An Overview of Frailty in Kidney Transplantation

Measurement, Management and Future Considerations

Meera N. Harhay; Maya K. Rao; Kenneth J. Woodside; Kirsten L. Johansen; Krista L. Lentine; Stefan G. Tullius; Ronald F. Parsons; Tarek Alhamad; Joseph Berger; XingXing S. Cheng; Jaqueline Lappin; Raymond Lynch; Sandesh Parajuli; Jane C. Tan; Dorry L. Segev; Bruce Kaplan; Jon Kobashigawa; Darshana M. Dadhania; Mara A. McAdams-DeMarco

Disclosures

Nephrol Dial Transplant. 2020;35(7):1099-1112.

Methodology

In 2017, members from the American Society of Transplantation (AST) Kidney Pancreas Community of Practice (KPCOP) formed a Frailty Work Group with the goal of summarizing the current literature on frailty metrics, the impact of frailty on end-stage kidney disease (ESKD) and KT populations and potential interventions and areas for additional research. This project was part of a larger AST initiative to build consensus related to frailty measurement and care in solid organ transplantation.^[4] We first conducted a PubMed search for literature on relevant topics in frailty, including search terms such as 'frail elderly', 'frail instrument' and 'kidney transplant'. Our search strategy yielded 641 unique articles. We supplemented this search with searches in the EMBASE, Community Index to Nursing and Allied Health Literature and Cochrane databases. An updated search of the PubMed database was also performed in April 2019. Members of the KPCOP Frailty Work Group were divided into six subgroups of three to four individuals who reviewed the literature on a specific subtopic and created a summary. The information was shared with the KPCOP Frailty Work Group via a series of teleconferences and web-based communications from August 2017 to February 2018. The products of the subgroups were collated into a single harmonized manuscript by three primary authors (M.N.H., M.K.R. and K.J.W.) and two senior authors (M.M.D. and D.M.D.). A complete draft was circulated to the work group for feedback and revision, resulting in the final review manuscript. All authors had continuous access to the working documents to provide input, critical review and revisions.

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Table 1. Summary of commonly utilized frailty and functional metrics in studies of dialysis and KT populations
Frailty indicator	Components	Limitations	Scoring	Populations studied
Clinical frailty scale [18]	8-point scale with brief descriptions based on clinical interview that takes into account: Mobility; energy; physical activity; function	Subjective Does not include multimorbidity but does include disability	From 1 (very fit) to 8 (very severely frail)	Incident dialysis [19]
Physical frailty phenotype [17]	Five components: Shrinking (i.e. unintentional weight loss); exhaustion; physical inactivity; weakness; slowness	Subjective and objective components	Score 0–5; 0 = Robust 1–2 = Intermediate ≥3 = Frail	KT [20–26] Prevalent hemodialysis [27,28] Incident dialysis [29]
Groningen frailty indicator [30]	15 items: mobility [4]; self-rated physical fitness [1]; vision [1]; hearing; nourishment [1]; morbidity [1]; cognition [1]; psychosocial [5]	Subjective and objective components Includes morbidity and disability	Scores 0–15	Predialysis clinic [31] Predialysis and prevalent dialysis [32] Incident dialysis [29] Prevalent dialysis [33]
Tilburg frailty indicator [34,35]	15 components: physical [8]; psychologic [4]; social [3]	Subjective Does not include morbidity or disability	Scores 0–15	Prevalent dialysis [33]
Frailty index [36,37]	Deficit accumulation, including comorbid illness, poor health attitudes, signs of disease and self-reported disabilities; 40–70 deficits typically included	Components vary Includes multimorbidity and disability	0–1, scored as the number of deficits present divided by the total number assessed	Predialysis and prevalent dialysis [32]
Edmonton frail scale [38]	Eight items: cognition; general health status; functional independence; social support; medication use; nutrition; mood; continence; functional performance	Subjective and objective Includes morbidity and disability	Scores 0–17; >7 = frail	Prevalent dialysis [33]
FRAIL scale [39]	Five domains: Fatigue; resistance (ability to climb one flight of stairs); ambulation (ability to walk 1 block); illnesses (>5); loss of weight (>5%)	Subjective Includes morbidity and disability	Scores 0–5; 0 = not frail 1–2 = pre-frail ≥3 = frail	Prevalent dialysis [33]
1994 frailty measure or Strawbridge questionnaire [40]	16 items, including 4 domains: physical functioning [4]; nutritive functioning [2]; cognitive functioning [4]; sensory problems [6]	Subjective Does not include morbidity or disability	Score of ≥3 on any item = problem or difficulty with that domain; frail = difficulty in ≥2 domains	Prevalent dialysis [33]
SF-12 PCS	12-item assessment of physical functioning. Subscale of the Kidney Disease Quality of Life-36 instrument	Subjective	0–100 (lower score = worse PF)	Prevalent dialysis [41,42] KT [43]
SPPB [44]	Three items: balance; chair standing; gait speed	Does not include multimorbidity or disability	Scores 0–12	KT [45,46]
Timed up and go [47]	Standing from chair, walking a short distance, returning and sitting	Does not include multimorbidity or disability	Score in seconds	KT [48]
Gait speed [49]	Timed walking over a short distance	Does not include multimorbidity or disability	Score in seconds or meters per second	ESKD [50]

