The Lumbar Spine Wound Complication Risk Framework is a research and educational platform developed at Balgrist University Hospital, University of Zurich. It integrates two complementary tools into a single interface: a preoperative risk-estimation calculator and a standardised complication classification system.
The calculator is grounded in a large retrospective cohort of 4,067 consecutive patients undergoing lumbar decompression or instrumented fusion between 2017 and 2023. Seven independent predictors of major wound complications (requiring operative revision) were identified through multivariate logistic regression:
The overall cohort complication rate was 3.0% (121/4,067); infection was confirmed in 75.2% of cases, with a mean time to revision of 24.6 ± 13.3 days.
The classification tab implements the SpineCRS system (Farshad et al., The Spine Journal, 2020), a four-axis framework stratifying perioperative complications by surgical complexity, cause (surgical vs. medical), therapeutic consequence (grades A–E), and neurological deficit. The system was validated against cumulative hospital stay in 934 consecutive spine surgery patients.
The platform is being expanded into a prospective multi-centre research tool, enabling structured data entry, case logging, and outcome tracking. The Log In feature will unlock authenticated case submission and longitudinal follow-up once the data infrastructure is in place.
This tool is provided for research, educational, and informational purposes only. It presents population-level estimates derived from a published reference cohort and is not intended to predict outcomes for, or guide clinical decisions about, any individual patient.
Additional references will be added as the project expands. For citation purposes, please refer to the primary study (Ref. 1) once published.
Country counts reflect enrolled institutions only. Surgeons may register only via an enrolled institution; institutions wishing to join the registry may contact the project coordinator.
SpineCRS maintains editorial independence. Industry partnerships are non-influencing and disclosed in full on this page once finalised.
case_local_refs) with row-level security restricting access to the registering surgeon. The main cases table contains only de-identified clinical data. No demographic or contact information is collected.
api.anthropic.com), which is operated on AWS infrastructure in the United States. This means that any text or photo you submit to the auto-fill feature briefly leaves the EU/Swiss environment for the duration of the call. The request and response are encrypted in transit, Anthropic does not retain API inputs for training, and — as noted above — nothing about the request is stored on SpineCRS servers afterwards. If your institutional data agreement requires that no clinical content leaves European infrastructure, please fill the Charlson score manually rather than using auto-fill.
This FAQ will be updated as the platform evolves. Suggestions for additional questions are welcome.
Patient factors
Comorbidities
Surgical factors
Classification Wizard
Reference — Classification System
Complication Classification System
About the Paper