Skip to main content

The 5-factor modified frailty index predicts health burden following surgery for pituitary adenomas

Abstract

Purpose

Frailty is known to influence cost-related surgical outcomes in neurosurgery, but quantifying frailty is often challenging. Therefore, we investigated the predictive value of the 5-factor modified frailty index (mFI-5) on total hospital charges, LOS, and 90-day readmission for patients undergoing pituitary surgery.

Methods

The medical records of all patients undergoing endoscopic endonasal resection of pituitary adenomas at an academic medical center between January 2017 and December 2018 were retrospectively reviewed. Bivariate statistical analyses were conducted using Fisher’s exact test, chi-square test, and independent samples t-test. Linear and logistic regression models were used for multivariate analysis.

Results

Our cohort (n = 234) had a mean age of 53.8 years (standard deviation 14.6 years). Sex distributions were equal, and most patients were Caucasian (59%). On multivariate linear regression, with each one-point increase in mFI-5, total LOS increased by 0.64 days in the overall cohort (p < 0.001), 1.08 days in the Cushing disease cohort (p = 0.045), and 0.59 days in non-functioning tumors cohort (p = 0.004). Total charges increased by $3954 in the whole cohort (p < 0.001), $10,652 in the Cushing disease cohort (p = 0.033), and $2902 in the non-functioning tumors cohort (p = 0.007) with each one-point increase in mFI-5. Greater mFI-5 scores were associated with greater odds of 90-day readmission in both overall and Cushing disease cohorts, but these associations did not reach statistical significance.

Conclusion

A patient’s mFI-5 score is significantly associated with increased length of stay and hospital charges for patients undergoing pituitary surgery. The mFI-5 may hold peri-operative value in patient counseling for pituitary adenoma surgery.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Data availability

Research data and code for statistical analyses are stored in an institutional repository and will be shared upon request to the corresponding author.

References

  1. Gittleman H, Ostrom QT, Farah PD (2014) Descriptive epidemiology of pituitary tumors in the United States. J Neurosurg 121:527–535. https://doi.org/10.3171/2014.5.JNS131819

    Article  PubMed  PubMed Central  Google Scholar 

  2. Rolston JD, Han SJ, Aghi MK (2016) Nationwide shift from microscopic to endoscopic transsphenoidal pituitary surgery. Pituitary 19:248–250. https://doi.org/10.1007/s11102-015-0685-y

    Article  PubMed  PubMed Central  Google Scholar 

  3. Rotenberg B, Tam S, Ryu W, Duggal N (2010) Microscopic versus endoscopic pituitary surgery: a systematic review. Laryngoscope 120:1292–1297. https://doi.org/10.1002/lary.20949

    Article  PubMed  PubMed Central  Google Scholar 

  4. Singh H, Essayed W, Cohen-Gadol A (2016) Resection of pituitary tumors: endoscopic versus microscopic. J Neurooncol 130:309–317. https://doi.org/10.1007/s11060-016-2124-y

    Article  PubMed  PubMed Central  Google Scholar 

  5. Khalafallah AM, Liang AL, Jimenez AE (2020) Trends in endoscopic and microscopic transsphenoidal surgery: a survey of the international society of pituitary surgeons between 2010 and 2020. Pituitary. https://doi.org/10.1007/s11102-020-01054-y

    Article  PubMed  PubMed Central  Google Scholar 

  6. Shah T, Churpek MM, Coca Perraillon M, Konetzka RT (2015) Understanding why patients with COPD get readmitted: a large National Study to delineate the medicare population for the readmissions penalty expansion. Chest 147:1219–1226. https://doi.org/10.1378/chest.14-2181

    Article  PubMed  PubMed Central  Google Scholar 

  7. Oosmanally N, Paul JE, Zanation AM, Ewend MG, Senior BA, Ebert CS Jr (2011) Comparative analysis of cost of endoscopic endonasal minimally invasive and sublabial-transseptal approaches to the pituitary. Int Forum Allergy Rhinol 1(4):242–249. https://doi.org/10.1002/alr.20048

    Article  PubMed  PubMed Central  Google Scholar 

  8. Thomas JG, Gadgil N, Samson SL, Takashima M, Yosher D (2014) Prospective trial of a short hospital stay protocol after endoscopic endonasal pituitary adenoma surgery. World Neurosurg 81(3–4):576–583. https://doi.org/10.1016/j.wneu.2013.11.014

    Article  PubMed  PubMed Central  Google Scholar 

  9. Sarkiss CA, Lee J, Papin JA et al (2015) Pilot study on early postoperative discharge in pituitary adenoma patients: effect of socioeconomic factors and benefit of specialized pituitary centers. J Neurol Surgery 76(4):323–330. https://doi.org/10.1055/s-0035-1549004