Table 2. Studies that have evaluated the association between frailty (and related constructs) and post-transplant outcomes
References	Design and participants	Frailty measure	Frailty distribution	Correlates of frailty	Outcomes
Garonzik-Wang et al. [21]^a	Prospective cohort 183 KT recipients at 1 US center (December 2008–April 2010) 35% LDKT	Physical frailty phenotype defined as score ≥3	Frailty at KT: 25% (46/183)	Baseline demographics, diabetes prevalence and donor traits were similar in frail and nonfrail recipients	DGF: 30% versus 15% in frail versus nonfrail KT recipients Frailty was independently associated with twice the risk of DGF [aRR 1.94 (95% CI 1.13–3.36)]
McAdams-DeMarco et al. [22]^a	Retrospective cohort 383 KT recipients at 1 US center (December 2008–December 2012) 39% LDKT	Physical frailty phenotype defined as score ≥3	Frailty at KT: 19% (72/383)	Frail sample includes more males (71% versus 58%, P = 0.046)	Frail KT recipients were more likely to experience EHR within 30 day (46% versus 28%, P = 0.005), regardless of age After adjusting for previously described registry-based risk factors, frailty predicted 61% higher risk of EHR [aRR 1.61 (95% CI 1.18–2.19)]
McAdams-DeMarco et al. [20]^a	Prospective cohort 349 KT recipients at 1 US center (December 2008–March 2014) 37% LDKT	Physical frailty phenotype defined as score ≥3	Frailty over time: At KT: 20%; 1 month: 33%; 2 months: 28%; 3 months: 17%		Frailty scores typically worsen at 1-month post-KT (mean change +0.4, P < 0.001), and improved by 3 months post-KT (mean change −0.3, P = 0.04) Recipients frail at time of KT were more than twice as likely to improve in post-KT frailty than nonfrail recipients [aHR 2.55 (95% CI 1.17–3.82)]
Reese et al. [41]	Retrospective cohort 19 242 KT recipients in US with linked Fresenius dialysis records 10% LDKT	SF-36 PF subscale quartile (SF-12 PCS), administered on dialysis (before listing and time-updated)	Median (IQR) subscale score: 55 (35–80)		After KT, lower PF score was associated with shorter 3-year survival (84% versus 92% for the lowest versus highest function quartiles) Compared with dialysis, KT was associated with a statistically significant survival benefit by 9 months for patients in every SF-12 PCS quartile
Harhay et al. [43]	Retrospective cohort 8870 hemodialysis patients who received KT in US—dialysis records linked to UNOS and Medicare claims data 18% LDKT	SF-36 Physical Function subscale quartile (SF-12 PCS), administered on dialysis (before listing) Hospitalizations in year before KT as proxy for frailty	28% with ≥1 pre-KT hospitalization		Lower PF score was associated with 1.24-fold EHR risk compared with higher quartiles (aOR 1.08–1.43) More than one pre-KT hospitalization associated with 1.32-fold higher EHR risk [aOR 1.32 (95% CI 1.17–1.49)]
Alhamad et al. [91]	Retrospective cohort 489 KT recipients at one center (2000–14) 29% LDKT	6-min walk test at the time of transplant evaluation	25% short walk <1101 feet 50% medium walk 1101–1414 feet Long walk >1414 feet	Recipients with short 6-min walk were more likely female and had a history of diabetes and stroke	Short walk distance was not associated with short-term risk of graft failure, but was associated with longer-term risk Selection bias, as recipients with short walk distance would be denied for transplant unless they have other favorable characteristics predicting excellent short-term outcomes
