Advertisement

A 10-Min Targeted Geriatric Assessment Predicts Mortality in Fast-Paced Acute Care Settings: A Prospective Cohort Study

  • Márlon J. R. AlibertiEmail author
  • K. E. Covinsky
  • D. Apolinario
  • S. J. Lee
  • S. Q. Fortes-Filho
  • J. A. Melo
  • S. S. C. Viana
  • C. K. Suemoto
  • W. Jacob-Filho
Article

Abstract

Objectives

To estimate whether a 10-minute Targeted Geriatric Assessment (10-TaGA) adds utility to sociodemographic characteristics and comorbidities in predicting one-year mortality in busy acute care settings. We have also compared the performance of 10-TaGA with the Identification of Seniors at Risk (ISAR) scale.

Design

Prospective cohort study.

Setting

Geriatric day hospital specializing in acute care in Brazil

Participants

751 older adults aged 79.4 ± 8.4 years (64% female), presenting non-surgical, medical illness requiring hospital-level care (e.g., intravenous therapy, laboratory test, radiology) for ≤ 12 hours.

Measurements

The 10-TaGA, an easy-to-administer screening tool based on the comprehensive geriatric assessment (CGA), provided a measure of cumulative deficits ranging from 0 (no deficits) to 1 (highest deficit) on admission. Standard risk factors, including sociodemographics (age, gender, ethnicity, income) and the Charlson comorbidity index, were evaluated. The ISAR, a well-validated screening tool, was used for comparison.

Results

During one year of follow-up, 130 (17%) participants died. Compared to the ISAR, 10-TaGA offered better accuracy in identifying older patients at risk of death (area under the receiver operating characteristic curve: [AUC] 0.70 vs 0.65; P = 0.03). In a Cox regression model adjusted for sociodemographics and comorbidities, each 0.1 increment in the 10-TaGA score (range 0–1) was associated with increased mortality (hazard ratio = 1.42, 95% confidence interval 1.27–1.59). The addition of 10-TaGA markedly improved the discrimination of the model, which already incorporated standard risk factors (AUC 0.76 vs 0.71; P = 0.005); adding ISAR (AUC 0.73 vs 0.71; P = 0.09) did not have this marked effect.

Conclusion

The 10-TaGA is an independent predictor of one-year mortality in acute care patients. This multidimensional screening tool offers better accuracy than ISAR when differentiating between older people at low and high risk of death in healthcare settings where providers have limited time and resources.

Key words

Comprehensive geriatric assessment screening tool acute care geriatric day hospital prognosis 

Supplementary material

12603_2018_1152_MOESM1_ESM.pdf (233 kb)
Supplementary material, approximately 232 KB.

