Multicenter external validation of prediction models for clinical outcomes after spinal fusion for lumbar degenerative disease.

BACKGROUND: Clinical prediction models (CPM), such as the SCOAP-CERTAIN tool, can be utilized to enhance decision-making for lumbar spinal fusion surgery by providing quantitative estimates of outcomes, aiding surgeons in assessing potential benefits and risks for each individual patient. External validation is crucial in CPM to assess generalizability beyond the initial dataset. This ensures performance in diverse populations, reliability and real-world applicability of the results. Therefore, we externally validated the tool for predictability of improvement in oswestry disability index (ODI), back and leg pain (BP, LP). METHODS: Prospective and retrospective data from multicenter registry was obtained. As outcome measure minimum clinically important change was chosen for ODI with ≥ 15-point and ≥ 2-point reduction for numeric rating scales (NRS) for BP and LP 12 months after lumbar fusion for degenerative disease. We externally validate this tool by calculating discrimination and calibration metrics such as intercept, slope, Brier Score, expected/observed ratio, Hosmer-Lemeshow (HL), AUC, sensitivity and specificity. RESULTS: We included 1115 patients, average age 60.8 ± 12.5 years. For 12-month ODI, area-under-the-curve (AUC) was 0.70, the calibration intercept and slope were 1.01 and 0.84, respectively. For NRS BP, AUC was 0.72, with calibration intercept of 0.97 and slope of 0.87. For NRS LP, AUC was 0.70, with calibration intercept of 0.04 and slope of 0.72. Sensitivity ranged from 0.63 to 0.96, while specificity ranged from 0.15 to 0.68. Lack of fit was found for all three models based on HL testing. CONCLUSIONS: Utilizing data from a multinational registry, we externally validate the SCOAP-CERTAIN prediction tool. The model demonstrated fair discrimination and calibration of predicted probabilities, necessitating caution in applying it in clinical practice. We suggest that future CPMs focus on predicting longer-term prognosis for this patient population, emphasizing the significance of robust calibration and thorough reporting.

Calculation of the minimum clinically important difference (MCID) using different methodologies: case study and practical guide.

INTRODUCTION: Establishing thresholds of change that are actually meaningful for the patient in an outcome measurement instrument is paramount. This concept is called the minimum clinically important difference (MCID). We summarize available MCID calculation methods relevant to spine surgery, and outline key considerations, followed by a step-by-step working example of how MCID can be calculated, using publicly available data, to enable the readers to follow the calculations themselves. METHODS: Thirteen MCID calculations methods were summarized, including anchor-based methods, distribution-based methods, Reliable Change Index, 30% Reduction from Baseline, Social Comparison Approach and the Delphi method. All methods, except the latter two, were used to calculate MCID for improvement of Zurich Claudication Questionnaire (ZCQ) Symptom Severity of patients with lumbar spinal stenosis. Numeric Rating Scale for Leg Pain and Japanese Orthopaedic Association Back Pain Evaluation Questionnaire Walking Ability domain were used as anchors. RESULTS: The MCID for improvement of ZCQ Symptom Severity ranged from 0.8 to 5.1. On average, distribution-based methods yielded lower MCID values, than anchor-based methods. The percentage of patients who achieved the calculated MCID threshold ranged from 9.5% to 61.9%. CONCLUSIONS: MCID calculations are encouraged in spinal research to evaluate treatment success. Anchor-based methods, relying on scales assessing patient preferences, continue to be the "gold-standard" with receiver operating characteristic curve approach being optimal. In their absence, the minimum detectable change approach is acceptable. The provided explanation and step-by-step example of MCID calculations with statistical code and publicly available data can act as guidance in planning future MCID calculation studies.

Predictive value of the five-repetition sit-to-stand test for outcomes after surgery for lumbar disc herniation: prospective study.

