Re-endoscopic third ventriculostomy versus ventriculoperitoneal shunting in failed endoscopic third ventriculostomy in pediatric patients with hydrocephalus: A systematic review
Background: The objective of this research article is to compare endoscopic treatment versus shunting procedures for failed endoscopic third ventriculostomies (ETVs) in pediatric patients with hydrocephalus. Methods: We did a systematic review based on preferred reporting items for systematic reviews and meta-analyses guidelines on Studies involving pediatric patients (aged 0–18 years) diagnosed with hydrocephalus, reporting on the use of repeat ETV (Re-ETV) or Ventriculoperitoneal shunting (VPS) as a treatment option following failed ETV. Comparative studies, including randomized controlled trials, cohort studies, and any prospective studies, are included. Studies published in the English language conducted between 2001 and 2023 are included. Results: Forty articles were selected for full-text review. Out of which nine articles that clearly addressed the topic of Re-ETV and/or VPS placement after failure of primary ETV were deemed suitable for analysis. A data set of 663 patients was analyzed. Re-ETV was done in 220 patients (33.18%) and VPS Placement was done in 443 patients (66.81%). The primary ETV failure rates ranged from 16.6 to 60.89%. There was a higher failure rate of Re-ETV (74.98%) compared to VPS (22.26%) indicating that VPS is generally more successful as a secondary intervention. The presence of hemorrhage during primary ETV suggested more benefit from VPS placement rather than Re-ETV (P < 0.05). Conclusion: Our systematic review suggests that VPS placement is the more prevalent choice after primary ETV failure, likely due to its higher overall success rate and the nature of complications. The wide variability in failure rates and follow-up durations suggests that treatment outcomes can differ greatly between patients and studies. Decisions regarding secondary interventions should be individualized, considering patient-specific factors such as age, complications, and timing of intervention.
Artificial intelligence image analysis for Hounsfield units in preoperative thoracolumbar CT scans: an automated screening for osteoporosis in patients undergoing spine surgery
OBJECTIVE This study aimed to develop an artificial intelligence (AI) model for automatically detecting Hounsfield unit (HU) values at the L1 vertebra in preoperative thoracolumbar CT scans. This model serves as a screening tool for osteoporosis in patients undergoing spine surgery, offering an alternative to traditional bone mineral density measurement methods like dual-energy x-ray absorptiometry. METHODS The authors utilized two CT scan datasets, comprising 501 images, which were split into training, validation, and test subsets. The nnU-Net framework was used for segmentation, followed by an algorithm to calculate HU values from the L1 vertebra. The model’s performance was validated against manual HU calculations by expert raters on 56 CT scans. Statistical measures included the Dice coefficient, Pearson correlation coefficient, intraclass correlation coefficient (ICC), and Bland-Altman plots to assess the agreement between AI and human-derived HU measurements. RESULTS The AI model achieved a high Dice coefficient of 0.91 for vertebral segmentation. The Pearson correlation coefficient between AI-derived HU and human-derived HU values was 0.96, indicating strong agreement. ICC values for interrater reliability were 0.95 and 0.94 for raters 1 and 2, respectively. The mean difference between AI and human HU values was 7.0 HU, with limits of agreement ranging from −21.1 to 35.2 HU. A paired t-test showed no significant difference between AI and human measurements (p = 0.21). CONCLUSIONS The AI model demonstrated strong agreement with human experts in measuring HU values, validating its potential as a reliable tool for automated osteoporosis screening in spine surgery patients. This approach can enhance preoperative risk assessment and perioperative bone health optimization. Future research should focus on external validation and inclusion of diverse patient demographics to ensure broader applicability.
