Are large language models valid tools for patient information on lumbar disc herniation? The spine surgeons' perspective.

Introduction: Generative AI is revolutionizing patient education in healthcare, particularly through chatbots that offer personalized, clear medical information. Reliability and accuracy are vital in AI-driven patient education. Research question: How effective are Large Language Models (LLM), such as ChatGPT and Google Bard, in delivering accurate and understandable patient education on lumbar disc herniation? Material and methods: Ten Frequently Asked Questions about lumbar disc herniation were selected from 133 questions and were submitted to three LLMs. Six experienced spine surgeons rated the responses on a scale from "excellent" to "unsatisfactory," and evaluated the answers for exhaustiveness, clarity, empathy, and length. Statistical analysis involved Fleiss Kappa, Chi-square, and Friedman tests. Results: Out of the responses, 27.2% were excellent, 43.9% satisfactory with minimal clarification, 18.3% satisfactory with moderate clarification, and 10.6% unsatisfactory. There were no significant differences in overall ratings among the LLMs (p = 0.90); however, inter-rater reliability was not achieved, and large differences among raters were detected in the distribution of answer frequencies. Overall, ratings varied among the 10 answers (p = 0.043). The average ratings for exhaustiveness, clarity, empathy, and length were above 3.5/5. Discussion and conclusion: LLMs show potential in patient education for lumbar spine surgery, with generally positive feedback from evaluators. The new EU AI Act, enforcing strict regulation on AI systems, highlights the need for rigorous oversight in medical contexts. In the current study, the variability in evaluations and occasional inaccuracies underline the need for continuous improvement. Future research should involve more advanced models to enhance patient-physician communication.

The use of the Core Yellow Flags Index for the assessment of psychosocial distress in patients undergoing surgery of the cervical spine.

BACKGROUND: Psychosocial distress (the presence of yellow flags) has been linked to poor outcomes in spine surgery. The Core Yellow Flags Index (CYFI), a short instrument assessing the 4 main yellow flags, was developed for use in patients undergoing lumbar spine surgery. This study evaluated its ability to predict outcome in patients undergoing cervical spine surgery. METHODS: Patients with degenerative spinal disorders (excluding myelopathy) operated in one centre, from 2015 to 2019, were asked to complete the CYFI at baseline and the Core Outcome Measures Index (COMI) at baseline and 3 and 12 months after surgery. The relationship between CYFI and COMI scores at baseline as well as the predictive ability of the CYFI on the COMI follow-up scores were tested using structural equation modelling. RESULTS: From 731 eligible patients, 547 (61.0 ± 12.5 years; 57.2% female) completed forms at all three timepoints. On a cross-sectional basis, preoperative CYFI and COMI scores were highly correlated (ß = 0.54, in men and 0.51 in women; each p < 0.001). CYFI added significantly and independently to the prediction of COMI at 3 months' FU in men (ß = 0.36) and 12 months' FU in men and women (both ß = 0.20) (all p < 0.001). CONCLUSION: The CYFI had a low to moderate but significant and independent association with cervical spine surgery outcomes. Implementing the CYFI in the preoperative workup of these patients could help refine outcome predictions and better manage patient expectations.

Reliability of a New Digital Tool for Photographic Analysis in Quantifying Body Asymmetry in Scoliosis.

Background: Advancements in non-ionizing methods for quantifying spinal deformities are crucial for assessing and monitoring scoliosis. In this study, we analyzed the observer variability of a newly developed digital tool for quantifying body asymmetry from clinical photographs. Methods: Prospective observational multicenter study. Initially, a digital tool was developed using image analysis software, calculating quantitative measures of body asymmetry. This tool was integrated into an online platform that exports data to a database. The tool calculated 10 parameters, including angles (shoulder height, axilla height, waist height, right and left waistline angles, and their difference) and surfaces of the left and right hemitrunks (shoulders, waists, pelvises, and total). Subsequently, an online training course on the tool was conducted for twelve observers not involved in its development (six research coordinators and six spine surgeons). Finally, 15 standardized back photographs of adolescent idiopathic scoliosis patients were selected from a multicenter image bank, representing various clinical scenarios (different age, gender, curve type, BMI, and pre- and postoperative images). The 12 observers measured the photographs at two different times with a three-week interval. For the second round, the images were randomly mixed. Inter- and intra-observer variabilities of the measurements were analyzed using intraclass correlation coefficients (ICCs), and reliability was measured by the standard error of measurement (SEM). Group comparisons were made using Student's t-test. Results: The mean inter-observer ICC for the ten measurements was 0.981, the mean intra-observer ICC was 0.937, and SEM was 0.3-1.3°. The parameter with the strongest inter- and intra-observer validity was the difference in waistline angles 0.994 and 0.974, respectively, while the highest variability was found with the waist height angle 0.963 and 0.845, respectively. No test-retest differences (p > 0.05) were observed between researchers (0.948 ± 0.04) and surgeons (0.925 ± 0.05). Conclusion: We developed a new digital tool integrated into an online platform demonstrating excellent reliability and inter- and intra-observer variabilities for quantifying body asymmetry in scoliosis patients from a simple clinical photograph. The method could be used for assessing and monitoring scoliosis and body asymmetry without radiation.