OBJECTIVE: It is unknown whether presence of pre-operative objective functional impairment (OFI) can predict post-operative outcomes in patients with lumbar disc herniation (LDH). We aimed to determine whether pre-operative OFI measured by the five-repetition sit-to-stand test (5R-STS) could predict outcomes at 12-months post-discectomy. METHODS: Adult patients with LDH scheduled for surgery were prospectively recruited from a Dutch short-stay spinal clinic. The 5R-STS time and patient reported outcome measures (PROMs) including Oswestry Disability Index, Roland-Morris Disability Questionnaire, Visual Analogue Scale (VAS) for back and leg pain, EQ-5D-3L health-related quality of life, EQ5D-VAS and ability to work were recorded pre-operatively and at 12-months. A 5R-STS time cut-off of ≥ 10.5 s was used to determine OFI. Mann-Whitney and Chi-square tests were employed to determine significant differences in post-operative outcomes between groups stratified by presence of pre-operative OFI. RESULTS: We recruited 134 patients in a prospective study. Twelve-month follow-up was completed by 103 (76.8%) patients. Mean age was 53.2 ± 14.35 years and 50 (48.5%) patients were female. Pre-operatively, 53 (51.5%) patients had OFI and 50 (48.5%) did not. Post-operatively, patients with OFI experienced a significantly greater mean change (p < 0.001) across all PROMs compared to patients without OFI, except leg pain (p = 0.176). There were no significant differences in absolute PROMs between groups at 12-months (all p > 0.05). CONCLUSIONS: The presence of OFI based on 5R-STS time does not appear to decrease a patient's likelihood of experiencing satisfactory post-operative outcomes. The 5R-STS cannot predict how a patient with LDH will respond to surgery at 12-month follow-up.

Identifying clusters of objective functional impairment in patients with degenerative lumbar spinal disease using unsupervised learning.

OBJECTIVES: The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment (OFI), and thus provides an adjunctive dimension in patient assessment. It is conceivable that there are different subsets of patients with OFI and degenerative lumbar disease. We aim to identify clusters of objectively functionally impaired individuals based on 5R-STS and unsupervised machine learning (ML). METHODS: Data from two prospective cohort studies on patients with surgery for degenerative lumbar disease and 5R-STS times of ≥ 10.5 s-indicating presence of OFI. K-means clustering-an unsupervised ML algorithm-was applied to identify clusters of OFI. Cluster hallmarks were then identified using descriptive and inferential statistical analyses. RESULTS: We included 173 patients (mean age [standard deviation]: 46.7 [12.7] years, 45% male) and identified three types of OFI. OFI Type 1 (57 pts., 32.9%), Type 2 (81 pts., 46.8%), and Type 3 (35 pts., 20.2%) exhibited mean 5R-STS test times of 14.0 (3.2), 14.5 (3.3), and 27.1 (4.4) seconds, respectively. The grades of OFI according to the validated baseline severity stratification of the 5R-STS increased significantly with each OFI type, as did extreme anxiety and depression symptoms, issues with mobility and daily activities. Types 1 and 2 are characterized by mild to moderate OFI-with female gender, lower body mass index, and less smokers as Type I hallmarks. CONCLUSIONS: Unsupervised learning techniques identified three distinct clusters of patients with OFI that may represent a more holistic clinical classification of patients with OFI than test-time stratifications alone, by accounting for individual patient characteristics.

Predictors of five-repetition sit-to-stand test performance in patients with lumbar degenerative disease.

BACKGROUND: The five-repetition sit-to-stand test (5R-STS) has recently been validated as an objective measure of functional impairment in patients with lumbar degenerative disease (LDD). Knowledge of factors influencing 5R-STS performance is useful to correct for confounders, create personalized adjusted test times, and potentially identify prognostic subgroups. We evaluate factors predicting the 5R-STS performance in patients with LDD. METHODS: Patients with LDD requiring surgery were included. Each participant performed the 5R-STS and completed a questionnaire that included their age, gender, weight, height, body mass index (BMI), smoking status, education level, employment type, ability to work, analgesic drug usage, history of previous spinal surgery, and EQ5D depression and anxiety domain. Surgical indication and index level of the spinal pathology were also recorded. Predictors of 5R-STS were identified through multivariable linear regression. RESULTS: The cohort consisted of 240 patients, 47.9% being female (mean age, 47.7 ± 13.6 years). In the final multivariable model incorporating confounders, height (regression coefficient (RC), 0.08; 95% confidence interval (CI), 0.003/0.16, p = 0.042) and being an active smoker (RC, 2.44; 95%CI, 0.56/4.32, p = 0.012) were significant predictors of worse 5R-STS performance. Full ability to work (RC, - 2.39; 95%CI, - 4.39/ - 0.39, p = 0.020) was associated with a better 5R-STS performance. Age, height, surgical indication, index level of pathology, history of previous spine surgery, history of pain, analgesic drug use, employment type, and severity of anxiety and depression symptoms demonstrated confounding effect on the 5R-STS time. CONCLUSIONS: Greater height, being an active smoker, and inability to work are significant predictors of worse 5R-STS performance in patients with LDD. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03303300 and NCT03321357.