Transforaminal lumbar interbody fusion subsidence: computed tomography analysis of incidence, associated risk factors, and impact on outcomes
OBJECTIVE The aims of this study were to 1) define the incidence of transforaminal lumbar interbody fusion (TLIF) interbody subsidence; 2) determine the relative importance of preoperative and intraoperative patient- and instrumentation-specific risk factors predictive of postoperative subsidence using CT-based assessment; and 3) determine the impact of TLIF subsidence on postoperative complications and fusion rates. METHODS All adult patients who underwent one- or two-level TLIF for lumbar degenerative conditions at a multi-institutional academic center between 2017 and 2019 were retrospectively identified. Patients with traumatic injury, infection, malignancy, previous fusion at the index level, combined anterior-posterior procedures, surgery with greater than two TLIF levels, or incomplete follow-up were excluded. Interbody subsidence at the superior and inferior endplates of each TLIF level was directly measured on the endplate-facing surface of both coronal and sagittal CT scans obtained greater than 6 months postoperatively. Patients were grouped based on the maximum subsidence at each operative level classified as mild, moderate, or severe based on previously documented < 2-mm, 2- to 4-mm, and ≥ 4-mm thresholds, respectively. Univariate and regression analyses compared patient demographics, medical comorbidities, preoperative bone quality, surgical factors including interbody cage parameters, and fusion and complication rates across subsidence groups. RESULTS A total of 67 patients with 85 unique fusion levels met the inclusion and exclusion criteria. Overall, 28% of levels exhibited moderate subsidence and 35% showed severe subsidence after TLIF with no significant difference in the superior and inferior endplate subsidence. Moderate (≥ 2-mm) and severe (≥ 4-mm) subsidence were significantly associated with decreases in cage surface area and Taillard index as well as interbody cages with polyetheretherketone (PEEK) material and sawtooth surface geometry. Severe subsidence was also significantly associated with taller preoperative disc spaces, decreased vertebral Hounsfield units (HU), the absence of bone morphogenetic protein (BMP) use, and smooth cage surfaces. Regression analysis revealed decreases in Taillard index, cage surface area, and HU, and the absence of BMP use predicted subsidence. Severe subsidence was found to be a predictor of pseudarthrosis but was not significantly associated with revision surgery. CONCLUSIONS Patient-level risk factors for TLIF subsidence included decreased HU and increased preoperative disc height. Intraoperative risk factors for TLIF subsidence were decreased cage surface area, PEEK cage material, bullet cages, posterior cage positioning, smooth cage surfaces, and sawtooth surface designs. Severe subsidence predicted TLIF pseudarthrosis; however, the causality of this relationship remains unclear.
Transforming Outcomes of Spine Surgery—Exploring the Power of Enhanced Recovery After Surgery Protocol: A Systematic Review and Meta-Analyses of 15 198 Patients
BACKGROUND AND OBJECTIVES: Enhanced recovery after surgery (ERAS) protocols aim to optimize patient outcomes by reducing the surgical stress response, expediting recovery, and reducing care costs. We aimed to evaluate the impact of implementing ERAS protocols on the perioperative surgical outcomes and financial implications associated with spine surgeries. METHODS: A systematic review and meta-analysis of peer-reviewed studies directly comparing outcome differences between spine surgeries performed with and without utilization of ERAS pathways was conducted along Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS: Of 676 unique articles identified, 59 with 15 198 aggregate patients (7748 ERAS; 7450 non-ERAS) were included. ERAS-treated patients had shorter operative times (mean difference [MD]: 10.2 mins; P < .01), shorter hospitalizations (MD: 1.41 days, P < .01), fewer perioperative complications (relative risk [RR] = 0.64, P < .01), lower postoperative opioid use (MD of morphine equivalent dose: 164.36 mg; P < .01), and more rapid mobilization/time to first out-of-bed ambulation (MD: 0.92 days; P < .01). Spine surgeries employing ERAS were also associated with lower total costs (MD: $1140.26/patient; P < .01), especially in the United States (MD: $2869.11/patient, P < .01) and lower postoperative visual analog pain scores (MD = 0.56, P < .01), without any change in odds of 30-day readmission (RR: 0.80, P = .13) or reoperation (RR: 0.88, P = .60). Subanalyses based on the region of spine showed significantly lower length of stay in both cervical and lumbar surgeries implementing ERAS. Type of procedure showed a significantly lesser time-to-initiate mobilization in fusion surgeries using ERAS protocols compared with decompression. CONCLUSION: The present meta-analysis indicates that current literature supports ERAS implementation as a means of reducing care costs and safely accelerating hospital discharge for patients undergoing spine surgery.
