Background
The progressive aging of the population in industrialized countries is accompanied by a dramatic increase in the prevalence of multiple chronic diseases [
1]. Traditionally, research has embraced the comorbidity conceptual framework, i.e. a framework which identifies an index disease and focuses on the probability of having other (secondary) diseases [
2]. In an attempt to meet the complex problems posed by older patients with multiple chronic diseases, the attention has progressively shifted from the comorbidity to the multimorbidity conceptual framework. In this approach the co-occurrence of two or more diseases is taken into consideration without identifying an index disease [
3,
4]. From the clinical point of view, the multimorbidity concept tends to push geriatric medicine towards an individual-oriented and no longer disease-oriented approach. Several different analytic approaches can be used to investigate multimorbidity. Studies explored multimorbidity by applying different methods (e.g. prevalence figures, conditional count, logistic regression models, cluster or network analysis and data mining techniques) to disease variables in different populations, and provided convincing evidence that chronic diseases may combine each other not simply due to chance [
5‐
10].
Chronic kidney disease (CKD) is among the most frequent chronic conditions observed among older patients, and it dramatically impacts health status and survival in the general population, as well as in older populations [
11‐
14]. Although CKD is known to be associated with several long lasting conditions, such as hypertension, diabetes, heart failure, anemia and osteoporosis, studies investigating patterns of multimorbidity including CKD provided heterogeneous results. Formiga et al. [
6] showed that CKD may contribute to a multimorbidity cluster including cardio- and cerebro-vascular disease, atrial fibrillation, diabetes mellitus and visual impairment. More recently, CKD was found to contribute to a larger cluster including cardiovascular diseases (excluded coronary artery disease), endocrine abnormalities, neurological disorders including dementia, respiratory and muscle-skeletal diseases, infections and sensory impairment [
10]. Thus, multimorbidity patterns involving CKD are worth of testing in other different populations.
Additionally, data about the impact of potentially relevant stratification variables on patterns of multimorbidity are very limited. Current evidence suggests that age, sex, and race/ethnicity may be associated with small but not negligible changes in multimorbidity patterns [
10]. However, whether patterns of multimorbidity may change as a function of physical performance has not been investigated until now, despite the bidirectional interplay of multimorbidity and functional decline is more and more recognized as a crucial step in the assessment of health and care needs of older complex patients [
15].
Finally, CKD severity may also affect multimorbidity patterns. Indeed, many of CKD-related concordant comorbidities, such as anemia, osteoporosis and heart failure, are known to be associated with the severity of CKD [
16].
By including a detailed collection of data about diagnoses and comprehensive geriatric assessment including short physical performance battery (SPPB) [
17], the Screening for CKD among Older People across Europe (SCOPE) study represents a valuable opportunity to explore multimorbidity patterns as well as the impact of physical performance and CKD severity on them in a population of older community-dwelling people. These were the main objectives of our study.
Discussion
Findings from the present study suggests that CKD significantly contributes to multimorbidity patterns in a population of older outpatients. Additionally, simple count of disease may hide several important information otherwise obtained by the analysis of most relevant pairs of co-occurring disease or disease clusters. Indeed, as already reported in former studies [
5,
6,
26,
27] the occurrence of individual conditions without any associated disease was rarely observed in our study population. Finally, and in a relevant way, our study also suggests that multimorbidity patterns may change as a function of physical performance as assessed by SPPB.
The most relevant co-occurring pairs involving CKD observed in our study where those with hypertension, anemia, CHF, atrial fibrillation, myocardial infarction, hip fracture, and to a lesser extent hearing impairment, diabetes and cancer. The weak association between CKD and diabetes was not surprising given that almost all diabetic patients also had high blood pressure in our study and removing hypertension from the multivariable model made statistically significant such association in pairs analysis. Additionally, it is worth noting that after stratification by SPPB score other significant pairs emerged among patients with SPPB = 5–8 (vision impairment) and SPPB = 0–4 (hearing impairment). Thus, it seems that a simple physical performance test, already known to predict mobility disability, ADL dependency, rehospitalization and death [
28‐
31], may also help to describe patients with somewhat different profiles of co-occurring pairs of diseases.
