Hastane dışı doğumlar: Bir olgu-kontrol çalışması
Amaç: Planlanmamış hastane dışı doğumlarla ilişkili etmenleri, riskleri ve mortaliteyi belirlemek.Gereç ve Yöntemler: Bu gözlemsel, geriye dönük, olgu-kontrol çalışması, 2005 ile 2013 yılları arasında Brezilya’nın bir ilinin hastane ağının tıbbi kayıtlarının incelenmesi yolu ile yürütülmüştür. Anne-çocukçiftleri hastane içi doğumlar ve planlanmamış hastane dışı doğumlarşeklinde iki gruba ayrılmıştır. Kantitatif değişkenler içeren hipoteztesti için Kolmogorov-Smirnov ya da Shapiro-Wilk testleri vasıtasıile dağılımın normalliği belirlendikten sonra, uygun olduğu şekildeparametrik ve nonparametrik yöntemler (sırası ile, t-testi ya da MannWhitney testi) kullanılmıştır. Katergorik değişkenler arasındaki ilişkiyi değerlendirmek için ki-kare test, Fisher’ın kesin testi, risk oranları,ve %95 güvenlik aralıkları kullanılmıştır. Tek başına çözümlendiklerinde hipotez testinde anlamlı p değerleri olan değişkenlerin topluanalizi için ikili lojistik regresyon uygulanmıştır. Bütün testlerde, p
Out-of-hospital deliveries: A case-control study
Aim: To identify the factors, risks, and mortality associated with unplanned out-of-hospital births. Material and Methods: This observational, retrospective, case-control study was conducted between 2005 and 2013 through a review of medical records from the hospital network of a county of Brazil. Mother-child dyads were divided into in-hospital births and unplanned out-of-hospital births. For hypothesis testing involving quantitative variables, parametric and nonparametric methods (t-test or Mann–Whitney test, respectively) were used as appropriate after ascertaining normality of distribution via the Kolmogorov-Smirnov or Shapiro-Wilk tests. The chi-square test, Fisher’s exact test, odds ratios, and 95% confidence intervals were used to assess the relationship between categorical variables. A binary logistic regression was applied for pooled analysis of those variables that, when analyzed in isolation, had significant p-values on hypothesis testing. In all tests, p-values
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