fréquence, pour la prédiction de l'accouchement prématuré, tandis que l'étude de sa propagation est rare. Tous les résultats des études antérieures n'ont pas montré un potentiel satisfaisant pour une application clinique. L'objectif de cette thèse est l'analyse de la propagation ainsi que de la non-linéarité des signaux EHG pendant la grossesse et le travail en vue d'une application clinique. Une analyse monovariée a été faite pour étudier la non-linéarité et la sensibilité des méthodes aux différentes caractéristiques des signaux. Une analyse bivariée a ensuite été menée pour l‟étude de la propagation de l‟EHG, en mesurant le couplage entre les voies ainsi que la direction de couplage, ce qui est une nouveauté de notre thèse. Dans cette analyse, nous proposons une approche de filtrage-fenêtrage pour améliorer les méthodes d'estimation du couplage et de sa direction. Une autre nouveauté de cette thèse est l'implantation d'un outil de localisation de source d'EHG pour étudier la dynamique de l'utérus au niveau de la source, et non pas au niveau des électrodes comme fait dans les études précédentes. Les résultats montrent que les méthodes non linéaires sont plus capables que les méthodes linéaires, de classifier les contractions de grossesse et de travail. La méthode de réversibilité de temps est la moins sensible à la fréquence d'échantillonnage et au contenu fréquentiel du signal. Les résultats indiquent également une augmentation de couplage et une concentration des directions vers le col de l‟utérus, en allant de la grossesse vers le travail. En respectant la non-stationnarité des signaux EHG et en se libérant de l'effet de filtrage de la graisse, très variable durant la grossesse et entre les différentes femmes, notre méthode de filtrage-fenêtrage (segmentation et filtrage du signal EHG pour ne garder que la composant FWL), améliore les performances des méthodes de connectivité. L'intensité des sources localisées et leur nombre sont plus élevés durant le travail que durant la grossesse. Les sources localisées sont actives et propagées durant le travail alors que durant la grossesse elles restent faibles et localisées. Une amélioration de la matrice d'électrodes du protocole expérimental de rat a été effectuée par le développement d'une électrode à succion. Ce protocole pourra ensuite être utilisé pour la validation de nos méthodes et celle du modèle électrophysiologique. / The uterine EMG -called Electrohysterogramme (EHG)- temporal, frequency, and time-frequency characteristics have been used for a long time for the prediction of preterm labor. However, the investigation of its propagation is rare. All the results of the previous studies did not show a satisfactory potential for clinical application. The objective of this thesis is the analysis of the propagation as well as of the nonlinear characteristics of EHG signals during pregnancy and labor for clinical application. A monovariate analysis was done to investigate the nonlinearity and the sensibility of methods to different characteristics of the signals. A bivariate analysis was then done for the investigation of the propagation of EHG by measuring the coupling between channels, as well as the direction of coupling, which is an innovative part of our thesis. In this analysis we propose a new approach to improve the coupling and direction estimation methods. Another innovation of this thesis is the implementation of a tool for EHG source localization to investigate the dynamic of the uterus at the source level, not at electrodes level as previously done. Results show that nonlinear methods are more able to classify pregnancy and labor contractions than linear ones, and that time reversibility method is the least sensitive to sampling frequency and frequency content of the signal. Results also indicate an increase in coupling and a concentration of coupling direction toward the cervix when going from pregnancy to labor. We also proposed to respect the nonstationarity of EHG signal and to recover the effect of variable fat filtering along pregnancy, by segmenting and filtering the EHG in its FWL component. This filtering-windowing approach permits to improve the performances of connectivity methods. Finally, the intensity of localized sources and their number is higher in labor than in pregnancy contractions. The identified sources are more active and more propagated in labor whereas in pregnancy they remain weak and local. An improvement in the electrode matrix of the rat experimental protocol has also been done by developing a suction electrode. This protocol can then be used for the validation of our methods and of the electrophysiological model.

