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Bajaj AI, Yap N, Derman PB, Konakondla S, Kashlan ON, Telfeian AE, Hofstetter CP. Comparative analysis of perioperative characteristics and early outcomes in transforaminal endoscopic lumbar diskectomy: general anesthesia versus conscious sedation. Eur Spine J 2023:10.1007/s00586-023-07792-4. [PMID: 37450041 DOI: 10.1007/s00586-023-07792-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 05/18/2023] [Accepted: 05/21/2023] [Indexed: 07/18/2023]
Abstract
PURPOSE To better understand how anesthesia type impacts patient selection and recovery in TELD, we conducted a multicenter prospective study which evaluates the differences in perioperative characteristics and outcomes between patients who underwent TELD with either general anesthesia (GA) or conscious sedation (CS). METHODS We prospectively collected data from all TELD performed by five neurosurgeons at five different medical centers between February and October of 2022. The study population was dichotomized by anesthesia scheme, creating CS and GA cohorts. This study's primary outcomes were the Oswetry Disability Index (ODI) and the Visual Analog Scale (VAS) for back and leg pain, assessed preoperatively and at 2-week follow-up. RESULTS A total of 52 patients underwent TELD for symptomatic lumbar disk herniation. Twenty-three patients received conscious sedation with local anesthesia, and 29 patients were operated on under general anesthesia. Patients who received CS were significantly older (60.0 vs. 46.7, p < 0.001) and had lower BMI (28.2 vs. 33.4, p = 0.005) than patients under GA. No intraoperative or anesthetic complications occurred in the CS and GA cohorts. Improvement at 2-week follow-up in ODI, VAS-back, and VAS-leg was greater in patients receiving CS relative to patients under GA, but these differences were not statistically significant. CONCLUSION In our multicenter prospective analysis of 52 patients undergoing TELD, we found that patients receiving CS were significantly older and had significantly lower BMI compared to patients under GA. On subgroup analysis, no statistically significant differences were found in the improvement of PROMs between patients in the CS and GA group.
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Affiliation(s)
- Ankush I Bajaj
- Department of Neurosurgery, Rhode Island Hospital, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Natalie Yap
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Peter B Derman
- Texas Back Institute, 6020 West Parker Rd, Plano, TX, 75093, USA
| | - Sanjay Konakondla
- Department of Neurosurgery, Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA, 17822, USA
| | - Osama N Kashlan
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Albert E Telfeian
- Department of Neurosurgery, Rhode Island Hospital, The Warren Alpert Medical School of Brown University, Providence, RI, USA
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Tang OY, Bajaj AI, Zhao K, Rivera Perla KM, Mary Ying YL, Jyung RW, Liu JK. In Reply: Association of Patient Frailty With Vestibular Schwannoma Resection Outcomes and Machine Learning Development of a Vestibular Schwannoma Risk Stratification Score. Neurosurgery 2022; 91:e141-e142. [DOI: 10.1227/neu.0000000000002155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 07/29/2022] [Indexed: 11/19/2022] Open
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Tang OY, Bajaj AI, Zhao K, Liu JK. Patient frailty association with cerebral arteriovenous malformation microsurgical outcomes and development of custom risk stratification score: an analysis of 16,721 nationwide admissions. Neurosurg Focus 2022; 53:E14. [DOI: 10.3171/2022.4.focus2285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/18/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE
Patient frailty is associated with poorer perioperative outcomes for several neurosurgical procedures. However, comparative accuracy between different frailty metrics for cerebral arteriovenous malformation (AVM) outcomes is poorly understood and existing frailty metrics studied in the literature are constrained by poor specificity to neurosurgery. This aim of this paper was to compare the predictive ability of 3 frailty scores for AVM microsurgical admissions and generate a custom risk stratification score.
METHODS
All adult AVM microsurgical admissions in the National (Nationwide) Inpatient Sample (2002–2017) were identified. Three frailty measures were analyzed: 5-factor modified frailty index (mFI-5; range 0–5), 11-factor modified frailty index (mFI-11; range 0–11), and Charlson Comorbidity Index (CCI) (range 0–29). Receiver operating characteristic curves were used to compare accuracy between metrics. The analyzed endpoints included in-hospital mortality, routine discharge, complications, length of stay (LOS), and hospitalization costs. Survey-weighted multivariate regression assessed frailty-outcome associations, adjusting for 13 confounders, including patient demographics, hospital characteristics, rupture status, hydrocephalus, epilepsy, and treatment modality. Subsequently, k-fold cross-validation and Akaike information criterion–based model selection were used to generate a custom 5-variable risk stratification score called the AVM-5. This score was validated in the main study population and a pseudoprospective cohort (2018–2019).
