Measuring quality of recovery (QoR-15) after degenerative spinal surgery: A prospective observational study.

Introduction: The Quality of Recovery (QoR-15) score evaluates patient's recovery after surgery and anesthesia. There is a lack of studies focusing on the patients' quality of recovery in the early post-discharge phase after elective lumbar spine surgery. Research question: We aimed to identify the QoR-15 score in patients who underwent surgery for degenerative low back conditions. Furthermore, we aimed to identify the individual items of the QoR-15 that are crucial for the patients' quality of recovery. Material and methods: The study was conducted at a spine center in Denmark from December 2021 to September 2022. Data were collected, using a mobile health application, preoperatively and at 3 time points after hospital discharge. Descriptive analysis followed by within-subjects longitudinal repeated measures was conducted. The individual items of the QoR-15 score were explored using a heatmap. Results: Data from 46 patients were analysed. The mean QoR-15 sum score at baseline was 105.4 ± 18.3. The mean QoR-15 sum scores were 108.1 ± 19.2 on post-discharge day 1, 118.5 ± 17.4 on day 7, and 120.7 ± 20.9 on day 14. The mean QoR-15 score from day 1 to day 7 improved significantly. Eight of the 15 items influenced the overall QoR-15 score. Discussion and conclusion: This study applied the QoR-15 score in lumbar spine surgery patients. We identified specific items from the QoR-15 scale that are crucial to improving patients' recovery after hospital discharge. Further research is needed to identify specific needs in the post-discharge period in this group of patients.

PROPOSE. Development and validation of a prediction model for shared decision making for patients with lumbar spinal stenosis.

Background: Decompression for lumbar spinal stenosis (LSS) is the most frequently performed spine surgery in Denmark. According to the Danish spine registry DaneSpine, at 1 year after surgery, about 75% of patients experiences considerable pain relief and around 66% improvement in quality of life. However, 25% do not improve very much. We have developed a predictive decision support tool, PROPOSE. It is intended to be used in the clinical conversation between healthcare providers and LSS patients as a shared decision-making aid presenting pros and cons of surgical intervention. This study presents the development and evaluation of PROPOSE in a clinical setting. Methods: For model development, 6.357 LSS patients enrolled in DaneSpine were identified. For model validation, predictor response and predicted outcome was collected via PROPOSE from 228 patients. Observed outcome at 1 year was retrieved from DaneSpine. All participants were treated at 3 Danish spine centers. The outcome measures presented are improvement in walking distance, the Oswestry Disability Index, EQ-5D-3L and leg/back pain on the Visual Analog Scale. Outcome variables were dichotomized into success (1) and failure (0). With the exception of walking distance, a success was defined as reaching minimal clinically important difference at 1-year follow-up. Models were trained using Multivariate Adaptive Regression Splines. Performance was assessed by inspecting confusion matrix, ROC curves and comparing GCV (generalized cross-validation) errors. Final performance of the models was evaluated on independent test data. Results: The walking distance model demonstrated excellent performance with an AUC of 0.88 and a Brier score of 0.14. The VAS leg pain model had the lowest discriminatory performance with an AUC of 0.67 and a Brier score of 0.22. Conclusions: PROPOSE works in a real-world clinical setting as a proof of concept and demonstrates acceptable performance. It may have the potential of aiding shared decision making.

Usability and performance expectancy govern spine surgeons' use of a clinical decision support system for shared decision-making on the choice of treatment of common lumbar degenerative disorders.

