Rechargeable Spinal Cord Stimulation Versus Nonrechargeable System for Patients With Failed Back Surgery Syndrome: A Cost-Consequences Analysis
Bibliographic record
Abstract
OBJECTIVES: Spinal cord stimulation (SCS) has been used for almost 40 years to treat refractory neuropathic pain after failed back surgery. Fully implantable non-rechargeable pulse generators have a battery life of between 2 and 5 years. A new SCS system with a rechargeable power source may last 10 to 25 years, or longer. The potential economic implications of longer battery life with a new SCS system has yet to be assessed. The study objective is to estimate the average difference in lifetime costs between rechargeable and non-rechargeable pulse generators used in treatment with SCS for failed back surgery syndrome. METHODS: A generalized state-transition probability framework was used to model costs. Input parameters for the base case analysis were obtained from several data sources including published literature, Medicare fee schedules, Medicare claims data, and expert opinion. RESULTS: A rechargeable SCS system is projected to require from 2.6 to 4.2 fewer battery generator replacements for battery depletion than a non-rechargeable SCS system. The total lifetime savings of a rechargeable system range from $104,000 to $168,833. In all of the one-way sensitivity analyses conducted, a rechargeable system saves money. Among all of the assumptions underlying the analysis, the annual cost after device removal contributes the most uncertainty. CONCLUSIONS: A rechargeable SCS system is projected to save up to $100,000 over a patient's lifetime. Fewer pulse generator replacements will also decrease patient discomfort and morbidity from procedural complications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".