Evaluation of factors associated with postoperative infection following sacral tumor resection
Bibliographic record
Abstract
OBJECT: Resection of sacral tumors has been shown to improve survival, since the oncological prognosis is commonly correlated with the extent of local tumor control. However, extensive soft-tissue resection in close proximity to the rectum may predispose patients to wound complications and infection. To identify potential risk factors, a review of clinical outcomes for sacral tumor resections over the past 5 years at a single institution was completed, paying special attention to procedure-related complications. METHODS: Between 2002 and 2007, 46 patients with sacral tumors were treated with surgery. Demographic data, details of surgery, type of tumor, and patient characteristics associated with surgical site infections (SSIs) were collected; these data included presence of the following variables: diabetes, obesity, smoking, steroid use, previous surgery, previous radiation, cerebrospinal fluid leak, number of spinal levels exposed, instrumentation, number of surgeons scrubbed in to the procedure, serum albumin level, and combined anterior-posterior approach. Logistic regression analysis was implemented to find an association of such variables with the presence of SSI. RESULTS: A total of 46 patients were treated for sacral tumor resections; 20 were male (43%) and 26 were female (57%), with an average age of 46 years (range 11-83 years). Histopathological findings included the following: chordoma in 19 (41%), ependymoma in 5 (11%), rectal adenocarcinoma in 5 (11%), giant cell tumor in 4 (9%), and other in 13 (28%). There were 18 cases of wound infection (39%), and 2 cases of repeat surgery for tumor recurrence (1 chordoma and 1 giant cell tumor). Factors associated with increased likelihood of infection included previous lumbosacral surgery (p = 0.0184; odds ratio [OR] 7.955) and number of surgeons scrubbed in to the operation (p = 0.0332; OR 4.018). Increasing age (p = 0.0864; OR 1.031), presence of complex soft-tissue reconstruction (p = 0.118; OR 3.789), and bowel and bladder dysfunction (p = 0.119; OR 2.667) demonstrated a trend toward increased risk of SSI. CONCLUSIONS: Patients undergoing sacral tumor surgery may be at greater risk for developing wound complications due to the extensive soft-tissue resections often required, especially with the increased potential for contamination from the neighboring rectum. In this study, it appears that previous lumbosacral surgery, number of surgeons scrubbed in, patient age, bowel and bladder dysfunction, and complex tissue reconstruction may predict those patients more prone to developing postoperative SSIs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".