Comparing image normalization techniques in an end-to-end model for automated modic changes classification from MRI images.

Introduction: Modic Changes (MCs) are MRI alterations in spine vertebrae's signal intensity. This study introduces an end-to-end model to automatically detect and classify MCs in lumbar MRIs. The model's two-step process involves locating intervertebral regions and then categorizing MC types (MC0, MC1, MC2) using paired T1-and T2-weighted images. This approach offers a promising solution for efficient and standardized MC assessment. Research question: The aim is to investigate how different MRI normalization techniques affect MCs classification and how the model can be used in a clinical setting. Material and methods: A combination of Faster R-CNN and a 3D Convolutional Neural Network (CNN) is employed. The model first identifies intervertebral regions and then classifies MC types (MC0, MC1, MC2) using paired T1-and T2-weighted lumbar MRIs. Two datasets are used for model development and evaluation. Results: The detection model achieves high accuracy in identifying intervertebral areas, with Intersection over Union (IoU) values above 0.7, indicating strong localization alignment. Confidence scores above 0.9 demonstrate the model's accurate levels identification. In the classification task, standardization proves the best performances for MC type assessment, achieving mean sensitivities of 0.83 for MC0, 0.85 for MC1, and 0.78 for MC2, along with balanced accuracy of 0.80 and F1 score of 0.88. Discussion and conclusion: The study's end-to-end model shows promise in automating MC assessment, contributing to standardized diagnostics and treatment planning. Limitations include dataset size, class imbalance, and lack of external validation. Future research should focus on external validation, refining model generalization, and improving clinical applicability.

A decade of experience in over 300 surgically treated spine patients with long-term oral anticoagulation: a propensity score matched cohort study.

PURPOSE: The aim of this study was to investigate the risks and outcomes of patients with long-term oral anticoagulation (OAC) undergoing spine surgery. METHODS: All patients on long-term OAC who underwent spine surgery between 01/2005 and 06/2015 were included. Data were prospectively collected within our in-house Spine Surgery registry and retrospectively supplemented with patient chart and administrative database information. A 1:1 propensity score-matched group of patients without OAC from the same time interval served as control. Primary outcomes were post-operative bleeding, wound complications and thromboembolic events up to 90 days post-surgery. Secondary outcomes included intraoperative blood loss, length of hospital stay, death and 3-month post-operative patient-rated outcomes. RESULTS: In comparison with the control group, patients with OAC (n = 332) had a 3.4-fold (95%CI 1.3-9.0) higher risk for post-operative bleeding, whereas the risks for wound complications and thromboembolic events were comparable between groups. The higher bleeding risk was driven by a higher rate of extraspinal haematomas (3.3% vs. 0.6%; p = 0.001), while there was no difference in epidural haematomas and haematoma evacuations. Risk factors for adverse events among patients with OAC were mechanical heart valves, posterior neck surgery, blood loss > 1000 mL, age, female sex, BMI > 30 kg/m2 and post-operative PTT levels. At 3-month follow-up, most patients reported favourable outcomes with no difference between groups. CONCLUSION: Although OAC patients have a higher risk for complications after spine surgery, the risk for major events is low and patients benefit similarly from surgery.

Evaluation of "appropriate use criteria" for surgical decision-making in lumbar degenerative spondylolisthesis. A controlled, multicentre, prospective observational study.

