A novel primary care clinical prediction rule for early detection of osteoporosis

The effects of osteoporosis (OP) can be significantly slowed if disease is detected early. We report on a clinical risk prediction rule developed from patient histories taken in an orthopaedic outpatient clinic, before confirmatory testing for OP. Data were extracted from routine audits of consecutive records of patients with recent wrist fracture, comprising demographic details, medications, past and current disease, and fracture details. Clinical prediction rule elements were tested against clinical suspicion of OP. The clinical prediction elements comprised sex and age risk, medications that predispose patients to OP and/or falls, previous fractures and disease/medical conditions that are known OP risks. The best cut point (6.5) demonstrated 100% sensitivity with clinical suspicion of OP. Patient history information is often available before OP is clinically suspected or a definitive diagnosis is made. Our clinical prediction rule will be useful in primary care settings where objective measures of bone health are not readily available. It will raise OP awareness amongst health care providers and patients, particularly those not previously suspected of having OP. It will assist in identifying at-risk patients early and commencing them on appropriate management, without waiting for definitive bone health tests.