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Association of baseline frailty status and age with postoperative morbidity and mortality following intracranial meningioma resection

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Abstract

Purpose

Although numerous studies have established advanced patient age as a risk factor for poor outcomes following intracranial meningioma resection, large-scale evaluation of frailty for preoperative risk assessment has yet to be examined.

Methods

Weighted discharge data from the National Inpatient Sample were queried for adult patients undergoing benign intracranial meningioma resection from 2015 to 2018. Complex samples multivariable logistic regression models and receiver operating characteristic curve analysis were performed to evaluate adjusted associations and discrimination of frailty, quantified using the 11-factor modified frailty index (mFI), for clinical endpoints.

Results

Among 20,250 patients identified (mean age 60.6 years), 35.4% (n = 7170) were robust (mFI = 0), 34.5% (n = 6985) pre-frail (mFI = 1), 20.1% (n = 4075) frail (mFI = 2), and 10.0% (n = 2020) severely frail (mFI ≥ 3). On univariable analysis, these sub-cohorts stratified by increasing frailty were significantly associated with the development of Clavien–Dindo grade IV (life-threatening) complications (inclusive of those resulting in mortality) (1.3% vs. 3.1% vs. 6.5% vs. 9.4%, p < 0.001) and extended length of stay (eLOS) (15.4% vs. 22.5% vs. 29.3% vs. 37.4%, p < 0.001). Following multivariable analysis, increasing frailty (aOR 1.40, 95% CI 1.17, 1.68, p < 0.001) and age (aOR 1.20, 95% CI 1.05, 1.38, p = 0.009) were both independently associated with development of life-threatening complications or mortality, whereas increasing frailty (aOR 1.20, 95% CI 1.10, 1.32, p < 0.001), but not age, was associated with eLOS. Frailty (by mFI-11) achieved superior discrimination in comparison to age for both endpoints (AUC 0.69 and 0.61, respectively).

Conclusion

Frailty may be more accurate than advanced patient age alone for prognostication of adverse events and outcomes following intracranial meningioma resection.

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Data availability

All data utilized in this analysis are available upon reasonable request of the corresponding author following completion of necessary onboarding and verification procedures specified by the Healthcare Cost and Utilization Project.

Code availability

Billing codes utilized in this analysis are available upon reasonable request of the corresponding author. Those used for identification of primary clinical endpoints are defined in the manuscript supplement.

References

  1. Marosi C, Hassler M, Roessler K et al (2008) Meningioma. Crit Rev Oncol Hematol 67(2):153–171

    Article  Google Scholar 

  2. Poon MT, Fung LH, Pu JK, Leung GK (2013) Outcome comparison between younger and older patients undergoing intracranial meningioma resections. J Neurooncol 114(2):219–227

    Article  Google Scholar 

  3. Ekşi M, Canbolat Ç, Akbaş A et al (2019) Elderly patients with intracranial meningioma: surgical considerations in 228 patients with a comprehensive analysis of the literature. World Neurosurg 132:e350–e365

    Article  Google Scholar 

  4. Rijnen SJM, Meskal I, Bakker M et al (2019) Cognitive outcomes in meningioma patients undergoing surgery: individual changes over time and predictors of late cognitive functioning. Neuro Oncol 21(7):911–922

    Article  Google Scholar 

  5. Runner RP, Bellamy JL, Vu CCL, Erens GA, Schenker ML, Guild GN 3rd (2017) Modified frailty index is an effective risk assessment tool in primary total knee arthroplasty. J Arthroplasty 32:S177–S182

    Article  Google Scholar 

  6. Mogal H, Vermilion SA, Dodson R et al (2017) Modified frailty index predicts morbidity and mortality after pancreaticoduodenectomy. Ann Surg Oncol 24(6):1714–1721

    Article  Google Scholar 

  7. Karam J, Tsiouris A, Shepard A, Velanovich V, Rubinfeld I (2013) Simplified frailty index to predict adverse outcomes and mortality in vascular surgery patients. Ann Vasc Surg 27(7):904–908

    Article  Google Scholar 

  8. Fried LP, Tangen CM, Walston J et al (2001) Frailty in older adults: evidence for a phenotype. J Gerontol A: Biol Sci Med Sci 56(3):M146-156

    Article  CAS  Google Scholar 

  9. Bonney PA, Chartrain AG, Briggs RG et al (2021) Frailty is associated with in-hospital morbidity and nonroutine disposition in brain tumor patients undergoing craniotomy. World Neurosurg 146:e1045–e1053