Orientador: Renato Passini Junior / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Ciencias Medicas / Made available in DSpace on 2018-08-04T01:25:35Z (GMT). No. of bitstreams: 1 Nomura_MarceloLuis_D.pdf: 838174 bytes, checksum: a795b39457b62a18ecb17c4609ece12d (MD5) Previous issue date: 2004 / Resumo: Objetivos: Identificar a taxa de prevalência e fatores de risco de colonização materna por estreptococo do grupo B (EGB) em gestantes com trabalho de parto prematuro (TPP) e/ou ruptura prematura pré-termo de membranas (RPM). Métodos: Foram colhidos dois swabs anais e vaginais de 203 gestantes atendidas no CAISM-UNICAMP. Um swab de cada local foi colocado em meio de transporte e enviados para cultura em placas de ágar-sangue, os outros dois foram incubados por 24 horas em meio de Todd-Hewitt para posterior semeadura em placas de ágar-sangue. Resultados: A prevalência de colonização materna por EGB foi de 27,6% (56 gestantes). As taxas de colonização por diagnóstico foram 34,7% para RPM, 25,2% para TPP e 17,8% para TPP + RPM. As variáveis raça branca, baixo nível de escolaridade e infecção urinária foram associadas a maiores taxas de colonização na análise multivariada. A presença de infecção urinária foi a única variável significativamente associada à colonização materna na análise multivariada. A taxa de detecção do estreptococo do grupo B foi significativamente maior com o uso do meio seletivo e com a associação de coleta de culturas anais e vaginais. A taxa de colonização neonatal foi de 3,1%. Ocorreram dois casos de sepse precoce por EGB nesta amostra, com prevalência estimada de 10,8 casos por mil nascidos vivos e mortalidade de 50%. Conclusão: A amostra avaliada apresenta altas taxas de colonização materna por Streptococcus agalactiae. É necessário o uso de meio de cultura seletivo e a associação de culturas anorretais e vaginais para aumentar a taxa de detecção do EGB. A incidência de sepse neonatal precoce foi elevada nesta população / Abstract: Objective: to study group B streptococcus maternal colonization rates and risk factors in women with preterm labor (PTL) and preterm premature rupture of membranes (PROM). Methods: Vaginal and anal swabs (two of each) were colected from 203 women followed at CAISM-UNICAMP. One of each swab was placed in transport media and then cultured in blood-agar plates, the other swabs were incubated in Todd-Hewitt selective media for 24 hours and then subcultured in blood-agar plates. Results: Maternal colonization rate was 27.6% (56 women). Colonization rates by admission diagnosis were 34.7% in PROM, 25.2% in PTL and 17.8% in PTL and PROM. White race, less than elementary education level and urinary tract infection were associated with maternal colonization in the univariate analysis. Urinary tract infection was the only variable associated with maternal colonization in a multivariate analysis. GBS detection rates were significantly higher with the use of selective culture media and with sampling of both vaginal and anorectal sites. Neonatal colonization rate was 3.1%. There were two cases of early-onset neoanatal sepsis caused by GBS, with an estimated prevalence of 10.8 cases per thousand live borns and a mortality rate of 50%. Conclusions: This sample of women had high GBS colonization rates. The use of selective culture media and collection of both anal and vaginal samples is necessary in order to maximize GBS detection rates. Early-onset neonatal sepsis incidence was high in this population / Doutorado / Tocoginecologia / Doutor em Tocoginecologia

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Tesis por compendio / [ES] El parto prematuro, definido como el nacimiento antes de las 37 semanas de gestación, es una importante preocupación mundial con implicaciones para la salud de los recién nacidos y los costes económicos. Afecta aproximadamente al 11% de todos los nacimientos, lo que supone más de 15 millones de individuos en todo el mundo. Los métodos actuales para predecir el parto prematuro carecen de precisión, lo que conduce a un sobrediagnóstico y a una viabilidad limitada en entornos clínicos. La electrohisterografía (EHG) ha surgido como una alternativa prometedora al proporcionar información relevante sobre la electrofisiología uterina. Sin embargo, los sistemas de predicción anteriores basados en EHG no se han trasladado de forma efectiva a la práctica clínica, debido principalmente a los sesgos en el manejo de datos desbalanceados y a la necesidad de modelos de predicción robustos y generalizables. Esta tesis doctoral pretende desarrollar un sistema de predicción del parto prematuro basado en inteligencia artificial utilizando EHG y datos obstétricos de mujeres sometidas a controles