Background <p>Clustering of outcomes occurs naturally in neonatal data due to multiple births clustered by mother and infants clustered within the neonatal unit administering their care. Estimating these cluster effects is important for neonatal study design and impacts upon sample sizes for neonatal trials.</p> Methods <p>We analysed retrospective data from all neonatal admissions in England and Wales between January 2016 and January 2020 held in the National Neonatal Research Database. Intracluster correlation coefficients (ICCs) and their 95% confidence intervals were calculated for core neonatal outcomes and those commonly used in trials, at the level of both the neonatal unit and mother. Results were stratified by gestational age and neonatal unit level of birth. To illustrate the impact of clustering, the design effect was estimated for a theoretical cluster trial.</p> Results <p>Intracluster correlation coefficients varied between outcomes and gestational age groups. Neonatal unit level intracluster correlation coefficients were low for mortality (0.0054, 95% CI 0.0039, 0.0068) and other core outcomes (severe necrotising enterocolitis 0.0042, 95% CI 0.0020, 0.0063) and were higher for outcomes related to care delivery (duration of intensive care 0.0237, 95% CI 0.0177, 0.0298; duration receiving parenteral nutrition 0.0265, 95% CI 0.0197, 0.0332). Gestation at birth was inversely correlated with neonatal unit ICC estimates. At the level of the mother, ICC estimates were generally larger, especially for preterm infants.</p> Conclusions <p>We have estimated ICCs for key neonatal outcomes at the level of both neonatal unit and mother with high precision using national, population-level routinely recorded data. These ICC estimates can be used to inform future neonatal studies and sample size calculations for neonatal trials.</p>

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Intracluster correlation coefficients for neonatal trials: an analysis of national population level clinical data

  • S. Jawad,
  • A. T. Prevost,
  • C. Gale

摘要

Background

Clustering of outcomes occurs naturally in neonatal data due to multiple births clustered by mother and infants clustered within the neonatal unit administering their care. Estimating these cluster effects is important for neonatal study design and impacts upon sample sizes for neonatal trials.

Methods

We analysed retrospective data from all neonatal admissions in England and Wales between January 2016 and January 2020 held in the National Neonatal Research Database. Intracluster correlation coefficients (ICCs) and their 95% confidence intervals were calculated for core neonatal outcomes and those commonly used in trials, at the level of both the neonatal unit and mother. Results were stratified by gestational age and neonatal unit level of birth. To illustrate the impact of clustering, the design effect was estimated for a theoretical cluster trial.

Results

Intracluster correlation coefficients varied between outcomes and gestational age groups. Neonatal unit level intracluster correlation coefficients were low for mortality (0.0054, 95% CI 0.0039, 0.0068) and other core outcomes (severe necrotising enterocolitis 0.0042, 95% CI 0.0020, 0.0063) and were higher for outcomes related to care delivery (duration of intensive care 0.0237, 95% CI 0.0177, 0.0298; duration receiving parenteral nutrition 0.0265, 95% CI 0.0197, 0.0332). Gestation at birth was inversely correlated with neonatal unit ICC estimates. At the level of the mother, ICC estimates were generally larger, especially for preterm infants.

Conclusions

We have estimated ICCs for key neonatal outcomes at the level of both neonatal unit and mother with high precision using national, population-level routinely recorded data. These ICC estimates can be used to inform future neonatal studies and sample size calculations for neonatal trials.