While the association between CKD and cardiovascular diseases, anemia, diabetes and mineral bone disease (including fractures) is well recognized and extensively addressed in clinical guidelines where specific recommendations are provided for these conditions [
32], the combination of CKD with cancer and sensory impairments deserves to be discussed. Chronic kidney disease (CKD) and cancer are strictly related each other. Cancer can cause CKD either directly or indirectly through the adverse effects of treatments. Conversely, CKD may represent a relevant risk factor for cancer [
33]. Indeed, though the increased risk of death observed among CKD patients is mainly attributable to cardiovascular disease, the incidence of cancer is also increased [
16]. Cancer can affect the kidney either as glomerular lesions or as a result of the toxic effects of medication or radiation with acute (thrombotic microangiopathy, acute kidney injury, interstitial nephropathies among others) or chronic processes (worsening of CKD after nephrectomy due to renal cancer, interstitial fibrosis, water and electrolytes disorders) [
34]. It is worth noting that we only considered history of cancer in our study, while patients carrying active malignancies during the last 24 months before enrollment were excluded. Nevertheless, older cancer survivors may be more likely to develop frailty or worsening of the health status, and such association may be especially relevant among individuals with a recent (< 10 years) history of cancer [
35].
Given the mean age of enrolled patients, the association between CKD and sensory impairment may be simply related to older age independent of kidney function. However, several potential mechanisms may underly such association. Hearing loss was found to be highly prevalent among CKD patients [
36,
37], and increasing serum creatinine or blood pressure was found associated with increasing hearing threshold [
38]. Several similarities between cochlea and kidney can be observed, including membranous structures, the central role of ciliated epithelial cells, and tubular organization [
39]. In experimental uremic animals, a significant decrease in cochlear Na + −K + -ATPase activity resulted in hearing impairment [
40]. Additionally, ototoxic medications may also contribute to the observed association. For example, furosemide may affect ionic gradients between the endolymph and perilymph thus altering endocochlear potential and leading to cochlear dysfunction [
41]. The association between CKD and vision impairment was also reported to be highly prevalent in CKD patients. A population study involving 10,033 adults aged 40–80 years showed that the prevalence of vision impairment and ocular disease were significantly higher in participants with (36.1 and 84.7%) compared to those without CKD (12.9 and 54.3%, both
p < 0.001) [
42]. Diabetic retinopathy and age-related macular degeneration are most consistently associated with CKD [
43]. It is worth noting that mechanisms underlying CKD, such as vascular remodeling, endothelial dysfunction, atherosclerosis, inflammation, and oxidative stress are also involved in the development of many eye diseases. Besides diabetes and hypertension, metabolic disorders associated with CKD, such as oxidative stress, uremia, anemia, as well as specific treatment, such as steroids and dialysis may be also involved [
43]. Despite this bulk of evidence, screening for vision and hearing impairment is not currently recommended in CKD clinical guidelines and our findings suggest for its potential usefulness in this vulnerable population.
Cluster analysis provided quietly consistent results showing that CKD may contribute to a cluster of multimorbidity including hypertension and sensory impairments in the whole study population. These findings are somewhat different from those reported in former studies and characteristics of population, as well as the list of diagnoses included in the analysis likely account for these differences. Marengoni et al. identified five major clusters (two linked to vascular diseases with hypertension and heart failure playing the main role and the others to dementia, diabetes mellitus, and malignancy) in a population of 1099 community-dwelling people aged 77 or more. However, CKD was not included in the list of diagnoses [
5]. In the study by Formiga et al. [
6], the list of diagnoses was very similar to that in our study and four main clusters were identified in a population of 328 oldest old people aged 85 or more. CKD contributed to a multimorbidity cluster including atrial fibrillation, heart failure, visual impairment, stroke, hypertension and diabetes mellitus [
6]. More recently, Zemedikun et al. [
10] identified 3 main multimorbidity clusters with CKD contributing to the wide cluster including cardiovascular diseases (excluded coronary artery disease), endocrine abnormalities, neurological disorders including dementia, respiratory and muscle-skeletal diseases, infections and sensory impairment. However, at variance from our study their analysis was carried out in a population younger than 70 years [
10].