Study design: Quantitative survey study is the study design. Objectives: The study aims to develop a model for the factors that drive or impede the use of an artificial intelligence clinical decision support system (CDSS) called PROPOSE, which supports shared decision-making on the choice of treatment of ordinary spinal disorders. Methods: A total of 62 spine surgeons were asked to complete a questionnaire regarding their behavioral intention to use the CDSS after being introduced to PROPOSE. The model behind the questionnaire was the Unified Theory of Acceptance and Use of Technology. Data were analyzed using partial least squares structural equation modeling. Results: The degree of ease of use associated with the new technology (effort expectancy/usability) and the degree to which an individual believes that using a new technology will help them attain gains in job performance (performance expectancy) were the most important factors. Social influence and trust in the CDSS were other factors in the path model. r2 for the model was 0.63, indicating that almost two-thirds of the variance in the model was explained. The only significant effect in the multigroup analyses of path differences between two subgroups was for PROPOSE use and social influence (p = 0.01). Conclusion: Shared decision-making is essential to meet patient expectations in spine surgery. A trustworthy CDSS with ease of use and satisfactory predictive ability promoted by the leadership will stand the best chance of acceptance and bridging the communication gap between the surgeon and the patient.

Impact of Preoperative Duration of Symptoms on Patient Satisfaction, Outcomes and Complications After Lumbar Discectomy: A Propensity-matched Comparison.

STUDY DESIGN: Observational study. OBJECTIVE: To identify associations between preoperative symptom duration and postoperative patient satisfaction. SUMMARY OF BACKGROUND DATA: Sciatica due to lumbar disk herniation (LDH) is a cause of disability and reduced quality life. Patients with severe pain and disability or were recovery is unacceptably slow, surgical intervention can be advised. For these patients, evidence-based recommendations on the timing of the surgical intervention needs to be established. METHODS: All patients who underwent discectomy at a Spine Centre, due to radicular pain from June 2010 to May 2019 were included. Pre- and postoperative data including demographic data, smoking, consumption of pain medication, comorbidity, back and leg-pain, health-related quality of life as measured by EQ-5D, ODI, previous spine surgery, sick leave, and duration of back and leg-pain before surgery were utilized. The patients were divided into four groups based on their self-reported duration of leg-pain before surgery. To minimize baseline differences between the groups, propensity-score matching was employed in a 1:1 fashion, balancing the groups on all reported preoperative factors. RESULTS: Of 1607 patients undergoing lumbar discectomy, four matched cohorts based on their self-reported duration of leg-pain before surgery were created. Each cohort consisted of 150 patients well balanced on preoperative factors. Overall 62.7% of the patients were satisfied with the surgical result ranging from 74.0% in the <3 months group to 48.7% in the >24 months group ( P <0.000). The portion of patients achieving a minimum clinically important difference for EQ-5D decreased from 77.4% with early intervention to 55.6% in the late group ( P <0.000). The number of surgical complications were not affected by the duration of preoperative leg-pain. CONCLUSION: We found significant difference in patient satisfaction and health-related quality of life in patients related to the duration of preoperative leg-pain due to symptomatic LDH. LEVEL OF EVIDENCE: 3.

Validating the predictive precision of the dialogue support tool on Danish patient cohorts.

Background: Despite advances in surgical techniques and diagnostics, some patients remain unsatisfied with the result following spine surgery. One way to improve patient satisfaction may be found in better alignment of expectations. Prognostic tools might prove useful in strengthening surgeon-patient communication prior to surgery. The purpose of this study is to assess the predictive capabilities of the Swedish based Dialogue Support (DS) tool for spine surgery on a Danish population. Methods: The study included the diagnoses lumbar disc herniation, lumbar spinal stenosis, and lumbar degenerative disc disease. A total of 5.954 patients were retrieved from the Danish national spine registry (DaneSpine). For each group, 200 random cases with complete preoperative and 1 year follow-up data were selected. Two outcome measures were used: Global assessment of pain (GA pain) and satisfaction with outcome. Predictions were produced by manual entry in the DS application. Goodness of fit tests were used to compare the predicted distribution of proportions with successful outcomes (GA pain) to the actual distribution in the three samples. Binomial tests were performed to evaluate the predicted proportion of satisfied patients. Furthermore, ROC-curves, calibration plots, and metrics were calculated to assess the predictive performance. Results: ROC curves showed comparable AUC values with the values reported by the developing authors of the DS from 0.62 to 0.73 (GA pain) and 0.64 to 0.70 (satisfaction with outcome). The calibration plots, however, revealed a low degree of concordance. For GA pain sensitivity varied from 92.4% to 99.3%, and specificity from 1.5% to 13.4%. For satisfaction, sensitivity varied from 97.1% to 99.2% and specificity from 0.0% to 2.9%. Conclusions: The predictive capabilities of the DS tool could not be generalized to the Danish sample cohorts. Further research on larger samples, provided full access to the underlying algorithms can be obtained, could produce a different result.