References

  1. 1.
    Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systematic review. JAMA 2012;307(2):182–192; doi: 10.1001/jama.2011.1966.CrossRefGoogle Scholar
  2. 2.
    Periyakoil VJ. Square Pegs; Round Holes: Our Healthcare System Is Failing Seriously Ill Older Americans in Their Last Years. J Am Geriatr Soc 2018;66(1):15–17; doi: 10.1111/jgs.15161.CrossRefGoogle Scholar
  3. 3.
    Hickman LD, Phillips JL, Newton PJ, Halcomb EJ, Al Abed N, Davidson PM. Multidisciplinary team interventions to optimise health outcomes for older people in acute care settings: A systematic review. Arch Gerontol Geriatr 2015;61(3):322–329; doi: 10.1016/j.archger.2015.06.021.CrossRefGoogle Scholar
  4. 4.
    Pilotto A, Ferrucci L, Franceschi M et al. Development and validation of a multidimensional prognostic index for one–year mortality from comprehensive geriatric assessment in hospitalized older patients. Rejuvenation Res 2008;11(1):151–161; doi: 10.1089/rej.2007.0569.CrossRefGoogle Scholar
  5. 5.
    Pilotto A, Cella A, Pilotto A et al. Three Decades of Comprehensive Geriatric Assessment: Evidence Coming From Different Healthcare Settings and Specific Clinical Conditions. J Am Med Dir Assoc 2017;18(2):192 e191–192 e111; doi: 10.1016/j.jamda.2016.11.004.CrossRefGoogle Scholar
  6. 6.
    Pilotto A, Rengo F, Marchionni N et al. Comparing the prognostic accuracy for allcause mortality of frailty instruments: a multicentre 1–year follow–up in hospitalized older patients. PLoS One 2012;7(1):e29090; doi: 10.1371/journal.pone.0029090.CrossRefGoogle Scholar
  7. 7.
    Graf CE, Zekry D, Giannelli S, Michel JP, Chevalley T. Comprehensive geriatric assessment in the emergency department. J Am Geriatr Soc 2010;58(10):2032–2033; doi: 10.1111/j.1532–5415.2010.03090.x.CrossRefGoogle Scholar
  8. 8.
    Graf CE, Zekry D, Giannelli S, Michel JP, Chevalley T. Efficiency and applicability of comprehensive geriatric assessment in the emergency department: a systematic review. Aging Clin Exp Res 2011;23(4):244–254; doi: 10.3275/7284.CrossRefGoogle Scholar
  9. 9.
    Conroy SP, Stevens T, Parker SG, Gladman JR. A systematic review of comprehensive geriatric assessment to improve outcomes for frail older people being rapidly discharged from acute hospital: ‘interface geriatrics’. Age Ageing 2011;40(4):436–443; doi: 10.1093/ageing/afr060.CrossRefGoogle Scholar
  10. 10.
    McCabe JJ, Kennelly SP. Acute care of older patients in the emergency department: strategies to improve patient outcomes. Open Access Emerg Med 2015;7:45–54; doi: 10.2147/OAEM.S69974.Google Scholar
  11. 11.
    Di Bari M, Salvi F, Roberts AT et al. Prognostic stratification of elderly patients in the emergency department: a comparison between the «Identification of Seniors at Risk» and the «Silver Code». J Gerontol A Biol Sci Med Sci 2012;67(5):544–550; doi: 10.2147/OAEM.S69974.CrossRefGoogle Scholar
  12. 12.
    Ellis G, Marshall T, Ritchie C. Comprehensive geriatric assessment in the emergency department. Clin Interv Aging 2014;9:2033–2043; doi: 10.2147/CIA.S29662.CrossRefGoogle Scholar
  13. 13.
    Hominick K, McLeod V, Rockwood K. Characteristics of Older Adults Admitted to Hospital versus Those Discharged Home, in Emergency Department Patients Referred to Internal Medicine. Can Geriatr J 2016;19(1):9–14; doi: 10.5770/cgj.19.195.CrossRefGoogle Scholar
  14. 14.
    Aliberti MJR, Apolinario D, Suemoto CK. Targeted Geriatric Assessment for Fast–Paced Healthcare Settings: Development, Validity, and Reliability. J Am Geriatr Soc 2018; doi: 10.1111/jgs.15303.Google Scholar
  15. 15.
    McCusker J, Bellavance F, Cardin S, Trepanier S, Verdon J, Ardman O. Detection of older people at increased risk of adverse health outcomes after an emergency visit: the ISAR screening tool. J Am Geriatr Soc 1999;47(10):1229–1237.CrossRefGoogle Scholar
  16. 16.
