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.

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.

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.

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.

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.

Association of maximum back and leg pain severity with objective functional impairment as assessed by five-repetition sit-to-stand testing: analysis of two prospective studies.

The five-repetition sit-to-stand (5R-STS) test was designed to capture objective functional impairment (OFI), and provides a new adjunctive dimension in patient assessment. Its interpretability and confounders remain poorly understood. We quantify the association among maximum patient-reported back (MBP) or leg pain (MLP) and OFI as measured by the 5R-STS using data from two prospective studies. Patients performed the 5R-STS test and completed visual analogue scales (VAS) for back and leg pain severity. Maximum pain severity was defined as VAS scores of 9 or 10. The association of MBP and MLP with 5R-STS test times as well as with the presence of OFI (> 10.5 s) and severe OFI (> 22.0 s) as determined by the 5R-STS baseline severity stratification was quantified by use of crude and adjusted regression models. A total of 258 patients were included. MBP and MLP were reported by 27 (10.5%) and 76 (29.5%) patients, respectively. Rates of OFI differed among patients with (92.6%) and without (55.0%) MBP (p < 0.001), while presence of MLP did not influence OFI (61.8% vs. 57.7%, p = 0.632). Similarly, severe OFI was more common among patients with MBP (33.3% vs. 9.1%, p < 0.001), but not among patients with MLP (17.1% vs. 9.3%, p = 0.119). In the adjusted logistic analysis, the influence of MBP on OFI persisted (odds ratio [OR] 10.08, confidence interval [CI] 2.73-65.74, p = 0.003), while MLP demonstrated no association (OR 0.91, CI 0.49-1.72, p = 0.780). These associations were consistent with findings pertaining to raw 5R-STS test times and in discectomy patients alone. There is a strong association of maximum back pain severity on VAS with the degree of OFI determined by 5R-STS testing. Radiculopathy with maximally strong back pain, however, does not seem to relevantly influence 5R-STS performance.Trial registration ClinicalTrials.gov : NCT03321357 & NCT03303300.

External validation of a prediction model for pain and functional outcome after elective lumbar spinal fusion.

OBJECTIVE: Patient-reported outcome measures following elective lumbar fusion surgery demonstrate major heterogeneity. Individualized prediction tools can provide valuable insights for shared decision-making. We externally validated the spine surgical care and outcomes assessment programme/comparative effectiveness translational network (SCOAP-CERTAIN) model for prediction of 12-month minimum clinically important difference in Oswestry Disability Index (ODI) and in numeric rating scales for back (NRS-BP) and leg pain (NRS-LP) after elective lumbar fusion. METHODS: Data from a prospective registry were obtained. We calculated the area under the curve (AUC), calibration slope and intercept, and Hosmer-Lemeshow values to estimate discrimination and calibration of the models. RESULTS: We included 100 patients, with average age of 50.4 ± 11.4 years. For 12-month ODI, AUC was 0.71 while the calibration intercept and slope were 1.08 and 0.95, respectively. For NRS-BP, AUC was 0.72, with a calibration intercept of 1.02, and slope of 0.74. For NRS-LP, AUC was 0.83, with a calibration intercept of 1.08, and slope of 0.95. Sensitivity ranged from 0.64 to 1.00, while specificity ranged from 0.38 to 0.65. A lack of fit was found for all three models based on Hosmer-Lemeshow testing. CONCLUSIONS: The SCOAP-CERTAIN tool can accurately predict which patients will achieve favourable outcomes. However, the predicted probabilities-which are the most valuable in clinical practice-reported by the tool do not correspond well to the true probability of a favourable outcome. We suggest that any prediction tool should first be externally validated before it is applied in routine clinical practice. These slides can be retrieved under Electronic Supplementary Material.

Conflicts of interest in randomized controlled trials reported in neurosurgical journals.