FUSE-ML: development and external validation of a clinical prediction model for mid-term outcomes after lumbar spinal fusion for degenerative disease.

BACKGROUND: Indications and outcomes in lumbar spinal fusion for degenerative disease are notoriously heterogenous. Selected subsets of patients show remarkable benefit. However, their objective identification is often difficult. Decision-making may be improved with reliable prediction of long-term outcomes for each individual patient, improving patient selection and avoiding ineffective procedures. METHODS: Clinical prediction models for long-term functional impairment [Oswestry Disability Index (ODI) or Core Outcome Measures Index (COMI)], back pain, and leg pain after lumbar fusion for degenerative disease were developed. Achievement of the minimum clinically important difference at 12 months postoperatively was defined as a reduction from baseline of at least 15 points for ODI, 2.2 points for COMI, or 2 points for pain severity. RESULTS: Models were developed and integrated into a web-app ( https://neurosurgery.shinyapps.io/fuseml/ ) based on a multinational cohort [N = 817; 42.7% male; mean (SD) age: 61.19 (12.36) years]. At external validation [N = 298; 35.6% male; mean (SD) age: 59.73 (12.64) years], areas under the curves for functional impairment [0.67, 95% confidence interval (CI): 0.59-0.74], back pain (0.72, 95%CI: 0.64-0.79), and leg pain (0.64, 95%CI: 0.54-0.73) demonstrated moderate ability to identify patients who are likely to benefit from surgery. Models demonstrated fair calibration of the predicted probabilities. CONCLUSIONS: Outcomes after lumbar spinal fusion for degenerative disease remain difficult to predict. Although assistive clinical prediction models can help in quantifying potential benefits of surgery and the externally validated FUSE-ML tool may aid in individualized risk-benefit estimation, truly impacting clinical practice in the era of "personalized medicine" necessitates more robust tools in this patient population.

Overweight and smoking promote recurrent lumbar disk herniation after discectomy.

PURPOSE: Recurrent lumbar disk herniation (rLDH) following lumbar microdiscectomy is common. While several risk factors for primary LDH have been described, risk factors for rLDH have only sparsely been investigated. We evaluate the effect of Body mass index (BMI) and smoking on the incidence and timing of rLDH. METHODS: From a prospective registry, we identified all patients undergoing primary tubular microdiscectomy (tMD), with complete BMI and smoking data, and a minimum 12-month follow-up. We defined rLDH as reherniation at the same level and side requiring surgery. Overweight was defined as BMI > 25, and obesity as BMI > 30. Intergroup comparisons and age- and gender-adjusted multivariable regression were carried out. We conducted a survival analysis to assess the influence of BMI and smoking on time to reoperation. RESULTS: Of 3012 patients, 166 (5.5%) underwent re-microdiscectomy for rLDH. Smokers were reoperated more frequently (6.4% vs. 4.0%, p = 0.007). Similarly, rLDH was more frequent in obese (7.5%) and overweight (5.9%) than in normal-weight patients (3.3%, p = 0.017). Overweight smokers had the highest rLDH rate (7.6%). This effect of smoking (Odds ratio: 1.63, 96% CI: 1.12-2.36, p = 0.010) and BMI (Odds ratio: 1.09, 95% CI: 1.02-1.17, p = 0.010) persisted after controlling for age and gender. Survival analysis demonstrated that rLDH did not occur earlier in overweight patients and/or smokers. CONCLUSIONS: BMI and smoking may directly contribute to a higher risk of rLDH, but do not accelerate rLDH development. Smoking cessation and weight loss in overweight or obese patients ought to be recommended with discectomy to reduce the risk for rLDH.

Machine learning-augmented objective functional testing in the degenerative spine: quantifying impairment using patient-specific five-repetition sit-to-stand assessment.

