Clinical and pathological outcomes after resection of intramedullary spinal cord tumors: a single-institution case series
Bibliographic record
Abstract
OBJECTIVE The objective of this study was to identify clinically relevant predictors of progression-free survival and functional outcomes in patients who underwent surgery for intramedullary spinal cord tumors (ISCTs). METHODS An institutional spinal tumor registry and billing records were reviewed to identify adult patients who underwent resection of ISCTs between 1993 and 2014. Extensive data were collected from patient charts and operative notes, including demographic information, extent of resection, tumor pathology, and functional and oncological outcomes. Survival analysis was used to determine important predictors of progression-free survival. Logistic regression analysis was used to evaluate the association between an "optimal" functional outcome on the Frankel or McCormick scale at 1-year follow-up and various clinical and surgical characteristics. RESULTS The consecutive case series consisted of 63 patients (50.79% female) who underwent resection of ISCTs. The mean age of patients was 41.92 ± 14.36 years (range 17.60-75.40 years). Complete microsurgical resection, defined as no evidence of tumor on initial postoperative imaging, was achieved in 34 cases (54.84%) of the 62 patients for whom this information was available. On univariate analysis, the most significant predictor of progression-free survival was tumor histology (p = 0.0027). Patients with Grade I/II astrocytomas were more likely to have tumor progression than patients with WHO Grade II ependymomas (HR 8.03, 95% CI 2.07-31.11, p = 0.0026) and myxopapillary ependymomas (HR 8.01, 95% CI 1.44-44.34, p = 0.017). Furthermore, patients who underwent radical or subtotal resection were more likely to have tumor progression than those who underwent complete resection (HR 3.46, 95% CI 1.23-9.73, p = 0.018). Multivariate analysis revealed that tumor pathology was the only significant predictor of tumor progression. On univariate analysis, the most significant predictors of an "optimal" outcome on the Frankel scale were age (OR 0.94, 95% CI 0.89-0.98, p = 0.0062), preoperative Frankel grade (OR 4.84, 95% CI 1.33-17.63, p = 0.017), McCormick score (OR 0.22, 95% CI 0.084-0.57, p = 0.0018), and region of spinal cord (cervical vs conus: OR 0.067, 95% CI 0.012-0.38, p = 0.0023; and thoracic vs conus: OR 0.015: 95% CI 0.001-0.20, p = 0.0013). Age, tumor pathology, and region were also important predictors of 1-year McCormick scores. CONCLUSIONS Extent of tumor resection and histopathology are significant predictors of progression-free survival following resection of ISCTs. Important predictors of functional outcomes include tumor histology, region of spinal cord in which the tumor is present, age, and preoperative functional status.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".