Associations between surgeons' preoperative expectations of lumbar surgery and patient-reported 2-year outcomes.

PURPOSE: Surgeons' preoperative expectations of lumbar surgery may be associated with patient-reported postoperative outcomes. METHODS: Preoperatively spine surgeons completed a validated Expectations Survey for each patient estimating amount of improvement expected (range 0-100). Preoperative variables were clinical characteristics, spine-specific disability (ODI), and general health (RAND-12). Two years postoperatively patients again completed these measures and global assessments of satisfaction. Surgeons' expectations were compared to preoperative variables and to clinically important pre- to postoperative changes (MCID) in ODI, RAND-12, and pain and to satisfaction using hierarchical models. RESULTS: Mean expectations survey score for 402 patients was a 57 (IQR 44-68) reflecting moderate expectations. Lower scores were associated with preoperative older age, abnormal gait, sensation loss, vacuum phenomena, foraminal stenosis, prior surgery, and current surgery to more vertebrae (all p ≤ .05). Lower scores were associated postoperatively with not attaining MCID for the ODI (p = .02), RAND-12 (p = .01), and leg pain (p = .01). There were no associations between surgeons' scores and satisfaction (p = .06-.27). 55 patients (14%) reported unfavorable global outcomes and were more likely to have had fracture/infection/repeat surgery (OR 3.2, CI 1.6-6.7, p = .002). CONCLUSION: Surgeons' preoperative expectations were associated with patient-reported postoperative improvement in symptoms and function, but not with satisfaction. These findings are consistent with clinical practice in that surgeons expect some but not complete improvement from surgery and do not anticipate that any particular patient will have markedly unfavorable satisfaction ratings. In addition to preoperative discussions about expectations, patients and surgeons should acknowledge different types of outcomes and address them jointly in postoperative discussions.

A neural network model for detection and classification of lumbar spinal stenosis on MRI.

OBJECTIVES: To develop a three-stage convolutional neural network (CNN) approach to segment anatomical structures, classify the presence of lumbar spinal stenosis (LSS) for all 3 stenosis types: central, lateral recess and foraminal and assess its severity on spine MRI and to demonstrate its efficacy as an accurate and consistent diagnostic tool. METHODS: The three-stage model was trained on 1635 annotated lumbar spine MRI studies consisting of T2-weighted sagittal and axial planes at each vertebral level. Accuracy of the model was evaluated on an external validation set of 150 MRI studies graded on a scale of absent, mild, moderate or severe by a panel of 7 radiologists. The reference standard for all types was determined by majority voting and in case of disagreement, adjudicated by an external radiologist. The radiologists' diagnoses were then compared to the diagnoses of the model. RESULTS: The model showed comparable performance to the radiologist average both in terms of the determination of presence/absence of LSS as well as severity classification, for all 3 stenosis types. In the case of central canal stenosis, the sensitivity, specificity and AUROC of the CNN were (0.971, 0.864, 0.963) for binary (presence/absence) classification compared to the radiologist average of (0.786, 0.899, 0.842). For lateral recess stenosis, the sensitivity, specificity and AUROC of the CNN were (0.853, 0.787, 0.907) compared to the radiologist average of (0.713, 0.898, 805). For foraminal stenosis, the sensitivity, specificity and AUROC of the CNN were (0.942, 0.844, 0.950) compared to the radiologist average of (0.879, 0.877, 0.878). Multi-class severity classifications showed similarly comparable statistics. CONCLUSIONS: The CNN showed comparable performance to radiologist subspecialists for the detection and classification of LSS. The integration of neural network models in the detection of LSS could bring higher accuracy, efficiency, consistency, and post-hoc interpretability in diagnostic practices.

Deep-learning reconstructed lumbar spine 3D MRI for surgical planning: pedicle screw placement and geometric measurements compared to CT.

