Machine Learning Models for Predicting Dysphonia Following Anterior Cervical Discectomy and Fusion : A Swedish Registry Study

BACKGROUND Dysphonia is one of the more common complications following anterior cervical discectomy and fusion (ACDF). ACDF is the gold standard for treating degenerative cervical spine disorders, and identifying high-risk patients is therefore crucial. PURPOSE This study aimed to evaluate different machine learning models to predict persistent dysphonia after ACDF. STUDY DESIGN A retrospective review of the nationwide Swedish spine registry (Swespine). PATIENT SAMPLE All adults in the Swespine registry who underwent elective ACDF between 2006 and 2020. OUTCOME MEASURES The primary outcome was self-reported dysphonia lasting at least 1 month after surgery. Predictive performance was assessed using discrimination and calibration metrics. METHODS Patients with missing dysphonia data at the 1-year follow-up were excluded. Data preprocessing involved one-hot encoding categorical variables, scaling continuous variables, and imputing missing values. Four machine learning models (logistic regression, random forest (RF), gradient boosting, K-nearest neighbor) were employed. The models were trained and tested using an 80:20 data split and 5-fold cross-validation, with performance metrics guiding the selection of the best model for predicting persistent dysphonia. RESULTS In total, 2,708 were included in the study. Twelve key predictors were identified. Four machine learning models were tested, with the RF model achieving the best performance (AUC=0.794). The most significant predictors across models included preoperative NDI, EQ5D$_{index}$, preoperative neurology, number of operated levels, and use of a fusion cage. The RF model, chosen for its superior performance, showed high sensitivity and consistent accuracy, but a low specificity and positive predictive value. CONCLUSIONS In this study, machine learning models were employed to identify predictors of persistent dysphonia following ACDF. Among the models tested, the RF classifier demonstrated superior performance, with an AUC value of 0.790. The RF model identified NDI, EQ5D$_{index}$, and number of fused vertebrae as key variables. These findings underscore the potential of machine learning models in identifying patients at increased risk for dysphonia persisting for more than 1 month after surgery

Difference in Clinical Presentation and Surgical Outcomes in Pediatric and Adult Patients With Chiari Malformation Type 1: A Single Center Retrospective Study

INTRODUCTION: Chiari malformation type 1 (CM1) is a common congenital disorder affecting both children and adults. Although pediatric and adult CM1 patients share many characteristics, the differences between the groups are not fully described. METHOD: A comparative analysis was made of two previously defined cohorts of adult and pediatric non-syndromic CM1, surgically treated at the study center. Clinical outcomes were assessed using the Chicago Chiari outcome scale (CCOS) and radiological outcomes were measured as change in cerebellar tonsil and syringomyelia status. RESULTS: A total of 209 patients (73 pediatric, 136 adults) were included, with median ages of 11 and 33 years, respectively. The proportion of female patients (62% vs 78%) was higher in the adult population (p = 0.012). Headache (p = 0.007), neck pain (p = 0.000), vertigo (p = 0.007), and sensory symptoms (p = 0.000) were more common in adults, while scoliosis (p = 0.000) and sleep apnea (p = 0.015) were more common in the pediatric population. Preoperative imaging findings did not differ significantly. After posterior fossa decompression, both groups scored a median CCOS of 15 at early follow-up (3 vs 4 months), though the pediatric population had a more favorable distribution of CCOS scores (p = 0.003). Postoperatively, syringomyelia status did not differ significantly between groups, but cerebellar tonsil status improved more frequently in adults (64% vs 88%, p = 0.000). CONCLUSION: This study demonstrates that while headache is the most common presenting symptom in both pediatric and adult CM1 patients, pediatric patients are more likely to present with scoliosis and sleep apnea. In contrast adult patients more frequently experience headache, neck pain, vertigo, and sensory symptoms. There were no differences in other preoperative imaging variables and outcomes were favorable for most patients in both groups

Correction to: Predictors of intracranial hemorrhage in adult patients on extracorporeal membrane oxygenation: an observational cohort study

In the original publication of this article [1], the first author’s name should be changed from Alexander Fletcher Sandersjöö to Alexander Fletcher-Sandersjöö. The family name of the author is Fletcher-Sandersjöö

