Laboratory reference intervals in the assessment of iron status in young children
Patricia C Parkin1,2,3,4, Jemila Hamid5, Cornelia M Borkhoff1,2,3,4
1Division of Pediatric Medicine and the Pediatric Outcomes Research Team (PORT), Hospital for Sick Children, Toronto, Ontario, Canada.
Insights
New reference intervals for pediatric iron status tests were established. Current guidelines may misclassify about 10% of young children, potentially underestimating iron deficiency.
Area of Science:
- Pediatric laboratory medicine
- Clinical chemistry
- Nutritional science
Background:
- Accurate iron status assessment in children is crucial for growth and development.
- Existing reference intervals may not reflect current pediatric populations.
- Clinical and Laboratory Standards Institute (CLSI) guidelines provide a framework for establishing reliable reference intervals.
Purpose of the Study:
- To establish pediatric reference intervals for iron status laboratory tests following CLSI guidelines.
- To compare the established reference intervals with current cut-off values for hemoglobin and serum ferritin in children aged 1-3 years.
Main Methods:
- Analysis of blood samples from 4334 healthy children (10 days to 10.6 years).
- Application of CLSI guidelines, including outlier removal, age partitioning, and statistical analysis (ANOVA).
- Calculation of age- and sex-specific reference intervals and 90% confidence intervals (CIs).
Main Results:
- Established age- and sex-specific reference intervals for multiple iron status biomarkers.
- Identified statistically significant differences between adjacent age partitions for most analytes.
- Found that approximately 10% of children aged 1-3 years were misclassified (underestimated) when using the new lower reference limits compared to existing cut-off values for hemoglobin and serum ferritin.
Conclusions:
- Clinical laboratories should consider adopting these updated pediatric reference intervals.
- Current cut-off values may lead to underestimation of iron deficiency in young children.
- Further research is needed to establish clinical outcome-based decision limits for iron status.
Objectives:
The primary objective was to establish reference intervals for laboratory tests used to assess iron status in young children using the Clinical and Laboratory Standards Institute guidelines. A secondary objective was to compare the lower limit of the reference interval with the currently recommended cut-off value for haemoglobin and serum ferritin in children 1-3 years of age.
Methods:
Blood samples were obtained from healthy children recruited during scheduled health supervision visits with their primary care physician. For our primary objective, outliers were removed; age partitions were selected and analysis of variance and pairwise comparisons were made between adjacent partitions; reference intervals and 90% CIs were calculated. For our secondary objective, we determined the proportion of children misclassified using the lower limit reference interval compared with the cut-off value.
Results:
Samples from 2305 male and 2029 female participants (10 days to 10.6 years) were used to calculate age and sex-specific reference intervals for laboratory tests of iron status. There were statistically significant differences between adjacent age partitions for most analytes. Approximately 10% of children 1-3 years of age were misclassified (underestimated) using the lower limit of the reference intervals rather than the currently recommended cut-off values for haemoglobin and serum ferritin.
Implications And Relevance:
Clinical laboratories may consider adopting published paediatric reference intervals. Reference intervals may misclassify (underestimate) children with iron deficiency as compared with currently recommended cut-off values. Future research on decision limits derived from clinical studies of outcomes is a priority.
More Related Videos
Related Concept Videos
01:03Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
01:21Confidence Intervals
A...
01:03Inertial Frames of Reference
01:27Non-inertial Frames of Reference
01:29Improper Integrals: Infinite Intervals
00:55Interval Level of Measurement
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...