The Influence of Baseline Clinical Status and Surgical Strategy on Early Good to Excellent Result in Spinal Lumbar Arthrodesis: A Machine Learning Approach.

The study aims to create a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome using a machine learning (ML) approach. A single spine surgery center retrospective review of prospectively collected data from January 2016 to December 2020 from the institutional registry (SpineREG) was performed. The inclusion criteria were age ≥ 18 years, both sexes, lumbar arthrodesis procedure, a complete follow up assessment (Oswestry Disability Index-ODI, SF-36 and COMI back) and the capability to read and understand the Italian language. A delta of improvement of the ODI higher than 12.7/100 was considered a "good early outcome". A combined target model of ODI (Δ ≥ 12.7/100), SF-36 PCS (Δ ≥ 6/100) and COMI back (Δ ≥ 2.2/10) was considered an "excellent early outcome". The performance of the ML models was evaluated in terms of sensitivity, i.e., True Positive Rate (TPR), specificity, i.e., True Negative Rate (TNR), accuracy and area under the receiver operating characteristic curve (AUC ROC). A total of 1243 patients were included in this study. The model for predicting ODI at 6 months' follow up showed a good balance between sensitivity (74.3%) and specificity (79.4%), while providing a good accuracy (75.8%) with ROC AUC = 0.842. The combined target model showed a sensitivity of 74.2% and specificity of 71.8%, with an accuracy of 72.8%, and an ROC AUC = 0.808. The results of our study suggest that a machine learning approach showed high performance in predicting early good to excellent clinical results.

The use of electronic PROMs provides same outcomes as paper version in a spine surgery registry. Results from a prospective cohort study.

BACKGROUND AND PURPOSE: Patient-Reported Measured Outcomes (PROMs) are essential to gain a full understanding of a patient's condition, and in spine surgery, these questionnaires are of help when tailoring a surgical strategy. Electronic registries allow for a systematic collection and storage of PROMs, making them readily available for clinical and research purposes. This study aimed to investigate the reliability between the electronic and paper form of ODI (Oswestry Disability Index), SF-36 (Short Form Health Survey 36) and COMI-back (Core Outcome Measures Index for the back) questionnaires. METHODS: A prospective analysis was performed of ODI, SF-36 and COMI-back questionnaires collected in paper and electronic format in two patients' groups: Pre-Operatively (PO) or at follow-up (FU). All patients, in both groups, completed the three questionnaires in paper and electronic form. The correlation between both methods was assessed with the Intraclass Correlation Coefficients (ICC). RESULTS: The data from 100 non-consecutive, volunteer patients with a mean age of 55.6 ± 15.0 years were analysed. For all of the three PROMs, the reliability between paper and electronic questionnaires results was excellent (ICC: ODI = 0.96; COMI = 0.98; SF36-MCS = 0.98; SF36-PCS = 0.98. For all p < 0.001). CONCLUSIONS: This study proved an excellent reliability between the electronic and paper versions of ODI, SF-36 and COMI-back questionnaires collected using a spine registry. This validation paves the way for stronger widespread use of electronic PROMs. They offer numerous advantages in terms of accessibility, storage, and data analysis compared to paper questionnaires.

Perioperative Predictive Factors for Positive Outcomes in Spine Fusion for Adult Deformity Correction.

PURPOSE: Identifying perioperative factors that may influence the outcomes of long spine fusion for the treatment of adult deformity is key for tailored surgical planning and targeted informed consent. The aim of this study was to analyze the association between demographic or perioperative factors and clinical outcomes 2 years after long spine fusion for the treatment of adult deformity. METHODS: This study is a multivariate analysis of retrospectively collected data. All patients who underwent long fusion of the lumbar spine for adult spinal deformity (January 2016-June 2019) were included. The outcomes of interest were the Oswestry disability index (ODI), visual analogic scale (VAS) preoperatively and at 1 and 2 years' follow up, age, body mass index, American Society of Anaesthesiologists (ASA) score, upper and lowest instrumented vertebrae (UIV and LIV, respectively), length of surgery, estimated blood loss, and length of hospital stay. RESULTS: Data from 192 patients were available. The ODI at 2 years correlated weakly to moderately with age (r = 0.4), BMI (r = 0.2), ASA (r = 0.3), and LIV (r = 0.2), and strongly with preoperative ODI (r = 0.6). The leg VAS at 2 years moderately correlated with age (r = 0.3) and BMI (r = 0.3). CONCLUSION: ODI and VAS at 2 years' follow-up had no to little association to preoperative age, health status, LIV, or other peroperative data, but showed a strong correlation with preoperative ODI and pain level.