Risk Factors for Early Postoperative Morbidity and Mortality following Extremity Metastatic Pathologic or Impending Fracture Fixation
Bibliographic record
Abstract
Background. As cancer survivorship continues to improve, the perioperative morbidity and mortality following surgical treatment of metastatic bone disease become an increasingly important consideration. The objective of this study is to identify risk factors for early postoperative complications and mortality following extremity prophylactic fixation and pathologic fracture stabilization. Methods. A single‐centre retrospective review of 185 patients (226 total surgeries) who underwent prophylactic fixation or pathologic fracture stabilization for extremity metastatic bone disease between 2005 and 2020 was performed. Skull, spine, pelvic, and revision surgeries along with diagnosis of primary bone neoplasm were excluded. Univariate, multivariate, and subgroup analyses were performed to identify predictors and independent risk factors for 30‐day postoperative morbidity and mortality. Results. Primary cancers included lung (n = 41), breast (n = 36), multiple myeloma (n = 35), prostate (n = 16), lymphoma (n = 11), renal cell carcinoma (n = 10), and other (n = 36). The 30‐day postoperative complication and mortality rates were 32.30% (n = 73) and 17.26% (n = 39), respectively. The most common complications were pulmonary‐related, cardiac events, surgical site infection, sepsis, and thromboembolism. Pathologic fracture, presence of extra‐skeletal metastases, longer surgical duration, and blood transfusion requirements were associated with 30‐day postoperative complications overall. A past medical history for cardiac disease was also associated with systemic but not local surgical complications. Pathologic fracture, presence of extra‐skeletal metastases, lung cancer, blood transfusion requirements, and increasing pack‐year smoking history were predictors for 30‐day mortality. In the multivariate analysis, pathologic fracture (p = 0.016) and presence of extra‐skeletal metastases (p = 0.029) were independent predictors of complications. For mortality, pathologic fracture (p = 0.014), presence of extra‐skeletal metastases (p = 0.0085), and increased blood transfusion requirements (p = 0.048) were independent risk factors. Conclusions. The findings of this study provide additional guidance for perioperative risk assessment and patient counselling. Additionally, improving clinical assessment tools to identify and quantify patients at risk of pathologic fractures becomes increasingly important given the significant morbidity and mortality associated with pathologic fracture treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.001 | 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".