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Prevalence of chronic kidney disease in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis

BMC Pulmonary MedicineBMC series – open, inclusive and trusted201616:158

https://doi.org/10.1186/s12890-016-0315-0

Received: 1 July 2016

Accepted: 7 November 2016

Published: 24 November 2016

Abstract

Background

The incidence and prevalence of chronic kidney disease (CKD) continue to rise worldwide. Increasing age, diabetes, hypertension, and cigarette smoking are well-recognized risk factors for CKD. Chronic obstructive pulmonary disease (COPD) is characterized by chronic airway inflammation leading to airway obstruction and parenchymal lung destruction. Due to some of the common pathogenic mechanisms, COPD has been associated with increased prevalence of CKD.

Methods

Systematic review of medical literature reporting the incidence and prevalence of CKD in patients with COPD using the Cochrane Collaboration Methodology, and conduct meta-analysis to study the cumulative effect of the eligible studies. We searched Medline via Ovid, PubMed, EMBASE and ISI Web of Science databases from 1950 through May, 2016. We included prospective and retrospective observational studies that reported the prevalence of CKD in patients with COPD.

Results

Our search resulted in 19 eligible studies of which 9 have been included in the meta-analysis. The definition of CKD was uniform across all the studies included in analysis. COPD was found to be associated with CKD in the included epidemiological studies conducted in many countries. Our meta-analysis showed that COPD was found to be associated with a significantly increased prevalence of CKD (Odds Ratio [OR] = 2.20; 95% Confidence Interval [CI] 1.83, 2.65). Study limitations: Studies included are observational studies. However, given the nature of our research question there is no possibility to perform a randomized control trial.

Conclusions

Patients with COPD have increased odds of developing CKD. Future research should investigate the pathophysiological mechanism behind this association, which may lead to better outcomes.

Keywords

Chronic obstructive pulmonary disease Emphysema Chronic bronchitis Chronic kidney disease Comorbidity Glomerular filtration rate

Background

Chronic kidney disease (CKD) is a major public health problem in the United States, with rising incidence and prevalence of kidney failure, with poor outcomes and high cost. There is an even higher prevalence of earlier stages of CKD. According to the Third National Health and Nutrition Examination Survey (NHANES III), it was estimated that 6.2 million people (3% of total US population) above the age of 12 years had a serum creatinine above 1.5 mg/dl and 8 million people had a glomerular filtration rate (GFR) <60 ml/min/1.73 m2 The majority of these people are greater than 65 years of age (5.9 million).

Diabetes, hypertension and cardiovascular disease are associated with greater prevalence of CKD [1, 2]. In addition, CKD has a complicated interrelationship with these diseases. As per United States Renal Data System (USRDS data), prevalence of stage 3 CKD has been increasing. Although the prevalence of hypertension (HTN) did not rise, the incidence of diabetes mellitus (DM) has increased 4 fold from 1980 to 2014 [3]. Studies have reported that CKD is an independent risk factor for cardiovascular disease [4]. In recent years, additional causes of CKD have been recognized such as unrecovered acute kidney injury (AKI) [5, 6] and use of proton pump inhibitors (PPIs) [7, 8], In this manuscript we analyze the association of CKD with COPD using the limited data available… Several studies have identified COPD as part of a systemic inflammatory syndrome [912] and reported on the association of comorbidities like lung cancer [13], osteoporosis [14], progression of atherosclerosis [15], and CKD. This systematic review was performed to assess the association of COPD with CKD.

Methods

Eligibility criteria

We included prospective and retrospective observational studies that reported the prevalence of CKD in patients with COPD when compared to those without COPD. Most of the studies established the diagnosis of COPD using Spirometry or ICD-9 codes obtained from their medical records while others were based on history or physician diagnosed COPD. Prevalence of CKD in the majority of the studies was reported based on eGFR obtained from laboratory data. We only included studies that reported data on adult populations.

