An overview of international literature from cystic fibrosis registries: 2. Neonatal screening and nutrition/growth
Received 7 July 2009; received in revised form 1 October 2009; accepted 5 November 2009.
Abstract
Background
This is the second article related to a review of the literature based on data from national cystic fibrosis (CF) registries up to June 2008 and covering a total of 115 studies. It focuses on two topics: neonatal screening (NS) and nutritional status, with particular reference to growth.
Methods
Ten papers meeting the inclusion criteria were found on the topic of NS and its impact on the course of the disease, and were analyzed according to a dedicated grid. The issue of nutrition was addressed by 14 studies, analyzed according to similar criteria.
Results
Most of the studies report benefits of early diagnosis by NS, albeit to variable degrees. The benefits were assessed in terms of better nutritional status and growth, but also in terms of lower overall morbidity rate as compared to subjects diagnosed by symptoms. The main biases of these studies, which partly undermine the validity of their results, are also analyzed.
A part of our analysis on nutrition/growth is dedicated to the identification of the most suitable parameters to define malnutrition: in children older than two years the body mass index percentile (BMIp) appears to be the most sensitive and significantly associated with respiratory function. Better nutritional status and satisfactory growth appear to be associated with better lung function and lower risk of death. The relationship between nutritional status and socio-economic status is also of interest.
Conclusions
CF registry studies support the outcome of cohort observational studies i.e. that pre-symptomatic early diagnosis is beneficial, especially in terms of nutritional status and growth. Studies on nutrition indicate that good nutritional status is associated with better respiratory function and prognosis. Regarding methods, the need emerged to manage potential biases of this kind of non randomized studies, resorting to suitable statistical techniques, such as matching and stratification and, above all, to multivariate methods able to provide estimates adjusted for the main covariates tested.
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