INTRODUCTION: Selecting patients with lumbar degenerative spondylolisthesis (LDS) for surgery is difficult. Appropriate use criteria (AUC) have been developed to clarify the indications for LDS surgery but have not been evaluated in controlled studies. METHODS: This prospective, controlled, multicentre study involved 908 patients (561 surgical and 347 non-surgical controls; 69.5 ± 9.7y; 69% female), treated as per normal clinical practice. Their appropriateness for surgery was afterwards determined using the AUC. They completed the Core Outcome Measures Index (COMI) at baseline and 12 months' follow-up. Multiple regression adjusting for confounders evaluated the influence of appropriateness designation and treatment received on the 12-month COMI and achievement of MCIC (≥ 2.2-point-reduction). RESULTS: As per convention, appropriate (A) and uncertain (U) groups were combined for comparison with the inappropriate (I) group. For the adjusted 12-month COMI, the benefit of surgery relative to non-surgical care was not significantly greater for the A/U than the I group (p = 0.189). There was, however, a greater treatment effect of surgery for those with higher baseline COMI (p = 0.035). The groups' adjusted probabilities of achieving MCIC were: 83% (A/U, receiving surgery), 71% (I, receiving surgery), 50% (A/U, receiving non-surgical care), and 32% (I, receiving non-surgical care). CONCLUSIONS: A/U patients receiving surgery had the highest chances of achieving MCIC, but the AUC were not able to identify which patients had a greater treatment effect of surgery relative to non-surgical care. The identification of other characteristics that predict a greater treatment effect of surgery, in addition to baseline COMI, is required to improve decision-making.

Patient-reported outcomes 1 and 2 years after transforaminal thoracic interbody fusion (TTIF).

STUDY DESIGN: Retrospective Cohort Study with prospectively collected data. PURPOSE: Transforaminal interbody fusion was initially designed for the lumbar spine. A similar approach was later introduced for the thoracic spine (TTIF). Here we report the surgical technique and the Core Outcome Measures Index (COMI) at 1-year and 2-year follow-ups, as well as the sagittal radiographic kyphosis correction of TTIF, achieved at 1 year and the latest follow-up. METHODS: All TTIF procedures from 2012 to 2020 were included. COMI scores were collected preoperatively and at 1- and 2-year follow-ups. The sagittal angle between the upper and lower endplates at the segment where TTIF was performed was measured on preoperative, 1-year postoperative, and last available radiographs. RESULTS: Seventy-nine TTIF procedures were performed for 64 patients (36% males; mean age 67.5 (SD 15.3) years). COMI score reduced from a mean value of 8.1 (SD 1.4) preoperatively to 4.7 (SD 2.7) at 1-year follow-up and 4.7 (SD 2.7) at 2-year follow-up. The mean correction of segmental kyphosis was 10.8 (SD 7.3, p < 0.0001) degrees at 1-year follow-up and 9.3 (SD 7.0, p < 0.0001) degrees at the final follow-up 3.4 (SD 1.4) years after the operation. Kaplan-Meier analysis for reoperations showed a 5-year survival of 91% (95% CI 0.795-1) for primary TTIF operations and survival of 77% (95% CI 0.651-0.899) for TTIFs performed after earlier fusion operations. CONCLUSIONS: TTIF is a feasible procedure in the thoracic spine. Kyphosis correction of approximately 10° was maintained at 1-year and final follow-up. Over 69% at 1-year and 61% at 2-year follow-up achieved MCID for COMI.

Far Lateral Lumbar Decompression Using the Far-Lateral Approach: Patient Reported Outcome is Associated with the Involved Vertebral Level and Coronal Segmental Angle.