Search strategy

In January 2016, we electronically searched PubMed, Medline (1950 onwards; access via Ovid), EMBASE (all years; access via Ovid) and Web of Science using a detailed search strategy with search terms described below and in Additional file 1. After initial detailed discussion of the aim of the study, the search strategy was outlined by the authors. Search terms used for COPD were: ‘COPD’, ‘chronic obstructive pulmonary disease’, ‘emphysema’, ‘chronic bronchitis’. Search terms used for CKD were: ‘chronic kidney disease’, ‘CKD’, ‘ESRD’, ‘end stage renal disease’, ‘renal insufficiency’, ‘renal failure’.

Inclusion criteria: We included all prospective and retrospective observational studies reporting the prevalence of CKD in patients with COPD compared to those without COPD; there were no restrictions on language of publication.

Exclusion criteria: We excluded studies that did not report the association of CKD with COPD; those that were not focused on the association of CKD with COPD; studies that did not have appropriate methodological study design of comparison groups; studies with data which was incompletely recorded; and those involving pediatric populations.

We reviewed keywords and related studies. From using the selected studies, we proceeded further in the literature search looking for “related articles” in PubMed. References of the included studies were manually searched to ensure inclusion of all related articles.

Selection process

Two reviewers independently reviewed the titles and abstracts of the citations resulting from the search using a standardized screening guide. Full text was obtained for the articles which were thought to be eligible by at least one of the reviewers.. Each reviewer reviewed these full texts independently to judge their eligibility to be included in our review. Disparities between the two reviewers about which studies should be included were discussed and resolved by a third reviewer.

Data abstraction

Data was independently extracted from the included studies by two reviewers (SG and SGK) using a standardized and pilot-tested form for data abstraction. Any differences in extracted data were discussed by the reviewers, and if not resolved, by discussion with a third reviewer. The pilot-tested form included study design, method used to diagnose COPD and CKD, population, methodological characteristics of the study, and the reported results. We recorded the effect measures derived from the regression models that adjusted for the maximum number of covariates. We rated the overall quality of evidence for each outcome using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach [16].

Data analysis

The kappa statistic was calculated to determine the agreement between the two reviewers of the full texts of the studies for inclusion eligibility. Meta-analysis was performed from the studies that reported the prevalence/incidence of CKD in patients with COPD compared to patients without COPD. In studies that did not report actual number of events, other available data (such as percentages) was used to calculate the number of events for the evaluated outcomes. For each outcome, we pooled the odds ratios (OR) of eligible studies using the generic inverse variance and the random effects model in Review Manager Version 5.3. The random effects model was used as the included studies evaluated different patient populations. We measured homogeneity across study results using the I2 statistic. We examined possible publication bias using inverted funnel plots.

Results

Our extensive electronic database search of databases in January, 2016 resulted in 7583 articles. A flow diagram with detailed outline of literature search is provided in Additional file 2. After detailed review of the articles, our literature search resulted in 17 studies related to the topic of our research. Manual search for related articles helped identify an additional study that was recently published and did not have a PubMed ID [17]. Another study was published in April 2016 while we were in the process of submission for publication [18]. As a result, we included 19 articles related to our topic of interest.

Nine of these studies reported the prevalence of CKD in patients with COPD compared to those without COPD [1726]. We reported a detailed review of these studies with data extraction in Table 1 and we included the results reported in these studies in a meta-analysis to estimate the cumulative effect. The remaining 10 studies did not meet inclusion criteria for meta-analysis [2735]. A detailed review of these articles is reported in Table 2. Eight of these 10 studies have been excluded since they are longitudinal studies that reported the prevalence of CKD in a cohort of patients with COPD [18, 2730, 3234]. One of the studies has been excluded due to the study design and since the data could not be used for analysis [31]. One other study was excluded due to use of non-standardized method to assess the prevalence of CKD and therefore did not meet criteria to be included in the systematic review [35]. The reviewers had very good agreement on study eligibility (kappa = 0.983). Using GRADE approach [16], the quality of evidence from the studies included in our review was found to be moderate to low.
Table 1

