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Related Concept Videos

Interval Level of Measurement00:55

Interval Level of Measurement

For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
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 the...
Pharmacokinetics in Geriatric Patients: Effect of Age on Drug Distribution01:00

Pharmacokinetics in Geriatric Patients: Effect of Age on Drug Distribution

Drug distribution in the human body is influenced by several factors, including plasma protein concentration, body composition, blood flow, tissue-protein concentration, and tissue fluid pH. Among these, changes in plasma protein concentration and body composition due to aging significantly affect how drugs are distributed within the body. Specifically, aging is associated with a decrease in albumin levels by about 10% and an increase in α1-acid glycoprotein levels. These alterations are not...
Two-Way ANOVA01:17

Two-Way ANOVA

The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
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Confidence Interval for Estimating Population Mean01:25

Confidence Interval for Estimating Population Mean

A point estimate of the population mean is obtained from a single sample. Such a point estimate does not represent a population well because it needs to account for variability in the population. Single point estimate can also be biased despite the sample being selected randomly. Thus, a point estimate is often unreliable. A confidence interval is needed to reduce this unreliability.
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
Confidence Intervals01:21

Confidence Intervals

An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A confidence...
The Ratio of X Chromosome to Autosomes02:45

The Ratio of X Chromosome to Autosomes

In most organisms, sex is determined by the ratio of X and Y chromosomes. However, in some organisms, such as Drosophila and C.elegans, sex is determined by the ratio of the number of X chromosomes to the number of sets of autosomes. The Y chromosome in Drosophila is active but does not determine sex. It contains genes responsible for the production of sperms in adult flies.  
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[Setting reference intervals without considering sex and age differences].

Takashi Kanno1, Yoichi Ohgushi, Takeo Shibata

  • 1Hamamatsu Foundation of Medical Center, Hamamatsu.

Rinsho Byori. the Japanese Journal of Clinical Pathology
|August 20, 2008
PubMed
Summary

Comparing laboratory reference intervals from two large populations revealed close agreement for many analytes. However, enzyme analytes showed partial correspondence, highlighting the need for precise sex- and age-specific reference intervals in health screening.

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Area of Science:

  • Clinical Chemistry
  • Biostatistics
  • Laboratory Medicine

Context:

  • Reference intervals are crucial for interpreting laboratory test results in health screening.
  • Two distinct large-scale reference populations were utilized for comparison.
  • Established statistical methods, including nonlinear optimizing and revised Hoffmann fitting, were employed to derive reference intervals.

Purpose:

  • To compare sex- and age-specific reference intervals for ten common laboratory analytes derived from two large, independent reference populations.
  • To identify analytes with consistent or discrepant reference intervals between the two populations.
  • To assess the clinical implications of using different reference intervals, particularly for enzyme analytes.

Summary:

  • Comparison of sex- and age-specific reference intervals for ten laboratory analytes showed close agreement for metabolic analytes (total cholesterol, fasting blood sugar, uric acid, total protein, albumin) between two large reference populations.
  • Enzyme analytes (aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, gamma-glutamyl transpeptidase) exhibited only partial correspondence in their reference intervals.
  • Significant age- and sex-related differences were observed for alkaline phosphatase, with lower activities in young females and higher activities in older females, a finding not consistently reflected across both datasets.

Impact:

  • The findings underscore the importance of utilizing precise, sex- and age-specific reference intervals for accurate interpretation of laboratory screening tests.
  • Failure to account for specific demographic variations, such as those observed for alkaline phosphatase, may lead to misdiagnosis, exemplified by potential misinterpretation in young women with hyperthyroidism.
  • This study emphasizes the need for careful validation and selection of reference intervals to ensure optimal diagnostic accuracy and patient care in clinical laboratory settings.