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Inclusion of Frailty Improves Predictive Modeling for Postoperative Outcomes in Surgical Management of Primary and Secondary Lumbar Spine Tumors

Shahrestani, Shane and Bakhsheshian, Joshua and Solaru, Samantha and Ton, Andy and Ballatori, Alexander M. and Chen, Xiao T. and Ariani, Rojine and Hsieh, Patrick and Buser, Zorica and Wang, Jeffrey C. (2021) Inclusion of Frailty Improves Predictive Modeling for Postoperative Outcomes in Surgical Management of Primary and Secondary Lumbar Spine Tumors. World Neurosurgery, 153 . e454-e463. ISSN 1878-8750. doi:10.1016/j.wneu.2021.06.143. https://resolver.caltech.edu/CaltechAUTHORS:20210730-181438996

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Abstract

Background: Malignant spinal tumors are common, continually increasing in incidence as a function of improved survival times for patients with cancer. Using predictive analytics and propensity score matching, we evaluated the influence of frailty on postoperative complications compared with age in patients with malignant neoplasms of the lumbar spine. Methods: We used the Nationwide Readmissions Database from 2016 and 2017 to identify patients with malignant neoplasms of the lumbar spine who received a fusion procedure. Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups. Propensity score matching for age, sex, Charlson Comorbidity Index, surgical approach, and number of levels fused was implemented between frail and nonfrail patients, identifying 533 frail patients and 538 nonfrail patients. The area under the curve (AUC) of each ROC served as a proxy for model performance. Results: Frail patients reported significantly higher inpatient lengths of stay, costs, infection, posthemorrhagic anemia, and urinary tract infections (P < 0.05). In addition, frail patients were more often discharged to skilled nursing facilities and short-term hospitals compared with nonfrail patients (P < 0.0001). Regression models for mortality (AUC = 0.644), nonroutine discharge (AUC = 0.600), and acute infection (AUC = 0.666) were improved when using frailty as the primary predictor. These models were also improved using frailty when predicting 30-day readmission and 90-day hardware failure. Conclusions: Frailty demonstrated a significant relationship with increased postoperative patient complications, length of stay, costs, and acute complications in patients receiving fusion following resection of a malignant neoplasm of the lumbar spine region. Frailty demonstrated better predictive validity of outcomes compared with patient age.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.wneu.2021.06.143DOIArticle
ORCID:
AuthorORCID
Shahrestani, Shane0000-0001-7561-4590
Bakhsheshian, Joshua0000-0003-2983-6082
Solaru, Samantha0000-0002-3371-3395
Ariani, Rojine0000-0003-1929-9914
Buser, Zorica0000-0002-5680-0643
Additional Information:© 2021 Elsevier Inc. Received 18 May 2021, Accepted 29 June 2021, Available online 6 July 2021. Conflict of interest statement: No conflicts of interest exist for the current study. Disclosures outside of submitted work are as follows: J.B. was funded by National Institutes of Health NINDS R25NS099008 USC Neurosurgery Research Education Training Program. Z.B. has been a consultant for Cerapedics, Xenco Medical, AO Spine; Research Support: SeaSpine (paid to the institution), Next Science (paid directly to institution), Motion Metrics (paid directly to institution) and has served as the following: North American Spine Society: committee member; Lumbar Spine Society: Co-chair Educational committee, AOSpine Knowledge Forum Degenerative: Associate member; and AOSNA Research committee member. J.C.W. has received royalties from Biomet, Seaspine, Amedica, DePuy Synthes; Investments/Options–Bone Biologics, Pearldiver, Electrocore, and Surgitech; served on the Board of Directors–Society for Brain Mapping and Therapeutics, AO Foundation, and editorial boards—Spine, The Spine Journal, Clinical Spine Surgery, and Global Spine Journal; and received fellowship funding (paid directly to institution): AO Foundation. CRediT authorship contribution statement: Shane Shahrestani: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing. Joshua Bakhsheshian: Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing. Samantha Solaru: Methodology, Writing – review & editing. Andy Ton: Methodology, Writing – review & editing. Alexander M. Ballatori: Methodology, Writing – review & editing. Xiao T. Chen: Methodology, Writing – review & editing. Rojine Ariani: Methodology, Writing – review & editing. Patrick Hsieh: Investigation, Methodology, Writing – review & editing. Zorica Buser: Conceptualization, Investigation, Project administration, Resources, Supervision, Writing – review & editing. Jeffrey C. Wang: Conceptualization, Investigation, Project administration, Resources, Supervision, Writing – review & editing.
Funders:
Funding AgencyGrant Number
NIHR25NS099008
Subject Keywords:Axial; Frailty; Malignant; Neoplasm; Predictive modeling; Spinal lumbar
DOI:10.1016/j.wneu.2021.06.143
Record Number:CaltechAUTHORS:20210730-181438996
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210730-181438996
Official Citation:Shane Shahrestani, Joshua Bakhsheshian, Samantha Solaru, Andy Ton, Alexander M. Ballatori, Xiao T. Chen, Rojine Ariani, Patrick Hsieh, Zorica Buser, Jeffrey C. Wang, Inclusion of Frailty Improves Predictive Modeling for Postoperative Outcomes in Surgical Management of Primary and Secondary Lumbar Spine Tumors, World Neurosurgery, Volume 153, 2021, Pages e454-e463, ISSN 1878-8750, https://doi.org/10.1016/j.wneu.2021.06.143.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110105
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:02 Aug 2021 17:22
Last Modified:24 Aug 2021 19:03

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