RESULTS
The authors analyzed 16,271 total AVM microsurgical admissions nationwide, with 21.0% being ruptured. The mFI-5, mFI-11, and CCI were all predictive of lower rates of routine discharge disposition, increased perioperative complications, and longer LOS (all p < 0.001). Their AVM-5 risk stratification score was calculated from 5 variables: age, hydrocephalus, paralysis, diabetes, and hypertension. The AVM-5 was predictive of decreased rates of routine hospital discharge (OR 0.26, p < 0.001) and increased perioperative complications (OR 2.42, p < 0.001), postoperative LOS (+49%, p < 0.001), total LOS (+47%, p < 0.001), and hospitalization costs (+22%, p < 0.001). This score outperformed age, mFI-5, mFI-11, and CCI for both ruptured and unruptured AVMs (area under the curve [AUC] 0.78, all p < 0.001). In a pseudoprospective cohort of 2005 admissions from 2018 to 2019, the AVM-5 remained significantly associated with all outcomes except for mortality and exhibited higher accuracy than all 3 earlier scores (AUC 0.79, all p < 0.001).
CONCLUSIONS
Patient frailty is predictive of poorer disposition and elevated complications, LOS, and costs for AVM microsurgical admissions. The authors’ custom AVM-5 risk score outperformed age, mFI-5, mFI-11, and CCI while using threefold less variables than the CCI. This score may complement existing AVM grading scales for optimization of surgical candidates and identification of patients at risk of postoperative medical and surgical morbidity.
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Affiliation(s)
- Oliver Y. Tang
- Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Ankush I. Bajaj
- Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Kevin Zhao
- Center for Skull Base and Pituitary Surgery, Neurological Institute of New Jersey, Newark, New Jersey
- Department of Neurological Surgery, New Jersey Medical School, Newark, New Jersey
- Saint Barnabas Medical Center, RWJ Barnabas Health, Livingston, New Jersey
| | - James K. Liu
- Center for Skull Base and Pituitary Surgery, Neurological Institute of New Jersey, Newark, New Jersey
- Department of Neurological Surgery, New Jersey Medical School, Newark, New Jersey
- Department of Otolaryngology–Head and Neck Surgery, New Jersey Medical School, Newark, New Jersey; and
- Saint Barnabas Medical Center, RWJ Barnabas Health, Livingston, New Jersey
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Tang OY, Barrios-Anderson A, Hobbs K, Palumbo M, Bajaj AI, Pugacheva A, Leary OP, Anderson MN, Feler JR, Pucci FG, Gokaslan ZL. Letter: The Brown Student Neurosurgery & Neurology Research Conference: A Model for Student-Centric Neurosurgical Research Dissemination in the Virtual Conference Era. Neurosurgery 2022; 90:e133-e136. [PMID: 35275103 DOI: 10.1227/neu.0000000000001930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 12/18/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Oliver Y Tang
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Adriel Barrios-Anderson
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Katherine Hobbs
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Marina Palumbo
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Ankush I Bajaj
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Alisa Pugacheva
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Owen P Leary
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Matthew N Anderson
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Joshua R Feler
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Francesco G Pucci
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Ziya L Gokaslan
- Department of Neurosurgery, The Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Department of Neurosurgery, Rhode Island Hospital, Providence, Rhode Island, USA
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Tang OY, Bajaj AI, Zhao K, Rivera Perla KM, Ying YLM, Jyung RW, Liu JK. Association of Patient Frailty With Vestibular Schwannoma Resection Outcomes and Machine Learning Development of a Vestibular Schwannoma Risk Stratification Score. Neurosurgery 2022; 91:312-321. [PMID: 35411872 DOI: 10.1227/neu.0000000000001998] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 02/12/2022] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Patient frailty is predictive of higher neurosurgical morbidity and mortality. However, existing frailty measures are hindered by lack of specificity to neurosurgery. OBJECTIVE To analyze the association between 3 risk stratification scores and outcomes for nationwide vestibular schwannoma (VS) resection admissions and develop a custom VS risk stratification score. METHODS We identified all VS resection admissions in the National Inpatient Sample (2002-2017). Three risk