OBJECTIVE: What is considered "abnormal" in clinical testing is typically defined by simple thresholds derived from normative data. For instance, when testing using the five-repetition sit-to-stand (5R-STS) test, the upper limit of normal (ULN) from a population of spine-healthy volunteers (10.5 seconds) is used to identify objective functional impairment (OFI), but this fails to consider different properties of individuals (e.g., taller and shorter, older and younger). Therefore, the authors developed a personalized testing strategy to quantify patient-specific OFI using machine learning. METHODS: Patients with disc herniation, spinal stenosis, spondylolisthesis, or discogenic chronic low-back pain and a population of spine-healthy volunteers, from two prospective studies, were included. A machine learning model was trained on normative data to predict personalized "expected" test times and their confidence intervals and ULNs (99th percentiles) based on simple demographics. OFI was defined as a test time greater than the personalized ULN. OFI was categorized into types 1 to 3 based on a clustering algorithm. A web app was developed to deploy the model clinically. RESULTS: Overall, 288 patients and 129 spine-healthy individuals were included. The model predicted "expected" test times with a mean absolute error of 1.18 (95% CI 1.13-1.21) seconds and R2 of 0.37 (95% CI 0.34-0.41). Based on the implemented personalized testing strategy, 191 patients (66.3%) exhibited OFI. Type 1, 2, and 3 impairments were seen in 64 (33.5%), 91 (47.6%), and 36 (18.8%) patients, respectively. Increasing detected levels of OFI were associated with statistically significant increases in subjective functional impairment, extreme anxiety and depression symptoms, being bedridden, extreme pain or discomfort, inability to carry out activities of daily living, and a limited ability to work. CONCLUSIONS: In the era of "precision medicine," simple population-based thresholds may eventually not be adequate to monitor quality and safety in neurosurgery. Individualized assessment integrating machine learning techniques provides more detailed and objective clinical assessment. The personalized testing strategy demonstrated concurrent validity with quality-of-life measures, and the freely accessible web app (https://neurosurgery.shinyapps.io/5RSTS/) enabled clinical application.

Enhanced Recovery After Surgery strategies for elective craniotomy: a systematic review.

OBJECTIVE: Enhanced Recovery After Surgery (ERAS) has led to a paradigm shift in perioperative care through multimodal interventions. Still, ERAS remains a relatively new concept in neurosurgery, and there is no summary of evidence on ERAS applications in cranial neurosurgery. METHODS: The authors systematically reviewed the literature using the PubMed/MEDLINE, Embase, Scopus, and Cochrane Library databases for ERAS protocols and elements. Studies had to assess at least one pre-, peri-, or postoperative ERAS element and evaluate at least one of the following outcomes: 1) length of hospital stay, 2) length of ICU stay, 3) postoperative pain, 4) direct and indirect healthcare cost, 5) complication rate, 6) readmission rate, or 7) patient satisfaction. RESULTS: A final 27 articles were included in the qualitative analysis, with mixed quality of evidence ranging from high in 3 cases to very low in 1 case. Seventeen studies reported a complete ERAS protocol. Preoperative ERAS elements include patient selection through multidisciplinary team discussion, patient counseling and education to adjust expectations of the postoperative period, and mental state assessment; antimicrobial, steroidal, and antiepileptic prophylaxes; nutritional assessment, as well as preoperative oral carbohydrate loading; and postoperative nausea and vomiting (PONV) prophylaxis. Anesthesiology interventions included local anesthesia for pin sites, regional field block or scalp block, avoidance or minimization of the duration of invasive monitoring, and limitation of intraoperative mannitol. Other intraoperative elements include absorbable skin sutures and avoidance of wound drains. Postoperatively, the authors identified early extubation, observation in a step-down unit instead of routine ICU admission, early mobilization, early fluid de-escalation, early intake of solid food and liquids, early removal of invasive monitoring, professional nutritional assessment, PONV management, nonopioid rescue analgesia, and early postoperative imaging. Other postoperative interventions included discharge criteria standardization and home visits or progress monitoring by a nurse. CONCLUSIONS: A wide range of evidence-based interventions are available to improve recovery after elective craniotomy, although there are few published ERAS protocols. Patient-centered optimization of neurosurgical care spanning the pre-, intra-, and postoperative periods is feasible and has already provided positive results in terms of improved outcomes such as postoperative pain, patient satisfaction, reduced length of stay, and cost reduction with an excellent safety profile. Although fast-track recovery protocols and ERAS studies are gaining momentum for elective craniotomy, prospective trials are needed to provide stronger evidence.

Magnetic resonance imaging-based synthetic computed tomography of the lumbar spine for surgical planning: a clinical proof-of-concept.

