» Articles » PMID: 29282014

Spectrum (characteristics) of Patients with Chronic Kidney Disease (CKD) with Increasing Age in a Major Metropolitan Renal Service

Overview
Journal BMC Nephrol
Publisher Biomed Central
Specialty Nephrology
Date 2017 Dec 29
PMID 29282014
Citations 14
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Aim of our study is to describe, in people with CKD, the demographic and clinical characteristics and outcomes with increasing age. The prevalence of CKD in Western populations, where longevity is the norm, is about 10-15%, but how age influence different characteristics of patients with CKD is largely not known.

Methods: One thousand two hundred sixty-five patients enrolled in the CKD.QLD registry at the Royal Brisbane and Women's Hospital were grouped according to age at consent i.e. <35, 35-44, 45-54, 55-64, 65-74, 75-84, 85+ years age groups, and were followed till start of renal replacement therapy (RRT), death, discharge or the censor date of September 2015.

Results: Age ranged from 17.6 to 98.5 years with medians of 70.1 and 69.9 years for males and females respectively: 7% were <35 years of age, with the majority (63%) >65 years old. The leading renal diagnoses changed from genetic real disease (GRD) and glomerulonephritis (GN) in the younger patients to renovascular disease (RVD) and hypertension (HTN) in older patients. With increasing age, there were often multiple renal disease diagnoses, more advanced stages of CKD, greater number of comorbidities, more frequent and more costly hospitalizations, and higher death rates. The rates of initiation of renal replacement therapy (RRT) rose from 4.5 per 100 person years in those age < 35 years to a maximum of 5.5 per 100 person years in 45-54 years age group and were lowest, at 0.5 per 100 person years in those >85 years. Mortality rates increased by age group from 1.3 to 17.0 per 100 person years in 35-44 year and 85+ year age groups respectively. Rates of hospitalization, length of stay and cost progressively increased from the youngest to eldest groups. Patients with diabetic nephropathy had highest incidence rate of RRT and death. The proportion of patients who lost more than 5mls/min/1.73m of eGFR during at least 12 months follow up increased from 13.3% in the youngest age group to 29.2% in the eldest.

Conclusion: This is the first comprehensive view, with no exclusions, of CKD patients seen in a public renal specialty referral practice, in Australia. The age distribution of patients encompasses the whole of adult life, with a broader range and higher median value than patients receiving RRT. Health status ranged from a single system (renal) disease in young adults through, with advancing age, renal impairment as a component of, or accompanying multisystem diseases, to demands and complexities of support of frail or elderly people approaching end of life. This great spectrum demands a broad understanding and capacity of renal health care providers, and dictates a need for a wider scope of health services provision incorporating multiple models of care.

Citing Articles

Baseline Characteristics of Frailty and Disease Stage in Older People Living With CKD.

Logan B, Pascoe E, Viecelli A, Johnson D, Comans T, Hawley C Kidney Int Rep. 2025; 10(1):120-133.

PMID: 39810773 PMC: 11725818. DOI: 10.1016/j.ekir.2024.10.009.


International comparison and time trends of first kidney transplant recipient characteristics across Europe: an ERA Registry study.

Boenink R, Kramer A, Masoud S, Rodriguez-Benot A, Helve J, Bistrup C Nephrol Dial Transplant. 2023; 39(4):648-658.

PMID: 37653455 PMC: 10966326. DOI: 10.1093/ndt/gfad189.


The Etiology of Kidney Failure in Indonesia: A Multicenter Study in Tertiary-Care Centers in Jakarta.

Hustrini N, Susalit E, Lydia A, Marbun M, Syafiq M, Yassir Ann Glob Health. 2023; 89(1):36.

PMID: 37273488 PMC: 10237240. DOI: 10.5334/aogh.4071.


Chronic kidney disease in public renal practices in Queensland, Australia, 2011-2018.

Hoy W, Wang Z, Zhang J, Diwan V, Cameron A, Venuthurupalli S Nephrology (Carlton). 2022; 27(12):934-944.

PMID: 36161428 PMC: 9828529. DOI: 10.1111/nep.14111.


Comparison Between Statistical Model and Machine Learning Methods for Predicting the Risk of Renal Function Decline Using Routine Clinical Data in Health Screening.

Cao X, Lin Y, Yang B, Li Y, Zhou J Risk Manag Healthc Policy. 2022; 15:817-826.

PMID: 35502445 PMC: 9056070. DOI: 10.2147/RMHP.S346856.


References
1.
Dienemann T, Fujii N, Orlandi P, Nessel L, Furth S, Hoy W . International Network of Chronic Kidney Disease cohort studies (iNET-CKD): a global network of chronic kidney disease cohorts. BMC Nephrol. 2016; 17(1):121. PMC: 5010740. DOI: 10.1186/s12882-016-0335-2. View

2.
Lash J, Go A, Appel L, He J, Ojo A, Rahman M . Chronic Renal Insufficiency Cohort (CRIC) Study: baseline characteristics and associations with kidney function. Clin J Am Soc Nephrol. 2009; 4(8):1302-11. PMC: 2723966. DOI: 10.2215/CJN.00070109. View

3.
Venuthurupalli S, Hoy W, Healy H, Salisbury A, Fassett R . CKD.QLD: chronic kidney disease surveillance and research in Queensland, Australia. Nephrol Dial Transplant. 2012; 27 Suppl 3:iii139-45. PMC: 3484715. DOI: 10.1093/ndt/gfs258. View

4.
Foley R, Parfrey P, Sarnak M . Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis. 1998; 32(5 Suppl 3):S112-9. DOI: 10.1053/ajkd.1998.v32.pm9820470. View

5.
Collins A, Foley R, Chavers B, Gilbertson D, Herzog C, Johansen K . 'United States Renal Data System 2011 Annual Data Report: Atlas of chronic kidney disease & end-stage renal disease in the United States. Am J Kidney Dis. 2011; 59(1 Suppl 1):A7, e1-420. DOI: 10.1053/j.ajkd.2011.11.015. View