PURPOSE: To test equivalency of deep-learning 3D lumbar spine MRI with "CT-like" contrast to CT for virtual pedicle screw planning and geometric measurements in robotic-navigated spinal surgery. METHODS: Between December 2021 and June 2022, 16 patients referred for spinal fusion and decompression surgery with pre-operative CT and 3D MRI were retrospectively assessed. Pedicle screws were virtually placed on lumbar (L1-L5) and sacral (S1) vertebrae by three spine surgeons, and metrics (lateral deviation, axial/sagittal angles) were collected. Vertebral body length/width (VL/VW) and pedicle height/width (PH/PW) were measured at L1-L5 by three radiologists. Analysis included equivalency testing using the 95% confidence interval (CI), a margin of ± 1 mm (± 2.08° for angles), and intra-class correlation coefficients (ICCs). RESULTS: Across all vertebral levels, both combined and separately, equivalency between CT and MRI was proven for all pedicle screw metrics and geometric measurements, except for VL at L1 (mean difference: - 0.64 mm; [95%CI - 1.05, - 0.24]), L2 (- 0.65 mm; [95%CI - 1.11, - 0.20]), and L4 (- 0.78 mm; [95%CI - 1.11, - 0.46]). Inter- and intra-rater ICC for screw metrics across all vertebral levels combined ranged from 0.68 to 0.91 and 0.89-0.98 for CT, and from 0.62 to 0.92 and 0.81-0.97 for MRI, respectively. Inter- and intra-rater ICC for geometric measurements ranged from 0.60 to 0.95 and 0.84-0.97 for CT, and 0.61-0.95 and 0.93-0.98 for MRI, respectively. CONCLUSION: Deep-learning 3D MRI facilitates equivalent virtual pedicle screw placements and geometric assessments for most lumbar vertebrae, with the exception of vertebral body length at L1, L2, and L4, compared to CT for pre-operative planning in patients considered for robotic-navigated spine surgery.

MRI after Lumbar Spine Decompression and Fusion Surgery: Technical Considerations, Expected Findings, and Complications.

Postoperative MRI of the lumbar spine is a mainstay for detailed anatomic assessment and evaluation of complications related to decompression and fusion surgery. Key factors for reliable interpretation include clinical presentation of the patient, operative approach, and time elapsed since surgery. Yet, recent spinal surgery techniques with varying anatomic corridors to approach the intervertebral disc space and implanted materials have expanded the range of normal (expected) and abnormal (unexpected) postoperative changes. Modifications of lumbar spine MRI protocols in the presence of metallic implants, including strategies for metal artifact reduction, provide important diagnostic information. This focused review discusses essential principles for the acquisition and interpretation of MRI after lumbar spinal decompression and fusion surgery, highlights expected postoperative changes, and describes early and delayed postoperative complications with examples.

The anatomical positioning change of retroperitoneal organs in prone and lateral position: an assessment for single-prone position lateral lumbar surgery.

PURPOSE: There are reports that performing lateral lumbar interbody fusion (LLIF) in a prone, single position (single-prone LLIF) can be done safely in the prone position because the retroperitoneal organs reflect anteriorly with gravity. However, only a few study has investigated the safety of single-prone LLIF and retroperitoneal organ positioning in the prone position. We aimed to investigate the positioning of retroperitoneal organs in the prone position and evaluate the safety of single-prone LLIF surgery. METHODS: A total of 94 patients were retrospectively reviewed. The anatomical positioning of the retroperitoneal organs was evaluated by CT in the preoperative supine and intraoperative prone position. The distances from the centre line of the intervertebral body to the organs including aorta, inferior vena cava, ascending and descending colons, and bilateral kidneys were measured for the lumbar spine. An "at risk" zone was defined as distance less than 10 mm anterior from the centre line of the intervertebral body. RESULTS: Compared to supine preoperative CTs, bilateral kidneys at the L2/3 level as well as the bilateral colons at the L3/4 level had statistically significant ventral shift with prone positioning. The proportion of retroperitoneal organs within the at-risk zone ranged from 29.6 to 88.6% in the prone position. CONCLUSIONS: The retroperitoneal organs shifted ventrally with prone positioning. However, the amount of shift was not large enough to avoid risk for organ injuries and substantial proportion of patients had organs within the cage insertion corridor. Careful preoperative planning is warranted when considering single-prone LLIF.

Differences in imaging and clinical characteristics are associated with higher rates of decompression-fusion versus decompression-alone in women compared to men for lumbar degenerative spondylolisthesis.