prenatales regulares. Este sistema implica la extracción de características relevantes, la optimización del subespacio de características y la evaluación de estrategias para abordar el reto de los datos desbalanceados para una predicción robusta. El estudio valida la eficacia de las características temporales, espectrales y no lineales para distinguir entre casos de parto prematuro y a término. Las nuevas medidas de entropía, en concreto la dispersión y la entropía de burbuja, superan a las métricas de entropía tradicionales en la identificación del parto prematuro. Además, el estudio trata de maximizar la información complementaria al tiempo que minimiza la redundancia y las características de ruido para optimizar el subespacio de características para una predicción precisa del parto prematuro mediante un algoritmo genético. Además, se ha confirmado la fuga de información entre el conjunto de datos de entrenamiento y el de prueba al generar muestras sintéticas antes de la partición de datos, lo que da lugar a una capacidad de generalización sobreestimada del sistema predictor. Estos resultados subrayan la importancia de particionar y después remuestrear para garantizar la independencia de los datos entre las muestras de entrenamiento y de prueba. Se propone combinar el algoritmo genético y el remuestreo en la misma iteración para hacer frente al desequilibrio en el aprendizaje de los datos mediante el enfoque de particio'n-remuestreo, logrando un área bajo la curva ROC del 94% y una precisión media del 84%. Además, el modelo demuestra un F1-score y una sensibilidad de aproximadamente el 80%, superando a los estudios existentes que consideran el enfoque de remuestreo después de particionar. Esto revela el potencial de un sistema de predicción de parto prematuro basado en EHG, permitiendo estrategias orientadas al paciente para mejorar la prevención del parto prematuro, el bienestar materno-fetal y la gestión óptima de los recursos hospitalarios. En general, esta tesis doctoral proporciona a los clínicos herramientas valiosas para la toma de decisiones en escenarios de riesgo materno-fetal de parto prematuro. Permite a los clínicos diseñar estrategias orientadas al paciente para mejorar la prevención y el manejo del parto prematuro. La metodología propuesta es prometedora para el desarrollo de un sistema integrado de predicción del parto prematuro que pueda mejorar la planificación del embarazo, optimizar la asignación de recursos y reducir el riesgo de parto prematuro. / [CA] El part prematur, definit com el naixement abans de les 37 setmanes de gestacio', e's una important preocupacio' mundial amb implicacions per a la salut dels nounats i els costos econo¿mics. Afecta aproximadament a l'11% de tots els naixements, la qual cosa suposa me's de 15 milions d'individus a tot el mo'n. Els me¿todes actuals per a predir el part prematur manquen de precisio', la qual cosa condueix a un sobrediagno¿stic i a una viabilitat limitada en entorns cl¿'nics. La electrohisterografia (EHG) ha sorgit com una alternativa prometedora en proporcionar informacio' rellevant sobre l'electrofisiologia uterina. No obstant aixo¿, els sistemes de prediccio' anteriors basats en EHG no s'han traslladat de manera efectiva a la pra¿ctica cl¿'nica, degut principalment als biaixos en el maneig de dades desequilibrades i a la necessitat de models de prediccio' robustos i generalitzables. Aquesta tesi doctoral prete'n desenvolupar un sistema de prediccio' del part prematur basat en intel·lige¿ncia artificial utilitzant EHG i dades obste¿triques de dones sotmeses a controls prenatals regulars. Aquest sistema implica l'extraccio' de caracter¿'stiques rellevants, l'optimitzacio' del subespai de caracter¿'stiques i l'avaluacio' d'estrate¿gies per a abordar el repte de les dades desequilibrades per a una prediccio' robusta. L'estudi valguda l'efica¿cia de les caracter¿'stiques temporals, espectrals i no lineals per a distingir entre casos de part prematur i a terme. Les noves mesures d'entropia, en concret la dispersio' i l'entropia de bambolla, superen a les me¿triques d'entropia tradicionals en la identificacio' del part prematur. A me's, l'estudi tracta de maximitzar la informacio' complementa¿ria al mateix temps que minimitza la redunda¿ncia i les caracter¿'stiques de soroll per a optimitzar el subespai de caracter¿'stiques per a una prediccio' precisa del part prematur mitjan¿cant un algorisme gene¿tic. A me's, hem confirmat la fugida d'informacio' entre el conjunt de dades d'entrenament i el de prova en generar mostres sinte¿tiques abans de la particio' de dades, la qual cosa dona lloc a una capacitat de generalitzacio' sobreestimada del sistema predictor. Aquests resultats subratllen