Evidence-Based Algorithmic Approach to Chronic Spinal Pain: Step-by-Step Clinical Framework From the Lecture of Dr. Debjyoti Dutta at ISSPCON 2026

Chronic spinal pain is one of the most prevalent, disabling, and economically burdensome conditions worldwide. At ISSPCON 2026, Dr. Debjyoti Dutta presented a comprehensive and structured lecture on the Evidence-Based Algorithmic Approach to Chronic Spinal Pain, emphasizing that spine care must transition from symptom-driven and image-driven practice to diagnosis-driven, reproducible clinical algorithms.

The Evidence-Based Algorithmic Approach to Chronic Spinal Pain offers a clear, stepwise roadmap that enhances patient outcomes, reduces overtreatment, and ensures the rational escalation of therapy. Below is the complete structured framework as presented.

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Understanding the Need for an Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Chronic spinal pain, defined as pain persisting beyond three months, affects cervical, thoracic, and lumbar regions and often involves overlapping nociceptive, neuropathic, and nociplastic mechanisms. Because multiple pain generators may coexist — including discs, facet joints, sacroiliac joints, nerve roots, muscles, and central sensitization — empirical treatment frequently fails.

The Evidence-Based Algorithmic Approach to Chronic Spinal Pain ensures structured decision-making based on clinical correlation rather than isolated MRI findings. Chronic spinal pain must always be diagnosis-driven, not image-driven.

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The 11-Step Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Step 1: Initial Patient Assessment in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

The first step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain begins with a meticulous history. Pain onset, duration, progression, location, and radiation pattern provide diagnostic direction. Differentiating axial pain from radicular pain is crucial. Mechanical versus inflammatory characteristics must be evaluated. Neuropathic descriptors such as burning, electric shock-like sensations, or paresthesia suggest nerve involvement. Aggravating and relieving factors refine clinical suspicion and narrow differential diagnosis.

A well-conducted history often identifies the probable pain generator before any imaging is obtained.

Step 2: Physical Examination in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

The second step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain is systematic physical examination. Inspection of posture, assessment of range of motion, and comprehensive neurological evaluation are mandatory. Provocative tests such as facet loading maneuvers, radicular tension signs (e.g., straight leg raise), and sacroiliac joint tests provide important diagnostic clues.

Clinical examination must always precede imaging. Imaging without clinical correlation frequently leads to overdiagnosis.

Step 3: Identification of Red Flags in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Safety is central to the Evidence-Based Algorithmic Approach to Chronic Spinal Pain. Red flags must be actively screened. Progressive neurological deficit, unexplained weight loss, persistent night pain, fever, infection risk, trauma, osteoporosis, or sphincter disturbance require urgent imaging or referral.

Recognizing serious pathology early prevents catastrophic delay in treatment.

Step 4: Baseline Investigations in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

The fourth step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain focuses on the appropriate imaging strategy. MRI or CT should not be routine. Imaging is indicated only when red flags exist or when clinical findings suggest a specific pathology requiring confirmation.

Imaging must be correlated with clinical findings. Degenerative changes are common in asymptomatic individuals; therefore, over-reliance on radiology leads to unnecessary procedures.

Step 5: Pain Generator-Based Classification in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Accurate identification of the pain generator is the cornerstone of the Evidence-Based Algorithmic Approach to Chronic Spinal Pain. Common categories include discogenic pain, facet joint–mediated pain, radicular pain, spinal stenosis, sacroiliac joint pain, myofascial pain, piriformis syndrome, and complex regional pain syndrome.

Without pain generator classification, interventions become empirical and outcomes inconsistent. Classification transforms chronic spinal pain management from generalized treatment to targeted therapy.

Step 6: Conservative Management in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

The sixth step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain emphasizes first-line conservative therapy for six to twelve weeks. This includes patient education, reassurance, activity modification, and structured physiotherapy. Pharmacological management may involve NSAIDs, neuropathic agents, and short-term muscle relaxants. Psychological screening is essential, as chronic spinal pain frequently involves biopsychosocial contributors.

Many patients improve significantly during this stage when therapy is structured and consistent.

Step 7: Reassessment After Conservative Therapy in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Reassessment is a defining feature of the Evidence-Based Algorithmic Approach to Chronic Spinal Pain. Pain intensity, functional improvement, quality of life, and treatment adherence must be evaluated. Patients are categorized as responders or non-responders. This structured reassessment prevents premature procedural escalation and ensures that interventions are justified.

Step 8: Diagnostic Interventional Procedures in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

If diagnosis remains uncertain or conservative therapy fails, the eighth step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain involves controlled diagnostic interventions. Image-guided medial branch blocks, selective nerve root blocks, and sacroiliac joint blocks help confirm the suspected pain generator.

Controlled, image-guided techniques improve diagnostic accuracy and reduce false-positive responses.

Step 9: Therapeutic Interventional Management in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Once the pain generator is confirmed, the ninth step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain introduces targeted therapeutic interventions. Epidural steroid injections may benefit selected radicular pain cases. Radiofrequency ablation is effective for confirmed facet-mediated pain. Sacroiliac joint injections and neuromodulation are reserved for appropriately selected patients.

Interventions must always be evidence-based and diagnosis-driven.

Step 10: Multidisciplinary Management in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

The tenth step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain recognizes that chronic spinal pain is biopsychosocial. Multidisciplinary care includes physical rehabilitation, cognitive behavioral therapy, lifestyle modification, weight management, and ergonomic correction.

Long-term outcomes improve significantly when structural treatment is combined with psychosocial and functional rehabilitation.

Step 11: Escalation Pathway in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

The final step in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain is structured escalation. Failure of interventional procedures mandates reassessment rather than repetition. Surgical consultation is considered only when clear indications exist. Avoiding premature surgery and emphasizing shared decision-making protects patients from unnecessary risk.

Escalation should be deliberate, not reactive.

Special Considerations in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Elderly patients, individuals with osteoporosis, failed back surgery syndrome, chronic opioid use, and significant psychosocial stressors require individualized adaptation of the Evidence-Based Algorithmic Approach to Chronic Spinal Pain. Algorithmic care ensures structured thinking while allowing clinical flexibility.

Outcome Measures and Follow-Up in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain

Long-term success in the Evidence-Based Algorithmic Approach to Chronic Spinal Pain requires monitoring of pain scores, functional scales, patient-reported outcomes, and relapse prevention strategies. Functional improvement remains the primary endpoint.

Conclusion: Why the Evidence-Based Algorithmic Approach to Chronic Spinal Pain Represents the Future of Spine Care

The structured framework presented at ISSPCON 2026 clearly demonstrates that chronic spinal pain management must be diagnosis-driven, stepwise, and evidence-based. The Evidence-Based Algorithmic Approach to Chronic Spinal Pain improves outcomes, reduces unnecessary procedures, enhances cost-effectiveness, and strengthens medico-legal safety.

In modern pain medicine, structured algorithms are no longer optional — they are essential for responsible and effective care.