Systematic review of 9 studies reporting prevalence of CKD in patients with COPD compared to controls; included in meta-analysis

Study

Population

COPD diagnosis method & Definition of CKD

Methodological features

Results

Baty et al.; 2013 [8]

Study design: Population based case-control study

Funding: Takeda Pharma AG, Switzerland

Setting & period: All hospitalizations in Switzerland between 2002 and 2010

COPD group: 340, 948 patients, 64% males, median age 73 years

Non-COPD group: 340,948 patients, 64% males, median age 73 years

Diagnosis of COPD: Based on ICD-10 codes

CKD definition: Based on ICD-10 code

Blinding of outcome adjudicator: not reported

Selection bias: none

Information bias: objective

outcome evaluation: no;

standardized CKD risk

measurement: no

Confounding: no Matching: yes. Adjustment in analysis: yes Confounding variables: no

Loss to follow up: none

4.39% of patients with COPD had Chronic kidney disease (ICD 10 code, N188) compared to 2.13% of patients without COPD (p < 0.001)

4.64% of patients with COPD had Chronic kidney disease unspecified (ICD 10 code, N189) compared to 2.25% of patients without COPD (p < 0.001)

Gjerde et al.; 2011 [9]

Study design: Case-control study

Funding: The Foundation for Respiratory Research, Center for Clinical Research, Bergen

Setting & period: Patients aged 40-76 years with COPD were recruited from health institutions in Hordaland County in Western Norway, where as those without COPD were recruited among former participants from a general population survey in Hordaland County; between 2006 and 2007

COPD group: 433 patients, 59.6% male

Non-COPD group: 233 patients

Diagnosis of COPD: using Spirometry

CKD definition: eGFR <60

Blinding of outcome adjudicator: not reported

Selection bias: yes, voluntarily included, not random

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: yes Matching: no. Adjustment in analysis: yes Confounding variables: no

Loss to follow up: none

Prevalence of undiagnosed renal failure in the COPD patients was 6.9%, significantly higher than among the subjects without COPD (p < 0.001)

Incalzi et al.; 2010 [10]

Study design: Case-control study

Funding: not reported

Setting & period: Participants aged 65 years and older were recruited from pulmonary medicine outpatient facilities in University of Palermo, Italy

COPD group: 356 patients

Non-COPD group: 290 patients

Diagnosis of COPD: Spirometry

CKD definition: eGFR < 60 using MDRD equation

Blinding of outcome adjudicator: not reported

Selection bias: no

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: no Matching: yes (age) Adjustment in analysis: yes Confounding variables: no

Loss to follow up: none

Overall prevalence of Chronic renal failure was 43.0% in COPD group and 23.4% in non-COPD group (p < 0.001)

Logistic regression analysis revealed significant association between COPD and concealed chronic renal failure (OR: 2.19; CI: 1.17-4.12) and overt chronic renal failure (OR: 1.94; CI: 1.01-4.66)

Joo et al.; 2012 [11]

Study design: Cross-sectional Survey

Funding: Grant of Korea Healthcare Technology R&D project

Setting & period: Database of the fourth Korean Health and Nutrition Examination Survey with a nationally representative sample, during 2008. Aged ≥ 40 years

COPD group: 354 patients, 67.2% male, mean age 64.6 years

Non-COPD group: 1823 patients, 36.9% male, mean age 54.4 years

Diagnosis of COPD: Spirometry, FEV1/FVC < 0.7

CKD definition: patients’ awareness of CKD diagnosis was surveyed

Blinding of outcome adjudicator: not reported

Selection bias: no

Information bias: objective

outcome evaluation: yes, for COPD diagnosis only;

standardized CKD risk

measurement: no

Confounding: yes Matching: no. Adjustment in analysis: yes Confounding variables: gender, mean age

Loss to follow up: none

0.6% of patients in COPD group had Chronic renal failure compared to 0.4% in non-COPD group (p = 0.41, not statistically significant)

Mapel et al.; 2013 [12]

Study design: retrospective case-control cohort analysis

Funding: grant from Pfizer Pharmaceuticals Inc.