STUDY DESIGN: Single centre retrospective study of prospectively collected data. OBJECTIVE: Analyse factors associated with patient reported outcome after far lateral decompression surgery (FLDS) for lumbar nerve root compression using the far-lateral approach. SUMMARY OF BACKGROUND DATA: To date, no studies have investigated the influence of vertebral level, coronal segmental Cobb angle, and the nature of the compressive tissue (hard/soft) on patient reported outcome following FLDS. METHODS: Patients who had undergone FLDS between 2005 and 2020 were included. Coronal segmental angle (CSCA) was measured on preoperative, posteroanterior radiographs. Primary outcome measure was the Core Outcome Measures Index (COMI) score at 2 years' follow-up (2Y-FU). Patients who had undergone microsurgical decompression using a midline approach (MID) served as a comparator group. RESULTS: There were 148 FLDS and 463 MID patients. In both groups there was a significant improvement in COMI score from preoperative to 2Y-FU (P<0.0001), with greater improvement in patients treated at higher vertebral levels than in those treated at L5/S1 (P=0.014). Baseline COMI, ASA grade, BMI, and low back pain as the "chief complaint" all had a significant association with the 2-year COMI score. The nature of compressive tissue showed no association with COMI score at 2Y-FU. In the FLDS group, there was a statistically significant correlation between the preoperative CSCA and change in COMI score preoperatively to 2Y-FU (P<0.001). The association was retained in multiple regression analysis controlling for confounders. A one-degree increase in CSCA was associated with a 0.35-point worse COMI score at 2Y-FU (P=0.003). CONCLUSION: Treatment of far lateral nerve root compression showed overall good patient reported outcome, but with less improvement with advanced coronal segmental angulation. Modified approaches and techniques might be preferable for the level L5/S1.

Automatic Calculation of Cervical Spine Parameters Using Deep Learning: Development and Validation on an External Dataset.

STUDY DESIGN: Retrospective data analysis. OBJECTIVES: This study aims to develop a deep learning model for the automatic calculation of some important spine parameters from lateral cervical radiographs. METHODS: We collected two datasets from two different institutions. The first dataset of 1498 images was used to train and optimize the model to find the best hyperparameters while the second dataset of 79 images was used as an external validation set to evaluate the robustness and generalizability of our model. The performance of the model was assessed by calculating the median absolute errors between the model prediction and the ground truth for the following parameters: T1 slope, C7 slope, C2-C7 angle, C2-C6 angle, Sagittal Vertical Axis (SVA), C0-C2, Redlund-Johnell distance (RJD), the cranial tilting (CT) and the craniocervical angle (CCA). RESULTS: Regarding the angles, we found median errors of 1.66° (SD 2.46°), 1.56° (1.95°), 2.46° (SD 2.55), 1.85° (SD 3.93°), 1.25° (SD 1.83°), .29° (SD .31°) and .67° (SD .77°) for T1 slope, C7 slope, C2-C7, C2-C6, C0-C2, CT, and CCA respectively. As concerns the distances, we found median errors of .55 mm (SD .47 mm) and .47 mm (.62 mm) for SVA and RJD respectively. CONCLUSIONS: In this work, we developed a model that was able to accurately predict cervical spine parameters from lateral cervical radiographs. In particular, the performances on the external validation set demonstrate the robustness and the high degree of generalizability of our model on images acquired in a different institution.

Fixed coronal malalignment (CM) in the lumbar spine independently impacts disability in adult spinal deformity (ASD) patients when considering the obeid-CM (O-CM) classification.

BACKGROUND: Postoperative flatback has been described in detail for sagittal plane considerations over the past 2 decades, and its correlations with disability are now accepted. Fixed Coronal Malalignment (CM) has been less described, and some authors report no significant association with the clinical outcome. The O-CM classification analyses CM and incorporates specific modifiers for each curve type. PURPOSE: This study evaluates the O-CM classification modifiers according to age, sagittal alignment, and patient-reported outcome measures (PROMs). Our hypothesis is that fixed CM correlates with PROMs independently from sagittal alignment and age. STUDY DESIGN: Retrospective analysis of a large adult spinal deformity (ASD) database prospectively collected. PATIENT SAMPLE: We included 747 patients from the database with long lumbar fusion (more than 3 levels), with at least two years of follow-up. Three categories of patients met the inclusion criteria (prior surgery at baseline and no revision surgery afterward, prior surgery at baseline and revision afterward, no prior surgery at baseline but fusion>3 levels and 2 years follow-up). OUTCOME MEASURES: All patients completed the Oswestry Disability Index (ODI), Short Form 36 (SF36), and Scoliosis Research Society 22 scores. METHODS: The patients were classified according to the six modifiers of the O-CM classification. Central Sacral Vertical Line (CSVL) above 2, 3, and 4 cm's impact on PROMs was analyzed. Multivariate analysis was performed on the relationship between PROMS and age, global tilt (GT), and CM modifiers. RESULTS: After multivariate analysis using age and GT as confounding factors, we found that CM independently affects PROMs starting at 2 cm offset. Disability increases linearly with CSVL. Patients classified with 2B modifiers have the worst SRS-22 total score, social life, and self-image. CONCLUSION: In a fused spine, CM independently affects disability in ASD patients. Disability increases linearly with CSVL. Despite previous reports that failed to find correlations of CM with PROMs, our study showed that fixed postoperative CM, according to O-CM classification, correlates independently from sagittal malalignment with worse PROMs. LEVEL OF EVIDENCE: III.