Evaluation of a Novel Teleradiology Technology for Image-Based Distant Consultations: Applications in Neurosurgery.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadIn emergency settings, fast access to medical imaging for diagnostic is pivotal for clinical decision making. Hence, a need has emerged for solutions that allow rapid access to images on small mobile devices (SMD) without local data storage. Our objective was to evaluate access times to full quality anonymized DICOM datasets, comparing standard access through an authorized hospital computer (AHC) to a zero-footprint teleradiology technology (ZTT) used on a personal computer (PC) or SMD using national and international networks at a regional neurosurgical center. Image datasets were sent to a senior neurosurgeon, outside the hospital network using either an AHC and a VPN connection or a ZTT (Image Over Globe (IOG)), on a PC or an SMD. Time to access DICOM images was measured using both solutions. The mean time using AHC and VPN was 250 ± 10 s (median 249 s (233-274)) while the same procedure using IOG took 50 ± 8 s (median 49 s (42-60)) on a PC and 47 ± 20 s (median 39 (33-88)) on a SMD. Similarly, an international consultation was performed requiring 23 ± 5 s (median 21 (16-33)) and 27 ± 1 s (median 27 (25-29)) for PC and SMD respectively. IOG is a secure, rapid and easy to use telemedicine technology facilitating efficient clinical decision making and remote consultations. Keywords: clinical decision-making; neurosurgery; remote consultation; telemedicine; teleradiology

Correction to: Predictors of intracranial hemorrhage in adult patients on extracorporeal membrane oxygenation: an observational cohort study.

[This corrects the article DOI: 10.1186/s40560-017-0223-2.]

Predictors of intracranial hemorrhage in adult patients on extracorporeal membrane oxygenation: an observational cohort study.

BACKGROUND: Intracranial hemorrhage (ICH) is a recognized complication of adults treated with extracorporeal membrane oxygenation (ECMO) and is associated with increased morbidity and mortality. However, the predictors of ICH in this patient category are poorly understood. The purpose of this study was to identify predictors of ICH in ECMO-treated adult patients. METHODS: We conducted a retrospective review of adult patients (≥18 years) treated with ECMO at the Karolinska University Hospital (Stockholm, Sweden) between September 2005 and June 2016, excluding patients with ICH upon admission or those who were treated with ECMO for less than 12 h. In a comparative analysis, the primary end-points were the difference in baseline characteristics and predictors of hemorrhage occurrence (ICH vs. non-ICH cohorts). The secondary end-point was difference in mortality between groups. Paired testing and uni- and multivariate regression models were applied. RESULTS: Two hundred and fifty-three patients were included, of which 54 (21%) experienced an ICH during ECMO treatment. The mortality for patients with ICH was 81% at 1 month and 85% at 6 months, respectively, compared to 28 and 33% in patients who did not develop ICH. When comparing ICH vs. non-ICH cohorts, pre-admission antithrombotic therapy (p = 0.018), high pre-cannulation Sepsis-related Organ Failure Assessment (SOFA) coagulation score (p = 0.015), low platelet count (p < 0.001), and spontaneous extracranial hemorrhage (p = 0.045) were predictors of ICH. In a multivariate regression model predicting ICH, pre-admission antithrombotic therapy and low platelet count demonstrated independent risk association. When comparing the temporal trajectories for coagulation variables in the days leading up to the detection of an ICH, plasma antithrombin significantly increased per patient over time (p = 0.014). No other temporal trajectories were found. CONCLUSIONS: ICH in adult ECMO patients is associated with a high mortality rate and independently associated with pre-admission antithrombotic therapy and low platelet count, thus highlighting important areas of potential treatment strategies to prevent ICH development

The Ever-Evolving Regulatory Landscape Concerning Development and Clinical Application of Machine Intelligence: Practical Consequences for Spine Artificial Intelligence Research

This paper analyzes the regulatory frameworks for artificial intelligence/machine learning AI/ML-enabled medical devices in the European Union (EU), the United States (US), and the Republic of Korea, with a focus on applications in spine surgery. The aim is to provide guidance for developers and researchers navigating regulatory pathways. A review of current literature, regulatory documents, and legislative frameworks was conducted. Key differences in regulatory bodies, risk classification, submission requirements, and approval pathways for AI/ML medical devices were examined in the EU, US, and Republic of Korea. The EU AI Act (2024) establishes a risk-based framework, requiring regulatory review based on device risk, with high-risk devices subject to stricter oversight. The US applies a more flexible approach, allowing multiple submission pathways and incorporating a focus on continuous learning. The Republic of Korea emphasizes possibilities of streamlined approval and with growing use of real-world data to support validation. Developers must ensure regulatory alignment early in the development process, focusing on key aspects like dataset quality, transparency, and continuous monitoring. Across all regions, the need for technical documentation, quality management systems, and bias mitigation are essential for approval. Developers are encouraged to adopt adaptable strategies to comply with evolving regulatory standards, ensuring models remain transparent, fair, and reliable. The EU’s comprehensive AI Act enforces stricter oversight, while the US and Korea offer more flexible pathways. Developers of spine surgery AI/ML devices must tailor development strategies to align with regional regulations, emphasizing transparent development, quality assurance, and postmarket monitoring to ensure approval success