Interestingly, when stratifying analysis according to physical performance, the cluster including CKD was “enriched” by a sub-cluster including anemia and osteoporosis (i.e. two well-known complications of CKD, namely CKD-related anemia and CKD-Mineral Bone Disease (CKD-MBD)) and diabetes (i.e. a leading cause of CKD) among patients with lowest SPPB scores. Thus, both co-occurring pairs and clustering of diseases may change as a function of SPPB among older people in the present study, and SPPB is among the most useful frailty tools for the identification of patients that may benefit from interventions aimed at improving functional capacity in primary care settings [
44]. Our findings are in keeping with current guidelines stating that frailty and sensory impairments are very relevant items when investigating multimorbidity, while defining multimorbidity by simple counts of health conditions may be misleading [
45]. Indeed, current evidence suggests that frailty and multimorbidity are strictly related each other in older adults [
46,
47]. Additionally, physical performance assessed by gait speed and grip strength was recently found significantly associated with both the development of multimorbidity and worsening pre-existing multimorbidity, with evidence of a dose–response relationship [
48]. Our results further strengthen the need to assess physical function in clinical practice and to establish specific function-oriented interventions able to reduce the burden of multimorbidity and related negative outcomes.
Finally, this is the first study including CKD severity in the analysis of multimorbidity patterns. Indeed, CKD severity was not considered in former multimorbidity studies [
6,
10]. Besides confirming that the strength of the association between CKD and selected complications, i.e. hypertension, sensory impairments, osteoporosis, anemia and CHF may increase together with CKD severity [
16], our study adds to current knowledge by showing that the complexity of multimorbidity cluster including CKD may also change in relation to CKD severity. These findings suggest that severity of individual diseases should be taken into consideration in future studies of multimorbidity among older complex patients.
Limitations of our study deserve to be mentioned. The cross-sectional design did not allow to investigate pathways leading to multimorbidity and the prognostic impact of specific multimorbidity patterns. Additionally, the list of diagnoses included in the analysis could not be considered exhaustive. However, we used a list of diagnoses very similar to that already used in studies investigating multimorbidity patterns. Nevertheless, the prevalence of individual diseases and that of individual diagnoses with multimorbidity was somewhat higher in the SCOPE study population compared to former studies [
5,
6,
10], likely because we enrolled older people attending outpatients services in participating institutions with an extensive assessment and a complete analysis of clinical documentation exhibited by patients and caregivers, while former studies were population-based [
5,
6,
10]. Our study did not include the assessment of severity of each individual disease other than CKD and findings from CKD severity analysis suggest that disease severity may represent a relevant confounder. The very rare occurrence of selected diagnoses without multimorbidity prevented us to explore differences between patients with and without multimorbidity. Finally, we need to recognize that while the analysis of co-occurring pairs may have an immediate clinical relevance, results obtained by hierarchical cluster analysis of diagnoses is less easy to be translated to clinical practice. Nevertheless, these exploratory data may represent a sound scientific basis for future studies on the clinical characterization of patient clusters and/or groups carrying specific multimorbidity patterns involving CKD. This study also has important strengths, including the enrollment of a real-world European population of older community-dwelling people and the opportunity to investigate the impact of objectively measured physical performance on patterns of multimorbidity.
Acknowledgements
SCOPE study investigators
Coordinating center, Fabrizia Lattanzio, Italian National Research Center on Aging (INRCA), Ancona, Italy – Principal Investigator. Andrea Corsonello, Silvia Bustacchini, Silvia Bolognini, Paola D’Ascoli, Raffaella Moresi, Giuseppina Di Stefano, Cinzia Giammarchi, Anna Rita Bonfigli, Roberta Galeazzi, Federica Lenci, Stefano Della Bella, Enrico Bordoni, Mauro Provinciali, Robertina Giacconi, Cinzia Giuli, Demetrio Postacchini, Sabrina Garasto, Annalisa Cozza, Francesco Guarasci, Sonia D’Alia - Italian National Research Center on Aging (INRCA), Ancona, Fermo and Cosenza, Italy – Coordinating staff. Romano Firmani, Moreno Nacciariti, Mirko Di Rosa, Paolo Fabbietti – Technical and statistical support.
Participating centers
• Department of Internal Medicine, Medical University of Graz, Austria: Gerhard Hubert Wirnsberger, Regina Elisabeth Roller-Wirnsberger, Carolin Herzog, Sonja Lindner
• Section of Geriatric Medicine, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, The Netherlands: Francesco Mattace-Raso, Lisanne Tap, Gijsbertus Ziere, Jeannette Goudzwaard.