Applied Machine Learning for Spine Surgeons: Predicting Outcome for Patients Undergoing Treatment for Lumbar Disc Herniation Using PRO Data.

STUDY DESIGN: Retrospective/prospective study. OBJECTIVE: Models based on preoperative factors can predict patients' outcome at 1-year follow-up. This study measures the performance of several machine learning (ML) models and compares the results with conventional methods. METHODS: Inclusion criteria were patients who had lumbar disc herniation (LDH) surgery, identified in the Danish national registry for spine surgery. Initial training of models included 16 independent variables, including demographics and presurgical patient-reported measures. Patients were grouped by reaching minimal clinically important difference or not for EuroQol, Oswestry Disability Index, Visual Analog Scale (VAS) Leg, and VAS Back and by their ability to return to work at 1 year follow-up. Data were randomly split into training, validation, and test sets by 50%/35%/15%. Deep learning, decision trees, random forest, boosted trees, and support vector machines model were trained, and for comparison, multivariate adaptive regression splines (MARS) and logistic regression models were used. Model fit was evaluated by inspecting area under the curve curves and performance during validation. RESULTS: Seven models were arrived at. Classification errors were within ±1% to 4% SD across validation folds. ML did not yield superior performance compared with conventional models. MARS and deep learning performed consistently well. Discrepancy was greatest among VAS Leg models. CONCLUSIONS: Five predictive ML and 2 conventional models were developed, predicting improvement for LDH patients at the 1-year follow-up. We demonstrate that it is possible to build an ensemble of models with little effort as a starting point for further model optimization and selection.

Wide Laminectomy, Segmental Bilateral Laminotomies, or Unilateral Hemi-Laminectomy for Lumbar Spinal Stenosis: Five-year Patient-reported Outcomes in Propensity-matched Cohorts.

STUDY DESIGN: Propensity-matched retrospective study of patients prospectively enrolled in Danespine. OBJECTIVE: The aim of this study was to report 5-year patient reported outcome in lumbar spinal stenosis (LSS) patients who underwent wide laminectomy (WL), segmental bilateral laminotomies (SBL), or unilateral hemilaminectomy (UHL) with bilateral decompression. SUMMARY OF BACKGROUND DATA: The optimal procedure for LSS remains controversial. Studies have shown no difference in short term outcomes among micro-laminectomy, hemi-laminotomies, broad laminectomy, and laminectomy with instrumented fusion. METHODS: Patients with spinal stenosis who were enrolled in DaneSpine at two spine centers from January 2010 until May 2014 and underwent WL0, SBL, or UHL with bilateral decompression were identified. Patients completed standard questionnaires preoperatively and 1, 2, and 5 years after surgery. Patients in the three cohorts were propensity-matched using age, sex, body mass index (BMI), smoking status, number of surgical levels, American Society of Anesthesiologists (ASA) score, and patient-reported outcome measures (PROMs). RESULTS: Propensity matching produced 62 cases in each group. There were no differences in PROM among the three cohorts at five years follow up. Twelve patients were re-operated at the index level. The most frequent indication of reoperation was repeat decompression after SBL. Regression analysis revealed no statistical significant associations between the incidence of reoperation and age, sex, number of operated levels, ASA score, BMI, center, smoking status, or having a dural tear at index operation. CONCLUSION: This study revealed no significant difference PROMs, reoperation rates or time to reoperation at five years follow up between SBLs, UHL, or WL in patients operated for central LSS.Level of Evidence: 4.