Feasibility and accuracy of a robotic guidance system for navigated spine surgery in a hybrid operating room: a cadaver study.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadThe combination of navigation and robotics in spine surgery has the potential to accurately identify and maintain bone entry position and planned trajectory. The goal of this study was to examine the feasibility, accuracy and efficacy of a new robot-guided system for semi-automated, minimally invasive, pedicle screw placement. A custom robotic arm was integrated into a hybrid operating room (OR) equipped with an augmented reality surgical navigation system (ARSN). The robot was mounted on the OR-table and used to assist in placing Jamshidi needles in 113 pedicles in four cadavers. The ARSN system was used for planning screw paths and directing the robot. The robot arm autonomously aligned with the planned screw trajectory, and the surgeon inserted the Jamshidi needle into the pedicle. Accuracy measurements were performed on verification cone beam computed tomographies with the planned paths superimposed. To provide a clinical grading according to the Gertzbein scale, pedicle screw diameters were simulated on the placed Jamshidi needles. A technical accuracy at bone entry point of 0.48 ± 0.44 mm and 0.68 ± 0.58 mm was achieved in the axial and sagittal views, respectively. The corresponding angular errors were 0.94 ± 0.83° and 0.87 ± 0.82°. The accuracy was statistically superior (p < 0.001) to ARSN without robotic assistance. Simulated pedicle screw grading resulted in a clinical accuracy of 100%. This study demonstrates that the use of a semi-automated surgical robot for pedicle screw placement provides an accuracy well above what is clinically acceptable

Serial S100B Sampling Detects Intracranial Lesion Development in Patients on Extracorporeal Membrane Oxygenation

Introduction: Intracranial lesion development is a recognized complication in adults treated with extracorporeal membrane oxygenation (ECMO) and is associated with increased mortality. As neurological assessment during ECMO treatment remains challenging, protein biomarkers of cerebral injury could provide an opportunity to detect intracranial lesion development at an early stage. The aim of this study was to determine if serially sampled S100B could be used to detect intracranial lesion development during ECMO treatment.Methods: We conducted an observational cohort study of all patients treated with ECMO at ECMO Center Karolinska (Karolinska University Hospital, Stockholm, Sweden) between January and August 2018, excluding patients who did not undergo a computerized tomography scan (CT) during treatment. S100B was prospectively collected at hospital admission and then once daily. The primary end-point was any type of CT verified intracranial lesion. Receiver operating characteristics (ROC) curves and Cox proportional hazards models were employed.Results: Twenty-nine patients were included, of which 15 (52%) developed an intracranial lesion and exhibited higher levels of S100B overall. S100B had a robust association with intracranial lesion development, especially during the first 200 hours following admission. The best area-under-curve (AUC) to predict intracranial lesion development was 40 and 140 hours following ECMO initiation, were a S100B level of 0.69μg/L had an AUC of 0.81 (0.628-0.997). S100B levels were markedly increased following the development of intracranial hemorrhage.Conclusions: Serial serum S100B samples in ECMO patients were both significantly elevated and had an increasing trajectory in patients developing intracranial lesions. Larger prospective trials are warranted to validate these findings and to ascertain their clinical utility

Long-Term Outcomes Following Posterior Fossa Decompression in Pediatric Patients with Chiari Malformation Type 1, a Population-Based Cohort Study

OBJECTIVE: Posterior fossa decompression for Chiari malformation type I (Chiari 1) is effective and associated with a low risk of complication. However, up to 20% of patients may experience continued deficits or recurring symptoms after surgical intervention. For pediatric patients, there are no established tools to predict outcomes, and the risk factors for unfavorable postoperative outcomes are poorly understood. Hence, our aim was to investigate baseline data and early postoperative predictors of poor outcomes as determined by the Chicago Chiari outcome scale (CCOS). METHODS: All pediatric patients (\u3c 18 years) receiving a posterior fossa decompression for Chiari 1 between the years of 2005 and 2020 at the study center were eligible for inclusion. Patients with congenital anomalies were excluded. RESULTS: Seventy-one pediatric patients with a median age of 9 years were included. Most patients (58%) were females. Chiari 1 was associated with syringomyelia (51%), scoliosis (37%), and hydrocephalus (7%). Perioperative complications occurred in 13 patients (18%) of which two required additional procedures under general anesthesia. On multivariable proportional odds logistic regression, motor deficits (OR: 0.09; CI95%: [0.01-0.62]; p = 0.015), and surgical complications (OR: 0.16; CI95%: [0.41-0.66]; p = 0.011) were significant predictors of worse outcomes. The presence of syringomyelia was identified as a predictor of better outcomes (OR: 4.42 CI95% [1.02-19.35]; p = 0.048). A persistent hydrocephalus during the early postoperative period after posterior fossa decompression was a strong predictor of worse long-term CCOS (OR: 0.026; CI95%: [0.002-0.328]; p = 0.005). CONCLUSION: Results from this study indicate that the existence of motor deficits and syringomyelia prior to surgery, and surgical complications and persistent hydrocephalus despite posterior fossa decompression, were useful predictors of long-term outcome