• Department of Geriatrics, Healthy Ageing Research Centre, Medical University of Lodz, Poland: Tomasz Kostka, Agnieszka Guligowska, Łukasz Kroc, Bartłomiej K Sołtysik, Małgorzata Pigłowska, Agnieszka Wójcik, Zuzanna Chrząstek, Natalia Sosowska, Anna Telążka, Joanna Kostka, Elizaveta Fife, Katarzyna Smyj, Kinga Zel.
• The Recanati School for Community Health Professions at the faculty of Health Sciences at Ben-Gurion University of the Negev, Israel: Rada Artzi-Medvedik, Yehudit Melzer, Mark Clarfield, Itshak Melzer; and Maccabi Healthcare services southern region, Israel: Rada Artzi-Medvedik, Ilan Yehoshua, Yehudit Melzer.
• Geriatric Unit, Internal Medicine Department and Nephrology Department, Hospital Universitari de Bellvitge, Institut d’Investigació Biomèdica de Bellvitge - IDIBELL, L’Hospitalet de Llobregat, Barcelona, Spain: Francesc Formiga, Rafael Moreno-González, Xavier Corbella, Yurema Martínez, Carolina Polo, Josep Maria Cruzado.
• Department of Geriatric Medicine, Hospital Clínico San Carlos, Madrid: Pedro Gil Gregorio, Sara Laínez Martínez, Mónica González Alonso, Jose A. Herrero Calvo, Fernando Tornero Molina, Lara Guardado Fuentes, Pamela Carrillo García, María Mombiedro Pérez.
• Department of General Internal Medicine and Geriatrics, Krankenhaus Barmherzige Brüder Regensburg and Institute for Biomedicine of Aging, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany: Alexandra Renz, Susanne Muck, Stephan Theobaldy, Andreas Bekmann, Revekka Kaltsa, Sabine Britting, Robert Kob, Christian Weingart, Ellen Freiberger, Cornel Sieber.
• Department of Medical Sciences, Uppsala University, Sweden: Johan Ärnlöv, Axel Carlsson, Tobias Feldreich.
Scientific advisory board (SAB)
Roberto Bernabei, Catholic University of Sacred Heart, Rome, Italy
Christophe Bula, University of Lausanne, Switzerland
Hermann Haller, Hannover Medical School, Hannover, Germany
Carmine Zoccali, CNR-IBIM Clinical Epidemiology and Pathophysiology of Renal Diseases and Hypertension, Reggio Calabria, Italy
Data and Ethics Management Board (DEMB)
Dr. Kitty Jager, University of Amsterdam, The Netherlands
Dr. Wim Van Biesen, University Hospital of Ghent, Belgium
Paul E. Stevens, East Kent Hospitals University NHS Foundation Trust, Canterbury, United Kingdom
We thank the BioGer IRCCS INRCA Biobank for the collection of the SCOPE samples.
Ethics approval and consent to participate
The study protocol was approved by ethics committees at all participating institutions, and complies with the Declaration of Helsinki and Good Clinical Practice Guidelines. All patients signed a written informed consent to be enrolled. Only baseline data are used in the present study. Ethics approvals have been obtained by Ethics Committees in participating institutions as follows:
Italian National Research Center on Aging (INRCA), Italy, #2015 0522 IN, January 27, 2016.
University of Lodz, Poland, #RNN/314/15/KE, November 17, 2015.
Medizinische Universität Graz, Austria, #28–314 ex 15/16, August 5, 2016
Erasmus Medical Center Rotterdam, The Netherland, #MEC-2016-036 - #NL56039.078.15, v.4, March 7, 2016.
Hospital Clínico San Carlos, Madrid, Spain, # 15/532-E_BC, September 16, 2016
Bellvitge University Hospital Barcellona, Spain, #PR204/15, January 29, 2016.
Friedrich-Alexander University Erlangen-Nürnberg, Germany, #340_15B, January 21, 2016.
Helsinki committee in Maccabi Healthcare services, Bait Ba-lev, Bat Yam, Israel, #45/2016, July 24, 2016.