BMC Pregnancy and Childbirth – Effect of early vitamin D supplementation on the incidence of preeclampsia in primigravid women: a randomised clinical trial in Eastern Democratic Republic of the Congo

Preeclampsia (PE) is a hypertensive disorder of pregnancy that affects around 5% of pregnant women globally and it can bring to preterm delivery, low birth weight and even to the death of the mothers and their newborns. The causes of preeclampsia are still largely unknown, however there has been progress in understanding the related pathophysiological mechanisms and risk factors. A series of studies have revealed how low vitamin D levels are associated with preeclampsia, although only few studies have been conducted to determine the benefits of maternal–fetal vitamin D supplementation.

In this multicenter, single-blind, randomized controlled trial, the authors evaluated the effect of vitamin D supplementation administered in early pregnancy on the incidence of PE in 1159 primigravidae in fourteen antenatal care health facilities in the Democratic Republic of Congo, along with the evaluation of adverse maternal-fetal-neonatal outcomes, such as preterm delivery, birth weight and height, mode of delivery, and APGAR score. The intervention group received a single monthly dose of cholecalciferol (60,000 IU) orally for 6 months, while the control group received no vitamin D supplementation or placebo.

The findings showed a significant reduction in the risk of preeclampsia, preterm and caesarean delivery in the intervention group, with newborns showing a higher APGAR score at the 5th minute in comparison to the control group. This study highlights the importance of monitoring the blood level of vitamins D throughout the pregnancy in the context of antenatal care, to reduce the maternal-fetal morbidity and mortality risks related to PE.

BMC Health Services Research – A cost-effectiveness analysis of a universal, preventative-focused, parent and infant programme

Parenting support groups through dedicated programmes can enhance parenting skills and parent-child relationships, reducing the risks of inadequate care and abuse. Parents with babies are the best target for these kind of interventions as the earliest childhood years have a critical influence on child development and are responsible for the well-being outcomes in adulthood.

This study explored the cost-effectiveness of a universal early parenting intervention called the Parent and Infant (PIN) programme in an Irish setting when compared to the services as usual (SAU). The PIN was represented by 15 sessions consisting of 106 parent-infant dyads that participated in a series of workshops with the aim to enhance parent knowledge and skills. The SAU group was represented by 84 parent-infant dyads that receive the usual care provided by their local health service. The primary outcome measure for the economic evaluation was the Parenting Sense of Competence Scale (PSOC).

The authors found that the parents in the PIN programme had positive outcomes in terms of parenting attitudes and that the PIN programme was cost-effective at a relatively low willingness-to-pay threshold when compared to SAU. The average cost of the PIN program was € 647 per dyad. This study provides important information for practitioners and policy makers and promote the debate on the importance of preventative parenting interventions.

BMC Primary Care – Project nature: promoting outdoor physical activity in children via primary care

In children of all ages, time spent outdoor is associated with an increase of physical activity (PA) and an improvement of physical, mental, and cognitive health. Family circumstances, environmental constraints and behavioral factors, are some of the barriers that parents meet when they try to support their children’s outdoor play.

This study described a primary care-based family-centered behavioral intervention named Project Nature (PN), aimed to promote active outdoor play in children. The first phase, “adaptation needs assessment” was used to understand barriers and facilitators to outdoor play and it was based on qualitative interviews and focus groups with 14 parents with children ages 3-10, and 14 pediatric providers. The second phase, “usability testing”, was used to adapt the existing PN toolkits for children ages 0-3, for older children and it was based on qualitative interviews for 20 parents and 5 clinical staff. The third phase, “pilot evaluation”, evaluated the preliminary efficacy of the adapted PN for older children, using pre-post quantitative surveys and qualitative interviews, and included 26 parents of children ages 4-10 years, and 4 pediatric providers.

Both providers and parents found that nature toys and brochure help children and parents to spend more time outdoors. This study highlighted the role of pediatric providers in encouraging outdoor play and the importance to have more policies to increase the number and the quality of the green spaces.

BMC Infectious Diseases – Enhancing detection of SARS-CoV-2 re-infections using longitudinal sero-monitoring: demonstration of a methodology in a cohort of people experiencing homelessness in Toronto, Canada

Polymerase chain reaction (PCR) testing is the most common technique used to estimate SARS-CoV-2 re-infectious, however the use of this approach solely can bring to an undercount of cases mostly due to testing availability, undermining the confidence in the re-infection rates.

In this longitudinal study the authors used data from a cohort study of 736 individuals experiencing homelessness in Toronto, Canada, between June and September 2021. This population was characterized by a higher COVID-19 infection burden when compared to housed counterparts and was prioritized for COVID-19 vaccination. The participants provided saliva and blood samples every three months. The samples were used respectively for PCR testing or Rapid antigen test (RAT) to test for current SARS-CoV-2 infection and for a plate-based enzyme-linked immunosorbent assay to test past SARS-CoV-2 infection/vaccination.

The combined approach with serology and testing data, defined as the comprehensive method, allowed to identify 37.4 re-infection events per 100 person-years, more than four-fold higher than the rate from test-only methods. Considering the short- and long-term health effects of multiple infections, accurate monitoring of re-infection is crucial. The findings of the study showed how the used of comprehensive method is a valuable approach to conduct effective public health surveillance pertinent to SARS-CoV-2 re-infectious.

BMC Medical Informatics and Decision Making – Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare

Machine-learning approach using Electronic Health Records (EHRs) has been implemented into routine care and it is now broadly used for patient classification and laboratory measurements, for predicting future hospitalization and in general to build models for their use in research and clinical practice. Diagnostic codes are used to generate clinical prediction models, however there is variability among institutions as each of them use different coding processes and clinical diagnostic practices.

This study addressed the challenge to create a gold standard labeling process for diagnostic codes that can be used across institutions. The authors selected three cohorts, SickKids from The Hospital for Sick Children, and StanfordPeds and StanfordAdults from Stanford Medicine, and they considered seven clinical outcomes for which they created four lab-based labels based on test result and one diagnosis-based label. The five labels were evaluated in each patient admission, with a proportion of admissions with a positive diagnosis-based label significantly higher for StanfordPeds compared to SickKids across all outcomes.

The findings highlight how as results of different diagnostic codes, two children with the same test results can be considered differently at two pediatric institutions, based on the different categorization and labeling of the tests. Although machine learning has the potential to improve the quality of clinical research, clinical institutions should work together to implement uniformed machine learning models.