The Epidemiology of Spondylodiscitis in Germany: A Descriptive Report of Incidence Rates, Pathogens, In-Hospital Mortality, and Hospital Stays between 2010 and 2020.

BACKGROUND: Spondylodiscitis can lead to significant morbidity and mortality. Understanding its up-to-date epidemiological characteristics and trends is important to improve patient care. METHODS: This study analyzed trends in the incidence rate of spondylodiscitis cases in Germany between 2010 and 2020, as well as the pathogens, in-hospital mortality rate, and length of hospital stay. Data were obtained from the Federal Statistical Office and the Institute for the Hospital Remuneration System database. The ICD-10 codes "M46.2-", "M46.3-" and "M46.4-" were evaluated. RESULTS: The incidence rate of spondylodiscitis increased to 14.4/100,000 inhabitants, with 59.6% cases occurring in patients 70 years or older and affecting mainly the lumbar spine (56.2%). Absolute case numbers increased from 6886 by 41.6% to 9753 in 2020 (IIR = 1.39, 95% CI 0.62-3.08). Staphylococci and Escherichia coli were the most coded pathogens. The proportion of resistant pathogens was 12.9%. In-hospital mortality rates increased to a maximum of 64.7/1000 patients in 2020, intensive care unit treatment was documented in 2697 (27.7%) cases, and the length of stay per case was 22.3 days. CONCLUSION: The sharply increasing incidence and in-hospital mortality rate of spondylodiscitis highlights the need for patient-centered therapy to improve patient outcomes, especially in the geriatric, frail population, which is prone to infectious diseases.

Increased incidence of vertebral fractures in German adults from 2009 to 2019 and the analysis of secondary diagnoses, treatment, costs, and in-hospital mortality.

The aim of this cross-sectional study was to present the nationwide rates of hospitalized patients with vertebral fractures over one decade and to comprehensively analyze the treatment characteristics and direct costs incurred in 2019. Therefore, the trends in the incidence rate were quantified based on annual ICD-10 diagnosis codes from all German medical facilities between 2009 and 2019, provided by the Federal Statistical Office (Destatis). The ICD-10 Codes "S12.0-2; S22.0-; S32.0-, and S32.1-2" were evaluated. The relative change from 2009 through 2019 was determined. Using data from the Institute for Hospital Remuneration Systems (InEK) for 2019 the secondary diagnoses, OPS-codes, intensive care unit (ICU) treatment, in-hospital mortality, the proportion of G-DRGs and cumulative costs were evaluated. The documented number of vertebral fractures increased by 45.6% between 2009 and 2019 to an incidence of 150.7 per 100,000 inhabitants. The lumbar spine was most commonly affected with an incidence of 70.5/100,000 inhabitants in 2019 (46.8% of all vertebral fractures). The highest increases were seen in the numbers of subaxial cervical fractures (+ 121.2%) and sacral fractures (+ 306.6%). Of all vertebral fractures in 2019, 63.7% were diagnosed in women and 69.0% in patients aged 70 years or older. Osteoporosis was documented in 17.9% of cases as a concomitant diagnosis. In 10.1% of all cases, an ICU treatment was documented. The in-hospital mortality was 2.0% in 2019. I68D was the most frequently used G-DRG code, accounting for 33.3% of cases. The total direct costs for inpatient treatment in 2019 amounted to €589,205,715. The evaluation of 955,091 vertebral fractures showed a sharp increase in the nation-wide incidence rate. The presented age and sex distribution, the comorbidity profile and the in-hospital mortality rate indicate the importance of comprehensive geriatric assessment and emphasize the need for spinal care centers to be established.

Does loss to follow-up lead to an overestimation of treatment success? Findings from a spine surgery registry of over 15,000 patients.