    Article  Google Scholar 

  10. Velanovich V, Antoine H, Swartz A, Peters D, Rubinfeld I (2013) Accumulating deficits model of frailty and postoperative mortality and morbidity: its application to a national database. J Surg Res 183(1):104–110

    Article  Google Scholar 

  11. Rockwood K, Song X, MacKnight C et al (2005) A global clinical measure of fitness and frailty in elderly people. CMAJ 173(5):489–495

    Article  Google Scholar 

  12. Dicpinigaitis AJ, Kalakoti P, Schmidt M et al (2021) Associations of baseline frailty status and age with outcomes in patients undergoing vestibular schwannoma resection. JAMA Otolaryngol Head Neck Surg 147:608

    Article  Google Scholar 

  13. Clavien PA, Barkun J, de Oliveira ML et al (2009) The Clavien–Dindo classification of surgical complications: five-year experience. Ann Surg 250(2):187–196

    Article  Google Scholar 

  14. Adams P, Ghanem T, Stachler R, Hall F, Velanovich V, Rubinfeld I (2013) Frailty as a predictor of morbidity and mortality in inpatient head and neck surgery. JAMA Otolaryngol Head Neck Surg 139(8):783–789

    Article  Google Scholar 

  15. Abt NB, Richmon JD, Koch WM, Eisele DW, Agrawal N (2016) Assessment of the predictive value of the modified frailty index for Clavien–Dindo grade IV critical care complications in major head and neck cancer operations. JAMA Otolaryngol Head Neck Surg 142(7):658–664

    Article  Google Scholar 

  16. Hall EC, Boyarsky BJ, Deshpande NA et al (2014) Perioperative complications after live-donor hepatectomy. JAMA Surg 149(3):288–291

    Article  Google Scholar 

  17. Meyer CP, Sun M, Karam JA et al (2017) Complications after metastasectomy for renal cell carcinoma-a population-based assessment. Eur Urol 72(2):171–174

    Article  Google Scholar 

  18. Khera R, Angraal S, Couch T et al (2017) Adherence to methodological standards in research using the national inpatient sample. JAMA 318(20):2011–2018

    Article  Google Scholar 

  19. Sastry RA, Pertsch NJ, Tang O, Shao B, Toms SA, Weil RJ (2020) Frailty and outcomes after craniotomy for brain tumor. J Clin Neurosci 81:95–100

    Article  Google Scholar 

  20. Shahrestani S, Lehrich BM, Tafreshi AR et al (2020) The role of frailty in geriatric cranial neurosurgery for primary central nervous system neoplasms. Neurosurg Focus 49(4):E15

    Article  Google Scholar 

  21. Theriault BC, Pazniokas J, Adkoli AS et al (2020) Frailty predicts worse outcomes after intracranial meningioma surgery irrespective of existing prognostic factors. Neurosurg Focus 49(4):E16

    Article  Google Scholar 

  22. Jimenez AE, Khalafallah AM, Huq S et al (2020) Predictors of nonroutine discharge disposition among patients with parasagittal/parafalcine meningioma. World Neurosurg 142:e344–e349

    Article  Google Scholar 

  23. McIntyre MK, Gandhi C, Long A et al (2019) Age predicts outcomes better than frailty following aneurysmal subarachnoid hemorrhage: a retrospective cohort analysis. Clin Neurol Neurosurg 187:105558

    Article  Google Scholar 

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Authors and Affiliations

Authors

Contributions

CAB and AJD conceived of the project and methodology. CAB, SFK, BCT, SFK, and SH composed the manuscript. AJD and SFK queried the database and completed statistical analysis. All authors interpreted the data and provided input on analysis and manuscript revision. All authors read and approved the final manuscript. CAB, FAM, WTC, MHS, and CDG provided supervision for the project.

Corresponding author

Correspondence to Christian A. Bowers.

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The authors declare that they have no conflict of interest.

Ethical approval

Given the public accessibility and de-identified nature of the information in this database, this study did not meet the requirements for institutional review board approval. For the same reason, patient consent was neither sought nor required.

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Dicpinigaitis, A.J., Kazim, S.F., Schmidt, M.H. et al. Association of baseline frailty status and age with postoperative morbidity and mortality following intracranial meningioma resection. J Neurooncol 155, 45–52 (2021). https://doi.org/10.1007/s11060-021-03841-4

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  • DOI: https://doi.org/10.1007/s11060-021-03841-4

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