Metabolic gestational age assessment in low resource settings: a validation protocol.

Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited.

Predicting post-discharge death or readmission: deterioration of model performance in population having multiple admissions per patient.

Background: To avoid biased estimates of standard errors in regression models, statisticians commonly limit the analytical dataset to one observation per patient.

Objective: Measure and explain changes in model performance when a model predicting 30-day risk of death or urgent readmission (derived on a dataset having one hospitalization per patient) was applied to all hospitalizations for study patients.

Methods: Using administrative data from Ontario, we identified all hospitalizations of 499,996 patients between 2004 and 2009.