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Comparison of the Risk Analysis Index and the modified 5-factor frailty index in predicting 30-day morbidity and mortality after spine surgery

Christian A. Bowers Department of Neurosurgery, University of New Mexico Hospital (UNMH), Albuquerque;

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Samantha Varela School of Medicine, University of New Mexico, Albuquerque, New Mexico;

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Matthew Conlon School of Medicine, New York Medical College, Valhalla, New York;

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Syed Faraz Kazim Department of Neurosurgery, University of New Mexico Hospital (UNMH), Albuquerque;

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瑞秋Thommen School of Medicine, New York Medical College, Valhalla, New York;

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Katie Roster School of Medicine, New York Medical College, Valhalla, New York;

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Daniel E. Hall Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh;
Geriatric Research Education and Clinical Center, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania

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Meic H. Schmidt Department of Neurosurgery, University of New Mexico Hospital (UNMH), Albuquerque;

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OBJECTIVE

Frailty’s role in preoperative risk assessment in spine surgery has increased in association with the increasing size of the aging population. However, previous frailty assessment tools have significant limitations. The aim of this study was to compare the predictive ability of the Risk Analysis Index (RAI) with the 5-factor modified frailty index (mFI-5) for postoperative spine surgery morbidity and mortality.

开云体育世界杯赔率

Data were collected from the American College of Surgeons National Surgical Quality Improvement Program database for adults > 18 years who underwent spine surgery between 2015 and 2019. Multivariate modeling and receiver operating characteristic curve analysis, including area under the curve/C-statistic calculations, were performed to evaluate the comparative discriminative ability of RAI and mFI-5 on postoperative outcomes.

RESULTS

In a cohort of 292,225 spine surgery patients, multivariate modeling showed that increasing RAI scores, and not increasing mFI-5 scores, were independent predictors of increased postoperative mortality for the trauma, tumor, and infection subcohorts. In the overall spine cohort, both increasing RAI and increasing mFI-5 scores were associated with increased mortality, but C-statistics indicated that the RAI (C-statistic 0.802 [95% CI 0.800–0.803], p < 0.0001, DeLong test) had superior discrimination compared with the mFI-5 (C-statistic 0.677 [95% CI 0.675–0.679], p < 0.0001, DeLong test). In subgroup analyses, the RAI had superior discriminative ability to mFI-5 for mortality in the trauma and infection groups (p < 0.001 and p = 0.039, respectively).

CONCLUSIONS

The RAI demonstrates superior discrimination to the mFI-5 for predicting postoperative mortality and morbidity after spine surgery and the RAI maintains conceptual fidelity to the frailty phenotype. Patients with high RAI scores may benefit from knowing the possibility of increased surgical risk with potential spine surgery.

缩写

ACS = American College of Surgeons ; ADL = activities of daily living ; CCI = Charlson Comorbidity Index ; CDIV = Clavien-Dindo grade IV ; CHF = congestive heart failure ; COPD = chronic obstructive pulmonary disease ; CPT = Current Procedural Terminology ; DM = diabetes mellitus ; ECI = Elixhauser Comorbidity Index ; eLOS = extended LOS ; ICD = International Classification of Diseases ; LOS = length of stay ; mFI-5 = 5-factor modified frailty index ; mFI-11 = 11-factor mFI ; NHD = nonhome discharge destination ; NSQIP = National Surgical Quality Improvement Program ; RAI = Risk Analysis Index ; ROC = receiver operating characteristic ; SSI = surgical site infection .

Supplementary Materials

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Figure from Vedantam et al. (pp 28–39).
  • 1

    IndrakantiSS,WeberMH,TakemotoSK,HuSS,PollyD,BervenSH.Value-based care in the management of spinal disorders: a systematic review of cost-utility analysis.Clin Orthop Relat Res.2012;470(4):11061123.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    ChanV,WilsonJRF,RavinskyR,et al.脆弱或者造成不利影响tcomes of patients undergoing spine surgery: a systematic review.Spine J.2021;21(6):9881000.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3

    O’LynngerTM,ZuckermanSL,MoronePJ,DewanMC,Vasquez-CastellanosRA,ChengJS.Trends for spine surgery for the elderly: implications for access to healthcare in North America.开云体育app官方网站下载入口.2015;77(suppl 4):S136S141.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    GumJL,HostinR,RobinsonC,et al.Impact of cost valuation on cost-effectiveness in adult spine deformity surgery.Spine J.2017;17(1):96101.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    SivasubramaniamV,PatelHC,OzdemirBA,PapadopoulosMC.Trends in hospital admissions and surgical procedures for degenerative lumbar spine disease in England: a 15-year time-series study.BMJ Open.2015;5(12):e009011.