OBJECTIVE: Computed tomography scanning of the lumbar spine incurs a radiation dose ranging from 3.5 mSv to 19.5 mSv as well as relevant costs and is commonly necessary for spinal neuronavigation. Mitigation of the need for treatment-planning CT scans in the presence of MRI facilitated by MRI-based synthetic CT (sCT) would revolutionize navigated lumbar spine surgery. The authors aim to demonstrate, as a proof of concept, the capability of deep learning-based generation of sCT scans from MRI of the lumbar spine in 3 cases and to evaluate the potential of sCT for surgical planning. METHODS: Synthetic CT reconstructions were made using a prototype version of the "BoneMRI" software. This deep learning-based image synthesis method relies on a convolutional neural network trained on paired MRI-CT data. A specific but generally available 4-minute 3D radiofrequency-spoiled T1-weighted multiple gradient echo MRI sequence was supplemented to a 1.5T lumbar spine MRI acquisition protocol. RESULTS: In the 3 presented cases, the prototype sCT method allowed voxel-wise radiodensity estimation from MRI, resulting in qualitatively adequate CT images of the lumbar spine based on visual inspection. Normal as well as pathological structures were reliably visualized. In the first case, in which a spiral CT scan was available as a control, a volume CT dose index (CTDIvol) of 12.9 mGy could thus have been avoided. Pedicle screw trajectories and screw thickness were estimable based on sCT findings. CONCLUSIONS: The evaluated prototype BoneMRI method enables generation of sCT scans from MRI images with only minor changes in the acquisition protocol, with a potential to reduce workflow complexity, radiation exposure, and costs. The quality of the generated CT scans was adequate based on visual inspection and could potentially be used for surgical planning, intraoperative neuronavigation, or for diagnostic purposes in an adjunctive manner.

Association of age with incidence and timing of recurrence after microdiscectomy for lumbar disc herniation.

OBJECTIVE: Recurrent lumbar disc herniation (LDH) is the most frequent reason for reoperation after lumbar microdiscectomy. While several risk factors for recurrent LDH have been well-described, the effect of age on recurrence remains unclear, especially concerning the timing of recurrent LDH. METHODS: From a prospective registry, we identified all patients who underwent tubular microdiscectomy for LDH. Recurrent LDH was defined as reoperation for LDH at the same index level and side. The associations among age and incidence of recurrent LDH as well as on time to recurrent LDH were statistically evaluated using multivariable analysis of covariance, linear regression, and Cox proportional hazards modelling. RESULTS: Of the 3013 patients who underwent surgery for LDH, 166 (5.5%) had to undergo reoperation due to LDH recurrence. Uni- and multivariable analysis revealed no influence of age on the incidence of recurrent LDH (both p > 0.05). Linear regression indicated earlier reoperation in older patients, both with (ß = -0.248) and without (ß = -0.374) correction for confounders (both p < 0.05). An additional survival analysis found that patients aged over 35 years had recurrent LDH significantly earlier (hazard ratio 0.617, p = 0.013). CONCLUSION: In an analysis of a large prospective database of patients undergoing microdiscectomy for lumbar disc herniation, we found that younger patients do not have a higher reoperation probability than their older counterparts, even after correcting for multiple confounders. However, older patients tend to experience recurrent LDH significantly earlier after the index surgery compared to younger patients.

Robot-Guided Transforaminal Versus Robot-Guided Posterior Lumbar Interbody Fusion for Lumbar Degenerative Disease.

OBJECTIVE: There have been no clinical studies comparing different robotic techniques. We compare minimally invasive, robot-guided transforaminal lumbar interbody fusion (RGTLIF) and mini-open robot-guided posterior lumbar interbody fusion (RG-PLIF). METHODS: Using data from a prospective institutional registry, we identified 38 patients who underwent RG-PLIF. Propensity score matching using a nearest-neighbor algorithm was implemented to select RG-TLIF controls. Twelve-month patient-reported outcome measures are presented. A reduction of ≥ 30% from baseline was defined as the minimum clinically important difference (MCID). RESULTS: Among the 76 included patients, there was no difference between RG-TLIF and RG-PLIF in surgical time (132.3 ± 29.4 minutes vs. 156.5 ± 53.0 minutes, p = 0.162), length of stay (55.9 ± 20.0 hours vs. 57.2 ± 18.8 hours, p = 0.683), and radiation dose area product (310.6 ± 126.1 mGy × cm2 vs. 287.9 ± 90.3 mGy × cm2, p = 0.370). However, while there was no difference among the 2 groups in terms of raw postoperative patient-reported outcome measures scores (all p > 0.05), MCID in leg pain was greater for RG-PLIF (55.3% vs. 78.9%, p = 0.028), and MCID in Oswestry Disability Index was greater for RG-TLIF (92.1% vs. 68.4%, p = 0.009). There was no difference concerning back pain (81.6% vs. 68.4%, p = 0.185). CONCLUSION: Our findings suggest that both RG-TLIF and RG-PLIF are viable and equally effective techniques in robotic spine surgery.

