Osteoporosis in Adult Patients Undergoing Spinal Reconstructive Surgery: Associated Complications and Management
Bibliographic record
Abstract
Study DesignLiterature review.ObjectivesTo provide an overview of the complications associated with and management strategies for adult patients with osteoporosis requiring spinal reconstructive surgery. Emphasis will be placed on screening, diagnosis, and perioperative medical and surgical management of these patients.MethodsA review of the literature was performed for studies examining osteoporosis in adult patients undergoing spine surgery, associated complications, treatment and prevention methodologies.ResultsThe reported incidence of osteoporosis in adult patients undergoing spinal reconstructive surgery was found to be 10% - 50%, whereas the incidence of osteopenia was 41.4% - 58.6%. DEXA scan is the most widely used modality for assessing bone mineral density (BMD) despite its limitations. Quantitative CT has been found to be the most optimal method for measuring BMD in the spine, yet, its availability is limited. Opportunistic CT scan-based Hounsfield Units (CTHU) have been found to correlate with osteoporosis and osteopenia, instrumentation loosening, proximal and distal junctional kyphosis, and pseudarthrosis. Patients treated with Teriparatide preoperatively and postoperatively were found to have a decreased rate of pseudarthrosis, screw loosening, and reoperation. Modifying surgical techniques can also improve outcomes. Such strategies could involve vertebral cement augmentation, iliac fixation in long constructs to the sacrum, and utilizing longer constructs when addressing spinal deformity or spinal instability.ConclusionsThe incidence of osteoporosis in patients undergoing spinal reconstruction is high. Appropriate preoperative and postoperative medical treatment can result in lower rates of adverse events related to osteoporosis. Surgical treatment and fixation can also be modified to account for suboptimal bone health.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".