PURPOSE: Patient-reported outcome measures (PROMs) are integral to the assessment of treatment success, but loss to follow-up (attrition) may lead to bias in the results reported. We sought to evaluate the extent, nature and implications of attrition in a long-established, single-centre spine registry. METHODS: The registry contained the data of 15,264 consecutive spine surgery patients. PROMs included the Core Outcome Measures Index (COMI) and a rating of the Global Treatment Outcome (GTO) and Satisfaction with Care. Baseline characteristics associated with returning a 12-month PROM (= "responder") were analysed (logistic regression). The 3-month outcomes of 12-month responders versus 12-month non-responders were compared (ANOVA and Chi-square). RESULTS: In total, 14,758/15,264 (97%) patients (60 ± 17y; 46% men) had consented to the use of their registry data for research. Preoperative, 3-month post-operative and 12-month post-operative PROMs were returned by 91, 90 and 86%, respectively. Factors associated with being a 12-month responder included: greater age, born in the country of the study, no private/semi-private insurance, better baseline status (lower COMI score), fewer previous surgeries, less comorbidity and no perioperative medical complications. 12-month non-responders had shown significantly worse outcomes in their 3-month PROMs than had 12-month responders (respectively, 66% vs 80% good GTO ("treatment helped/helped a lot"); 77% vs 88% satisfied/very satisfied; and 49% vs 63% achieved MCIC on COMI). CONCLUSION: Although attrition in this cohort was relatively low, 12-month non-responders displayed distinctive characteristics and their early outcomes were significantly worse than those of 12-month responders. If loss to follow-up is not addressed, treatment success will likely be overestimated, with erroneously optimistic results being reported.

Prevention of Surgical Site Infections in Spine Surgery: An International Survey of Clinical Practices Among Expert Spine Surgeons.

STUDY DESIGN: Questionnaire-based survey. OBJECTIVES: Surgical site infection (SSI) is a common complication in spine surgery but universal guidelines for SSI prevention are lacking. The objectives of this study are to depict a global status quo on implemented prevention strategies in spine surgery, common themes of practice and determine key areas for future research. METHODS: An 80-item survey was distributed among spine surgeons worldwide via email. The questionnaire was designed and approved by an International Consensus Group on spine SSI. Consensus was defined as more than 60% of participants agreeing to a specific prevention strategy. RESULTS: Four hundred seventy-two surgeons participated in the survey. Screening for Staphylococcus aureus (SA) is not common, whereas preoperative decolonization is performed in almost half of all hospitals. Body mass index (BMI) was not important for surgery planning. In contrast, elevated HbA1c level and hypoalbuminemia were often considered as reasons to postpone surgery. Cefazoline is the common drug for antimicrobial prophylaxis. Alcohol-based chlorhexidine is mainly used for skin disinfection. Double-gloving, wound irrigation, and tissue-conserving surgical techniques are routine in the operating room (OR). Local antibiotic administration is not common. Wound closure techniques and postoperative wound dressing routines vary greatly between the participating institutions. CONCLUSIONS: With this study we provide an international overview on the heterogeneity of SSI prevention strategies in spine surgery. We demonstrated a large heterogeneity for pre-, peri- and postoperative measures to prevent SSI. Our data illustrated the need for developing universal guidelines and for testing areas of controversy in prospective clinical trials.

Association between sagittal alignment and loads at the adjacent segment in the fused spine: a combined clinical and musculoskeletal modeling study of 205 patients with adult spinal deformity.

PURPOSE: Sagittal malalignment is a risk factor for mechanical complications after surgery for adult spinal deformity (ASD). Spinal loads, modulated by sagittal alignment, may explain this relationship. The aims of this study were to investigate the relationships between: (1) postoperative changes in loads at the proximal segment and realignment, and (2) absolute postoperative loads and postoperative alignment measures. METHODS: A previously validated musculoskeletal model of the whole spine was applied to study a clinical sample of 205 patients with ASD. Based on clinical and radiographic data, pre-and postoperative patient-specific alignments were simulated to predict loads at the proximal segment adjacent to the spinal fusion. RESULTS: Weak-to-moderate associations were found between pre-to-postop changes in lumbar lordosis, LL (r = - 0.23, r = - 0.43; p < 0.001), global tilt, GT (r = 0.26, r = 0.38; p < 0.001) and the Global Alignment and Proportion score, GAP (r = 0.26, r = 0.37; p < 0.001), and changes in compressive and shear forces at the proximal segment. GAP score parameters, thoracic kyphosis measurements and the slope of upper instrumented vertebra were associated with changes in shear. In patients with T10-pelvis fusion, moderate-to-strong associations were found between postoperative sagittal alignment measures and compressive and shear loads, with GT showing the strongest correlations (r = 0.75, r = 0.73, p < 0.001). CONCLUSIONS: Spinal loads were estimated for patient-specific full spinal alignment profiles in a large cohort of patients with ASD pre-and postoperatively. Loads on the proximal segments were greater in association with sagittal malalignment and malorientation of proximal vertebra. Future work should explore whether they provide a causative mechanism explaining the associated risk of proximal junction complications.