Global adoption of robotic technology into neurosurgical practice and research.

Recent technological advancements have led to the development and implementation of robotic surgery in several specialties, including neurosurgery. Our aim was to carry out a worldwide survey among neurosurgeons to assess the adoption of and attitude toward robotic technology in the neurosurgical operating room and to identify factors associated with use of robotic technology. The online survey was made up of nine or ten compulsory questions and was distributed via the European Association of the Neurosurgical Societies (EANS) and the Congress of Neurological Surgeons (CNS) in February and March 2018. From a total of 7280 neurosurgeons who were sent the survey, we received 406 answers, corresponding to a response rate of 5.6%, mostly from Europe and North America. Overall, 197 neurosurgeons (48.5%) reported having used robotic technology in clinical practice. The highest rates of adoption of robotics were observed for Europe (54%) and North America (51%). Apart from geographical region, only age under 30, female gender, and absence of a non-academic setting were significantly associated with clinical use of robotics. The Mazor family (32%) and ROSA (26%) robots were most commonly reported among robot users. Our study provides a worldwide overview of neurosurgical adoption of robotic technology. Almost half of the surveyed neurosurgeons reported having clinical experience with at least one robotic system. Ongoing and future trials should aim to clarify superiority or non-inferiority of neurosurgical robotic applications and balance these potential benefits with considerations on acquisition and maintenance costs.

Five-Repetition Sit-to-Stand Test Performance in Healthy Individuals: Reference Values and Predictors From 2 Prospective Cohorts.

OBJECTIVE: The 5-repetition-sit-to-stand (5R-STS) test is an objective test of functional impairment- commonly used in various diseases, including lumbar degenerative disc diseases. It is used to measure the severity of disease and to monitor recovery. We aimed to evaluate reference values for the test, as well as factors predicting 5R-STS performance in healthy adults. METHODS: Healthy adults ( > 18 years of age) were recruited, and their 5R-STS time was measured. Their age, sex, weight, height, body mass index (BMI), smoking status, education level, work situation and EuroQOL-5D Healthy & Anxiety category were recorded. Linear regression analysis was employed to identify predictors of 5R-STS performance. RESULTS: We included 172 individuals with mean age of 39.4 ± 14.1 years and mean BMI of 24.0 ± 4.0 kg/m2. Females constituted 57%. Average 5R-STS time was 6.21 ± 1.92 seconds, with an upper limit of normal of 12.39 seconds. In a multivariable model, age (regression coefficient [RC], 0.07; 95% confidence interval [CI], 0.05/0.09; p < 0.001), male sex (RC, -0.87; 95% CI, -1.50 to -0.23; p = 0.008), BMI (RC, 0.40; 95% CI, 0.10-0.71; p = 0.010), height (RC, 0.13; 95% CI, 0.04-0.22; p = 0.006), and houseworker status (RC, -1.62; 95% CI, -2.93 to -0.32; p = 0.016) were significantly associated with 5R-STS time. Anxiety and depression did not influence performance significantly (RC, 0.82; 95% CI, -0.14 to 1.77; p = 0.097). CONCLUSION: The presented reference values can be applied as normative data for 5R-STS in healthy adults, and are necessary to judge what constitutes abnormal performance. We identified several significant factors associated with 5R-STS performance that may be used to calculate individualized expected test times.

Influence of dynamic preoperative body mass index changes on patient-reported outcomes after surgery for degenerative lumbar spine disease.