PURPOSE: The goals were to ascertain if differences in imaging/clinical characteristics between women and men were associated with differences in fusion for lumbar degenerative spondylolisthesis. METHODS: Patients had preoperative standing radiographs, CT scans, and intraoperative fluoroscopic images. Symptoms and comorbidity were obtained from patients; procedure (fusion-surgery or decompression-alone) was obtained from intraoperative records. With fusion surgery as the dependent variable, men and women were compared in multivariable logistic regression models with clinical/imaging characteristics as independent variables. The sample was dichotomized, and analyses were repeated with separate models for men and women. RESULTS: For 380 patients (mean age 67, 61% women), women had greater translation, listhesis angle, lordosis, and pelvic incidence, and less diastasis and disc height (all p ≤ 0.03). The rate of fusion was higher for women (78% vs. 65%; OR 1.9, p = 0.008). Clinical/imaging variables were associated with fusion in separate models for men and women. Among women, in the final multivariable model, less comorbidity (OR 0.5, p = 0.05), greater diastasis (OR 1.6, p = 0.03), and less anterior disc height (OR 0.8, p = 0.0007) were associated with fusion. Among men, in the final multivariable model, opioid use (OR 4.1, p = 0.02), greater translation (OR 1.4, p = 0.0003), and greater diastasis (OR 2.4, p = 0.0002) were associated with fusion. CONCLUSIONS: There were differences in imaging characteristics between men and women, and women were more likely to undergo fusion. Differences in fusion within groups indicate that decisions for fusion were based on composite assessments of clinical and imaging characteristics that varied between men and women.

Performance of hybrid artificial intelligence in determining candidacy for lumbar stenosis surgery.

PURPOSE: Lumbar spinal stenosis (LSS) is a condition affecting several hundreds of thousands of adults in the United States each year and is associated with significant economic burden. The current decision-making practice to determine surgical candidacy for LSS is often subjective and clinician specific. In this study, we hypothesize that the performance of artificial intelligence (AI) methods could prove comparable in terms of prediction accuracy to that of a panel of spine experts. METHODS: We propose a novel hybrid AI model which computes the probability of spinal surgical recommendations for LSS, based on patient demographic factors, clinical symptom manifestations, and MRI findings. The hybrid model combines a random forest model trained from medical vignette data reviewed by surgeons, with an expert Bayesian network model built from peer-reviewed literature and the expert opinions of a multidisciplinary team in spinal surgery, rehabilitation medicine, interventional and diagnostic radiology. Sets of 400 and 100 medical vignettes reviewed by surgeons were used for training and testing. RESULTS: The model demonstrated high predictive accuracy, with a root mean square error (RMSE) between model predictions and ground truth of 0.0964, while the average RMSE between individual doctor's recommendations and ground truth was 0.1940. For dichotomous classification, the AUROC and Cohen's kappa were 0.9266 and 0.6298, while the corresponding average metrics based on individual doctor's recommendations were 0.8412 and 0.5659, respectively. CONCLUSIONS: Our results suggest that AI can be used to automate the evaluation of surgical candidacy for LSS with performance comparable to a multidisciplinary panel of physicians.

Comprehensive Error Analysis for Robotic-assisted Placement of Pedicle Screws in Pediatric Spinal Deformity: The Initial Learning Curve.

BACKGROUND: Surgical navigation improves pedicle screw insertion accuracy and reliability. Robotic-assisted spinal surgery and screw placement has not been fully assessed in pediatric patients with spine deformity undergoing posterior spinal fusion. The purpose of this study was to describe the learning curve for robotically assisted pedicle screw placement in pediatric patients. METHODS: A retrospective review on a consecutive series of the first 19 pediatric patients who underwent posterior spinal fusion by a single surgeon using robotic navigation was performed. Demographics, curve parameters, pedicle diameter, vertebral rotation, and additional outcome measures were recorded. Screw position was assessed with calibrated intraoperative 3-dimensional fluoroscopic images. All complications of planned and placed robotically placed screws were recorded. RESULTS: A total of 194 left-sided screws were planned as robot-assisted. One hundred sixty-eight of the robotically planned screws (86.6%) were placed with robot assistance; 29 robotically planned screws (15.0%) were abandoned or converted to freehand. The mean time per robotically placed screw was 3.6±2.4 minutes. Fifteen breaches (8.9%) and 1 anterior perforation occurred with 2 critical (>2 to 4 mm) breaches, 1 was associated with a durotomy, and both occurred in the first case. There were no intraoperative/postoperative neuromonitoring changes and no sequela from the durotomy. Six breaches occurred in the first case. The odds ratio of obtaining a breach in screws with a matched trajectory was 0.275 (95% confidence interval: 0.089-0.848). CONCLUSIONS: Screw time and accuracy improved and the number of breaches decreased after 10 cases. This series had 2 critical breaches (between 2 and 4 mm) on the first case. Overall, excluding the 2 critical breaches, 98.8% of robotically executed screws were placed without a critical breach, which is comparable to previous pediatric deformity studies. Caution should be exercised during the initial training period to avoid complications as experience and training lead to an improved understanding of surgical planning, skive, and soft-tissue pressure on the end-effector all of which can impact accuracy of robotically assisted pedicle screw placement. LEVEL OF EVIDENCE: Case Series, IV.

