Literature DB >> 11251764

Evaluating and managing acute low back pain in the primary care setting.

S J Atlas1, R A Deyo.   

Abstract

Acute low back pain is a common reason for patient calls or visits to a primary care clinician. Despite a large differential diagnosis, the precise etiology is rarely identified, although musculoligamentous processes are usually suspected. For most patients, back symptoms are nonspecific, meaning that there is no evidence for radicular symptoms or underlying systemic disease. Because episodes of acute, nonspecific low back pain are usually self-limited, many patients treat themselves without contacting their primary care clinician. When patients do call or schedule a visit, evaluation and management by primary care clinicians is appropriate. The history and physical examination usually provide clues to the rare but potentially serious causes of low back pain, as well as to identify patients at risk for prolonged recovery. Diagnostic testing, including plain x-rays, is often unnecessary during the initial evaluation. For patients with acute, nonspecific low back pain, the primary emphasis of treatment should be conservative care, time, reassurance, and education. Current recommendations focus on activity as tolerated (though not active exercise while pain is severe) and minimal if any bed rest. Referral for physical treatments is most appropriate for patients whose symptoms are not improving over 2 to 4 weeks. Specialty referral should be considered for patients with a progressive neurologic deficit, failure of conservative therapy, or an uncertain or serious diagnosis. The prognosis for most patients is good, although recurrence is common. Thus, educating patients about the natural history of acute low back pain and how to prevent future episodes can help ensure reasonable expectations.

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Mesh:

Year:  2001        PMID: 11251764      PMCID: PMC1495170          DOI: 10.1111/j.1525-1497.2001.91141.x

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  93 in total

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9.  Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

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10.  What is the role of imaging in acute low back pain?

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