Psychological factors demonstrably and often massively influence outcomes of degenerative spine surgery, and one could hypothesize that preoperative weight loss may correlate with motivation and lifestyle adjustment, thus leading to potentially enhanced outcomes. We aimed to evaluate the effect of preoperative weight loss or gain, respectively, on patient-reported outcomes after lumbar spine surgery. Weight loss was defined as a BMI decrease of ≤ - 0.5 kg/m2 over a period of at least 1 month, and weight gain as a BMI increase of ≥ 0.5 kg/m2 in the same time period, respectively. The primary endpoint was set as the achievement of the minimum clinically important difference (MCID) in the ODI at 1 or 2 years postoperatively. A total of 154 patients were included. Weight loss (odds ratio (OR): 1.18, 95% confidence interval (CI): 0.52 to 2.80) and weight gain (OR: 1.03, 95% CI: 0.43 to 2.55) showed no significant influence on MCID achievement for ODI compared to a stable BMI. The same results were observed when analysing long-term NRS-BP and NRS-LP. Regression analysis showed no correlation between BMI change and PROM change scores for any of the three PROMs. Adjustment for age and gender did not alter results. Our findings suggest that both preoperative weight loss and weight gain may have no measurable effect on long-term postoperative outcome compared to a stable BMI. Weight loss preoperatively-as a potential surrogate sign of patient motivation and lifestyle change-may thus not influence postoperative outcomes.

Machine learning in neurosurgery: a global survey.

BACKGROUND: Recent technological advances have led to the development and implementation of machine learning (ML) in various disciplines, including neurosurgery. Our goal was to conduct a comprehensive survey of neurosurgeons to assess the acceptance of and attitudes toward ML in neurosurgical practice and to identify factors associated with its use. METHODS: The online survey consisted of nine or ten mandatory questions and was distributed in February and March 2019 through the European Association of Neurosurgical Societies (EANS) and the Congress of Neurosurgeons (CNS). RESULTS: Out of 7280 neurosurgeons who received the survey, we received 362 responses, with a response rate of 5%, mainly in Europe and North America. In total, 103 neurosurgeons (28.5%) reported using ML in their clinical practice, and 31.1% in research. Adoption rates of ML were relatively evenly distributed, with 25.6% for North America, 30.9% for Europe, 33.3% for Latin America and the Middle East, 44.4% for Asia and Pacific and 100% for Africa with only two responses. No predictors of clinical ML use were identified, although academic settings and subspecialties neuro-oncology, functional, trauma and epilepsy predicted use of ML in research. The most common applications were for predicting outcomes and complications, as well as interpretation of imaging. CONCLUSIONS: This report provides a global overview of the neurosurgical applications of ML. A relevant proportion of the surveyed neurosurgeons reported clinical experience with ML algorithms. Future studies should aim to clarify the role and potential benefits of ML in neurosurgery and to reconcile these potential advantages with bioethical considerations.

Timing of Surgery in Tubular Microdiscectomy for Lumbar Disc Herniation and Its Effect on Functional Impairment Outcomes.

OBJECTIVE: While it has been established that surgery for lumbar disc herniation, excluding emergent indications, should only be performed after weeks of conservative treatment, it has also been established that late surgery is associated with poorer outscomes in terms of leg pain. However, nothing is known concerning the timinig and functional outcome. We quantify the association of time to surgery (TTS) with functional impairment outcome and identify a maximum TTS cutoff. METHODS: A consecutive series of patients who underwent tubular microdiscectomy for lumbar disc herniation was included. A reduction of ≥ 30% in the Oswestry Disability Index from baseline to 12 months was defined as the minimum clinically important difference (MCID). TTS was defined as time of symptom onset to surgery in weeks. The maximum TTS cutoffs were derived both quantitatively by an area under the curve (AUC) analysis, as well as qualitatively based on cutoff-specific MCID rates. RESULTS: Inclusion was met by 372 patients, among which 327 (87.9%) achieved MCID. MCID achievement was associated with lower TTS (hazard ratio, 0.725; 95% confidence interval, 0.557-0.944; p = 0.014). The optimum maximum TTS based on AUC was 21.5 weeks. The qualitative analysis showed a continuous drop of MCID rates with increasing TTS, with values > 80% until week 14. CONCLUSION: Our findings suggest that longer TTS is associated with a poorer patient-reported outcome in terms of functional impairment, and that-depending on the calculation method and according to the literature-a maximum TTS of between 14 to 22 weeks should likely be aimed for.

Initial classification of low back and leg pain based on objective functional testing: a pilot study of machine learning applied to diagnostics.