The incidence and risk factors for post-operative ileus after spinal fusion surgery: a multivariate analysis.

PURPOSE: Post-operative ileus is a recognized complication of surgery. Little is known about the incidence and risk factors for post-operative ileus following spinal fusion surgery. To report the incidence and to assess for independent risk factors of post-operative ileus after spinal fusion surgery. METHODS: Retrospective single-centre cohort study. Patients with prolonged or recurrent post-operative ileus were identified by review of hospital stay documentation. Patients with post-operative ileus were matched 1:2 to a control cohort without post-operative ileus. Uni and multi variate analyses were performed on demographic, comorbidity, surgical indication, medication, and peri-operative details to identify risk factors for post-operative ileus. RESULTS: Two thousand six hundred and twenty five patients underwent spinal fusion surgery between January 2012 and December 2012. Forty nine patients with post-operative ileus were identified (1.9 %). Post-operative length of hospital stay was significantly longer for patients with post-operative ileus (9.3 ± 5.2 days), than control patients (5.5 ± 3.2 days) (p < 0.001). Independent risk factors were Lactated Ringers solution (aOR: 2.12, p < 0.001), 0.9 % NaCl solution (aOR: 2.82, p < 0.001), and intra-operative hydromorphone (aOR: 2.31, p < 0.01) and a history of gastro-oesophageal reflux (aOR: 4.86, p = 0.03). Albumin administration (aOR: 0.09, p < 0.01) was protective against post-operative ileus. CONCLUSIONS: Post-operative ileus is multifactorial in origin, and this study identified intra-operative hydromorphone and post-operative crystalloid fluid administration ≥2 litres as independent risk factors for the development of ileus.

Reasons for Revision Surgery after Cervical Disc Arthroplasty based on Medical Device Reports Maintained by the United States Food and Drug Administration.

STUDY DESIGN: Retrospective Database review. OBJECTIVE: Analyze revisions of CDAs reported to the MAUDE database. SUMMARY OF BACKGROUND DATA: Cervical disc arthroplasty (CDA) has emerged as a motion-preserving alternative to anterior cervical discectomy and fusion (ACDF) for degenerative cervical disease, demonstrating comparable outcomes. Despite the availability of variable CDA designs, there is limited data on the specific complications of individual CDAs. The Drug Administration's Manufacturer and User Facility Device Experience (MAUDE) database has been used to systematically report complications associated with CDAs. However, data on specific reasons for CDA revision remains scarce. The purpose of this study is to compare common complications associated with revision for different CDAs. METHODS: The MAUDE database was queried from January 2005 to September 2023, including all nine FDA-approved CDAs. The full-text reports of each complication were categorized based on whether revision surgery was performed, the complications and the type of CDA collected and compared. RESULTS: A total of 678 revisions for nine CDAs were reported: Mobi-C (239), M6 (167), Prodisc-C (88), Prestige (60), PCM (44), Bryan (35), Secure (23), Simplify (21), and Discover (1). The top three complications associated with revision were migration (23.5%), neck pain (15.5%), and heterotopic ossification (6.6%). The most common complications per device were migration for Mobi-C (26.4%), Prodisc-C (21.3%), Prestige (24.6%), PCM (84.1%), Bryan (48.6%), Secure (30.4%), and Discover (100%). For M6, the most common complications associated with revision surgery were osteolysis (18.6%) and neck pain (18.6%), while neck pain (23.8%) was the most common for the Simplify. CONCLUSION: The MAUDE database highlights complications related to CDA revision in which the primary complications consistently include implant migration, neck pain, and heterotopic ossification ,varying in their rerelvance depending on the CDA.

Anterior cervical osteotomy of diffuse idiopathic skeletal hyperostosis lesions with computer-assisted navigation surgery: A case report.

Key Clinical Message: Diffuse idiopathic skeletal hyperostosis (DISH) involves spine ligament ossification. Computer-assisted navigation (CAN) effectively aids complex surgeries, such as anterior cervical osteotomy, to alleviate progressive DISH-related dysphagia. Abstract: We describe a 68-year-old man with sudden onset dysphagia to both solids and liquids. Radiographic Imaging revealed DISH lesions from C2 down to the thoracic spine. The patient was successfully treated with CAN anterior osteotomy and resection of DISH lesions from C3-C6 and had complete symptom relief within 2 weeks post-operatively.