OBJECTIVE: Randomized controlled trials (RCTs) form the basis of today's evidence-based approach to medicine, and play a critical role in guidelines and the drug and device approval process. Conflicts of interest (COIs) are commonplace in medical research, but little is known about their influence. The authors aimed to evaluate the extent and influence of COIs in recent RCTs published in core neurosurgical journals using a cross-sectional analysis. METHODS: Through review of 6 general neurosurgical journals, all interventional RCTs published from January 2009 to January 2019 were identified. Because it is difficult to objectively assess study outcome, the authors opted for a strict rating approach based on the statistical significance of unambiguously reported primary endpoints, and the reported statistical protocol. RESULTS: A total of 129 RCTs met the inclusion criteria. During the study period, the Journal of Neurosurgery published the largest number of RCTs (n = 40, 31%). Any potential COI was disclosed by 57%, and a mean of 12% of authors had a personal COI. Nonfinancial industry involvement was reported in 10%, while 31% and 20% received external support and sponsoring, respectively. Study registration was reported by 56%, while 51% of studies were blinded. Registration showed an increasing trend from 17% to 76% (p < 0.001). The median randomized sample size was 92 (interquartile range 50-153), and 8% were designed to investigate noninferiority or equality. Sixty-three RCTs (49%) unambiguously reported a primary endpoint, of which 13% were composite primary endpoints. In 43%, study outcome was positive, which was associated with a noninferiority design (31% vs 3%, p = 0.007) and a composite primary endpoint (46% vs 9%, p = 0.002). Potential COIs were not significantly associated with study positivity (69% vs 59%, p = 0.433). In the multivariate analysis, only a composite primary endpoint remained predictive of a positive study outcome (odds ratio 6.34, 95% confidence interval 1.51-33.61, p = 0.017). CONCLUSIONS: This analysis provides an overview of COIs and their potential influence on recent trials published in core neurosurgical journals. Reporting of primary endpoints, study registration, and uniform disclosure of COIs are crucial to ensure the quality of future neurosurgical randomized trials. COIs do not appear to significantly influence the outcome of randomized neurosurgical trials.

A Systematic Review and Meta-Analysis of Perioperative Parameters in Robot-Guided, Navigated, and Freehand Thoracolumbar Pedicle Screw Instrumentation.

BACKGROUND: Robotic guidance (RG) and navigation (NV) have been shown to reduce radiologic and clinically relevant pedicle screw malpositions. It remains unknown if there are any additional benefits to these techniques in intraoperative and perioperative end points. METHODS: We conducted a systematic review in MEDLINE, Embase, Scopus, and the Cochrane Library and identified controlled studies comparing RG, NV, and freehand (FH) thoracolumbar pedicle screw insertion and carried out random-effects meta-analyses. RESULTS: Thirty-two studies (24,008 patients) were included. Only 8 studies (26%) were randomized, and study quality was rated as very low or low in 24 cases (77%). Compared with NV, FH procedures showed longer length of hospital stay (Δ, 0.7 days; 95% confidence interval, 0.2-1.2; P = 0.006) and more overall complications (odds ratio, 1.6; 95% confidence interval, 1.3-1.9; P < 0.001). No statistically significant differences among RG and FH were identified, likely because of lack in statistical power (all P > 0.05). In particular, both RG and NV did not show increased intraoperative radiation use, as determined by seconds of fluoroscopy, compared with FH (both P > 0.05). CONCLUSIONS: It seems that navigation may offer potential benefits in perioperative outcomes such as length of hospital stay and overall complications, without significant increase in intraoperative radiation, which cannot yet be said for robotic guidance. The findings must be interpreted with caution, because the evidence is severely limited in both quantity and quality. Further evaluation will establish any demonstrable intraoperative or perioperative benefits to computer assistance, which may warrant the high costs often associated with these devices.

Pedicle Screw Revision in Robot-Guided, Navigated, and Freehand Thoracolumbar Instrumentation: A Systematic Review and Meta-Analysis.

OBJECTIVE: Various computer-based guidance systems have been devised to reduce costly screw-related complications, yet their clinical effectiveness has never been comparatively assessed in a meta-analysis. We aimed to evaluate the incidence of clinically relevant pedicle screw revisions among robot-guided, navigated, and freehand spinal instrumentation. METHODS: Controlled trials comparing robot-guided, navigated, or freehand spinal instrumentation for any indication and that specifically reported the proportion of patients who experienced pedicle screw revisions were included. Estimates were pooled using random-effects meta-analyses. Sensitivity analyses including zero-event trials and assessing per screw incidences were carried out. RESULTS: Among 37 studies (7095 patients), intraoperative revisions in robot-guided (odds ratio [OR], 3.6; 95% confidence interval [CI], 0.7-19.4; P = 0.14) and navigated (OR, 1.5; 95% CI, 0.3-7.2; P = 0.64) procedures were comparable to freehand. Although postoperative revisions were reduced in robot-guided (OR, 0.3; 95% CI, 0.1-0.9; P = 0.04) and navigated (OR, 0.3; 95% CI, 0.2-0.5; P < 0.001) procedures, statistical significance was lost in sensitivity analyses for robotic guidance, but not for navigation. The pooled incidence of malpositioned screws requiring postoperative revision was 2.1%. CONCLUSIONS: Based on the available data in the peer-reviewed literature, computer assistance in the form of robotic guidance or navigation has the potential to reduce the incidence of costly and clinically relevant postoperative revisions for screw malposition. It is essential to further investigate on a higher level of evidence if the clinical benefits of computer assistance warrant the high acquisition and maintenance costs inherent to these systems.