OBJECTIVE: The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment and thus provided an adjunctive dimension in patient assessment. The clinical interpretability and confounders of the 5R-STS remain poorly understood. In clinical use, it became apparent that 5R-STS performance may differ between patients with lumbar disk herniation (LDH), lumbar spinal stenosis (LSS) with or without low-grade spondylolisthesis, and chronic low back pain (CLBP). We seek to evaluate the extent of diagnostic information contained within 5R-STS testing. METHODS: Patients were classified into gold standard diagnostic categories based on history, physical examination, and imaging. Crude and adjusted comparisons of 5R-STS performance were carried out among the three diagnostic categories. Subsequently, a machine learning algorithm was trained to classify patients into the three categories using only 5R-STS test time and patient age, gender, height, and weight. RESULTS: From two prospective studies, 262 patients were included. Significant differences in crude and adjusted test times were observed among the three diagnostic categories. At internal validation, classification accuracy was 96.2% (95% CI 87.099.5%). Classification sensitivity was 95.7%, 100%, and 100% for LDH, LSS, and CLBP, respectively. Similarly, classification specificity was 100%, 95.7%, and 100% for the three diagnostic categories. CONCLUSION: 5R-STS performance differs according to the etiology of back and leg pain, even after adjustment for demographic covariates. In combination with machine learning algorithms, OFI can be used to infer the etiology of spinal back and leg pain with accuracy comparable to other diagnostic tests used in clinical examination. These slides can be retrieved under Electronic Supplementary Material.

Objective functional impairment in lumbar degenerative disease: concurrent validity of the baseline severity stratification for the five-repetition sit-to-stand test.

OBJECTIVE: The five-repetition sit-to-stand (5R-STS) test provides a new dimension of clinical assessment by capturing objective functional impairment (OFI). Through the utilization of data from two prospective studies, the authors sought to evaluate the concurrent validity of the proposed 5R-STS baseline severity stratification (BSS) for OFI with the following levels based on time to completion in seconds: none, ≤ 10.4; mild, 10.5-15.2; moderate, 15.3-22.0; and severe, > 22.0 seconds. METHODS: Patients with degenerative diseases of the spine performed the 5R-STS test and completed visual analog scales (VASs) for back and leg pain, the Oswestry Disability Index (ODI), the Roland-Morris Disability Questionnaire (RMDQ), and EQ-5D questionnaires. The degree of OFI severity was assessed based on the previously proposed BSS, and its association with patient-reported scales was evaluated using ANOVA as well as crude and adjusted linear regression models. RESULTS: Our sample included 240 patients, of whom 101 exhibited no OFI, whereas 80, 34, and 25 were judged to have mild, moderate, and severe OFI, respectively. A higher baseline severity was strongly associated with loss of working ability (p < 0.001), as well as results of all patient-reported scales (p ≤ 0.001), with the exception of the VAS for leg pain (p = 0.556). Crude and adjusted regression analyses corroborated these findings, although only patients with moderate and severe OFI as judged by using the 5R-STS BSS demonstrated clinically relevant differences compared with patients without OFI. CONCLUSIONS: The degree of OFI-based on the 5R-STS BSS-is strongly associated with measures of back pain, subjective functional impairment, and health-related quality of life. However, leg pain severity is not reflected within the dimension of OFI measured by the 5R-STS. The proposed BSS appears to be a concurrently valid and clinically relevant measure of OFI in patients with degenerative spinal pathologies.

A comparison of economy between two different backpack designs for runners.

We compared two backpack designs (back/front or back only) in twelve recreational runners (age 22.0 ± 1.7years). An initial incremental exercise test (VO2max 52.2 ± 4.7 ml kg-1.min-1) was conducted, followed by four tests of 20 min duration (running speed 9.8 ± 1.1 km/h) with loads carried of 0, 1 kg, 3 kg, and 6 kg with the two backpack designs in a randomized order. Economy was assessed by energy cost of running (CR), oxygen cost (O2 cost), heart rate (HR) and rate of perceived exertion (RPE). Repeated measure ANOVA revealed a non-significant main effect for CR, O2 cost, HR, RPE between systems. Post-hoc comparison of significant time × position interaction showed for CR, F(3,33) = 5.34, p < .01, ηp2 = 0.33, and O2 cost, F(3,33) = 5.15, p < .01, ηp2 = 0.32, that carrying weight in the back/front were significantly lower after 20 min (CR: p = .02 and O2 cost: p = .03). These results suggest, that for longer runs the equal distribution of weight is advantageous.