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A new approach to defining normal vertebral dimensions

Black, Dennis M., Cummings, Steven R., Stone, Katie, Hudes, Estie, Palermo, Lisa, Steiger, Peter·1991·Journal of Bone and Mineral Research

Abstract

We developed a method for estimating the mean and standard deviation of ratios of normal vertebral heights from a sample that includes people with and without vertebral fractures. This method assumes that the measurements in normal vertebrae have a Gaussian distribution and that, for any vertebral level, the prevalence of abnormal measurements is less than 10%. Under these assumptions, normal values for nonfractured vertebrae can be estimated from several statistical properties of Gaussian distributions. We applied these methods to the lateral spinal radiographs of 2992 women aged 65–70 years who were recruited from population-based listings. The estimated means and standard deviations for ratios of dimensions in nonfractured vertebrae were very similar to those based on studies of premenopausal women. Our method may be useful for defining normal values from large populations that include normal and abnormal women, does not require x-rays of normal premenopausal women, avoids the potential biases of defining normality based on qualitative judgment, and can be applied to other types of physical and biochemical measurements.

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Metadata

Authors
Black, D. M., Cummings, S. R., Stone, K., Hudes, E., Palermo, L., & Steiger, P.
Venue
Journal of Bone and Mineral Research
Published
1991-08-01
Volume
6
Issue
8
Pages
883-892
ISSN
  • 0884-0431 (ISSN-L)
  • 1523-4681
OpenAlex
W2095030031
Cited by
267
References
0
FWCI
13.50
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A new approach to defining normal vertebral dimensions. https://app.cochat.ai/papers/10.1002/jbmr.5650060814
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Black, D. M., Cummings, S. R., Stone, K., Hudes, E., Palermo, L., & Steiger, P. (1991). A new approach to defining normal vertebral dimensions. Journal of Bone and Mineral Research. https://doi.org/10.1002/jbmr.5650060814

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.