Does the choice of bottle nipple affect the oral feeding performance of very-low-birthweight (VLBW) infants?

BACKGROUND: There is a continuous debate regarding the best bottle nipple to be used to enhance the bottle-feeding performance of a preterm infant. Aim: To verify that feeding performance can be improved by using the bottle nipple with the physical characteristics that enhance infants' sucking skills. METHODS: Ten "healthy" VLBW infants (941+/-273 g) were recruited. Feeding performance was monitored at two time periods, when taking 1-2 and 6-8 oral feedings/d. At each time and within 24 h, performance was monitored using three different bottle nipples offered in a randomized order. Rate of milk transfer (ml/min) was the primary outcome measure. The sucking skills monitored comprised stage of sucking, suction amplitude, and duration of the generated negative intraoral suction pressure. RESULTS: At both times, infants demonstrated a similar rate of milk transfer among all three nipples. However, the stage of sucking, suction amplitude, and duration of the generated suction were significantly different between nipples at 1-2, but not 6-8 oral feedings/d.CONCLUSION: We did not identify a particular bottle nipple that enhanced bottle feeding in healthy VLBW infants. Based on the notion that afferent sensory feedback may allow infants to adapt to changing conditions, we speculate that infants can modify their sucking skills in order to maintain a rate of milk transfer that is appropriate with the level of suck-swallow-breathe coordination achieved at a particular time. Therefore, it is proposed that caretakers should be more concerned over monitoring the coordination of suck-swallow-breathe than over the selection of bottle nipples.

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^