Assessing intraoperative pedicle screw placement accuracy using biplanar radiographs compared to three-dimensional imaging.

To date, biplanar imaging (2D) has been the method of choice for pedicle screw (PS) positioning and verified for the anteroposterior view and (spinal midline) M-line method. In recent years, the use of intraoperative three-dimensional (3D) imaging has become available with the Gertzbein-Robbins system (GRS) to assess PS breach and positioning confirmation. The aim is to determine if 2D imaging is sufficient to assess PS position in comparison to advanced 3D imaging.Retrospective review of prospectively collected data from 204 consecutive adult patients who underwent posterior thoracic and lumbar instrumented fusion for degenerative spinal surgery by a single surgeon (2019-2022).Of the 204 patients, 187 (91.6%) had intraoperative images available for analysis. A total of 1044 PS implants were used; 922 (88.3%) were robotically placed. Postoperative CT scans were verified with M-line/GRS findings. Among 103 patients (50.5%) with a total of 362 screws, (34.7%) had postoperative CT, intraoperative 3D scan, and intraoperative 2D scan for analysis. Postoperative CT findings were consistent with all GRS findings, validating that 3D imaging was accurate. Screws (1%) were falsely verified by the M-line as 3D imaging confirmed false negative or positive findings.In our series, intraoperative 3D scan was as accurate as postoperative CT scan in assessing PS breach. A significant number of PS may be falsely read as accurate on 2D imaging, that is in fact inaccurate when assessed on 3D imaging. An intraoperative post-instrumentation 3D scan may be preferable to prevent postoperative recognition of a falsely verified screw on biplanar imaging.

Robot-Assisted Lumbar Pedicle Screw Placement Based on 3D Magnetic Resonance Imaging.

STUDY DESIGN: Human Cadaveric Study. OBJECTIVE: This study aims to explore the feasibility of using preoperative magnetic resonance imaging (MRI), zero-time-echo (ZTE) and spoiled gradient echo (SPGR), as source data for robotic-assisted spine surgery and assess the accuracy of pedicle screws. METHODS: Zero-time-echo and SPGR MRI scans were conducted on a human cadaver. These images were manually post-processed, producing a computed tomography (CT)-like contrast. The Mazor X robot was used for lumbar pedicle screw-place navigating of MRI. The cadaver underwent a postoperative CT scan to determine the actual position of the navigated screws. RESULTS: Ten lumbar pedicle screws were robotically navigated of MRI (4 ZTE; 6 SPGR). All MR-navigated screws were graded A on the Gertzbein-Robbins scale. Comparing preoperative robotic planning to postoperative CT scan trajectories: The screws showed a median deviation of overall 0.25 mm (0.0; 1.3), in the axial plane 0.27 mm (0.0; 1.3), and in the sagittal plane 0.24 mm (0.0; 0.7). CONCLUSION: This study demonstrates the first successful registration of MRI sequences, ZTE and SPGR, in robotic spine surgery here used for intraoperative navigation of lumbar pedicle screws achieving sufficient accuracy, showcasing potential progress toward radiation-free spine surgery.

Biomechanical Motion Changes in Adjacent and Noncontiguous Segments Following Single-Level Anterior Cervical Discectomy and Fusion: A Computed Tomography-Based 3D Motion Capture Study.

