Meta-Analysis: Risk for Hypertension in Living Kidney Donors

Context Does kidney donation increase a person's risk for hypertension? Contribution This review found 10 studies that compared blood pressure between kidney donors and healthy adults with similar age, sex, and ethnicity. Studies suggested that within 5 to 10 years of donation, kidney donors may have about a 5mm Hg increase in blood pressure over that anticipated with normal aging. Cautions Actual risks for hypertension were unclear because studies did not define hypertension uniformly and had incomplete follow-up information on many donors. Implications We need large, prospective, controlled studies with prolonged follow-up to better inform potential kidney donors of long-term risks associated with donation. The Editors Despite its advantages, living kidney donation remains a complex ethical, moral, and medical issue. Living kidney donation is practiced with the expectation that the risk for minimal short-term and long-term harm for the donor is outweighed by the psychological benefits of altruism and improved recipient health. The short-term complications of living donation are well established (1). However, the long-term risk for hypertension remains uncertain. A better understanding of this risk is central to donor selection and consent. This knowledge guides health policy on reimbursing costs of antihypertensive medication and the need for ongoing surveillance of the more than 80000 persons who have donated a kidney (2). The primary question of this review was whether normotensive adults who donate a kidney develop higher blood pressure and risk for hypertension compared with healthy nondonors acting as control participants. Reasons for considerably different estimates in the literature were also explored in meta-regression. Methods Study Selection We included studies in any language that examined 10 or more healthy normotensive adults who donated a kidney and had their blood pressure assessed at least 1 year later. We compiled citations from MEDLINE and EMBASE bibliographic databases from 1966 through November 2005. An experienced librarian developed the search strategies using sensitive terms for identifying clinical prognostic studies of living kidney donors (3, 4). We pilot-tested the search strategies and modified them to ensure that they identified known eligible articles. The final strategies included the terms living donors, cohort studies, course, longitudinal studies, hypertension, and blood pressure. We also compiled citations from information provided by primary study authors, the Science Citation Index, the Related Articles feature on PubMed, reference lists of previous reviews (5, 6), and reference lists of all studies included in our review. All citations were downloaded into Reference Manager, version 10.0 (Thomson ISI Research-Soft, Philadelphia, Pennsylvania). Pairs of reviewers independently evaluated the eligibility of each citation, and the full-text article was retrieved if either reviewer considered the citation potentially relevant. For all English-language publications, pairs of reviewers independently evaluated the eligibility of the full-text article; disagreements were resolved by a third reviewer. With the help of translators, a single reviewer evaluated the eligibility of all nonEnglish-language full-text articles. When data from the same group of donors were described in multiple publications, we reviewed all of the publications and cited the most representative one. Data Abstraction Pairs of reviewers independently abstracted the following data from all English-language studies meeting eligibility criteria: setting, methods, donor characteristics, control group characteristics, prognostic features, and hypertension outcomes. Disagreements were resolved by a third reviewer. For Czechoslovakian, Dutch, French, German, Italian, Japanese, Norwegian, Serbo-Croatian, and Spanish articles, data were abstracted by a single reviewer with the help of a translator. We attempted to contact primary authors of all included studies to confirm data and obtain missing data. Statistical Analysis Reviewer agreement on study eligibility was quantified by using the statistic. Variance estimates for changes in blood pressure before and after donation were not reported in most studies. If not reported, variance estimates were derived from t-statistics when available. Otherwise, variance estimates were calculated with where represents the correlation between the blood pressure measurements before and after donation (7). For the 2 studies that reported predonation, postdonation, and change variance estimates, we calculated average correlation coefficients of 0.92 and 0.84 for systolic blood pressure and diastolic pressure, respectively. To be conservative, we used a correlation of 0.5 to impute missing change variance estimates in the final meta-regression. We performed sensitivity analyses to this choice