Setting & period: patients aged 40 years or older seen in 4 hospitals and a network of outpatient clinics of Lovelace Health Systems (LHS) in New Mexico, USA during the study period 2005-2008

COPD group: 2284 patients of LHS aged 40 or more with COPD and have at least 2 outpatient clinic visits or one hospitalization and enrolled with LHS for at least 12 months during the study period; 47.5% men; mean age 70.3 +/- 9.8 yrs

Non-COPD group: 5959 randomly selected patients without a diagnosis of COPD and be of same age and gender

Diagnosis of COPD: ICD-9 diagnosis code of COPD

CKD definition: ICD-9 codes and abnormal renal function tests

Blinding of outcome adjudicator: not reported

Selection bias: none

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: no Matching: yes (age, gender). Adjustment in analysis: yes Confounding variables: no

Loss to follow up: none

Chronic renal failure was more than three times more prevalent among COPD patients (2.89%) than among controls (0.79%) (p < 0.001)

Nagorni-Obradovic; 2014 [13]

Study design: cross sectional study (case-control analysis)

Funding: Ministry of Education and Science of the Republic of Serbia

Setting & period: 10,013 nationally representative sample of adults aged 40 years or older who participated in multipurpose health survey of population of Serbia in 2006

COPD group: 653 patients, 46.6% male, mean age 62.8 years (SD: 12.4)

Non-COPD group: 9.360 patients, 54.4% male, mean age 59.3 years (SD: 12.2)

Diagnosis of COPD: Self-reported history of chronic bronchitis and emphysema

CKD definition: Self-reported history of chronic renal disease

Blinding of outcome adjudicator: N/A

Selection bias: no

Information bias: objective

outcome evaluation: no;

standardized CKD risk

measurement: no

Confounding: no Matching: no

Adjustment in analysis: yes (age, gender, educational level, smoking) Confounding variables: no

Loss to follow up: n/a

20.6% of COPD patients reported having a diagnosis of chronic renal failure compared to 9.3% of non-COPD patients (p < 0.01)

Schnell et al., 2012 [14]

Study design: cross-sectional study (case-control analysis)

Funding: Johns Hopkins, NCRR and NIH

Setting & period: non-institutionalized civilians in the US aged 45 years or more who participated in the National Health and Nutrition Examination Survey (NHANES) from 1998 through 2008

COPD group: 995 patients, 39.9% males, mean age 62.7 years (CI: 61.7-63.8)

Non-COPD group: 14,828 patients, 47% males, mean age 60 years (CI: 59.6-60.3)

Diagnosis of COPD: positive response in NHANES questions to either chronic bronchitis or emphysema with negative response to current asthma

CKD definition: NHANES question with positive response to eGFR < 60 as calculated using MDRD equation

Blinding of outcome adjudicator: N/A

Selection bias: no

Information bias: objective

outcome evaluation: no;

standardized CKD risk

measurement: yes

Confounding: no Matching: no

Adjustment in analysis: yes Confounding variables: none

Loss to follow up: n/a

16.2% of patients with physician diagnosed COPD reported having low eGFR, compared to 10.5% of patients without physician diagnosed COPD (p < 0.0001)

Van Gestel et al.; 2009 [15]

Study design: cohort study

Funding: none

Setting & period: 3358 patients who underwent elective vascular surgery or lower limb arterial reconstruction surgeries between January 1990 to December 2006

COPD group: 1310 patients

Non-COPD group: 2048 patients

Diagnosis of COPD: post bronchodilator pulmonary function test

CKD definition: based on calculated eGFR <60 estimated using MDRD equation

Blinding of outcome adjudicator: not reported

Selection bias: yes, convenience sample

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: yes. Matching: No. Adjustment in analysis: yes Confounding variables: age, gender, type of surgery, current smoking, previous heart failure, hypertension, Diabetes, hyperlipidemia