BACKGROUND: Anterior cervical discectomy and fusion (ACDF) is known to elicit adverse biomechanical effects on immediately adjacent segments; however, its impact on the kinematics of the remaining nonadjacent cervical levels has not been understood. This study aimed to explore the biomechanical impact of ACDF on kinematics beyond the immediate fusion site. We hypothesized that compensatory motion following single-level ACDF is not predictably distributed to adjacent segments due to compensation from noncontiguous levels. METHODS: Six fresh-frozen cervical spines (C2-T1) underwent fluoroscopic screening and sagittal and coronal reformats from computed tomography scans and were utilized to grade segmental degeneration. Each specimen was tested to 30° of flexion and extension intact and following single-level ACDF at the C5-C6 level. The motions of each vertebral body were tracked using 3-dimensional (3D) motion capture into an inverse kinematics model, facilitating correlations between the 3D reconstruction from computed tomography images and the 3D motion capture data. This model was used to calculate each level's flexion/extension range of motion (ROM). RESULTS: Single-level fusion at the C5-C6 level across all specimens resulted in a significant motion reduction of -6.8° (P = 0.002). No significant change in ROM occurred in the immediate adjacent segments C4-C5 (P = 0.07) or C6-C7 (P = 0.15). Hypermobility was observed in 2 specimens (33%) exclusively in adjacent segments. In contrast, the other 4 spines (66%) displayed hypermobility at noncontiguous segments. Hypermobility occurred in 42% (5/12) of the adjacent segments, 28% (5/18) of the noncontiguous segments, and 50% (3/6) of the cervicothoracic segments. CONCLUSION: Single-level ACDF impacts ROM beyond adjacent segments, extending to noncontiguous levels. Compensatory motion, not limited to adjacent levels, may be influenced by degenerative changes in noncontiguous segments. Surprisingly, hypermobility may not occur in adjacent segments after ACDF. CLINICAL RELEVANCE: Overall, the multifaceted biomechanical effects of ACDF underscore the need for a comprehensive understanding of cervical spine dynamics beyond immediate adjacency, and it needs to be taken into consideration when planning single-level ACDF.

An Artificial Intelligence-Based Support Tool for Lumbar Spinal Stenosis Diagnosis from Self-Reported History Questionnaire.

OBJECTIVES: Symptomatic lumbar spinal stenosis (LSS) leads to functional impairment and pain. While radiologic characterization of the morphological stenosis grade can aid in the diagnosis, it may not always correlate with patient symptoms. Artificial intelligence (AI) may diagnose symptomatic LSS in patients solely based on self-reported history questionnaires. METHODS: We evaluated multiple machine learning (ML) models to determine the likelihood of LSS using a self-reported questionnaire in patients experiencing low back pain and/or numbness in the legs. The questionnaire was built from peer-reviewed literature and a multidisciplinary panel of experts. Random forest, lasso logistic regression, support vector machine, gradient boosting trees, deep neural networks, and automated machine learning models were trained and performance metrics were compared. RESULTS: Data from 4827 patients (4690 patients without LSS: mean age 62.44, range 27-84 years, 62.8% females, and 137 patients with LSS: mean age 50.59, range 30-71 years, 59.9% females) were retrospectively collected. Among the evaluated models, the random forest model demonstrated the highest predictive accuracy with an area under the receiver operating characteristic curve (AUROC) between model prediction and LSS diagnosis of 0.96, a sensitivity of 0.94, a specificity of 0.88, a balanced accuracy of 0.91, and a Cohen's kappa of 0.85. CONCLUSIONS: Our results indicate that ML can automate the diagnosis of LSS based on self-reported questionnaires with high accuracy. Implementation of standardized and intelligence-automated workflow may serve as a supportive diagnostic tool to streamline patient management and potentially lower health care costs.

The Impact of the COVID-19 Pandemic on Ambulatory Lumbar Spine Decompression Surgery.

Background Only a few studies have examined the impact of the coronavirus disease 2019 pandemic on spine ambulatory surgeries and changes in trends. Therefore, we investigated trends during the pre-pandemic period and three pandemic stages in patients undergoing lumbar decompression procedures in the ambulatory surgery (AMS) setting. Methodology A total of 2,670 adult patients undergoing one- or two-level lumbar decompression surgery were retrospectively reviewed. Patients were categorized into the following four groups: 1: pre-pandemic (before the pandemic from January 1, 2019, to March 16, 2020); 2: restricted period (when elective surgery was canceled from March 17, 2020, to June 30, 2020); 3: post-restricted 2020 (July 1, 2020, to December 31, 2020, before vaccination); and 4: post-restricted 2021 (January 1, 2021 to December 31, 2021 after vaccination). Simple and multivariable logistic regression analyses as well as retrospective interrupted time series (ITS) analysis were conducted comparing AMS patients in the four periods. Results Patients from the restricted pandemic period were younger and healthier, which led to a shorter length of stay (LOS). The ITS analysis demonstrated a significant drop in mean LOS at the beginning of the restricted period and recovered to the pre-pandemic levels in one year. Multivariable logistic regression analyses indicated that the pandemic was an independent factor influencing the LOS in post-restricted phases. Conclusions As the post-restricted 2020 period itself might be independently influenced by the pandemic, these results should be taken into account when interpreting the LOS of the patients undergoing ambulatory spine surgery in post-restricted phases.

Severe Intervertebral Vacuum Phenomenon is Associated With Higher Preoperative Low Back Pain, ODI, and Indication for Fusion in Patients With Degenerative Lumbar Spondylolisthesis.

