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[Methods and normal ranges for predicting diseases].

M Okada1

  • 1Department of Laboratory Medicine, Niigata University School of Medicine.

Rinsho Byori. the Japanese Journal of Clinical Pathology
|August 1, 1992
PubMed
Summary
This summary is machine-generated.

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Establishing true normal ranges for disease prediction requires long-term cohort studies. This research introduces a mathematical method to identify key data for building essential laboratory databases and serum banks.

Area of Science:

  • Biostatistics
  • Clinical Chemistry
  • Epidemiology

Context:

  • Accurate disease prediction relies on validated laboratory tests and established normal ranges.
  • Defining 'healthy' subjects is challenging due to the need to exclude individuals with undetected diseases.
  • Longitudinal cohort studies are necessary to identify truly healthy individuals for establishing reliable reference ranges.

Purpose:

  • To address the dilemma in defining normal ranges for laboratory tests.
  • To propose a method for identifying truly healthy subjects through long-term observation.
  • To highlight the importance of laboratory database systems and serum banks for accurate health assessments.

Summary:

  • This study addresses the challenge of defining normal ranges for laboratory tests used in disease prediction.

Related Experiment Videos

  • It proposes a longitudinal cohort approach to identify truly healthy individuals over 10-20 years.
  • A mathematical method is presented for selecting significant data items for a comprehensive laboratory database and decision-making.

    • Impact:

    • Enables the development of more accurate diagnostic criteria for various diseases.
    • Facilitates the creation of robust laboratory databases and serum banks for future research.
    • Improves the reliability of disease prediction models by utilizing data from truly healthy cohorts.