    Aliberti MJ, Suemoto CK, Fortes–Filho SQ et al. The Geriatric Day Hospital: Preliminary Data on an Innovative Model of Care in Brazil for Older Adults at Risk of Hospitalization. J Am Geriatr Soc 2016;64(10):2149–2153; doi: 10.1111/jgs.14342.CrossRefGoogle Scholar
  17. 17.
    Frenkel WJ, Jongerius EJ, Mandjes–van Uitert MJ, van Munster BC, de Rooij SE. Validation of the Charlson Comorbidity Index in acutely hospitalized elderly adults: a prospective cohort study. J Am Geriatr Soc 2014;62(2):342–346; doi: 10.1111/jgs.12635.CrossRefGoogle Scholar
  18. 18.
    Katz S, Akpom CA. A measure of primary sociobiological functions. Int J Health Serv 1976;6(3):493–508.CrossRefGoogle Scholar
  19. 19.
    Apolinario D, Lichtenthaler DG, Magaldi RM et al. Using temporal orientation, category fluency, and word recall for detecting cognitive impairment: the 10–point cognitive screener (10–CS). Int J Geriatr Psychiatry 2016;31(1):4–12; doi: 10.1002/gps.4282.CrossRefGoogle Scholar
  20. 20.
    van Marwijk HW, Wallace P, de Bock GH, Hermans J, Kaptein AA, Mulder JD. Evaluation of the feasibility, reliability and diagnostic value of shortened versions of the geriatric depression scale. Br J Gen Pract 1995;45(393):195–199.Google Scholar
  21. 21.
    Singler K, Heppner HJ, Skutetzky A, Sieber C, Christ M, Thiem U. Predictive validity of the identification of seniors at risk screening tool in a German emergency department setting. Gerontology 2014;60(5):413–419; doi: 10.1159/000358825.CrossRefGoogle Scholar
  22. 22.
    Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)––a metadata–driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–381; doi: 10.1016/j.jbi.2008.08.010.CrossRefGoogle Scholar
  23. 23.
    Royston P, Ambler G, Sauerbrei W. The use of fractional polynomials to model continuous risk variables in epidemiology. Int J Epidemiol 1999;28(5):964–974.CrossRefGoogle Scholar
  24. 24.
    Youden WJ. Index for rating diagnostic tests. Cancer 1950;3(1):32–35.CrossRefGoogle Scholar
  25. 25.
    DeLong ER, DeLong DM, Clarke–Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44(3):837–845.CrossRefGoogle Scholar
  26. 26.
    Amblas–Novellas J, Martori JC, Espaulella J et al. Frail–VIG index: a concise frailty evaluation tool for rapid geriatric assessment. BMC Geriatr 2018;18(1):29; doi: 10.1186/s12877–018–0718–2.CrossRefGoogle Scholar
  27. 27.
    Wou F, Gladman JR, Bradshaw L, Franklin M, Edmans J, Conroy SP. The predictive properties of frailty–rating scales in the acute medical unit. Age Ageing 2013;42(6):776–781; doi: 10.1093/ageing/aft055.CrossRefGoogle Scholar
  28. 28.
    Inzitari M, Gual N, Roig T et al. Geriatric Screening Tools to Select Older Adults Susceptible for Direct Transfer From the Emergency Department to Subacute Intermediate–Care Hospitalization. J Am Med Dir Assoc 2015;16(10):837–841; doi: 10.1016/j.jamda.2015.04.009.CrossRefGoogle Scholar
  29. 29.
    Yao JL, Fang J, Lou QQ, Anderson RM. A systematic review of the identification of seniors at risk (ISAR) tool for the prediction of adverse outcome in elderly patients seen in the emergency department. Int J Clin Exp Med 2015;8(4):4778–4786.Google Scholar

Copyright information

© Serdi and Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  • Márlon J. R. Aliberti
    • 1
    • 2
    • 3
    • 4
  • K. E. Covinsky
    • 2
    • 3
  • D. Apolinario
    • 1
  • S. J. Lee
    • 2
    • 3
  • S. Q. Fortes-Filho
    • 1
  • J. A. Melo
    • 1
  • S. S. C. Viana
    • 1
  • C. K. Suemoto
    • 1
  • W. Jacob-Filho
    • 1
  1. 1.Division of GeriatricsUniversity of Sao Paulo Medical SchoolSao PauloBrazil
  2. 2.Division of GeriatricsUniversity of California, San Francisco (UCSF)San FranciscoUSA
  3. 3.Veterans Affairs Medical CenterSan FranciscoUSA
  4. 4.Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo, Sao PauloBrazil

Personalised recommendations