STUDY DESIGN: Retrospective study of prospective collected data. OBJECTIVE: To analyze the association between intervertebral vacuum phenomenon (IVP) and clinical parameters in patients with degenerative spondylolisthesis. SUMMARY OF BACKGROUND DATA: IVP is a sign of advanced disc degeneration. The correlation between IVP severity and low back pain in patients with degenerative spondylolisthesis has not been previously analyzed. METHODS: We retrospectively analyzed patients with degenerative spondylolisthesis who underwent surgery. Vacuum phenomenon was measured on computed tomography scan and classified into mild, moderate, and severe. A lumbar vacuum severity (LVS) scale was developed based on vacuum severity. The associations between IVP at L4/5 and the LVS scale, preoperative and postoperative low back pain, as well as the Oswestry Disability Index was assessed. The association of IVP at L4/5 and the LVS scale and surgical decision-making, defined as decompression alone or decompression and fusion, was assessed through univariable logistic regression analysis. RESULTS: A total of 167 patients (52.7% female) were included in the study. The median age was 69 years (interquartile range 62-72). Overall, 100 (59.9%) patients underwent decompression and fusion and 67 (40.1%) underwent decompression alone. The univariable regression demonstrated a significantly increased odds ratio (OR) for back pain in patients with more severe IVP at L4/5 [OR=1.69 (95% CI 1.12-2.60), P =0.01]. The univariable regressions demonstrated a significantly increased OR for increased disability with more severe L4/L5 IVP [OR=1.90 (95% CI 1.04-3.76), P =0.04] and with an increased LVS scale [OR=1.17 (95% CI 1.02-1.35), P =0.02]. IVP severity of the L4/L5 were associated with higher indication for fusion surgery. CONCLUSION: Our study showed that in patients with degenerative spondylolisthesis undergoing surgery, the severity of vacuum phenomenon at L4/L5 was associated with greater preoperative back pain and worse Oswestry Disability Index. Patients with severe IVP were more likely to undergo fusion.

Predicting conversion of ambulatory ACDF patients to inpatient: a machine learning approach.

BACKGROUND CONTEXT: Machine learning is a powerful tool that has become increasingly important in the orthopedic field. Recently, several studies have reported that predictive models could provide new insights into patient risk factors and outcomes. Anterior cervical discectomy and fusion (ACDF) is a common operation that is performed as an outpatient procedure. However, some patients are required to convert to inpatient status and prolonged hospitalization due to their condition. Appropriate patient selection and identification of risk factors for conversion could provide benefits to patients and the use of medical resources. PURPOSE: This study aimed to develop a machine-learning algorithm to identify risk factors associated with unplanned conversion from outpatient to inpatient status for ACDF patients. STUDY DESIGN/SETTING: This is a machine-learning-based analysis using retrospectively collected data. PATIENT SAMPLE: Patients who underwent one- or two-level ACDF in an ambulatory setting at a single specialized orthopedic hospital between February 2016 to December 2021. OUTCOME MEASURES: Length of stay, conversion rates from ambulatory setting to inpatient. METHODS: Patients were divided into two groups based on length of stay: (1) Ambulatory (discharge within 24 hours) or Extended Stay (greater than 24 hours but fewer than 48 hours), and (2) Inpatient (greater than 48 hours). Factors included in the model were based on literature review and clinical expertise. Patient demographics, comorbidities, and intraoperative factors, such as surgery duration and time, were included. We compared the performance of different machine learning algorithms: Logistic Regression, Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost). We split the patient data into a training and validation dataset using a 70/30 split. The different models were trained in the training dataset using cross-validation. The performance was then tested in the unseen validation set. This step is important to detect overfitting. The performance was evaluated using the area under the curve (AUC) of the receiver operating characteristics analysis (ROC) as the primary outcome. An AUC of 0.7 was considered fair, 0.8 good, and 0.9 excellent, according to established cut-offs. RESULTS: A total of 581 patients (59% female) were available for analysis. Of those, 140 (24.1%) were converted to inpatient status. The median age was 51 (IQR 44-59), and the median BMI was 28 kg/m2 (IQR 24-32). The XGBoost model showed the best performance with an AUC of 0.79. The most important features were the length of the operation, followed by sex (based on biological attributes), age, and operation start time. The logistic regression model and the SVM showed worse results, with an AUC of 0.71 each. CONCLUSIONS: This study demonstrated a novel approach to predicting conversion to inpatient status in eligible patients for ambulatory surgery. The XGBoost model showed good predictive capabilities, superior to the older machine learning approaches. This model also revealed the importance of surgical duration time, BMI, and age as risk factors for patient conversion. A developing field of study is using machine learning in clinical decision-making. Our findings contribute to this field by demonstrating the feasibility and accuracy of such methods in predicting outcomes and identifying risk factors, although external and multi-center validation studies are needed.