Loss to follow up: none

COPD was associated with a higher risk of prevalent CKD even after adjustment for confounding variables – OR: 1.22 (1.03 – 1.44) (p = 0.03)

A borderline significant relationship was observed for mild COPD while moderate COPD was independently associated with CKD. No significant association was found between severe COPD and CKD

Yoshizawa et al.; 2015 [6]

Study design: retrospective case-control cohort analysis

Funding: none

Setting & period: outpatient clinic visits of Kanamecho Hospital, Tokyo, Japan for the study period of May 2011 to April 2012

COPD group: 108 stable COPD patients; 83.3% males; mean age 74.3 ± 7.1 year.

Non-COPD group: 73 patients of the same outpatient practice; 49.3% males; mean age 71.8 ± 7.3 years

Diagnosis of COPD: spirometry reading of FEV1/FVC less than 70% after inhalation of a bronchodilator, and severity of obstruction judged according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria

CKD definition: eGFR less than 60 mL/min/1.73 m2 as per calculation based on serum Creatinine and serum Cystatin levels separately

Blinding of outcome adjudicator: not reported

Selection bias: no

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: yes. Matching: No. Adjustment in analysis: yes Confounding variables: age, gender, BMI, hypertension, Diabetes, hyperlipidemia

Loss to follow up: none

Prevalence of CKD (using Se Cr for calculation of eGFR) was significantly higher in COPD group - OR: 4.91 (1.94 – 12.46) (p = 0.0004)

Prevalence of CKD (using Se Cys for calculation of eGFR) was significantly higher in COPD group - OR: 6.30 (2.99 – 13.26) (p < 0.0001)

Table 2

Systematic review of 10 studies reporting prevalence of CKD in patients with COPD; excluded from meta-analysis

Study

Population

COPD diagnosis method & Definition of CKD

Methodological features

Results

Almagro et al., 2002 [17]

Study design: prospective cohort study

Funding: not reported

Setting & period: patients hospitalized to an acute-care hospital in Barcelona (Spain) for acute exacerbation of COPD, between October 1996 and May 1997

Patient group: 135 patients, 96% male, median age 72.2 ± 9.25 years

Diagnosis of COPD: Spirometry

CKD definition: not defined, diagnosis information obtained from Charlson index

Selection bias: yes, patients admitted with COPD exacerbation

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

4.4% of the patients are reported to have renal failure

Almagro et al., 2009 [18]

Study design: Cross-sectional, multi-center study

Funding:

Setting & period: patients admitted with COPD exacerbation to any of the participating 26 hospital centers throughout Spain, consecutively between January 1, 2007 and December 31, 2008

Patient group: 398 patients, 89% male, mean age of 73.7 years

Diagnosis of COPD: Spirometry

CKD definition: not defined, comorbidity information obtained from Charlson index and an ad hoc questionnaire

Selection bias: patients admitted with COPD exacerbation

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

6.5% of patients are reported to have moderate kidney failure

Almagro et al.; 2012 [16]

Study design: Longitudinal, observational, multi-center study

Funding: provided by Chiesi España

Setting & period: Patients hospitalized for COPD exacerbation to 70 ED and internal medicine services in Spain between October 2009 and October 2010

Patient group: 606 patients, 89.9% male, median age 72.6 years (range, 41-94)

Diagnosis of COPD: Spirometry

CKD definition: not defined, diagnosis information obtained using Charlson index and a questionnaire

Selection bias: yes, patients admitted with COPD exacerbation

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

15.5% of patients are reported to have Kidney disease with serum creatinine <3

0.7% of patients are reported to have Kidney disease with serum creatinine >3

Antonelli Incalzi et al., 1997 [19]

Study design: Retrospective cohort study

Funding: not reported

Setting & period: Consecutive patients discharged from Catholic University in Rome between the years 1980 and 1990, after an acute exacerbation of COPD