Does diabetes affect outcome or reoperation rate after lumbar decompression or arthrodesis? A matched analysis of the Quality Outcomes Database data set
OBJECTIVE Diabetes mellitus (DM) is a known risk factor for postsurgical and systemic complications after lumbar spinal surgery. Smaller studies have also demonstrated diminished improvements in patient-reported outcomes (PROs), with increased reoperation and readmission rates after lumbar surgery in patients with DM. The authors aimed to examine longer-term PROs in patients with DM undergoing lumbar decompression and/or arthrodesis for degenerative pathology. METHODS The Quality Outcomes Database was queried for patients undergoing elective lumbar decompression and/or arthrodesis for degenerative pathology. Patients were grouped into DM and non-DM groups and optimally matched in a 1:1 ratio on 31 baseline variables, including the number of operated levels. Outcomes of interest were readmissions and reoperations at 30 and 90 days after surgery in addition to improvements in Oswestry Disability Index, back pain, and leg pain scores and quality-adjusted life-years at 90 days after surgery. RESULTS The matched decompression cohort comprised 7836 patients (3236 [41.3] females) with a mean age of 63.5 ± 12.6 years, and the matched arthrodesis cohort comprised 7336 patients (3907 [53.3%] females) with a mean age of 64.8 ± 10.3 years. In patients undergoing lumbar decompression, no significant differences in nonroutine discharge, length of stay (LOS), readmissions, reoperations, and PROs were observed. In patients undergoing lumbar arthrodesis, nonroutine discharge (15.7% vs 13.4%, p < 0.01), LOS (3.2 ± 2.0 vs 3.0 ± 3.5 days, p < 0.01), 30-day (6.5% vs 4.4%, p < 0.01) and 90-day (9.1% vs 7.0%, p < 0.01) readmission rates, and the 90-day reoperation rate (4.3% vs 3.2%, p = 0.01) were all significantly higher in the DM group. For DM patients undergoing lumbar arthrodesis, subgroup analyses demonstrated a significantly higher risk of poor surgical outcomes with the open approach. CONCLUSIONS Patients with and without DM undergoing lumbar spinal decompression alone have comparable readmission and reoperation rates, while those undergoing arthrodesis procedures have a higher risk of poor surgical outcomes up to 90 days after surgery. Surgeons should target optimal DM control preoperatively, particularly for patients undergoing elective lumbar arthrodesis.
Immunohistochemical markers predicting recurrence following resection and radiotherapy in chordoma patients: insights from a multicenter study [RETRACTED]
OBJECTIVE Chordomas are rare tumors that often recur regardless of surgery with negative margins and postoperative radiotherapy. The predictive accuracy of widely used immunohistochemical (IHC) markers in addressing the recurrence of skull base chordomas (SBCs) is yet to be determined. This study aimed to investigate IHC markers in the prediction of recurrence after SBC resection with adjuvant radiation therapy. METHODS The authors reviewed the records of patients who had treatment for SBC between January 2017 and June 2021 across the Mayo Clinic in Minnesota, Florida, and Arizona. Exclusion criteria included patients who had no histopathology or recurrence as an outcome. Histopathological markers included cytokeratin A1/A3 only, epithelial membrane antigen (EMA), S100 protein, pan-cytokeratin, IN1, GATA3, CAM5.2, OSCAR, and chondroid. Information from patient records was abstracted, including treatment, clinical and radiological follow-up duration, demographics, and histopathological factors. Decision tree and random forest classifiers were trained and tested to predict the recurrence based on unseen data using an 80/20 split. RESULTS A total of 38 patients with a diagnosis of SBC who underwent resection (gross-total resection: 42.1%; and subtotal resection: 57.9%) and radiation therapy were extracted from the medical records. The mean patient age was 48.2 (SD 19.6) years; most patients were male (n = 23; 60.5%) and White (n = 36; 94.7%). Pan-cytokeratin was associated with an increased risk of postoperative recurrence (OR 14.67, 95% CI 2.44–88.13; p = 0.00517) after resection and adjuvant radiotherapy. The decision tree analysis found pan-cytokeratin–positive tumors to have a 78% chance of being classified as a recurrence, with an accuracy of 75%. The distribution of minimal depth in the prediction of postoperative recurrence indicates that the most important variables were pan-cytokeratin, followed by cytokeratin A1/A3 and EMA. CONCLUSIONS The authors’ machine learning algorithm identified pan-cytokeratin as the largest contributor to recurrence among other IHC markers after SBC resection. Machine learning may facilitate the prediction of outcomes in rare tumors, such as chordomas.