Intravenous Ketorolac Substantially Reduces Opioid Use and Length of Stay After Lumbar Fusion: A Randomized Controlled Trial.

STUDY DESIGN: A randomized, double-blinded, placebo-controlled trial. OBJECTIVE: To examine the effect of intravenous ketorolac (IV-K) on hospital opioid use compared with IV-placebo (IV-P) and IV acetaminophen (IV-A). SUMMARY OF BACKGROUND DATA: Controlling postoperative pain while minimizing opioid use after lumbar spinal fusion is an important area of study. PATIENTS AND METHODS: Patients aged 18 to 75 years undergoing 1 to 2 level lumbar fusions between April 2016 and December 2019 were included. Patients with chronic opioid use, smokers, and those on systemic glucocorticoids or contraindications to study medications were excluded. A block randomization scheme was used, and study personnel, hospital staff, and subjects were blinded to the assignment. Patients were randomized postoperatively. The IV-K group received 15 mg (age > 65) or 30 mg (age < 65) every six hours (q6h) for 48 hours, IV-A received 1000 mg q6h, and IV-P received normal saline q6h for 48 hours. Demographic and surgical details, opioid use in morphine milliequivalents, opioid-related adverse events, and length of stay (LOS) were recorded. The primary outcome was in-hospital opioid use up to 72 hours. RESULTS: A total of 171 patients were included (58 IV-K, 55 IV-A, and 58 IV-P) in the intent-to-treat (ITT) analysis, with a mean age of 57.1 years. The IV-K group had lower opioid use at 72 hours (173 ± 157 mg) versus IV-A (255 ± 179 mg) and IV-P (299 ± 179 mg; P = 0.000). In terms of opiate use, IV-K was superior to IV-A ( P = 0.025) and IV-P ( P = 0.000) on ITT analysis, although on per-protocol analysis, the difference with IV-A did not reach significance ( P = 0.063). When compared with IV-P, IV-K patients reported significantly lower worst ( P = 0.004), best ( P = 0.001), average ( P = 0.001), and current pain ( P = 0.002) on postoperative day 1, and significantly shorter LOS ( P = 0.009) on ITT analysis. There were no differences in opioid-related adverse events, drain output, clinical outcomes, transfusion rates, or fusion rates. CONCLUSIONS: By reducing opioid use, improving pain control on postoperative day 1, and decreasing LOS without increases in complications or pseudarthrosis, IV-K may be an important component of "enhanced recovery after surgery" protocols.

Transient neurological deficit following midthoracic decompression for severe stenosis: a series of three cases.

PURPOSE: To report three cases of transient perioperative neurological deficit in the absence of direct cord insult following decompression of the severely stenotic thoracic spine. METHODS: The clinical and radiographic electronic medical records of three patients who underwent decompression for severe midthoracic stenosis with transient neurological deficits perioperatively were reviewed. The cases are presented with consideration of possible underlying mechanisms and multimodality intraoperative monitoring (IOM) findings. RESULTS: Two patients had neurologic changes on IOM and Stagnara wake-up test, the remaining patient had absent motor and sensory potentials at baseline and throughout the case. IOM changes were observed immediately following decompression in the absence of direct cord insult or displacement. Postoperatively all patients experienced neurological motor deficits which presented as complete paralysis of the right lower extremity in two of the patients and the left lower extremity in one patient. The deficit was transient-improvement of motor strength occurred between 1 and 13 months of follow-up in all patients. CONCLUSION: Decompression of a severely stenotic region of the thoracic spinal cord may lead to a complete yet transient motor deficit in the perioperative period in the absence of direct mechanical cord insult. Potential etiologies include ischemia-reperfusion injury, microthrombi, and altered perfusion due to internal recoil of spinal cord architecture following decompression. IOM may show conspicuous findings in such events, however, may not be relied upon when baseline potentials are sub-optimal. Recognition of this short-lived neurological deficit following decompression of the severely stenotic thoracic spine will improve preoperative patient counseling and merits further study for determination of the precise pathophysiology.