External validation of the deep learning system "SpineNet" for grading radiological features of degeneration on MRIs of the lumbar spine.

BACKGROUND: Magnetic resonance imaging (MRI) is used to detect degenerative changes of the lumbar spine. SpineNet (SN), a computer vision-based system, performs an automated analysis of degenerative features in MRI scans aiming to provide high accuracy, consistency and objectivity. This study evaluated SN's ratings compared with those of an expert radiologist. METHOD: MRIs of 882 patients (mean age, 72 ± 8.8 years) with degenerative spinal disorders from two previous trials carried out in our spine center between 2011 and 2019, were analyzed by an expert radiologist. Lumbar segments (L1/2-L5/S1) were graded for Pfirrmann Grades (PG), Spondylolisthesis (SL) and Central Canal Stenosis (CCS). SN's analysis for the equivalent parameters was generated. Agreement between methods was analyzed using kappa (κ), Spearman correlation (ρ) and Lin's concordance correlation (ρc) coefficients and class average accuracy (CAA). RESULTS: 4410 lumbar segments were analyzed. κ statistics showed moderate to substantial agreement in PG between the radiologist and SN depending on spinal level (range κ 0.63-0.77, all levels together 0.72; range CAA 45-68%, all levels 55%), slight to substantial agreement for SL (range κ 0.07-0.60, all levels 0.63; range CAA 47-57%, all levels 56%) and CCS (range κ 0.17-0.57, all levels 0.60; range CAA 35-41%, all levels 43%). SN tended to record more pathological features in PG than did the radiologist whereas the contrary was the case for CCS. SL showed an even distribution between methods. CONCLUSION: SN is a robust and reliable tool with the ability to grade degenerative features such as PG, SL or CCS in lumbar MRIs with moderate to substantial agreement compared to the current gold-standard, the radiologist. It is a valuable alternative for analyzing MRIs from large cohorts for diagnostic and research purposes.

Surgeons' risk perception in ASD surgery: The value of objective risk assessment on decision making and patient counselling.

BACKGROUND: Surgeons often rely on their intuition, experience and published data for surgical decision making and informed consent. Literature provides average values that do not allow for individualized assessments. Accurate validated machine learning (ML) risk calculators for adult spinal deformity (ASD) patients, based on 10 year multicentric prospective data, are currently available. The objective of this study is to assess surgeon ASD risk perception and compare it to validated risk calculator estimates. METHODS: Nine ASD complete (demographics, HRQL, radiology, surgical plan) preoperative cases were distributed online to 100 surgeons from 22 countries. Surgeons were asked to determine the risk of major complications and reoperations at 72 h, 90 d and 2 years postop, using a 0-100% risk scale. The same preoperative parameters circulated to surgeons were used to obtain ML risk calculator estimates. Concordance between surgeons' responses was analyzed using intraclass correlation coefficients (ICC) (poor < 0.5/excellent > 0.85). Distance between surgeons' and risk calculator predictions was assessed using the mean index of agreement (MIA) (poor < 0.5/excellent > 0.85). RESULTS: Thirty-nine surgeons (74.4% with > 10 years' experience), from 12 countries answered the survey. Surgeons' risk perception concordance was very low and heterogeneous. ICC ranged from 0.104 (reintervention risk at 72 h) to 0.316 (reintervention risk at 2 years). Distance between calculator and surgeon prediction was very large. MIA ranged from 0.122 to 0.416. Surgeons tended to overestimate the risk of major complications and reintervention in the first 72 h and underestimated the same risks at 2 years postop. CONCLUSIONS: This study shows that expert surgeon ASD risk perception is heterogeneous and highly discordant. Available validated ML ASD risk calculators can enable surgeons to provide more accurate and objective prognosis to adjust patient expectations, in real time, at the point of care.

