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Simulated growth data will be shown to clinicians in two formats - (1) as weight vs.age charts, (2) as weight Z-score vs. age charts. Clinicians will be asked to identify whether growth is too fast, too slow, or normal. The test will take a total of 10 minutes.
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BACKGROUND Optimization of growth is essential for preterm infants. Optimum post-natal growth has been shown to improve long-term developmental outcomes. Close monitoring of weight gain, including early identification of growth faltering, is an important part of appropriate nutritional management in the Neonatal Intensive Care Unit.
Current practices in neonatal intensive care units involve the routine use of growth charts to track and identify patterns in the growth of preterm infants. Perhaps the most popular growth chart in use today is the Fenton Growth Chart. To interpret this chart, a patient's growth curve is plotted over a set of standard curves (typically representing the 10th, 25th, 50th, 75th and 90th weight-for-age centile). The curves are then visually compared to identify patterns in growth (adequate, slow, or catch-up growth). Patterns in neonatal growth may be subtle and current growth curves may be prone to misinterpretation. This may be due to biases inherent in the human visual perception system, including the difficulty in visually estimating slopes and angles between two curves.
An improved growth chart would use horizontal lines rather than curves, and would have no oblique lines to skew visual perception. Z-score growth charts accomplish this. Z-score growth charts are created using the same standardized data used to create the Fenton Growth Chart. Z-scores represent standard deviation scores. Rather than using a set of standard curves to represent average healthy growth, the z-score chart uses a single horizontal line. This allows for easier comparison when plotting a patient's weights over time. Such charts may lead to more accurate interpretation of overall growth patterns.
This study will compares the accuracy of interpretation of the growth data using the same standard - once as presented using traditional weight-vs.-age charts, and again using the same data displayed as Z-score vs age charts.
INCLUSION AND EXCLUSION CRITERIA
It will include UC Davis Medical Center healthcare personnel who interpret growth charts for preterm infants. This may include the following:
NUMBER OF SUBJECTS This will be a single center study. The sample size needed for 80% power with an alpha of 0.05 is estimated to be at least 40. Approaching 45-50 providers should be sufficient to achieve this number.
RECRUITMENT METHODS Healthcare providers who meet the inclusion criteria will be approached on an individual and/or group basis. We may attempt to hold a meeting (perhaps at lunch time) when volunteers may participate in the study.
COMPENSATION TO SUBJECTS If there is a meeting held at lunchtime for volunteers to participate in this study, there may be a small lunch provided (such as sandwiches, pizza and/or soft drinks). When subjects are approached on an individual basis, there will be no compensation offered.
STUDY TIMELINES
STUDY ENDPOINTS Primary endpoint: after 40-50 persons have completed the study. Primary or secondary safety endpoints: there are no foreseeable safety issues with participating in this questionnaire based study.
PROCEDURES INVOLVED
Study design:
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Inclusion criteria
It will include UC Davis Medical Center healthcare personnel who interpret growth charts for preterm infants. This may include the following:
Exclusion criteria
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Data sourced from clinicaltrials.gov
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