An Algorithmic Approach to Diagnosis and Management of Low Back Pain

The structural basis of chronic low back pain has been well described (1). Facet joints have been implicated as responsible for spinal pain in 15% to 52% of patients with chronic low back pain in controlled studies based on the type of population studied and the setting (2). Controlled studies also have reported the prevalence of discogenic pain as 26% to 39% of patients suffering with chronic low back pain (3, 4). Similarly, controlled studies have shown the sacroiliac joint to be a source of back pain or referred pain, with a prevalence of 2% (3), 19% (5) and 30% (6) in selected population groups. Postlaminectomy syndrome or pain following operative procedures of the spine is also a common entity in modern medicine (7). However, the exact incidence and prevalence of postlaminectomy syndrome is not known. It is estimated that 20% to 30% of spinal surgeries may not be successful as a result of the surgery’s being inadequate, incorrect, or unnecessary. Poor outcomes also may result following a well-indicated and wellperformed surgical procedure. Similarly, the role of ligaments, muscles and other structures in chronic low back pain has not been identified by controlled studies. A structural cause for chronic low back pain may be identified in only 15% of patients with radiological investigations, electromyographic studies, and physical and clinical examination. Bogduk (8) postulated that precision diagnostic injections could assist in arriving at a definite diagnosis in low back pain in approximately 70% to 80% of the patients based on studies by Schwarzer et al (4, 5, 9-12). Manchikanti et al (3) evaluated the relative contributions of various structures in chronic low back pain in 120 patients. Utilizing controlled precision diagnostic blocks, including disc injections, facet joint blocks, and sacroiliac joint injections, they showed that 40% of the patients were diagnosed with pain emanating from facet joints, 26% with discogenic pain and 2% with sacroiliac joint pain. Thus, utilizing controlled diagnostic blocks with an algorithmic approach allows a structure causing the low back pain to be identified in 68% of patients. Manchikanti et al (3) also showed that 13% of patients suffered with potential segmental dural/nerve root pain. If segmental dural/nerve root pain is considered as a reasonable alternative, structures responsible for chronic low back pain are identified in 81% of patients. However, this still leaves 19% of patients without an identified structure responsible for low back pain.