Perspective: A Proposed Diagnostic and Treatment Algorithm for Management of Lumbar Spinal Stenosis: An Integrated...

Newly-introduced minimally invasive interventions have filled a gap between conservative care and open surgical procedures in the treatment and management of lumbar spinal stenosis (LSS), allowing expanded access to patient care. This spectrum of care involves an important interplay between advanced practice providers, interventional pain physicians, and spine surgeons.

Using an integrated team approach starting with history taking; static and dynamic imaging; and conservative care, we developed a simple, understandable clinical algorithm that serves as a foundation for physicians to confidently make objective decisions regarding diagnosing and treating LSS throughout the entire clinical course of the condition. We believe this could potentially lead to more efficient and effective care for patients suffering from LSS with neurogenic claudication.

A decision tree approach was utilized with "either/or" choices at each branch or node in the algorithm. Activities are divided into examination procedures and corresponding treatment interventions. Symptom and radiographic severity grading as well as assessing clinical status employed published validated standards. Commensurate treatment choices were selected based on published LSS-specific clinical practice guidelines and/or meta-analyses.

This algorithm recommends a systematic rule set for LSS diagnostic and treatment options. Initially, LSS symptom severity is graded based on the patient's pain relief with spinal flexion. This is correlated with radiographic severity assessment graded as mild, moderate, or severe. Radiographic severity combined with dynamic imaging prescribes a choice of treatment options and a risk/benefit discussion with the patient. These options include conservative management, minimally invasive methods such as interspinous process decompression, and more invasive surgical procedures such as laminectomy for increasing grades of radiographic severity.

Understanding that each patient with LSS is managed on a case-by-case basis, the treatment options recommended by this algorithm should be considered "soft guidance." As such, integrated team/patient consultation is recommended to ensure maximum clinical benefit. A risk/benefit assessment and discussion should be performed with each individual patient.

Our proposed algorithm offers an easy-to-use clinical tool and general foundation for identifying, evaluating, and treating patients with intermittent neurogenic claudication associated with LSS.