The research team, led by Deniz Türküm Atikcan of Etimesgut Şehit Sait Ertürk State Hospital in Ankara and Emre Vuraloglu of Ondokuz Mayıs University in Samsun, followed 212 adult kidney transplant recipients who did not have diabetes before their operation. The researchers collected baseline anthropometric and laboratory measurements prior to transplantation, then tracked fasting plasma glucose and HbA1c—two standard markers of glycemic control—at three, six, and twelve months after surgery. The primary outcome was deliberately strict: diabetes-range glycemia, defined as a fasting plasma glucose of at least 126 mg/dL or an HbA1c of at least 6.5 percent at any follow-up visit during the first post-transplant year.

The headline result is striking. Diabetes-range glycemia occurred in 121 of the 212 recipients, or 57.1 percent, during the first year after transplantation. Even more telling is the pattern behind that number: only 12 patients, or 5.7 percent, met the criterion at a single visit, while 109 patients—more than half of the entire cohort—showed diabetes-range values at two or more visits. That distinction is clinically important. A single elevated reading can reflect transient stress, infection, or medication changes, but persistent abnormalities across multiple visits suggest a genuine and sustained disturbance of glucose metabolism rather than a laboratory fluke.

When the researchers turned to statistical modeling, the association with pre-transplant body mass index emerged clearly. In a multivariable logistic regression model that adjusted for other factors, each 1 kg/m² increase in baseline BMI was associated with higher odds of developing diabetes-range glycemia, with an adjusted odds ratio of 1.21 and a 95 percent confidence interval of 1.09 to 1.34, a result that reached statistical significance at p less than 0.001. In practical terms, a patient entering surgery with a BMI of 30 would carry substantially greater risk than a patient with a BMI of 24, simply because of the accumulated effect of those unit-by-unit increases in odds.

But the study went beyond a single snapshot. Using linear mixed-effects models—a statistical framework designed to track how measurements change within individuals over time while accounting for variation between people—the researchers examined longitudinal glycemic trajectories. The models included time, baseline BMI, and crucially a time-by-BMI interaction term. That interaction proved significant for both fasting plasma glucose and HbA1c, with p values below 0.001 for both. What this means biologically is that recipients with higher baseline BMI did not merely start from a riskier position; their glucose measures climbed more steeply over the first post-transplant year than those of their leaner counterparts. The metabolic deterioration was itself accelerated by excess weight.

The mechanistic backdrop to these findings is well understood in transplant medicine, even if this study did not test mechanisms directly. The immunosuppressive drugs that keep the immune system from attacking a new kidney are notoriously diabetogenic. Calcineurin inhibitors such as tacrolimus impair insulin secretion from pancreatic beta cells, corticosteroids promote insulin resistance and increase appetite, and sirolimus has been linked to beta-cell dysfunction as well. Layered on top of a pre-existing state of insulin resistance—which higher BMI typically reflects—these medications can push a patient across the diagnostic threshold for diabetes. The new study adds a quantitative dimension to that picture, showing that the pre-transplant metabolic substrate, summarized by BMI, strongly conditions how severe the pharmaceutical insult becomes.

Perhaps the most practically provocative result comes from the exploratory receiver operating characteristic analysis. The researchers assessed how well pre-transplant BMI alone discriminated between recipients who did and did not develop diabetes-range glycemia, and the area under the curve came out at 0.823, with a 95 percent confidence interval of 0.760 to 0.881. An AUC above 0.8 is generally considered to indicate good discriminatory performance, and it is notable that a single, routinely measured anthropometric variable achieved it. Using the Youden index, a standard method for balancing sensitivity and specificity, the analysis identified a cut-off of 26.0 kg/m²—just above the conventional threshold for overweight—as the value that best separated high-risk from lower-risk recipients in this cohort.

The authors are appropriately cautious about that cut-off. Because it was derived from the same dataset used to evaluate it, it is exploratory by nature and requires external validation in independent cohorts before it could be adopted in clinical practice. Cut-offs derived from a single retrospective cohort often shift when tested elsewhere, particularly across populations with different ethnic backgrounds, body compositions, and immunosuppression protocols. Still, the mere existence of a candidate threshold near the overweight boundary is a useful signal: it suggests that the relevant metabolic risk may begin to accumulate at weights that many clinicians and patients would not consider alarming.

The study’s design carries limitations worth keeping in view. It was retrospective, meaning the investigators analyzed data collected during routine care rather than prospectively assigning measurements, so residual confounding cannot be excluded despite multivariable adjustment. The cohort came from a single country, and details of immunosuppressive regimens, donor characteristics, and lifestyle factors are not fully elaborated in the available summary. The outcome definition also captured diabetes-range glycemia rather than a formal clinical diagnosis of post-transplant diabetes mellitus, which involves additional diagnostic criteria and clinical judgment. These caveats do not undermine the central association, but they frame how far the conclusions can be generalized.

Even with those qualifications, the implications for transplant care are concrete. The findings support the importance of pre-transplant metabolic risk assessment: a simple BMI measurement, already part of every transplant workup, could flag patients who warrant closer glycemic surveillance after surgery, earlier lifestyle intervention, or more careful selection among diabetogenic immunosuppressive agents. With more than half of this cohort showing diabetes-range values at multiple visits during the first year, the scale of the problem is hard to ignore. Post-transplant diabetes is associated with worse graft outcomes and increased cardiovascular risk, so preventing it—or catching it early—has consequences that extend well beyond a laboratory number. This study from Türkiye adds weight to a growing consensus that the fight against post-transplant diabetes begins before the transplant itself, on the scale, in the clinic, and in the conversations clinicians have with patients while they are still waiting for a kidney.

Subject of Research: The association between pre-transplant body mass index and diabetes-range glycemia in the first year after kidney transplantation

Article Title: Association of pre-transplant body mass index with diabetes-range glycemia during the first year after kidney transplantation: a retrospective cohort study from Türkiye

Article References: Atikcan, D. T., & Vuraloglu, E. (2026). Association of pre-transplant body mass index with diabetes-range glycemia during the first year after kidney transplantation: a retrospective cohort study from Türkiye. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02621-3

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02621-3

Keywords: kidney transplantation, body mass index, diabetes, post-transplant diabetes mellitus, HbA1c, fasting plasma glucose, immunosuppression, insulin resistance, retrospective cohort study, metabolic risk, Türkiye, endocrinology