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.

Management and outcome of spinal implant-associated surgical site infections in patients with posterior instrumentation: analysis of 176 cases.

PURPOSE: The management of implant-associated surgical site infections (SSI) in patients with posterior instrumentation is challenging. Evidence regarding the most appropriate treatment and the need for removal of implants is equivocal. We sought to evaluate the management and outcome of such patients at our institution. METHODS: We searched our prospectively documented databases for eligible patients with posterior spinal instrumentation, excluding the cervical spine (January 2008-June 2018). Patient files were reviewed, demographic data and treatment details were recorded. Patient-reported outcome (PRO) was assessed with the Core Outcome Measures Index (COMI) preoperatively and postoperatively at 3 and 12 months. RESULTS: A total of 170 patients underwent 210 revisions for 176 SSIs. Two-thirds presented within four weeks (105/176, 59.7%, median 22.5d, 7d-11.1y). The most common pathogens were Staphylococcus aureus (n = 79/210, 37.6%) and Staphylococcus epidermidis (n = 56/210, 26.7%). Debridement and implant retention was performed in 135/210 (64.3%) revisions and partial replacement in 62/210 (29.5%). In 28/176 SSI (15.9%), persistent infection required multiple revisions (≤ 4). Surgery was followed by intravenous and oral antimicrobial treatment (10-12w). In 139/176 SSIs (79%) with ≥ 1y follow-up, infection was cured in 115/139 (82.7%); relapse occurred in 9 (relapse rate: 5.1%). Two patients (1.4%) died. COMI decreased significantly (8.2 ± 1.5 vs. 4.8 ± 2.9, p < 0.0001) over 12 months. 72.7% of patients were (very) satisfied with their care. CONCLUSION: Patients with SSI after posterior (thoraco-)lumbo(-sacral) instrumentation can be successfully treated in most cases with surgical and specific antibiotic treatment. An interdisciplinary approach is recommended. Loose implants should be replaced. In some cases, multiple revisions may be necessary. Patient outcomes were satisfactory.

Is There a Difference in Clinical Features, Microbiological Epidemiology and Effective Empiric Antimicrobial Therapy Comparing Healthcare-Associated and Community-Acquired Vertebral Osteomyelitis?

BACKGROUND: Empiric antibiotic therapy for suspected vertebral osteomyelitis (VO) should be initiated immediately in severely ill patients, and might be necessary for culture-negative VO. The current study aimed to identify differences between community-acquired (CA) and healthcare-associated (HA) VO in terms of clinical presentation, causative pathogens, and antibiotic susceptibility. METHODS: Cases of adult patients with VO treated at a German university orthopaedic trauma center between 2000 and 2020 were retrospectively reviewed. Patient history was used to distinguish between CA and HA VO. Susceptibility of antibiotic regimens was assessed based on antibiograms of the isolated pathogens. RESULTS: A total of 155 patients (with a male to female ratio of 1.3; and a mean age of 66.1 ± 12.4 years) with VO were identified. In 74 (47.7%) patients, infections were deemed healthcare-associated. The most frequently identified pathogens were Staphylococcus aureus (HAVO: 51.2%; CAVO: 46.8%), and Coagulase-negative Staphylococci (CoNS, HAVO: 31.7%; CAVO: 21.3%). Antibiograms of 45 patients (HAVO: n = 22; CAVO: n = 23) were evaluated. Significantly more methicillin-resistant isolates, mainly CoNS, were found in the HAVO cohort (27.3%). The highest rate of resistance was found for cefazolin (HAVO: 45.5%; CAVO: 26.1%). Significantly higher rates of resistances were seen in the HAVO cohort for mono-therapies with meropenem (36.4%), piperacillin-tazobactam (31.8%), ceftriaxone (27.3%), and co-amoxiclav (31.8%). The broadest antimicrobial coverage was achieved with either a combination of piperacillin-tazobactam + vancomycin (CAVO: 100.0%; HAVO: 90.9%) or meropenem + vancomycin (CAVO: 100.0%; HAVO: 95.5%). CONCLUSION: Healthcare association is common in VO. The susceptibility pattern of underlying pathogens differs from CAVO. When choosing an empiric antibiotic, combination therapy must be considered.