    • Search Google Scholar
    • Export Citation
  • 6

    DeyoRA.Back surgery—who needs it?N Engl J Med.2007;356(22):22392243.

  • 7

    MengerRP,SavardekarAR,FarokhiF,SinA.A cost-effectiveness analysis of the integration of robotic spine technology in spine surgery.Neurospine.2018;15(3):216224.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    ChoPG,KimTH,LeeH,JiGY,ParkSH,ShinDA.Incidence, reasons, and risk factors for 30-day readmission after lumbar spine surgery for degenerative spinal disease.Sci Rep.2020;10(1):12672.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    PierceKE,NaessigS,KummerN,et al.The five-item modified frailty index is predictive of 30-day postoperative complications in patients undergoing spine surgery.Spine (Phila Pa 1976).2021;46(14):939943.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    WilsonJRF,BadhiwalaJH,MoghaddamjouA,YeeA,WilsonJR,FehlingsMG.Frailty is a better predictor than age of mortality and perioperative complications after surgery for degenerative cervical myelopathy: an analysis of 41,369 patients from the NSQIP database 2010-2018.J Clin Med.2020;9(11):3491.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    ZreikJ,AlviMA,YolcuYU,SebastianAS,FreedmanBA,BydonM.Utility of the 5-item modified frailty index for predicting adverse outcomes following elective anterior cervical discectomy and fusion.World Neurosurg.2021;146:e670e677.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    SubramaniamS,AalbergJJ,SorianoRP,DivinoCM.New 5-factor modified frailty index using American College of Surgeons NSQIP data.J Am Coll Surg.2018;226(2):173181.e8.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    ElixhauserA,SteinerC,HarrisDR,CoffeyRM.Comorbidity measures for use with administrative data.Med Care.1998;36(1):827.

  • 14

    D’HooreW,SicotteC,TilquinC.Risk adjustment in outcome assessment: the Charlson comorbidity index.Methods Inf Med.1993;32(5):382387.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    WalstonJ,Bandeen-RocheK,ButaB,et al.Moving frailty toward clinical practice: NIA Intramural Frailty Science Symposium summary.J Am Geriatr Soc.2019;67(8):15591564.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    HallDE,AryaS,SchmidKK,et al.Development and initial validation of the Risk Analysis Index for measuring frailty in surgical populations.JAMA Surg.2017;152(2):175182.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    WanMA,ClarkJM,NuñoM,CookeDT,BrownLM.Can the Risk Analysis Index for frailty predict morbidity and mortality in patients undergoing high-risk surgery?Ann Surg.2022;276(6):e721e727.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    McIsaacDI,AucoinSD,van WalravenC.A Bayesian comparison of frailty instruments in noncardiac surgery: a cohort study.Anesth Analg.2021;133(2):366373.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    EssesG,AndreopoulosE,LinHM,AryaS,DeinerS.A comparison of three frailty indices in predicting morbidity and mortality after on-pump aortic valve replacement.Anesth Analg.2018;126(1):3945.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    ShahR,BorrebachJD,HodgesJC,et al.Validation of the Risk Analysis Index for evaluating frailty in ambulatory patients.J Am Geriatr Soc.2020;68(8):18181824.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    AryaS,VarleyP,YoukA,et al.Recalibration and external validation of the Risk Analysis Index: a surgical frailty assessment tool.Ann Surg.2020;272(6):9961005.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    BoydS,TseW,LavingiaK,AmendolaM.Frailty measurement and implications for cerebrovascular disease management in a veteran based population.Ann Vasc Surg.2021;76:134141.

    • Search Google Scholar
    • Export Citation
  • 23

    MadyLJ,BaddourK,HodgesJC,et al.The impact of frailty on mortality in non-surgical head and neck cancer treatment: shifting the clinical paradigm.Oral Oncol.2022;126:105766.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    VarleyPR,BorrebachJD,AryaS,et al.Clinical utility of the Risk Analysis Index as a prospective frailty screening tool within a multi-practice, multi-hospital integrated healthcare system.Ann Surg.2021;274(6):e1230e1237.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25

    RothenbergKA,GeorgeEL,BarretoN,et al.Frailty as measured by the Risk Analysis Index is associated with long-term death after carotid endarterectomy.J Vasc Surg.2020;72(5):17351742.e1733.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    AgarwalN,GoldschmidtE,TaylorT,et al.Impact of frailty on outcomes following spine surgery: a prospective cohort analysis of 668 patients.开云体育app官方网站下载入口.2021;88(3):552557.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27

    RavalMV,PawlikTM.Practical guide to surgical data sets: National Surgical Quality Improvement Program (NSQIP) and pediatric NSQIP.JAMA Surg.2018;153(8):764765.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    KazimSF,DicpinigaitisAJ,BowersCA,et al.Frailty status is a more robust predictor than age of spinal tumor surgery outcomes: a NSQIP analysis of 4,662 patients.Neurospine.2022;19(1):5362.

