Mostrando entradas con la etiqueta infants. Mostrar todas las entradas
Mostrando entradas con la etiqueta infants. Mostrar todas las entradas

29.3.14

Clinical guidelines for postpartum women and infants in primary care: a systematic review.

Haran C, van Driel M, Mitchell BL, Brodribb WE(1).

BACKGROUND: While many women and infants have an uneventful course during the postpartum period, others experience significant morbidity. Effective postpartum care in the community can prevent short, medium and long-term consequences of unrecognised and poorly managed problems. The use of rigorously developed, evidence-based guidelines has the potential to improve patient care, impact on policy and ensure consistency of care across health sectors. This study aims to compare the scope and content, and assess the quality of clinical guidelines about routine postpartum care in primary care.
METHODS: PubMed, the National Guideline Clearing House, Google, Google Scholar and relevant college websites were searched for relevant guidelines. All guidelines regarding routine postpartum care published in English between 2002 and 2012 were considered and screened using explicit selection criteria. The scope and recommendations contained in the guidelines were compared and the quality of the guidelines was independently assessed by two authors using the AGREE II instrument.
RESULTS: Six guidelines from Australia (2), the United Kingdom (UK) (3) and the United States of America (USA) (1), were included. The scope of the guidelines varied greatly. However, guideline recommendations were generally consistent except for the use of the Edinburgh Postnatal Depression Scale for mood disorder screening and the suggested time of routine visits. Some recommendations lacked evidence to support them, and levels or grades of evidence varied between guidelines. The quality of most guidelines was adequate. Of the six AGREE II domains, applicability and editorial independence scored the lowest, and scope, purpose and clarity of presentation scored the highest.

CONCLUSIONS: Only one guideline provided comprehensive recommendations for the care of postpartum women and their infants. As well as considering the need for region specific guidelines, further research is needed to strengthen the evidence supporting recommendations made within guidelines. Further improvement in the editorial independence and applicability domains of the AGREE ll criteria would strengthen the quality of the guidelines.

28.8.13

Estimating overweight risk in childhood from predictors during infancy.

Pediatrics. 2013 Aug;132(2):e414-21. doi: 10.1542/peds.2012-3858.Epub 2013Jul15.
Weng SF, Redsell SA, Nathan D, Swift JA, Yang M, Glazebrook C.

OBJECTIVE: The aim of this study was to develop and validate a risk score
algorithm for childhood overweight based on a prediction model in infants.
METHODS: Analysis was conducted by using the UK Millennium Cohort Study. The
cohort was divided randomly by using 80% of the sample for derivation of the risk
algorithm and 20% of the sample for validation. Stepwise logistic regression
determined a prediction model for childhood overweight at 3 years defined by the 
International Obesity Task Force criteria. Predictive metrics R(2), area under
the receiver operating curve (AUROC), sensitivity, specificity, positive
predictive value (PPV), and negative predictive value (NPV) were calculated.
RESULTS: Seven predictors were found to be significantly associated with
overweight at 3 years in a mutually adjusted predictor model: gender, birth
weight, weight gain, maternal prepregnancy BMI, paternal BMI, maternal smoking in
pregnancy, and breastfeeding status. Risk scores ranged from 0 to 59
corresponding to a predicted risk from 4.1% to 73.8%. The model revealed
moderately good predictive ability in both the derivation cohort (R(2) = 0.92,
AUROC = 0.721, sensitivity = 0.699, specificity = 0.679, PPV = 38%, NPV = 87%)
and validation cohort (R(2) = 0.84, AUROC = 0.755, sensitivity = 0.769,
specificity = 0.665, PPV = 37%, NPV = 89%).
CONCLUSIONS: Using a prediction algorithm to identify at-risk infants could
reduce levels of child overweight and obesity by enabling health professionals to
target prevention more effectively. Further research needs to evaluate the
clinical validity, feasibility, and acceptability of communicating this risk.