stratification scores were analyzed: modified Frailty Index-5, modified Frailty Index-11(mFI-11), and Charlson Comorbidity Index (CCI). Survey-weighted multivariate regression evaluated associations between frailty and inpatient outcomes, adjusting for patient demographics, hospital characteristics, and disease severity. Subsequently, we used k-fold cross validation and Akaike Information Criterion-based model selection to create a custom risk stratification score. RESULTS We analyzed 32 465 VS resection admissions. High frailty, as identified by the mFI-11 (odds ratio [OR] = 1.27, P = .021) and CCI (OR = 1.72, P < .001), predicted higher odds of perioperative complications. All 3 scores were also associated with lower routine discharge rates and elevated length of stay (LOS) and costs (all P < .05). Our custom VS-5 score (https://skullbaseresearch.shinyapps.io/vs-5_calculator/) featured 5 variables (age ≥60 years, hydrocephalus, preoperative cranial nerve palsies, diabetes mellitus, and hypertension) and was predictive of higher mortality (OR = 6.40, P = .001), decreased routine hospital discharge (OR = 0.28, P < .001), and elevated complications (OR = 1.59, P < .001), LOS (+48%, P < .001), and costs (+23%, P = .001). The VS-5 outperformed the modified Frailty Index-5, mFI-11, and CCI in predicting routine discharge (all P < .001), including in a pseudoprospective cohort (2018-2019) of 3885 admissions. CONCLUSION Patient frailty predicted poorer inpatient outcomes after VS surgery. Our custom VS-5 score outperformed earlier risk stratification scores.
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Affiliation(s)
- Oliver Y Tang
- Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Ankush I Bajaj
- Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Kevin Zhao
- Center for Skull Base and Pituitary Surgery, Neurological Institute of New Jersey, Newark, New Jersey, USA.,Department of Neurological Surgery, New Jersey Medical School, Newark, New Jersey, USA.,Saint Barnabas Medical Center, RWJBarnabas Health, Livingston, New Jersey, USA
| | - Krissia M Rivera Perla
- Department of Neurosurgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.,Department of Plastic Surgery, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yu-Lan Mary Ying
- Saint Barnabas Medical Center, RWJBarnabas Health, Livingston, New Jersey, USA.,Department of Otolaryngology-Head and Neck Surgery, New Jersey Medical School, Newark, New Jersey, USA
| | - Robert W Jyung
- Saint Barnabas Medical Center, RWJBarnabas Health, Livingston, New Jersey, USA.,Department of Otolaryngology-Head and Neck Surgery, New Jersey Medical School, Newark, New Jersey, USA
| | - James K Liu
- Center for Skull Base and Pituitary Surgery, Neurological Institute of New Jersey, Newark, New Jersey, USA.,Department of Neurological Surgery, New Jersey Medical School, Newark, New Jersey, USA.,Saint Barnabas Medical Center, RWJBarnabas Health, Livingston, New Jersey, USA.,Department of Otolaryngology-Head and Neck Surgery, New Jersey Medical School, Newark, New Jersey, USA
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Tang OY, Pugacheva A, Bajaj AI, Rivera Perla KM, Weil RJ, Toms SA. The National Inpatient Sample: A Primer for Neurosurgical Big Data Research and Systematic Review. World Neurosurg 2022; 162:e198-e217. [PMID: 35247618 DOI: 10.1016/j.wneu.2022.02.113] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 02/25/2022] [Accepted: 02/26/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE The National Inpatient Sample - the largest all-payer inpatient database in the United States - is an important instrument for big data analysis of neurosurgical inquiries. However, earlier research has determined that many NIS studies are limited by common methodological pitfalls. In this study, we provide the first primer of NIS methodological procedures in the setting of neurosurgical research and review all published neurosurgical studies utilizing the NIS. METHODS We designed a protocol for neurosurgical big data research using the NIS, based on the authors' subject matter expertise, NIS documentation, and input and verification from the Healthcare Cost and Utilization Project. We subsequently used a comprehensive search strategy to identify all neurosurgical studies utilizing the NIS in the PubMed and MEDLINE, Embase, and Web of Science databases from inception to August 2021. Studies underwent qualitative categorization (years of the NIS studied, neurosurgical subspecialty, age group, and thematic focus of study objective) and analysis of longitudinal trends. RESULTS We identified a canonical, four-step protocol for NIS analysis: study population selection, defining additional clinical variables, identification and coding