Objectives: Our study aimed to evaluate the effects of being overweight on kidney transplant.

Materials and Methods: Our study evaluated kidney transplant recipients with body mass index ranging from 25 to 30 kg/m² versus patients with body mass index ranging from 18.5 to 29.9 kg/m², who were identified through PubMed, Embase, and Cochrane Library searches up to October 2015. Outcomes analyzed included delayed graft function, acute rejection, graft loss, and patient survival. Furthermore, sensitivity analysis and funnel plots were conducted to evaluate the strength of our meta-analysis.

Results: Eight studies were included in the meta-analysis. No association between being overweight and kidney transplant outcomes, including delayed graft function (risk ratio of 0.99; 95% confidence interval, 0.73-1.35), acute rejection (risk ratio of 1.11;95% confidence interval, 0.88-1.40), graft loss (risk ratio of 1.10; 95% confidence interval, 0.86-1.39), and patient survival (risk ratio of 0.98; 95% confidence interval, 0.94-1.01) was found. Significant hetero-geneity was calculated among studies investigating the relation between delayed graft function and being overweight. However, sensitivity analysis and funnel plots demonstrated that the results were stable.

Conclusions: The meta-analysis results suggested that overweight patients and patients with normal weight have similar outcomes after kidney transplant. However, for Chinese individuals, the conclusion should be further verified by additional studies.

Key words : Body mass index, China, Kidney transplant

Introduction

As being overweight and obesity continue to become a global public health issue, the number of end-stage renal disease patients with obesity has also risen rapidly.¹ Thus, the role of the obesity epidemic on kidney disease risk has received increasing interest.²

Surgical or transplant-related complications have been recognized as adverse events of obesity. However, the effects of obesity on graft and patient survival are still controversial. For example, some studies support that obesity results in poor outcomes after renal transplant, including higher patients and graft mortality, higher delayed graft function (DGF), and acute rejection (AR) incidence.^3,4 However, other studies have not found significant associations between obesity and these poor outcomes.^5,6 Therefore, it is necessary to systematically assess the role of obesity on kidney transplant.

Recently, several meta-analyses and systematic reviews have been designed to investigate this issue^7,8; these studied individuals with body mass index (BMI) above 30 kg/m². For Asian individuals, the World Health Organization Western Pacific Regional Office has modified the BMI cut-off value at 25 kg/m² to define obesity.⁹ Thus, our meta-analysis was aimed at evaluating the role of having a BMI ranging from 25 to 30 kg/m² on renal transplant risk versus having a normal weight.

Materials and Methods

Search strategy
Relevant articles published before October 2015 were systematically searched throughout PubMed (http://www.ncbi.nlm.nih.gov/pubmed), Embase (http://www.elsevier.com/online-tools/embase), and Cochrane library (http://www.cochranelibrary.com/) databases. The main key words used for the search were as follows: “obesity” or “overweight” or “body mass index” and “transplantation” or “kidney transplantation.” A bibliography of reviews and identified articles was manually searched. Paper editions of articles were also manually reviewed.

Selection criteria
Studies meeting the following selection criteria were enrolled in the meta-analysis: (1) studies that compared renal transplant patients with BMI ranging from 18.5 to 25 kg/m² with renal transplant patients having BMI ranging from 25 to 30 kg/m²; (2) studies that evaluated renal transplant outcomes, including DGF, AR episodes, and graft or patient survival; (3) studies that reported genotype frequency or reports in which this could be calculated.

Studies were excluded if data in the studies reported results that could not be used for statistical analyses. In addition, nonoriginal studies, including reviews, letters, and comments, were also excluded.

Data extraction and quality assessment
The extraction form was previously designed, and all data were extracted independently by 2 investigators in accordance with the form. Data extracted included the first author’s name, year of publication, number and age of the enrolled patients, region, follow-up duration, and covariates that might influence research outcomes.

The Newcastle-Ottawa Scale with a maximum of 9 points was applied to evaluate the quality of the enrolled literatures.¹⁰ Three categories were calculated in the scale: selection of the study groups (accounting for 0-4 points), quality of the adjustment for confounding (accounting for 0-2 points), and ascertainment of the outcome of interest in the cohorts (accounting for 0-3 points). A total score of 7 or higher was regarded as high quality, 5 or 6 was considered moderate, and scores equal or lower than 4 were defined as low quality.

Statistical analyses
Risk ratio (RR) with its 95% confidence interval (CI) was used to evaluate the role of being overweight on kidney transplant. Heterogeneity among individual studies was examined by Cochran Q statistic and I2 test.¹¹ Significant heterogeneity occurred if P < .05 (Q statistic) and/or I2 > 50%, and then the random effects model was selected; otherwise, the fixed-effect model would be used.

Sensitivity analysis was performed to confirm the robustness of the results through omitting 1 study at a time. Finally, funnel plots were calculated to evaluate publication bias. All statistic analyses were carried out using Review Manager 5.0 (Review Manager, REVMAN, Copenhagen, Denmark).

