Abstract
Objective To develop a predictive model of early postoperative morbidity and mortality with
the purpose of assisting in the selection of the candidates for spinal metastasis
surgery.
Methods A retrospective analysis of consecutive patients operated for metastatic spinal disease.
The possible prognostic preoperative characteristics were gender, age, comorbidities,
tumor growth rate, and leukocyte and lymphocyte count in the peripheral blood. The
postoperative outcomes were 30-day mortality, 90-day mortality and presence of complications.
A predictive model was developed based on factors independently associated with these
three outcomes. The final model was then tested for the tendency to predict adverse
events, discrimination capacity and calibration.
Results A total of 205 patients were surgically treated between 2002 and 2015. The rates
of the 30-day mortality, 90-day mortality and presence of complications were of 17%,
42% and 31% respectively. The factors independently associated with these three outcomes,
which constituted the predictive model, were presence of comorbidities, no slow-growing
primary tumor, and lymphocyte count below 1,000 cells/µL. Exposure to none, one, two
or three factors was the criterion for the definition of the following categories
of the predictive model: low, moderate, high and extreme risk respectively. Comparing
the risk categories, there was a progressive increase in the occurrence of outcomes,
following a linear trend. The discrimination capacity was of 72%, 73% and 70% for
30-day mortality, 90-day mortality and complications respectively. No lack of calibration
occurred.
Conclusion The predictive model estimates morbidity and mortality after spinal metastasis surgery
and hierarchizes risks as low, moderate, high and extreme.
Keywords
spine/surgery - comorbidity - lymphocytes - morbidity - mortality - neoplasm metastasis
- postoperative complications