Patient group: 270 patients, 83% male, mean age 67 ± 9 (SD) years

Diagnosis of COPD: Spirometry

CKD definition: not defined, obtained from Charlson’s index

Selection bias: patients likely with severe COPD

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

6.6% of patients were noted to have chronic renal failure

Death in these patients was predicted by several variables including chronic renal failure (HR 1.79; 95% CI 1.05–3.02)

Chen et al.; 2016 [7]

Study design: Case-Cohort study

Funding: Ministry of Science of Technology, Taiwan

Setting & period: Patients aged 40 years or older who had inpatient hospitalization between 1998 and 2008 with Longitudinal Health Insurance Database

(LHID) 2000 as the case group

COPD group: 7,739 patients, 67.5% males, mean age 71.7 years

Non-COPD group: 15,478 patients, 67.5% males, mean age 71.7 years

Diagnosis of COPD: Based on hospitalization for COPD

CKD definition: Clinical diagnosis

Blinding of outcome adjudicator: not reported

Selection bias: none

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: no Matching: yes. Adjustment in analysis: yes Confounding variables: yes; age, gender, first diagnosis of COPD

Loss to follow up: none

Overall incidence of CKD was higher in COPD group than in non-COPD group. The adjusted hazard ratio of case was 1.61 (P <0.0001) times that of control.

Ford, E S.; 2015 [20]

Study design: retrospective case-control study

Funding: None

Setting & period: 5711 American men and women aged 40 to 79 years who participated in the Third National Health and Nutrition Examination Survey (NHANES III) during the term 1988 through 1994 and followed through 2006

COPD group: 1390 participants

Non-COPD group: 4321 participants

Diagnosis of COPD: spirometry

CKD definition: eGFR calculation using the Chronic Kidney Disease Epidemiology Collaboration equations

Blinding of outcome adjudicator: not reported

Selection bias: no

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: yes

Confounding: no Matching: yes. Adjustment in analysis: yes Confounding variables: no

Loss to follow up: none

The rates of incidence or prevalence of CKD was not reported.

Comparative data on mean eGFR values in COPD group and Non-COPD group was reported.

Adjusted mean levels of eGFR were significantly lower in adults with moderate-severe COPD (87.7 mL/min/1.73 m2) than in adults with normal lung function (89.6 mL/min/1.73 m2) (p = 0.015)

García-Olmos et al., 2013 [21]

Study design: Observational, cross-sectional study

Funding: CDTI/Ministry of Science and Innovation

Setting & period: practice population allocated to 129 Family Physicians, conducted in a health area of the Madrid

Patient group: 3,183 patients, 76% male, mean age of 71.41 ± 11.50 years

Diagnosis of COPD: from clinical history in EMR

CKD definition: not defined, obtained from EMR

Selection bias: not validated COPD diagnostic method

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

6.34% of patients have chronic renal failure

Marti et al., 2005 [22]

Study design: Retrospective cohort study

Funding: In part by grant from Fundacio ‘noma’Catalana de Pneumologia and by Red Respira-ISCIII-RTIC-03/11

Setting & period: patients with COPD initiating LTOT >15 h/day during 1992–1999 in a tertiary teaching hospital (Vall d’Hebron Hospital, Barcelona, Spain)

Patient group: 128 patients, 98.4% male, mean age ± SD 68.9 ± 9.7 years

Diagnosis of COPD: PFTs

CKD definition: not defined, assessed using Charlson index

Selection bias: yes, COPD patients only on long term O2 therapy

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

1.6% of patients are reported to have renal disease

Terzano et al., 2010 [23]

Study design: Prospective longitudinal study

Funding:

Setting & period: Consecutive COPD patients admitted to four hospitals in Italy for acute exacerbation from 1999 to 2000, and followed up until December 2007

Patient group: 288 patients, 78.8% male, mean age 69.2 years (SD ± 6.4)

Diagnosis of COPD: standardized

CKD definition: not defined, assessed using Charlson index

Selection bias: yes, patients admitted for acute exacerbation

Information bias:

Objective outcome evaluation: no;

standardized CKD risk measurement: no

26.3% of patients are reported to have chronic renal failure

Van Manen et al.; 2001 [24]

Study design: case control study

Funding: Boehringer Ingelheim NL supplied materials and personnel for performing lung function testing

Setting & period: Adults aged 40 years or more who visited outpatient practices in urban and suburban regions of western part of Netherlands from October 1996 through June 1997

COPD group: 290 patients (male 64.1%; mean age 65.8 years)

Non-COPD group: 421 patients (male 41.1%; mean age 65.9 years)

Diagnosis of COPD: Pulmonary function tests

CKD definition: not reported

Blinding of outcome adjudicator: not reported

Selection bias: no

Information bias: objective

outcome evaluation: yes;

standardized CKD risk

measurement: no

Confounding: no Matching: no Adjustment in analysis: yes Confounding variables: no

Loss to follow up: none

The study population was surveyed to estimate the prevalence of a set of 23 diseases in patients with COPD compared to patients without COPD.

Self-reported renal disease was included in general and no specifications on chronic kidney disease or renal failure was surveyed.

Renal disease was reported 0.3% in patients with COPD compared to 0.2% in non-COPD patients

Results from meta-analysis (Fig. 1) showed statistically significant higher prevalence of CKD among COPD patients compared to controls without COPD; OR 2.20 [95% CI: 1.83, 2.65]. I2 value of 82% indicates minimal heterogeneity among the studies included in the analysis. Funnel plot of the included studies revealed lack of publication bias (Fig. 2).
Fig. 1

Meta- analysis to assess the cumulative prevalence of CKD in patients with COPD when compared to control groups

Fig. 2

Funnel plot to assess for publication bias among the studies included in meta-analysis

The study periods of almost all the studies were in the last 2 decades except one study [30]. Three of the 9 studies included in meta-analysis utilized nationally representative samples in their respective countries [22, 24, 25]. Only 2 studies reported data on hospitalized patients [19, 26] while the remaining 4 studies included patients from outpatient settings [17, 20, 21, 23]. Of the 10 studies that were excluded from the meta-analysis, six studies reported data on hospitalized patients [18, 2730, 34]

Patient population included was aged 40 years or older. Studies included in the meta-analysis had similar gender representation with male participant rates reported from 40% to 65% except one study that reported 83% male participation [17]. Nine of the 10 studies that were not included in the meta-analysis but were included in the systematic review reported predominant male participation ranging from 80% to 98% [18, 2734].

Of the studies included in meta-analysis, only one study analyzed prevalence of CKD in COPD and control groups based on gender [24]. Van Gestel et al. analyzed the association between prevalence of CKD and severity of COPD [26]. Therefore sub-group analysis could not be performed for prevalence based on gender and severity of COPD.

The reported diagnostic methods and definitions for COPD and CKD were uniform across all the included studies. The value of eGFR reported under laboratory data was used to define CKD in most of these studies. Matching was performed in control group selection in 3 of the 9 studies included in the meta-analysis [19, 21, 23]. All the included studies performed adjustment in analysis for the identified confounding variables.

Discussion

Our meta-analysis validated previously published results showing a significant increase in prevalence of CKD in patients with COPD compared to patients without COPD. To our knowledge, this is the first meta-analysis conducted on this topic.

Advancing age, diabetes, hypertension, body mass index (BMI), and cigarette smoking have previously been identified as risk factors for new-onset kidney disease [36]. Advancing age, history of asthma, severe respiratory problems in childhood, passive smoking, and exposure to biomass fuel for heating were identified as risk factors for COPD in never-smokers whereas increasing age, history of asthma, and severe respiratory problems in childhood, increasing lifetime exposure to cigarette smoking were identified as independent risk factors for development of COPD in ever-smokers [37]. Many studies have reported on the high prevalence of CKD in COPD patients across different populations and our meta-analysis validated these previously published results. Moreover, all the studies included in our analysis adjusted for co-variates including age, gender, BMI, and smoking status and this allowed for drawing a conclusion on the independent association of CKD with COPD.