Results

Study selection
Figure 1 shows our process of study selection for the present study. In total, based on the search criteria, 3104 articles were originally enrolled (PubMed: 899; Embase: 2141; Cochrane library: 64). After duplicate documents and those obviously irrelevant were eliminated, we browsed the abstracts of the 327 remaining studies. After that, 229 articles were excluded, including 115 irrelevant topics, 72 irrelevant outcomes, and 42 unoriginal articles, which left 98 articles remaining. After full texts were checked, 90 articles were excluded (articles with irrelevant BMI grouping: 79; articles with duplicate population: 6; articles with data that could not be extracted: 5). Finally, 8 eligible studies were included in this meta-analysis.^6,7,12-17

Characteristics and quality of the enrolled studies
Table 1 shows the basic information for the meta-analysis. The enrolled 8 studies were published between 2010 and 2014. Among the enrolled 8 studies, patients in 5 studies were from America, patients from 2 studies were located in Australia,^12,17 and 1 study was conducted in Brazil.15 The follow-up period ranged from 1 to 10 years. Moreover, the Newcastle-Ottawa Scale scores of the included studies were all more than 5, indicating that these were medium- and high-quality research studies.

Meta-analysis of overweight and posttransplant outcomes: Delayed graft function
Delayed graft function was assessed in 7 studies,^6,7,12-15,17 which included 957 patients with BMI ranging from 25 to 30 kg/m² and 1320 patients with BMI ranging from 18.5 to 25 kg/m². As shown in Figure 2A, significant heterogeneity was observed among enrolled studies (I2 = 75%, P < .001), and effect size was pooled using the random effects model. No significant increased risk was observed for overweight patients compared with patients with normal weight (RR = 0.99; 95% CI, 0.73-1.35). As shown in Figure 2B, the funnel plot shape shows that no significant publication bias occurred. Moreover, results remained unchanged when we omitted 1 study at a time.

Meta-analysis of overweight and posttransplant outcomes: Acute rejection and graft loss
Five studies accounting for 1499 patients evaluated AR episodes.6,7,14-16 Figure 3A shows that no significant heterogeneity occurred among enrolled studies (I2 = 0%, P = .86). In addition, no significantly increased AR risk was observed for overweight patients compared with patients with normal weight (RR = 1.11; 95% CI, 0.88-1.40). In addition, sensitivity analysis suggested that the results were stable.

In total, 5 studies researched graft loss, which included 630 overweight patients and 1130 patients with normal weight.^6,7,13-15 Figure 3B shows that no significant relation was observed between graft loss and being overweight for renal transplant patients (RR = 1.10; 95% CI, 0.86-1.39), and significant heterogeneity was calculated among studies (I2 = 0%; P = .45). The result remained unchanged after sensitivity analysis.

Meta-analysis of overweight and posttransplant outcomes: Patient survival
Patient survival was investigated in 4 studies,6,7,14,15 which included 487 overweight patients and 820 patients with normal patients. As shown Figure 4, the fixed-effect model was used to pool effect size because of insignificant heterogeneity among enrolled individual studies (I2 = 19%, P = .29), and no significant relation was observed (RR = 0.98; 95% CI, 0.94-1.01). The result also remained unchanged after sensitivity analysis.

Discussion

To the best of our knowledge, no meta-analysis has been designed to evaluate the role of being overweight on kidney transplant. Moreover, the obesity definition in Asian versus other populations is different, defining obesity as those with BMI more than 25 kg/m². Thus, we tried to explore kidney transplant outcomes between patients with BMI ranging from 25 to 30 kg/m2 and patients with BMI ranging from 18.5 to 29.9 kg/m². After effect size was pooled, no associations between being overweight and outcomes after kidney transplant, including DGF, AR, graft loss, and patient survival, were found. However, sensitivity analysis and funnel plots demonstrated that the results were stable. In summary, the findings from the meta-analysis suggested that overweight patients and patients with normal weight have similar outcomes after kidney transplant.

Different from the conclusion on obese patients, we did not find a significant relation between being overweight and kidney transplant risk. Despite this, we found that overweight patients were more easily diagnosed with obesity-linked diseases, including cardiovascular disease, diabetes mellitus, and hypertension, which could influence the results in an analysis having a longer follow-up period.

In 2006, Chow and associates evaluated the role of obesity among an Asian kidney transplant population, and the study suggested that patients with a BMI cut-off value of more than 25 kg/m² may have increased graft loss risk.¹⁸ However, in our meta-analysis, no significant relation was observed between being overweight and graft loss. One reason was that the population that we enrolled were patients with BMIs ranging from 25 to 30 kg/m². Moreover, our conclusion was based on a population other than Asians, and patients who underwent kidney transplant were limited.¹⁹ In addition, Asian and Pacific Islander patients experience better survival than white individuals.20 Therefore, for Asians, further study is needed to verify the conclusion.

Some limitations should be noted. First, although results of our meta-analysis were verified by sensitivity analysis, significant heterogeneity was calculated among studies investigating the relation between DGF and being overweight. The significant heterogeneity might be attributed to different follow-up periods in enrolled individual studies. Second, although all enrolled studies were shown to be of moderate or high quality for the meta-analysis, posttransplant outcomes were not independently related. Many other confounding factors such as physical background may be present, which could not be adjusted in these enrolled observational studies.

In summary, the findings from this meta-analysis suggest that overweight patients and patients with normal weight have similar outcomes after kidney transplant. However, for Chinese individuals, the conclusion should be further verified by additional studies.

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