of correlation, and the results were qualitatively similar. For this study-level meta-analysis, the Q statistic was used to determine whether between-study heterogeneity was present; a P value less than 0.1 was considered statistically significant. The I2 statistic was used to quantify the magnitude of heterogeneity, with values of 0% to 30%, 31% to 50%, and greater than 50% representing mild, moderate, and notable heterogeneity, respectively (8). When justified, results were mathematically pooled by using techniques that accounted for within-study and between-study heterogeneity (random-effects method) (911). Reasons for diversity in study results were explored by using univariate and multivariate meta-regressions of donor cohorts: mixed models for continuous outcomes (PROC MIXED procedure, SAS statistical software, SAS Institute, Inc., Cary, North Carolina) and logistic normal random-effects models for binary outcomes (PROC NLMIXED procedure, SAS statistical software, SAS Institute, Inc.). At the study level, the association between the following donor characteristics and outcomes of hypertension, postdonation blood pressure, and change in blood pressure were considered: average age, the proportion of donors who were female, and average predonation blood pressure. Although potential donors vary in race, sex, and age at the time of nephrectomy, all are healthy and are confirmed to have normal blood pressure and renal function through rigorous evaluation. Nonetheless, we hypothesized that similar to the general population, donors would be more likely to develop hypertension if they were older, were male, and had a higher predonation blood pressure. Similarly, features of study methods associated with blood pressure outcomes after donation were considered. In meta-regression, we tested whether the study was conducted prospectively, the proportion of donors lost to follow-up, the duration of follow-up after nephrectomy, and the method by which blood pressure was assessed. For each meta-regression, only studies for which the factor of interest was available were included in the analysis. The explanatory ability of each factor was quantified by the proportion of between-study variability on the logit scale for binary outcomes and the proportion of between-study variability for continuous outcomes (11). A 2-tailed P value of 0.05 or less was considered statistically significant for binary outcomes, whereas for continuous outcomes, statistical significance was inferred by the proportion of variability explained by the factor and from the size of residual variance (11). Best-fit lines in meta-regression graphs were generated by generalized estimating equations (SAS procedure, PROC GENMOD, SAS statistical software) (12, 13). The generalized estimating equation models used estimates from the meta-regression models as the input values and were weighted by the estimated variances. An exchangeable correlation matrix was assumed for all such models. For models of binary outcomes, a binomial distribution with the logit link was used; for models of continuous outcomes, a normal distribution with the identity link was used. The 95% CI for each best-fit meta-regression line was computed as where g is the link function, xj is the vector of covariates, z is the percentile of the normal distribution, and x is the estimated standard error of the linear predictor. The variance estimate of the linear predictor was calculated as where is the empirical covariance matrix. The number of studies comparing donors with control participants was small and precluded meta-regression of these results. All analyses were conducted using SAS, version 8.02 (SAS Institute Inc.), and RevMan, version 4.2 (Cochrane Collaboration, Oxford, United Kingdom). Results were graphed in R 2.0.1 (R Foundation for Statistical Computing, Vienna, Austria). Role of the Funding Sources This review was supported by the London Multi-Organ Transplant Program, the Canadian Institutes of Health Research, the Physicians Services Incorporated Foundation, and the Canadian Council for Donation and Transplantation. Dr. Garg was supported by a Canadian Institutes of Health Research Clinician Scientist Award. Dr. Yang was supported by a Biomedical Fellowship from the Kidney Foundation of Canada. The study sponsors had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. Results We screened 2886 citations and retrieved and evaluated the eligibility of 262 full-text articles. In addition to excluding studies ineligible for our review, we excluded 1 study that only reported mean arterial pressure in the absence of systolic blood pressure, diastolic blood pressure, or hypertension results (14). Some study cohorts also contained a substantial number of extended-criteria donors with hypertension, proteinuria, or a glomerular filtration rate of less than 80 mL/min per 1.73 m2 before surgery and did not separate reported outcomes from healthy donors. Becau