of outcomes, and statistical analysis. Methodological nuances discussed include identifying neurosurgery-specific admissions, addressing missing data, calculating additional severity and hospital-specific metrics, coding perioperative complications, and applying survey weights to make nationwide estimates. Inherent database limitations and common pitfalls of NIS studies discussed include lack of disease process-specific variables and data following the index admission, inability to calculate certain hospital-specific variables after 2011, performing state-level analyses, conflating hospitalization charges and costs, and not following proper statistical methodology for performing survey-weighted regression. In a systematic review, we identified 647 neurosurgical studies utilizing the NIS. While almost 60% of studies were published after 2015, <10% of studies analyzed NIS data after 2015. The average sample size of studies was 507,352 patients (standard deviation=2,739,900). Most studies analyzed cranial procedures (58.1%) and adults (68.1%). The most prevalent topic areas analyzed were surgical outcome trends (35.7%) and health policy and economics (17.8%), while patient disparities (9.4%) and surgeon or hospital volume (6.6%) were the least studied. CONCLUSIONS We present a standardized methodology to analyze the NIS, systematically review the state of the NIS neurosurgical literature, suggest potential future directions for neurosurgical big data inquiries, and outline recommendations to improve the design of future neurosurgical data instruments.
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Affiliation(s)
- Oliver Y Tang
- The Warren Alpert Medical School of Brown University, Providence, RI, USA; Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - Alisa Pugacheva
- The Warren Alpert Medical School of Brown University, Providence, RI, USA; Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - Ankush I Bajaj
- The Warren Alpert Medical School of Brown University, Providence, RI, USA; Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA
| | - Krissia M Rivera Perla
- The Warren Alpert Medical School of Brown University, Providence, RI, USA; Harvard T.H Chan School of Public Health, Boston, MA, USA
| | - Robert J Weil
- Southcoast Brain & Spine, Southcoast Health, Dartmouth, MA, USA
| | - Steven A Toms
- The Warren Alpert Medical School of Brown University, Providence, RI, USA; Department of Neurosurgery, Rhode Island Hospital, Providence, RI, USA.
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Abstract
PURPOSE Fellowship programs' online content plays a key role in prospective Abdominal Radiology applicants' evaluation of programs. The purpose of this study is to examine the online accessibility of Abdominal Radiology fellowships, the comprehensiveness of the program websites' content, and evaluate whether specific program characteristics are associated with differentiated website comprehensiveness. METHODS A list of 67 Abdominal Radiology fellowship programs was obtained from the Society of Abdominal Radiology (SAR) website. Each of the 65 publicly-available fellowship websites was scored for the presence of 19 binary variables related to the program's attributes and curriculum to assess informational comprehensiveness. Comprehensiveness scores were compared by program characteristics (accreditation status, region, and size) using Kruskal-Wallis and two-tailed t tests. RESULTS Mean comprehensiveness score of Abdominal Radiology fellowship websites as measured by online criteria met was 52.6% (10.0 ± 3.0/19). Application requirements and information, rotation scheduling, and program director contact were found on more than 87.5% of the 65 websites, whereas salary and benefits, social information, and alumni were listed on fewer than 33.8% (22/65) of websites. Program accreditation status, region, and size were not associated with difference in mean comprehensiveness scores. CONCLUSIONS There is a discrepancy between information commonly sought by prospective Abdominal Radiology fellowship applicants and what is available on fellowship program websites. Programs and applicants alike may benefit from programs strengthening their online material.
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Affiliation(s)
- Jack H Ruddell
- Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA.
| | - Zachary J Hartley-Blossom
- Department of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Ankush I Bajaj
- Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA
| | - David Grand
- Department of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Adam E M Eltorai
- Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA
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