Digit Ratio (2D:4D) in Newborns: Influences of Prenatal Testosterone and Maternal Environment

Introduction: The 2D:4D digit ratio is sexually-dimorphic, probably due to testosterone action through the perinatal period. We characterize the 2D:4D ratio in newborn (NB) infants, in between the pre- and postnatal surges of testosterone, and relate it to the mother's 2D:4D and to testosterone levels in the amniotic fluid (AF). Subjects and methods: Testosterone was assayed in samples of maternal plasma and AF collected at amniocentesis. Shortly after birth, 106 NBs and their mothers were measured for 2D:4D ratio. Results: NB males had lower mean 2D:4D ratios than females but this dimorphism was significant only for the left hand (males: 0.927; females: 0.950; p=0.004). Mothers who had sons had lower 2D:4D ratios than those who had daughters and the mother's 2D:4D were higher than those of NBs regardless of sex. Both hands of NB females were negatively correlated with AF testosterone and positively correlated with the mother's 2D:4D, but males showed no significant associations. Maternal plasma testosterone also showed a negative weak correlation with NB's digit ratio in both sexes. Conclusions: Sexual dimorphism at birth was only significant for the left hand, in contrast with reports of greater right hand dimorphism, suggesting that postnatal testosterone is determinant for 2D:4D stabilization. The lower 2D:4D ratios in mothers who had sons support claims that hormone levels in parents are influential for determining their children's sex. NB female's digit ratio, but not males', was associated to the level of AF testosterone. The mother's 2D:4D ratios were positively correlated with their daughters' 2D:4D, but the same was not observed for male NBs, suggesting that prenatal testosterone levels in male fetus lead their 2D:4D ratios to stray from their mothers' with high individual variability.

Modeling in-Hospital Patient Survival During the First 28 Days After Intensive Care Unit Admission: a Prognostic Model for Clinical Trials in General Critically Ill Patients

OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.