McAdams-DeMarco et al. [92]^a	Prospective cohort 443 KT recipients at 2 centers (May 2014–17) 35% LDKT	Physical Frailty Phenotype defined as score ≥2			Frail recipients had worse physical (P < 0.001) and kidney disease–specific HRQOL (P = 0.001), but similar mental HRQOL (P = 0.43) Frail recipients experienced significantly greater rates of improvement in physical HRQOL [frail: 1.35 points/month (95% CI 0.65–2.05); nonfrail: 0.34 points/month (95% CI −0.17 to 0.85); P = 0.02] and kidney disease–specific HRQOL [frail: 3.75 points/month (95% CI 2.89–4.60); nonfrail: 2.41 points/month (95% CI 1.78–3.04); P = 0.01], but no difference in mental HRQOL
McAdams-DeMarco et al. [59]^a	Prospective cohort 663 KT recipients at one center (December 2008–August 2015) 39% LDKT	Physical frailty phenotype defined as score ≥2	Frailty at KT: 20%	Age was the only conventional factor associated with frailty However, factors rarely measured as part of clinical practice (e.g. HRQOL, IADL disability and depressive symptoms) were significant correlates of frailty	KT recipients with exhaustion and slowed walking speed [HR 2.43 (95% CI 1.17–5.03)] and poor grip strength, exhaustion and slowed walking speed [HR 2.61 (95% CI 1.14–5.97)] had increased mortality risk over an average of 3.1 years of follow-up
Lynch et al. [93]	Retrospective cohort 37 623 Medicare-insured KT recipients in the USRDS (January 2000–December 2010) %LDKT not reported	Hospitalization days within 1 year before KT as proxy for frailty	Hospitalization days in pre-KT year: 0: 51%; 1–7: 25%; 8–14: 11%; 15+: 13%	Patients with highest level of pre-KT hospitalization days were more commonly: women, previous transplant recipients, diabetic and those with CHF, atherosclerotic vascular disease and COPD	After adjusting for other baseline factors, pre-KT hospitalization days (1–7, 8–14, 15+) bore graded associations with readmission in the first year after KT [aHR 1.28 (95% CI 1.17–1.70)] and with mortality [aHR 1.42 (95% CI 1.20–1.70)] and all-cause graft loss [aHR 1.30 (95% CI 1.15–1.44)] >3 years post-KT
Lynch et al. [78]	Retrospective cohort 51 111 Medicare-insured KT recipients in the USRDS (January 2000–December 2010) 0% LDKT	Hospitalization days in first year after waitlisting as a proxy for frailty	Hospitalization days in first year after listing: 0: 46.9%; 1–7: 22.6%; 8–14: 11.7%; 15+: 18.7%	More hospitalization days associated with female sex, white race, previous transplant, diabetes, CHF, atherosclerotic vascular disease and COPD	After adjusting for other baseline factors, hospitalization days after listing (1–7, 8–14, 15+) bore graded associations with death after listing [aHR 1.49 (95% CI 1.24–2.07)] and with decreased likelihood of KT Model using wait-list hospitalization days alone had higher predictive accuracy for wait-list mortality than EPTS score