The mechanism by which COPD potentiates the development of CKD remains unclear. Several hypotheses have been put forward. It might be related to the fact that COPD is mainly a disease of the elderly population who have comorbidities such as DM, HTN and CAD, known risk factors associated with CKD. COPD has been associated with systemic inflammation [912]. Pro-inflammatory cytokines, especially tumor necrosis factor-alpha (TNF-α), play an important role in inflammation [38, 39], and have been shown to increase endothelial inflammation and atherosclerosis. This inflammation is also potentially related to development of diabetes, muscle wasting, and kidney disease. In a meta-analysis of observational studies, COPD was associated with increased serum concentration of several inflammatory mediators [40]. This association can be explained in part by smoking.

COPD is associated with microalbuminuria and in hypoxemic and hypercapnic patients effective renal flow was found to be reduced. These changes may be reflective of increased renin-angiotensin system activity seen in COPD patients. In the Multi-Ethnic Study of Atherosclerosis cohort, Harris et al. found an inverse relation between FEV1 and FVC with urinary albumin excretion and urine albumin to urine creatinine ratio [41]. This finding suggests that systemic microvascular injury may contribute to development of CKD in COPD patients.

Medical management of COPD may contribute to the development of CKD. Mapel et al. [23] showed that COPD patients were more likely to be on potentially nephrotoxic medications than controls. This includes recurrent use of antibiotics, as well as PPIs and certain cardiovascular drugs. Our study highlights the high prevalence of CKD in COPD patients and draws attention to the clinical implications.

Our study has a few limitations. First and foremost, we included observational studies in this systematic review and meta-analysis. Observational studies, inherently, depict associations and aid in hypothesis-making but do not establish cause and effect relationships. Additionally, we could not perform subgroup analysis to estimate the differential prevalence of CKD in relation to the severity of COPD that would have otherwise contributed to establishing causal relationship. Another limitation is that although 18 studies were identified to be relevant, only 9 studies could be included in our meta-analysis owing to differences in the study designs and reported results. However, funnel plot analysis did not reveal any publication bias.

Conclusions

In conclusion, results from our systematic review and meta-analysis strongly support the association of increased prevalence of CKD in patients with COPD. Implications for future research include a need for studies to further investigate the pathophysiological mechanisms in COPD patients that lead to a higher incidence of CKD in these patients. Results from these studies may then be applied to improve the treatment of COPD, reducing the incidence of CKD in COPD patients and thereafter decrease their morbidity and mortality.

Abbreviations

AKI: 

Acute kidney injury

BMI: 

Body mass index

CI: 

Confidence interval

CKD: 

Chronic kidney disease

COPD: 

Chronic obstructive pulmonary disease

eGFR: 

Estimated glomerular filtration rate

ESRD: 

End stage renal disease

FEV1: 

Forced expiratory volume in 1 second

FVC: 

Forced vital capacity

GFR: 

Glomerular filtration rate

NHANES III: 

Third National Health and Nutrition Study

OR: 

Odds ratio

PPI: 

Proton pump inhibitor

Declarations

Acknowledgements

None.

Funding

None.

Availability of data and material

Not applicable.

Authors’ contributions

SG. Research question, study protocol, Literature search, Data abstraction for systematic review, Meta-analysis, writing manuscript, submission for publication. SKG: Literature search, Data abstraction for systematic review, Meta-analysis, writing manuscript. JWL: Study protocol, third reviewer of data abstraction, preparation of manuscript. PA: Research question, formulation of protocol, supervision of data abstraction, preparation of manuscript. All authors read and approved the final manuscript.

Competing interests

Authors declare no financial affiliations or conflicts of interest in submitting the study for publication.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Division of Nephrology at VAMC
(2)
Department of Medicine, SUNY
(3)
Division of Nephrology at VAMC
(4)
Department of Medicine, Virginia Commonwealth University

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Copyright

© The Author(s). 2016