Journal of Osteoporosis and Physical Activity
Open Access

Development and Validation of Mikkeli Osteoporosis Index

Clinton Horowitz^{* *}Correspondence: Clinton Horowitz, Department of Orthopedic Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA, Email:

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Description

Mikkeli Osteoporosis Index (MOI) was developed from Fracture Index (FI), a valid fracture risk score, to spot additionally pathology. MOI risk factors area unit age, weight, previous fracture, case history of hip fracture or spinal pathology, smoking, shortening of the stature, and use of arms to rise from a chair. The association of those risk factors with BMD was examined in development cohorts of 300 Finnish postmenopausal ladies with a fracture and in a very social control of 450 ladies aged 65-72. Validation cohorts enclosed two hundred fracture patients and a social control of 945 women aged 58-69 [1]. MOI known leg bone neck pathology in these cohorts moreover because the Osteoporosis Self- Assessment Tool (OST). Within the pooled fracture cohort, the association of BMI-based FRAX fracture risk with MOI was perspective. Once BMD activity, MOI known well FRAX hip fracture risk-based Intervention Thresholds (ITs) [2-4].

Osteoporosis prediction rules attempt to choose patients for bone densitometry. A recent review updates the performance of outwardly valid instruments that reported performance characteristics in Cochrane info between 2001 and 2009. 23 studies of fourteen instruments to predict low BMD reported United Self-Defense Force of Colombia estimates travel principally between 0.5 and 0.7. Of these, Osteoporosis Self- Assessment Screening Tool (OST) includes solely age and weight but has similar space under the ROC-curve estimates because the different a lot of difficult instruments. Its validity in distinguishing pathology has been confirmed in multiple freelance population cohorts each in men and women [3].

Most fractures occur in patients with traditional or osteopenic bone mass and instruments that predict low bone density correlate solely with modesty with clinical fractures. Fracture risk assessment tools use Clinical Risk Factors (CRF) to predict fractures, and combining bone densitometry with risk score sometimes ends up in higher United Self-Defense Force of Colombia estimates. Recent metaanalyses and reviews have disclosed the most BMD-independent CRFs for pathology fractures: Increasing age, low weight, previous fracture, case history of pathology fracture, smoking, adrenal cortical steroid medical care, contractile organ disorders, and alcohol excess.

Fracture Index (FI) may be a valid risk score for fracture prediction in white women over the age of 65. It includes six CRFs: Increasing age over sixty-five, fracture once age fifty, maternal hip fracture, weight below 58 kg, smoking, and also the use of arms to rise from a chair test. The recommendations of the National Osteoporosis Foundation (NOF) for risk assessment contain the primary five of those factors. Additionally the recent social Women’s Health Initiative (WHI) formula foretold hip fracture among five years moreover as BMD. The WHI CRFs embrace the five factors higher than and, in addition, general health, race, physical activity, sex hormone use, and polygenic disease. WHO fracture risk assessment tool FRAX integrates BMD with CRFs: Age, weight/height (BMI), previous fracture, parent broken hip, current smoking, use of glucocorticoids, use of alcohol three or a lot of units/day, autoimmune disorder, and causes of secondary pathology.

The aim was to develop from FI a risk score that identifies each fracture risk factors and low BMD in Finnish population. We have a tendency to name this easy additive score Mikkeli Osteoporosis Index (MOI), and compared the correlation of MOI, FI, and OST with BMD. We have a tendency to any compare the higher than scores with FRAX fracture risk and also the concordance of MOI with FRAX to spot Intervention Thresholds (ITs) projected by the WHO Collaborating cluster. The development and validation cohorts were freelance of every different however were of an equivalent nation. The populationbased FPS development cohort just age varies, and thus the impact older on BMD may be analysed only in fracture patients [3-5].

The scale of the fracture Validation Cohort two was restricted, however it represents typical clinical white feminine patients during which pathology CDRs would be applied. Each management teams were representative population-based cohorts with a high participation rate and long follow-up [4,5]. 2 specially trained nurses registered and picked up the management cluster knowledge, whereas employees’ nurses registered and 2 pathology nurses registered and collected the corresponding knowledge within the clinical fracture series. Also, misinterpretations of the measure reprints were excluded within the population cohorts, which can justify the upper AUCs for pathology identification within the OSTPRE population controls. MOI identifies pathology and fracture risk factors with one figure and, once BMD activity, Intervention Thresholds in concordance with FRAX.

References

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