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RISS 인기검색어
- 검색키워드
- 저자 : Syed Faraz Kazim (검색결과 3 건)
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Syed Faraz Kazim,Alis J. Dicpinigaitis,Christian A. Bowers,Smit Shah,William T. Couldwell,Rachel Thommen,Daniel J. Alvarez-Crespo,Matthew Conlon,Omar H. Tarawneh,John Vellek,Kyril L. Cole,Jose F. Domi 대한척추신경외과학회 2022 Neurospine Vol.19 No.1
Objective: The present study aimed to evaluate the effect of baseline frailty status (as measured by modified frailty index-5 [mFI-5]) versus age on postoperative outcomes of patients undergoing surgery for spinal tumors using data from a large national registry. Methods: The National Surgical Quality Improvement Program database was used to collect spinal tumor resection patients’ data from 2015 to 2019 (n = 4,662). Univariate and multivariate analyses for age and mFI-5 were performed for the following outcomes: 30-day mortality, major complications, unplanned reoperation, unplanned readmission, hospital length of stay (LOS), and discharge to a nonhome destination. Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminative performance of age versus mFI-5. Results: Both univariate and multivariate analyses demonstrated that mFI-5 was a more robust predictor of worse postoperative outcomes as compared to age. Furthermore, based on categorical analysis of frailty tiers, increasing frailty was significantly associated with increased risk of adverse outcomes. ‘Severely frail’ patients were found to have the highest risk, with odds ratio 16.4 (95% confidence interval [CI],11.21–35.44) for 30-day mortality, 3.02 (95% CI, 1.97–4.56) for major complications, and 2.94 (95% CI, 2.32–4.21) for LOS. In ROC curve analysis, mFI-5 score (area under the curve [AUC] = 0.743) achieved superior discrimination compared to age (AUC = 0.594) for mortality. Conclusion: Increasing frailty, as measured by mFI-5, is a more robust predictor as compared to age, for poor postoperative outcomes in spinal tumor surgery patients. The mFI-5 may be clinically used for preoperative risk stratification of spinal tumor patients.
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Matthew Conlon,Rachel Thommen,Syed Faraz Kazim,Alis J. Dicpinigaitis,Meic H. Schmidt,Rohini G. McKee,Christian A. Bowers 대한척추신경외과학회 2022 Neurospine Vol.19 No.4
Objective: To assess the discriminative ability of the Risk Analysis Index-administrative (RAI-A) and its recalibrated version (RAI-Rev), compared to the 5-factor modified frailty index (mFI-5), in predicting postoperative outcomes in patients undergoing surgical intervention for traumatic spine injuries (TSIs). Methods: The Current Procedural Terminology (CPT) and International Classification of Disease-9 (ICD-9) and ICD-10 codes were used to identify patients ≥ 18 years who underwent surgical intervention for TSI from National Surgical Quality Improvement Program (ACS-NSQIP) database 2015–2019 (n = 6,571). Multivariate analysis and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the comparative discriminative ability of RAI-Rev, RAI-A, and mFI-5 for 30-day postoperative outcomes. Results: Multivariate regression analysis showed that with all 3 frailty scores, increasing frailty tiers resulted in worse postoperative outcomes, and patients identified as frail and severely frail using RAI-Rev and RAI-A had the highest odds of poor outcomes. In the ROC curve/ C-statistics analysis for prediction of 30-day mortality and morbidity, both RAI-Rev and RAI-A outperformed mFI-5, and for many outcomes, RAI-Rev showed better discriminative performance compared to RAI-A, including mortality (p = 0.0043, DeLong test), extended length of stay (p = 0.0042), readmission (p < 0.0001), reoperation (p = 0.0175), and nonhome discharge (p < 0.0001). Conclusion: Both RAI-Rev and RAI-A performed better than mFI-5, and RAI-Rev was superior to RAI-A in predicting postoperative mortality and morbidity in TSI patients. RAIbased frailty indices can be used in preoperative risk assessment of spinal trauma patients.
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Alexander J. Kassicieh,Kavelin Rumalla,Aaron C. Segura,Syed Faraz Kazim,John Vellek,Meic H. Schmidt,Peter C. Shin,Christian A. Bowers 대한척추신경외과학회 2023 Neurospine Vol.20 No.1
Objective: The endoscopic spine surgery (ESS) approach is associated with high levels of patient satisfaction, shorter recovery time, and reduced complications. The present study reports multicenter, international data, comparing ESS and non-ESS approaches for singlelevel lumbar decompression, and proposes a frailty-driven predictive model for nonhome discharge (NHD) disposition. Methods: Cases of ESS and non-ESS lumbar spine decompression were queried from the American College of Surgeons National Surgical Quality Improvement Program database (2017–2020). Propensity score matching was performed on baseline characteristics frailty score (measured by risk analysis index [RAI] and modified frailty index-5 [mFI-5]). The primary outcome of interest was NHD disposition. A predictive model was built using logistic regression with RAI as the primary driver. Results: Single-level nonfusion spine lumbar decompression surgery was performed in 38,686 patients. Frailty, as measured by RAI, was a reliable predictor of NHD with excellent discriminatory accuracy in receiver operating characteristic (ROC) curve analysis: C-statistic: 0.80 (95% confidence interval [CI], 0.65–0.94) in ESS cohort, C-statistic: 0.75 (95% CI, 0.73–0.76) overall cohort. After propensity score matching, there was a reduction in total operative time (89 minutes vs. 103 minutes, p = 0.049) and hospital length of stay (LOS) (0.82 days vs. 1.37 days, p < 0.001) in patients treated endoscopically. In ROC curve analysis, the frailty-driven predictive model performed with excellent diagnostic accuracy for the primary outcome of NHD (C-statistic: 0.87; 95% CI, 0.85–0.88). Conclusion: After frailty-based propensity matching, ESS is associated with reduced operative time, shorter hospital LOS, and decreased NHD. The RAI frailty-driven model predicts NHD with excellent diagnostic accuracy and may be applied to preoperative decisionmaking with a user-friendly calculator: nsgyfrailtyoutcomeslab.shinyapps.io/lumbar_decompression_dischargedispo.
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