    Article  Google Scholar 

  10. Younus I, Gerges MM, Dobri GA, Ramakrishna R, Schwartz TH (2019) Readmission after endoscopic transsphenoidal pituitary surgery: analysis of 584 consecutive cases. J Neurosurg. https://doi.org/10.3171/2019.7.jns191558

    Article  PubMed  PubMed Central  Google Scholar 

  11. Knuf KM, Maani CV, Cummings AK (2018) Clinical agreement in the American Society of Anesthesiologists physical status classification. Perioper Med 19:7–14. https://doi.org/10.1186/s13741-018-0094-7

    Article  Google Scholar 

  12. Sankar A, Johnson SR, Beattie WS, Tait G, Wijeysundera DN (2014) Reliability of the American Society of Anesthesiologists physical status scale in clinical practice. Br J Anaesth 113(3):424–432. https://doi.org/10.1093/bja/aeu100

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. Whitmore RG, Stephen JH, Vernick C et al (2014) ASA grade and charlson comorbidity index of spinal surgery patients: correlation with complications and societal costs. Spine J 14(1):31–38. https://doi.org/10.1016/j.spinee.2013.03.011

    Article  PubMed  PubMed Central  Google Scholar 

  14. Subramaniam S, Aalberg JJ, Soriano RP, Divino CM (2018) New 5-factor modified frailty index using American College of Surgeons NSQIP data. J Am Coll Surg 226(2):173–181.e8. https://doi.org/10.1016/j.jamcollsurg.2017.11.005

    Article  PubMed  PubMed Central  Google Scholar 

  15. Groman RF, Rubin KY (2013) Neurosurgical practice and health care reform: moving toward quality-based health care delivery. Neurosurg Focus. https://doi.org/10.3171/2012.9.focus12308

    Article  PubMed  PubMed Central  Google Scholar 

  16. Keehan SP, Stone DA, Poisal JA et al (2017) National Health Expenditure Projections, 2016–25: price increases, aging push sector to 20 percent of economy. Health Aff 36(3):553–563. https://doi.org/10.1377/hlthaff.2016.1627

    Article  Google Scholar 

  17. Eamer GJ, Clement F, Holroyd-Leduc J, Wagg A, Padwal R, Khadaroo RG (2019) Frailty predicts increased costs in emergent general surgery patients: a prospective cohort cost analysis. Surgery 166(1):82–87. https://doi.org/10.1016/j.surg.2019.01.033

    Article  PubMed  PubMed Central  Google Scholar 

  18. Makary MA, Segev DL, Pronovost PJ et al (2010) Frailty as a predictor of surgical outcomes in older patients. J Am Coll Surg 210(6):901–908. https://doi.org/10.1016/j.jamcollsurg.2010.01.028

    Article  PubMed  Google Scholar 

  19. Okabe H, Ohsaki T, Ogawa K et al (2019) Frailty predicts severe postoperative complications after elective colorectal surgery. Am J Surg 217(4):677–681. https://doi.org/10.1016/j.amjsurg.2018.07.009

    Article  PubMed  PubMed Central  Google Scholar 

  20. Robinson TN, Wu DS, Pointer L, Dunn CL, Cleveland JC Jr, Moss M (2013) Simple frailty score predicts postoperative complications across surgical specialties. Am J Surg 206(4):544–550. https://doi.org/10.1016/j.amjsurg.2013.03.012

    Article  PubMed  PubMed Central  Google Scholar 

  21. Wang HT, Fafard J, Ahern S, Vendittoli P-A, Hebert P (2018) Frailty as a predictor of hospital length of stay after elective total joint replacements in elderly patients. BMC Musculoskelet Disord 19(1):14. https://doi.org/10.1186/s12891-018-1935-8

    Article  PubMed  PubMed Central  Google Scholar 

  22. Traven SA, McGurk KM, Reeves RA, Walton ZJ, Woolf SK, Slone HS (2019) Modified frailty index predicts medical complications, length of stay, readmission, and mortality following total shoulder arthroplasty. J Shoulder Elb Surg 28(10):1854–1860. https://doi.org/10.1016/j.jse.2019.03.009

    Article  Google Scholar 

  23. Traven SA, Reeves RA, Slone HS, Walton ZJ (2019) Frailty predicts medical complications, length of stay, readmission, and mortality in revision hip and knee arthroplasty. J Arthroplasty 34(7):1412–1416. https://doi.org/10.1016/j.arth.2019.02.060

    Article  PubMed  PubMed Central  Google Scholar 

  24. Asemota AO, Ishii M, Brem H, Gallia GL (2019) Costs and their predictors in transsphenoidal pituitary surgery. Neurosurgery 85(5):695–707. https://doi.org/10.1093/neuros/nyy441

