Weight a minute: The smaller and more immature, the more predictable the autonomic regulation?

Aim: To investigate the relation between autonomic regulation, measured using heart rate variability (HRV), body weight and degree of prematurity in infants. Further to assess utility to include body weight in a machine learning-based sepsis prediction algorithm.

Methods: Longitudinal cohort study including 378 infants hospitalised in two neonatal intensive care units.

Vital sign-based detection of sepsis in neonates using machine learning.

Aim: Sepsis is a leading cause of morbidity and mortality in neonates. Early diagnosis is key but difficult due to non-specific signs. We investigate the predictive value of machine learning-assisted analysis of non-invasive, high frequency monitoring data and demographic factors to detect neonatal sepsis.

Midwives' experiences of working conditions, perceptions of professional role and attitudes towards mothers in Mozambique.

Background: low- and middle-income countries still have a long way to go to reach the fifth Millennium Development Goal of reducing maternal mortality. Mozambique has accomplished a reduction of maternal mortality since the 1990s, but still has among the highest in the world. A key strategy in reducing maternal mortality is to invest in midwifery.