^aDistinct samples/analyses from the same cohort.
LDKT, living donor kidney transplantation; aHR, adjusted hazard ratio; USRDS, US Renal Data Service; IADL, independent activities of daily living.

Authors and Disclosures

Meera N. Harhay^1–3,*, Maya K. Rao^4,*, Kenneth J. Woodside^5,*, Kirsten L. Johansen⁶, Krista L. Lentine⁷, Stefan G. Tullius⁸, Ronald F. Parsons⁹, Tarek Alhamad¹⁰, Joseph Berger¹¹, XingXing S. Cheng¹², Jaqueline Lappin¹³, Raymond Lynch⁹, Sandesh Parajuli¹⁴, Jane C. Tan¹², Dorry L. Segev^15,16, Bruce Kaplan¹⁷, Jon Kobashigawa¹⁸, Darshana M. Dadhania^19,* and Mara A. McAdams-DeMarco^15,16,*

¹Department of Medicine, Division of Nephrology, Drexel University College of Medicine, Philadelphia, PA, USA, ²Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA, ³Tower Health Transplant Institute, Tower Health System, West Reading, PA, USA, ⁴Division of Nephrology, Columbia University Vagelos College of Physicians & Surgeons, New York, NY, USA, ⁵Department of Surgery, University of Michigan, Ann Arbor, MI, USA, ⁶Hennepin Healthcare, University of Minnesota, Minneapolis, MN, USA, ⁷Center for Abdominal Transplantation, St Louis University School of Medicine, St Louis, MO, USA, ⁸Department of Surgery, Division of Transplant Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA, ⁹Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA, ¹⁰Division of Nephrology, Washington University School of Medicine, St Louis, MO, USA, ¹¹Department of Internal Medicine, Division of Nephrology, UT Southwestern Medical Center, Dallas, TX, USA, ¹²Department of Medicine, Division of Nephrology, Stanford University School of Medicine, Palo Alto, CA, USA, ¹³St. David's North Austin Medical Center, North Austin, TX, USA, ¹⁴Department of Medicine, Division of Nephrology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA, ¹⁵Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA, ¹⁶Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, ¹⁷Vice President System Office, Baylor Scott and White Health, Temple, TX, USA, ¹⁸Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA and ¹⁹Department of Transplantation Medicine, New York Presbyterian Hospital - Weill Cornell Medical Center, New York, NY, USA

Correspondence to
Meera N. Harhay; E-mail: mnh52@drexel.edu; Twitter handles: @MeeraHarhay; @McAdamsDeMarco; @KristaLentine; @ronaldfparsons; @Dorry_Segev

*These authors contributed equally to this work.

Authors' Contributions
M.N.H., M.K.R., K.J.W., K.L.J., K.L.L., S.G.T., R.F.P., T.A., J.B., X.S.C., J.L., R.L., S.P., J.C.T., D.L.S., B.K., J.K., D.M.D. and M.A.M.-D. participated in research design. M.N.H., M.K.R., K.J.W., K.L.J., K.L.L., S.G.T, R.F.P., T.A., J.B., X.S.C., J.L., R.L., S.P., J.C.T., D.L.S., B.K., J.K., D.M.D. and M.A.M.-D. participated in writing of the article. M.N.H., M.K.R., K.J.W., K.L.J., K.L.L., S.G.T., R.F.P., T.A., J.B., X.S.C., J.L., R.L., S.P., J.C.T., D.L.S., B.K., J.K., D.M.D. and M.A.M.-D. participated in the performance of the research. M.N.H., M.K.R., K.J.W., K.L.J., K.L.L., S.G.T., R.F.P., T.A., J.B., X.S.C., J.L., R.L., S.P., J.C.T., D.L.S., B.K., J.K., D.M.D. and M.A.M.-D. reviewed and approved the final manuscript.

Conflict of Interest Statement
D.L.S. reports personal fees from Sanofi-Aventis and Novartis outside the submitted work. D.M.D. reports personal fees from Veloxis Pharmaceutical, Inc. and AlloVir Inc. outside the submitted work. There are no other disclosures or financial conflicts of interest reported. Results presented in this article have not been published previously in whole or part.