    • Search Google Scholar
    • Export Citation
  • 29

    YagiM,MichikawaT,HosoganeN,et al.The 5-item modified frailty index is predictive of severe adverse events in patients undergoing surgery for adult spinal deformity.Spine (Phila Pa 1976).2019;44(18):E1083E1091.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30

    PorockD,Parker-OliverD,PetroskiGF,RantzM.The MDS Mortality Risk Index: the evolution of a method for predicting 6-month mortality in nursing home residents.BMC Res Notes.2010;3:200.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31

    GeorgeEL,HallDE,YoukA,et al.Association between patient frailty and postoperative mortality across multiple noncardiac surgical specialties.JAMA Surg.2021;156(1):e205152.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32

    GeorgeEL,MassarwehNN,YoukA,et al.Comparing Veterans Affairs and private sector perioperative outcomes after noncardiac surgery.JAMA Surg.2022;157(3):231239.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33

    CovellMM,RumallaK,KassiciehAJ,et al.Frailty measured by Risk Analysis Index and adverse discharge outcomes after adult spine deformity surgery: analysis of 3104 patients from a prospective surgical registry (2011-2020).Spine J.Published online December 23, 2022. doi:10.1016/j.spinee.2022.12.014

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    ClavienPA,BarkunJ,de OliveiraML,et al.The Clavien-Dindo classification of surgical complications: five-year experience.Ann Surg.2009;250(2):187196.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    DeLongER,DeLongDM,Clarke-PearsonDL.Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.Biometrics.1988;44(3):837845.

    • Search Google Scholar
    • Export Citation
  • 36

    AkbikOS,Al-AdliN,PernikMN,et al.A comparative analysis of frailty, disability, and sarcopenia with patient characteristics and outcomes in adult spinal deformity surgery.Global Spine J.Published online April 2, 2022. doi:10.1177/21925682221082053

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    DicpinigaitisAJ,KazimSF,SchmidtMH,et al.协会基线脆弱地位和年龄的智慧h postoperative morbidity and mortality following intracranial meningioma resection.J Neurooncol.2021;155(1):4552.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    HuqS,KhalafallahAM,JimenezAE,et al.Predicting postoperative outcomes in brain tumor patients with a 5-factor modified frailty index.开云体育app官方网站下载入口.2020;88(1):147154.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39

    YoungermanBE,NeugutAI,YangJ,HershmanDL,WrightJD,BruceJN.The modified frailty index and 30-day adverse events in oncologic neurosurgery.J Neurooncol.2018;136(1):197206.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40

    ElsamadicyAA,SandhuMRS,FreedmanIG,et al.Impact of frailty on morbidity and mortality in adult patients presenting with an acute traumatic cervical spinal cord injury.World Neurosurg.2021;153:e408e418.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41

    MaslinkC,ChengK,SmithTR,DasS.Advanced age is not a universal predictor of poorer outcome in patients undergoing neurosurgery.World Neurosurg.2019;130:e375e382.

    • Search Google Scholar
    • Export Citation
  • 42

    RockwoodK,AndrewM,MitnitskiA.A comparison of two approaches to measuring frailty in elderly people.J Gerontol A Biol Sci Med Sci.2007;62(7):738743.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43

    AliR,SchwalbJM,NerenzDR,AntoineHJ,RubinfeldI.Use of the modified frailty index to predict 30-day morbidity and mortality from spine surgery.J Neurosurg Spine.2016;25(4):537541.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    JungJM,ChungCK,KimCH,YangSH,KoYS.The modified 11-item frailty index and postoperative outcomes in patients undergoing lateral lumbar interbody fusion.Spine (Phila Pa 1976).2022;47(5):396404.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    ShinJI,KothariP,PhanK,et al.Frailty index as a predictor of adverse postoperative outcomes in patients undergoing cervical spinal fusion.Spine (Phila Pa 1976).2017;42(5):304310.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    TseW,NewtonD,AmendolaM,GeorgeM,PfeiferJ.Frailty index predicts long-term mortality and postoperative complications in patients undergoing endovascular aortic aneurysm repair.J Vasc Surg.2020;72(5):16741680.

    • PubMed
    • Search Google Scholar
    • Export Citation

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