Osteopenia and Sarcopenia as Potential Risk Factors for Surgical Site Infection after Posterior Lumbar Fusion: A Retrospective Study.
Alberto RuffilliMarco ManzettiTosca CerasoliFrancesca BarileGiovanni ViroliMatteo TraversariFrancesca SalamannaMilena FiniCesare FaldiniPublished in: Microorganisms (2022)
Surgical site infection (SSI) is a feared complication in spinal surgery, that leads to lower outcomes and increased healthcare costs. Among its risk factors, sarcopenia and osteopenia have recently attracted particular interest. The purpose of this article is to evaluate the influence of sarcopenia and osteopenia on the postoperative infection rate in patients treated with posterior fusion for degenerative diseases of the lumbar spine. This retrospective study included data from 308 patients. Charts were reviewed and central sarcopenia and osteopenia were evaluated through magnetic resonance images (MRI), measuring the psoas to lumbar vertebral index (PLVI) and the M score. Multivariate linear regression was performed to identify independent risk factors for infection. The postoperative SSI rate was 8.4%. Patients with low PLVI scores were not more likely to experience postoperative SSI ( p = 0.68), while low M-score patients were at higher risk of developing SSI ( p = 0.04). However, they did not generally show low PLVI values ( p = 0.5) and were homogeneously distributed between low and high PLVI ( p = 0.6). Multivariate analysis confirmed a low M score to be an independent risk factor for SSI ( p = 0.01). Our results suggest that osteopenia could have significant impact on spinal surgery, and prospective studies are needed to better investigate its role.
Keyphrases
- surgical site infection
- end stage renal disease
- magnetic resonance
- healthcare
- skeletal muscle
- risk factors
- minimally invasive
- ejection fraction
- chronic kidney disease
- patients undergoing
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- magnetic resonance imaging
- spinal cord
- type diabetes
- patient reported outcomes
- metabolic syndrome
- acute coronary syndrome
- big data
- insulin resistance
- coronary artery disease