Development and validation of risk stratification models for adult spinal deformity surgery

Abstract

<jats:sec><jats:title>OBJECTIVE</jats:title><jats:p>Adult spinal deformity (ASD) surgery has a high rate of major complications (MCs). Public information about adverse outcomes is currently limited to registry average estimates. The object of this study was to assess the incidence of adverse events after ASD surgery, and to develop and validate a prognostic tool for the time-to-event risk of MC, hospital readmission (RA), and unplanned reoperation (RO).</jats:p></jats:sec><jats:sec><jats:title>METHODS</jats:title><jats:p>Two models per outcome, created with a random survival forest algorithm, were trained in an 80% random split and tested in the remaining 20%. Two independent prospective multicenter ASD databases, originating from the European continent and the United States, were queried, merged, and analyzed. ASD patients surgically treated by 57 surgeons at 23 sites in 5 countries in the period from 2008 to 2016 were included in the analysis.</jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p>The final sample consisted of 1612 ASD patients: mean (standard deviation) age 56.7 (17.4) years, 76.6% women, 10.4 (4.3) fused vertebral levels, 55.1% of patients with pelvic fixation, 2047.9 observation-years. Kaplan-Meier estimates showed that 12.1% of patients had at least one MC at 10 days after surgery; 21.5%, at 90 days; and 36%, at 2 years. Discrimination, measured as the concordance statistic, was up to 71.7% (95% CI 68%–75%) in the development sample for the postoperative complications model. Surgical invasiveness, age, magnitude of deformity, and frailty were the strongest predictors of MCs. Individual cumulative risk estimates at 2 years ranged from 3.9% to 74.1% for MCs, from 3.17% to 44.2% for RAs, and from 2.67% to 51.9% for ROs.</jats:p></jats:sec><jats:sec><jats:title>CONCLUSIONS</jats:title><jats:p>The creation of accurate prognostic models for the occurrence and timing of MCs, RAs, and ROs following ASD surgery is possible. The presented variability in patient risk profiles alongside the discrimination and calibration of the models highlights the potential benefits of obtaining time-to-event risk estimates for patients and clinicians.</jats:p></jats:sec>

Quantifying the collective influence of social determinants of health using conditional and cluster modeling

“…Scientists, clinicians and policy makers have recognized the influence of biopsychosocial factors on self-reported health outcomes [6]. Care pathways and risk stratification schemes commonly take into account biological and psychological factors [7,8], yet noticeably less attention has been paid to social factors such as social determinants of health (SDoH). SDoH are broadly defined as the conditions in which people are born, work, live and play and include areas such as economic stability, education, social and community context, and environment [9].…”

Artificial Intelligence for Adult Spinal Deformity

“…The ISSG and ESSG also sought to build upon the work of prior postoperative outcomes studies on a much larger scale, to validate the utility of prognostic tools for predicting major complications, hospital readmission, and unplanned reoperation in surgically treated ASD patients. 27 A large concern for patients considering deformity correction surgery for ASD continues to be the relatively high rate of complications, given the complexity of surgical intervention. Currently, surgeons are only able to inform patients about the risks of major complications based on prospective registries, which contain generalized estimates for entire populations, and have little utility for individual patients.…”

“…The models were trained using a standard 80% partition for the training set, and a 20% partition for independent testing, showcasing adequate predictive accuracy with AUC ranging from 0.67-0.92. 27 Accurate prognostic models such as these will prove to be incredible resources for optimizing patient selection, which in turn maximizes chances for surgical success by minimizing risk of complications and readmissions.…”

Repeat Radiography in Monitoring Structural Changes in the Treatment of Spinal Disorders in Chiropractic and Manual Medicine Practice: Evidence and Safety

“…These contemporary methods should prove to help humanity by reducing the need for risky surgical procedures that are often associated with adverse events including major complications, hospital readmissions, and unplanned reoperations. 82…”