External Validation of the Spinal Orthopedic Research Group Index for Spinal Epidural Abscess 90-Day Mortality in a Geographically Remote Population

STUDY DESIGN:Retrospective cohort study. OBJECTIVE:To externally validate the Spinal Orthopaedic Research Group (SORG) index for predicting 90-day mortality from spinal epidural abscess and compare its utility to the 11-item modified frailty index (mFI-11) and Charlson comorbidity index (CCI). SUMMARY OF BACKGROUND DATA:Providing a mortality estimate may guide informed patient and clinician decision-making. A number of prognostic tools and calculators are available to help predict the risk of mortality from spinal epidural abscess, including the SORG index, which estimates 90-day postdischarge mortality. External validation is essential before wider use of any clinical prediction tool. MATERIALS AND METHODS:Patients were identified using hospital coding. Medical and radiologic records were used to confirm the diagnosis. Mortality data and data to calculate the SORG index, mFI-11, and CCI were collected. Area under the curve and calibration plots were used to analyze. RESULTS:One hundred and fifty patients were included: 58 were female (39%), with a median age of 63 years. Fifteen deaths (10%) at 90 days postdischarge and 20 (13%) at one year. The mean SORG index was 13.6%, the mean CCI 2.75, and the mean mFI-11 was 1.34. The SORG index ( P =0.0006) and mFI-11 ( P <0.0001) were associated with 90-day mortality. Area under the curve for SORG, mFI-11, and CCI were 0.81, 0.84, and 0.49, respectively. The calibration slope for the SORG index showed slight overestimation in the middle ranges of the predicted probability, more so than mFI-11, and was not well-calibrated over the higher ranges of predicted probability. CONCLUSIONS:This study externally validated the SORG index, demonstrating its utility in our population at predicting 90-day mortality; however, it was less well calibrated than the mFI-11. Variations in algorithm performance may be a result of differences in socioethnic composition and health resources between development and validation centres. Continued multicenter data input may help improve such algorithms and their generalisability.