Mu Sigma is an Indian decision sciences firm that primarily offers data analytics services. The firm's name is derived from the statistical terms "Mu (μ)" and "Sigma (σ)" which symbolize the mean and the standard deviation, respectively, of a probability distribution.
Introduction: As spine surgery volume continues to grow, ensuring patient safety and minimizing complications are increasingly critical. Disruptive bleeding-defined as hemorrhagic events requiring clinical intervention-is a significant perioperative challenge. This study aimed to: (1) quantify disruptive bleeding incidence; (2) evaluate associations between patient demographics, Elixhauser Comorbidity Index (ECI), and bleeding risk; and (3) assess the impact of disruptive bleeding on mortality, ventilator use, length of inpatient stay, 90-day readmissions, and inpatient costs. Methods: A nationwide healthcare database was used to identify patients who underwent spine surgery in 2019. Patients were subdivided by the Elixhauser Comorbidity Index (ECI) from 0 to ≥6, and multivariate logistic regression was employed to analyze for potential association with disruptive bleeding. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated for each ECI classification. After controlling for baseline demographics, generalized linear models were used to evaluate how disruptive bleeding influenced hospital mortality, ventilator use, 90-day readmission rates, lengths of inpatient stay, and inpatient costs. Results: Among 165,461 patients undergoing spine surgery, 15,337 (9.3%) experienced disruptive bleeding. Women and Medicare coverage were associated with higher bleeding risk (p < 0.05). Disruptive bleeding odds increased with comorbidity burden, ranging from OR = 2.31 (95% CI 1.92-2.77) for ECI = 5 to OR = 3.32 (95% CI 2.73-4.06) for ECI ≥ 6. Disruptive bleeding was associated with increased ventilator use (18.4 versus 8.2% for ECI ≥ 6; p < 0.001) and inpatient mortality (3.0 versus 0.7% for ECI ≥ 6; p < 0.001). Hospital stays were significantly prolonged (10.4 versus 6.6 days for ECI ≥ 6; p < 0.001), 90-day readmission rates were higher (19.8 versus 14.7%; p < 0.001), and inpatient costs increased substantially ($68,000 versus $37,500; p < 0.001). Conclusions: Disruptive bleeding in spine surgery is more frequent among patients with elevated comorbidity burdens and is linked to greater mortality, ventilator dependence, and healthcare resource use. These findings highlight the importance of proactive risk stratification and targeted perioperative management strategies for high-risk patients undergoing spine surgery.