    Article  PubMed  PubMed Central  Google Scholar 

  25. Parasher AK, Workman AD, Kidwai SM et al (2018) Costs in pituitary surgery: racial, socioeconomic, and hospital factors. J Neurol Surg 79(6):522–527. https://doi.org/10.1055/s-0038-1635081

    Article  Google Scholar 

  26. Little AS, Chapple K, Jahnke H, White WL (2014) Comparative inpatient resource utilization for patients undergoing endoscopic or microscopic transsphenoidal surgery for pituitary lesions. J Neurosurg 121(1):84–90. https://doi.org/10.3171/2014.2.JNS132095

    Article  PubMed  PubMed Central  Google Scholar 

  27. Shahrestani S, Ballatori AM, Chen XT et al (2020) Analysis of modifiable and nonmodifiable risk factors in patients undergoing pituitary surgery. J Neurosurg. https://doi.org/10.3171/2020.4.JNS20417

    Article  PubMed  PubMed Central  Google Scholar 

  28. Tomlinson SB, Piper K, Kimmel KT, Vates GE (2017) Preoperative frailty score for 30-day morbidity and mortality after cranial neurosurgery. World Neurosurg 107:959–965. https://doi.org/10.1016/j.wneu.2017.07.081

    Article  PubMed  PubMed Central  Google Scholar 

  29. Harland TA, Wang M, Gunaydin D et al (2020) Frailty as a predictor of neurosurgical outcomes in brain tumor patients. World Neurosurg 133:e813–e818. https://doi.org/10.1016/j.wneu.2019.10.010

    Article  PubMed  PubMed Central  Google Scholar 

  30. Asemota AO, Gallia GL (2020) Impact of frailty on short-term outcomes in patients undergoing transsphenoidal pituitary surgery. J Neurosurg 132(2):360–370. https://doi.org/10.3171/2018.8.JNS181875

    Article  Google Scholar 

  31. Youngerman BE, Neugut AI, Yang J, Hershman DL, Wright JD, Bruce JN (2018) The modified frailty index and 30-day adverse events in oncologic neurosurgery. J Neurooncol 136(1):197–206. https://doi.org/10.1007/s11060-017-2644-0

    Article  PubMed  PubMed Central  Google Scholar 

  32. Wasfy JH, Kennedy KF, Masoudi FA et al (2018) Predicting length of stay and the need for postacute care after acute myocardial infarction to improve healthcare efficiency. Circ Cardiovasc Qual Outcomes. https://doi.org/10.1161/CIRCOUTCOMES.118.004635

    Article  PubMed  PubMed Central  Google Scholar 

  33. Howard R, Yin YS, McCandless L, Wang S, Englesbe M, Machado-Arando D (2019) Taking control of your surgery: impact of a prehabilitation program on major abdominal surgery. J Am Coll Surg 228(1):72–80. https://doi.org/10.1016/j.jamcollsurg.2018.09.018

    Article  PubMed  PubMed Central  Google Scholar 

  34. Nielsen PR, Andreasen J, Asmussen M, Tønnesen H (2008) Costs and quality of life for prehabilitation and early rehabilitation after surgery of the lumbar spine. BMC Health Serv Res 8:209. https://doi.org/10.1186/1472-6963-8-209

    Article  PubMed  PubMed Central  Google Scholar 

  35. Kidwai SM, Yang A, Gray ML et al (2019) Hospital charge variability across New York state: sociodemographic factors in pituitary surgery. J Neurol Surg 80(6):612–619. https://doi.org/10.1055/s-0038-1676839

    Article  Google Scholar 

  36. Lee CC, Kimmell KT, Lalonde A et al (2016) Geographic variation in cost of care for pituitary tumor surgery. Pituitary 19(5):515–521. https://doi.org/10.1007/s11102-016-0738-x

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

None.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Debraj Mukherjee.

Ethics declarations

Conflict of interest

All the authors declared that they have no conflict of interest.

Ethical approval

This retrospective chart review study involving human participants was in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The Human Investigation Committee (IRB) of Johns Hopkins University approved this study.

Informed consent

Our Institutional Review Board (IRB) approved the waiver of informed consent for this single-institution, retrospective, HIPAA-compliant study (IRB number 00209855).

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Khalafallah, A.M., Shah, P.P., Huq, S. et al. The 5-factor modified frailty index predicts health burden following surgery for pituitary adenomas. Pituitary 23, 630–640 (2020). https://doi.org/10.1007/s11102-020-01069-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11102-020-01069-5

Keywords

  • Frailty
  • mFI-5
  • Comorbidities
  • Pituitary surgery
  • Length of stay
  • Charges