Impact of preoperative spinal injections within 30 days of lumbar decompression on surgical outcomes: a matched institutional study
OBJECTIVE The authors sought to determine how the temporal proximity of lumbar epidural spinal injection prior to surgery impacts clinical outcomes (e.g., 30-day readmission, postoperative complications, CSF leak) in patients undergoing lumbar decompression without fusion. METHODS The authors queried their institutional registry to identify patients who underwent elective lumbar decompression for spondylotic pathology between January 2019 and March 2022 at multiple centers within the same hospital network. Patients were divided into groups based on the time between their surgical date and the most recent preoperative spinal injection: group 1, patients with duration < 1 month; group 2, 1–3 months; and group 3, no spinal injection within 3 months. Primary outcomes of interest were the length of hospital stay, postoperative complications, rate of intraoperative CSF leak, and rates of reoperation and hospital readmission. For patients in groups 1 and 2, the authors also recorded the number of injections within 12 months prior to surgery to better understand the effect of multiple recent injections. The independent Student t-test and Pearson’s chi-square test were mainly performed for univariate analyses of the continuous and categorical variables, respectively. RESULTS A total of 121 and 283 patients received a spinal injection at < 1 month and 1–3 months prior to surgery, respectively, and were separately matched in a 3:1 ratio with 2562 patients with no history of preoperative spinal injection within 3 months before surgery. Among the matched cohorts, patients who received spinal injections < 1 month before lumbar decompression had significantly higher risks of 30-day complication (7.4% vs 0.8%, OR 9.6, p < 0.001), 30-day readmission (5.8% vs 2.2%, OR 3.5, p = 0.049), and 90-day readmission (9.1% vs 2.8%, OR 3.5, p = 0.003) than patients with no history of spinal injection. However, compared with patients with no history of spinal injection, the patients who received spinal injections 1–3 months before surgery were not at higher risk for postoperative complications or readmission. The CSF leak rates were significantly different between the three patient cohorts (10.7% vs 6.7% vs 4.9% for the < 1 month, 1–3 months, and no injection cohorts, respectively; p = 0.02). CONCLUSIONS Lumbar decompression within 1 month of preoperative spinal injection was associated with higher risks of readmission and postoperative complications, including CSF leak. However, with the exception of CSF leak, these risks were no longer observed when spinal injection occurred 1–3 months prior to lumbar decompression.
Immunohistochemical markers predicting long-term recurrence following clival and spinal chordoma resection: a multicenter study
OBJECTIVE Chordomas are rare tumors from notochordal remnants and account for 1%–4% of all primary bone malignancies, often arising from the clivus and sacrum. Despite margin-negative resection and postoperative radiotherapy, chordomas often recur. Further, immunohistochemical (IHC) markers have not been assessed as predictive of chordoma recurrence. The authors aimed to identify the IHC markers that are predictive of postoperative long-term (≥ 1 year) chordoma recurrence by using trained multiple tree-based machine learning (ML) algorithms. METHODS The authors reviewed the records of patients who had undergone treatment for clival and spinal chordomas between January 2017 and June 2021 across the Mayo Clinic enterprise (Minnesota, Florida, and Arizona). Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient record. Decision tree and random forest classifiers were trained and tested to predict long-term recurrence based on unseen data using an 80/20 split. RESULTS One hundred fifty-one patients diagnosed and treated for chordomas were identified: 58 chordomas of the clivus, 48 chordomas of the mobile spine, and 45 chordomas sacrococcygeal in origin. Patients diagnosed with cervical chordomas were the oldest among all groups (58 ± 14 years, p = 0.009). Most patients were male (n = 91, 60.3%) and White (n = 139, 92.1%). Most patients underwent resection with or without radiation therapy (n = 129, 85.4%). Subtotal resection followed by radiation therapy (n = 51, 33.8%) was the most common treatment modality, followed by gross-total resection then radiation therapy (n = 43, 28.5%). Multivariate analysis showed that S100 and pan-cytokeratin are more likely to predict the increase in the risk of postoperative recurrence (OR 3.67, 95% CI 1.09–12.42, p= 0.03; and OR 3.74, 95% CI 0.05–2.21, p = 0.02, respectively). In the decision tree analysis, a clinical follow-up > 1897 days was found in 37% of encounters and a 90% chance of being classified for recurrence (accuracy = 77%). Random forest analysis (n = 500 trees) showed that patient age, type of surgical treatment, location of tumor, S100, pan-cytokeratin, and EMA are the factors predicting long-term recurrence. CONCLUSIONS The IHC and clinicopathological variables combined with tree-based ML tools successfully demonstrated a high capacity to identify recurrence patterns with an accuracy of 77%. S100, pan-cytokeratin, and EMA were the IHC drivers of recurrence. This shows the power of ML algorithms in analyzing and predicting outcomes of rare conditions of a small sample size.
