Mortality of twins and singletons

Mortality of Twins and Singletons Yin Bun Cheung, Ph.D. Paul Yip, Ph.D. Johan Karlberg, M.D., Ph.D. Readings Objectives: mortality patterns • Understand the patterns of gestational age-specific neonatal mortality in twins and singletons. • Appreciate the (non-) comparability between twins and singletons. Objectives: statistical models • Learn a flexible way to handle interaction / effectmodification. • Interpretation of a (logistic) regression model in different ways. Mortality by gestational age • Does the mortality difference between twins & singletons depend on gestational age? • Do twins and singletons have the same gestational age pattern of mortality? Difficulties in research • Sample size • Referral bias • Statistical adjustment / matching A study based on Swedish Medical Birth Registry • All births born in Sweden in 1982-1995. • Includes 32,942 twins and 1.5 million singletons. • Details in Reading 1. Cumulative distribution of GA 100 . 75 Percent 50 25 0 24 26 28 30 32 34 36 38 40 42 Singletons Twins Gestational age (weeks) Odds ratios of short GA in twins and singletons Risk factors Mother smoke Prior still-birth Twins Singletons 1.16* 1.39* 0.87 1.57* P=0.14 Goodness-of-fit P=0.08 * P<0.05 Varying-coefficient model Mortality impact of twin pregnancy as a function of GA: Log odds=a1+b1GA+b2GA2+ 2)Twin+... (a2+c1GA+c2GA Varying-coefficient model As a model of separate curves: Log odds in singletons: 2 a1+b1GA+b2GA Log odds in twins: (a1+a2)+(b1+c1)GA+(b2+c2)GA2 Birth weight SDS by GA 3 2 1 0 -1 -2 -3 28 30 32 34 36 38 40 42 Mean SDS Singletons Twins Gestational age (weeks) Size at birth in twins Growth restriction in twins concentrates in late pregnancy. •Physical constraints in utero? •Limited placental function? •Selection bias? Neonatal deaths per 1000 200 180 160 140 120 100 80 60 40 20 0 28 30 32 34 36 38 40 42 Neonatal death Singletons Twins Gestational age (weeks) A varying-coefficient logistic regression model • The impact of twin pregnancy as a quadratic function of GA. • Adjusted for confounders, e.g. prior still-birth, smoking. • With & without adjustment for size at birth. Log OR, fully adjusted 5 4 3 2 1 0 -1 -2 28 30 32 34 36 38 40 42 Log odds ratio Gestational age (weeks) Log odds, fully adjusted 4 Log odds 2 0 -2 -4 -6 28 30 32 34 36 38 40 Singletons Twins 42 Gestational age (weeks) Is twin birth hazardous? Why? • Twins had lower odds of death prior to 36 weeks of GA; higher odds thereafter. • Longer GA was related to lower mortality. But the decline was sharper in singletons than in twins. Log OR, not adjusted for size at birth 5 4 3 2 1 0 -1 -2 28 30 32 34 36 38 40 42 Log odds ratio Gestational age (weeks) Log odds, not adjusted for size at birth 4 Log odds 2 0 -2 -4 -6 28 30 32 34 36 38 40 Singletons Twins 42 Gestational age (weeks) The role of fetal growth and size at birth? • Without adjustment for size at birth the log OR climbed up faster after around 34 weeks. • Twins’ mortality reached it’s lowest point at 38 weeks; it turned upward after that. Clinical interpretations • Twins have an earlier development • In utero environment in late pregnancy not good for twins • Residual confounding Optimal GA for twins The optimal gestational age for twins appeared to be 37-39 weeks in terms of neonatal mortality. This is earlier than singletons’. Readings 1 Cheung YB, Yip P, Karlberg J. Mortality of twins and singletons by gestational age. Am J Epidemiol 2000;152:1107-16. 2 Lie RT. Intersecting perinatal mortality curves by gestational age -- are appearances deceiving? Am J Epidemiol 2000;152:1117-19. 3 Cheung YB, Yip P, Karlberg J. Respond to “Are appearances deceiving”. Am J Epidemiol 2000;152:1120.