Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis.

Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for...

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Publicado en:Maternal & Child Health Journal Vol. 20; no. 9; pp. 1895 - 1904
Autores principales: Fernández, Leónides, Mediano, Pilar, García, Ricardo, Rodríguez, Juan, Marín, María
Formato: algorithm research tables/charts Journal Article
Publicado: Springer Nature Sep2016
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10995-016-2000-6
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        atl: Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis.
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        au:
          Fernández, Leónides
          Mediano, Pilar
          García, Ricardo
          Rodríguez, Juan
          Marín, María
        affil: Departamento de Nutrición, Bromatología y Tecnología de los Alimentos , Universidad Complutense de Madrid , Ciudad Universitaria, Avda. Puerta de Hierro, s/n 28040 Madrid Spain
      sug:
        subj:
          Mastitis Risk Factors
          Decision Trees Utilization
          Lactation
          Human
          Logistic Regression
          Female
          Pregnancy
          Step-Wise Multiple Regression
          Breast Feeding
          Questionnaires
          ROC Curve
          Sensitivity and Specificity
          Bivariate Statistics
          Multivariate Analysis
          Spain
          Chi Square Test
          Odds Ratio
          Confidence Intervals
          Data Analysis Software
          Case Control Studies
          Retrospective Design
          Bias (Research)
          Funding Source
          Female
      ab: Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for predicting this condition with a stepwise logistic regression (LR) model. Methods Data from 368 cases (breastfeeding women with mastitis) and 148 controls were collected by a questionnaire about risk factors related to medical history of mother and infant, pregnancy, delivery, postpartum, and breastfeeding practices. The performance of the DT and LR analyses was compared using the area under the receiver operating characteristic (ROC) curve. Sensitivity, specificity and accuracy of both models were calculated. Results Cracked nipples, antibiotics and antifungal drugs during breastfeeding, infant age, breast pumps, familial history of mastitis and throat infection were significant risk factors associated with mastitis in both analyses. Bottle-feeding and milk supply were related to mastitis for certain subgroups in the DT model. The areas under the ROC curves were similar for LR and DT models (0.870 and 0.835, respectively). The LR model had better classification accuracy and sensitivity than the DT model, but the last one presented better specificity at the optimal threshold of each curve. Conclusions The DT and LR models constitute useful and complementary analytical tools to assess the risk of lactational infectious mastitis. The DT approach identifies high-risk subpopulations that need specific mastitis prevention programs and, therefore, it could be used to make the most of public health resources.
      pubtype: Academic Journal
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        research
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      ougenre: Article
    language: English
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