Using machine learning to predict 30-day readmission and reoperation following resection of supratentorial high-grade gliomas: an ACS NSQIP study involving 9418 patients
OBJECTIVE High-grade gliomas (HGGs) are among the rarest yet most aggressive tumor types in neurosurgical practice. In the current literature, few studies have assessed the drivers of early outcomes following resection of these tumors and investigated their association with quality of care. The authors aimed to identify the clinical predictors for 30-day readmission and reoperation following HGG surgery using the American College of Surgeons (ACS) National Surgical Quality Improvement Project (NSQIP) database and sought to create web-based applications predicting each outcome. METHODS Using the ACS NSQIP database, the authors conducted a retrospective, multicenter cohort analysis of patients who underwent resection of supratentorial HGGs between January 1, 2016, and December 31, 2020. Demographics and comorbidities were extracted. The primary outcomes were 30-day unplanned readmission and reoperation. A stratified 80:20 split of the available data was carried out. Supervised machine learning algorithms were trained to predict 30-day outcomes. RESULTS A total of 9418 patients were included in our cohort. The observed rate of unplanned readmission within 30 days of surgery was 13.0% (n = 1221). In terms of predictors, weight, chronic steroid use, preoperative blood urea nitrogen level, and white blood cell count were associated with a higher risk of readmission. The observed rate of unplanned reoperation within 30 days of surgery was 5.2% (n = 489). In terms of predictors, increased weight, longer operative time, and more days between hospital admission and operation were associated with an increased risk of early reoperation. The random forest algorithm showed the highest predictive performance for early readmission (area under the curve [AUC] = 0.967), while the XGBoost algorithm showed the highest predictive performance for early reoperation (AUC = 0.985). Web-based tools for both outcomes were deployed ( https://glioma-readmission.herokuapp.com/ and https://glioma-reoperation.herokuapp.com/ ). CONCLUSIONS In this study, the authors provide the first nationwide analysis for short-term outcomes in patients undergoing resection of supratentorial HGGs. Multiple patient, hospital, and admission factors were associated with readmission and reoperation, confirmed by machine learning predicting patients’ prognosis, leading to better planning preoperatively and subsequently improved personalized patient care.
Bone morphogenetic proteins in spine surgery: a scientometric analysis to date
OBJECTIVE Bone morphogenetic proteins (BMPs) are part of the transforming growth factor–beta superfamily and are involved in bone formation and repair. In spine surgery, recombinant human BMP (rhBMP) is used as an alternative to autografts for spinal fusions. This study aimed to evaluate bibliometric parameters and citations of the literature on BMPs to provide an overview of how the field has evolved. METHODS A comprehensive search of the literature was conducted using Elsevier’s Scopus database to capture all the published and indexed studies relevant to BMPs from 1955 to the present. A discrete set of validated bibliometric parameters was extracted and analyzed. All statistical analyses were performed using R 4.1.1. RESULTS The 100 most cited articles were published between 1994 and 2018 by 472 unique authors in 40 sources (e.g., journals and books). On average, there were 279 citations per publication and 17.69 citations per publication per year. The United States had the publications with the most citations (n = 23,761), followed by Hong Kong (n = 580) and the United Kingdom (n = 490). The three institutions in the United States with the greatest number of publications in the field were Emory University (n = 14), Hughston Clinic (n = 9), Hospital for Special Surgery (n = 6), and University of California (n = 6). CONCLUSIONS The authors evaluated and characterized the 100 most cited articles about BMP. Most of the publications were clinical in nature and focused on BMP’s application in spine surgery. While early scientific efforts focused on basic science research to advance the understanding of BMP’s mechanism of action in promoting bone formation, the majority of the more recent publications are clinically focused. It will be beneficial to conduct more controlled clinical trials to compare the outcomes of BMP use with other methods.