la importa¿ncia de particionar i despre's remostrejar per a garantir la independe¿ncia de les dades entre les mostres d'entrenament i de prova. Proposem combinar l'algorisme gene¿tic i el remostreig en la mateixa iteracio' per a fer front al desequilibri en l'aprenentatge de les dades mitjan¿cant l'enfocament de particio'-remostrege, aconseguint una a¿rea sota la corba ROC del 94% i una precisio' mitjana del 84%. A me's, el model demostra una puntuacio' F1 i una sensibilitat d'aproximadament el 80%, superant als estudis existents que consideren l'enfocament de remostreig despre's de particionar. Aixo¿ revela el potencial d'un sistema de prediccio' de part prematur basat en EHG, permetent estrate¿gies orientades al pacient per a millorar la prevencio' del part prematur, el benestar matern-fetal i la gestio' o¿ptima dels recursos hospitalaris. En general, aquesta tesi doctoral proporciona als cl¿'nics eines valuoses per a la presa de decisions en escenaris de risc matern-fetal de part prematur. Permet als cl¿'nics dissenyar estrate¿gies orientades al pacient per a millorar la prevencio' i el maneig del part prematur. La metodologia proposada e's prometedora per al desenvolupament d'un sistema integrat de prediccio' del part prematur que puga millorar la planificacio' de l'embara¿s, optimitzar l'assignacio' de recursos i millorar la qualitat de l'atencio'. / [EN] Preterm delivery, defined as birth before 37 weeks of gestation, is a significant global concern with implications for the health of newborns and economic costs. It affects approximately 11% of all births, amounting to more than 15 million individuals worldwide. Current methods for predicting preterm labor lack precision, leading to overdiagnosis and limited practicality in clinical settings. Electrohysterography (EHG) has emerged as a promising alternative by providing relevant information about uterine electrophysiology. However, previous prediction systems based on EHG have not effectively translated into clinical practice, primarily due to biases in handling imbalanced data and the need for robust and generalizable prediction models. This doctoral thesis aims to develop an artificial intelligence based preterm labor prediction system using EHG and obstetric data from women undergoing regular prenatal check-ups. This system entails extracting relevant features, optimizing the feature subspace, and evaluating strategies to address the imbalanced data challenge for robust prediction. The study validates the effectiveness of temporal, spectral, and non-linear features in distinguishing between preterm and term labor cases. Novel entropy measures, namely dispersion and bubble entropy, outperform traditional entropy metrics in identifying preterm labor. Additionally, the study seeks to maximize complementary information while minimizing redundancy and noise features to optimize the feature subspace for accurate preterm delivery prediction by a genetic algorithm. Furthermore, we have confirmed leakage information between train and test data set when generating synthetic samples before data partitioning giving rise to an overestimated generalization capability of the predictor system. These results emphasize the importance of using partitioning-resampling techniques for ensuring data independence between train and test samples. We propose to combine genetic algorithm and resampling method at the same iteration to deal with imbalanced data learning using partition-resampling pipeline, achieving an Area Under the ROC Curve of 94% and Average Precision of 84%. Moreover, the model demonstrates an F1-score and recall of approximately 80%, outperforming existing studies on partition-resampling pipeline. This finding reveals the potential of an EHG-based preterm birth prediction system, enabling patient-oriented strategies for enhanced preterm labor prevention, maternal-fetal well-being, and optimal hospital resource management. Overall, this doctoral thesis provides clinicians with valuable tools for decision-making in preterm labor maternal-fetal risk scenarios. It enables clinicians to design a patient-oriented strategies for enhanced preterm birth prevention and management. The proposed methodology holds promise for the development of an integrated preterm birth prediction system that can enhance pregnancy planning, optimize resource allocation, and ultimately improve the outcomes for both mother and baby. / Nieto Del Amor, F. (2023). Design and assessment of a computer-assisted artificial intelligence system for predicting preterm labor in women attending regular check-ups. Emphasis in imbalance data learning technique [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/200900 / Compendio