Preoperative Computed Tomography Parameters and Deterioration of Remaining Kidney Function in Living Donors

Residual renal volume as a long-term independent predictive factor of developing chronic kidney disease after donor nephrectomy

To assess the long-term association between the residual renal volume and the progression of chronic kidney disease (CKD) in kidney donors following open or laparoscopic donor nephrectomy. A retrospective observational study involving 452 individuals who underwent open or laparoscopic donor nephrectomy at Ramathibodi Hospital, Bangkok, Thailand. The study spanned over a comprehensive 60-month monitoring period. Residual renal volume was determined through Computer Tomography. Patient characteristics, surgical techniques, donated kidney side, and estimated glomerular filtration rate (eGFR) were collected and analysed. In a multivariate analysis, a residual renal volume exceeding 50% of original volume is associated with an increased likelihood of developing CKD, with a hazard ratio (HR) of 1.675 (P < 0.05), and male gender has a hazard ratio (HR) of 4.013 (P < 0.001). Additionally, age is identified as a minor risk factor for developing CKD, with hazard ratio (HR) of 1.107 (P < 0.001). Higher residual renal volume, male gender, and older age were identified as independent risk factors for the development of CKD following open or laparoscopic donor nephrectomy during long-term follow-up.

Is a Patient with Paget's Disease of Bone Suitable for Living Kidney Donation?-Decision-Making in Lack of Clinical Evidence

Living donor kidney transplantation is a widely performed medical procedure. Living kidney donation requires an in-depth health assessment of candidates. The potential living kidney donor must remain healthy after kidney removal. A consequence of donation can be a decrease in glomerular filtration rate (GFR), and donors can become at risk of developing chronic kidney disease (CKD). We present a rationale for potential living kidney donor withdrawal due to Paget's disease of bone (PDB) based on a literature review. The treatment for PDB includes the use of, for example, non-steroidal anti-inflammatory drugs (NSAIDs), which can lead to acute kidney injury (AKI) as well as CKD, or bisphosphonates, which are not recommended for patients with decreased GFR.

Multivariate analysis of CT imaging, laboratory, and demographical features for prediction of acute kidney injury in COVID-19 patients: a Bi-centric analysis

PURPOSE

To develop and externally validate a multivariate prediction model for the prediction of acute kidney injury (AKI) in COVID-19, based on baseline renal perfusion from contrast-enhanced CT together with clinical and laboratory parameters.

METHODS

In this retrospective IRB-approved study, we identified COVID-19 patients who had a standard-of-care contrast-enhanced abdominal CT scan within 5 days of their COVID-19 diagnosis at our institution (training set; n = 45, mean age 65 years, M/F 23/22) and at a second institution (validation set; n = 41, mean age 61 years, M/F 22/19). The CT renal perfusion parameter, cortex-to-aorta enhancement index (CAEI), was measured in both sets. A multivariate logistic regression model for predicting AKI was constructed from the training set with stepwise feature selection with CAEI together with demographical and baseline laboratory/clinical data used as input variables. Model performance in the training and validation set was evaluated with ROC analysis.

RESULTS

AKI developed in 16 patients (35.6%) of the training set and in 6 patients (14.6%) of the validation set. Baseline CAEI was significantly lower in the patients that ultimately developed AKI (P = 0.003). Logistic regression identified a model combining baseline CAEI, blood urea nitrogen, and gender as most significant predictor of AKI. This model showed excellent diagnostic performance for prediction of AKI in the training set (AUC = 0.89, P < 0.001) and good performance in the validation set (AUC 0.78, P = 0.030).

CONCLUSION

Our results show diminished renal perfusion preceding AKI and a promising role of CAEI, combined with laboratory and demographic markers, for prediction of AKI in COVID-19.

Computed Tomography Parameters and Estimated Glomerular Filtration Rate Formulas for Peridonation Living Kidney Donor Assessment

BACKGROUND

Renal function is usually described by the estimated glomerular filtration rate (eGFR). The standard method used for living kidney donor evaluation in our center is the 24-hour urine creatinine clearance (CrCl) and kidney morphology assessment with computed tomography (CT). The aim of the study was the analysis of the correlation of CrCl with 15 published eGFR formulas and morphologic CT parameters to choose the most accurate kidney function estimation method before and after donation.

METHODS

The study included 39 living donors (18 male and 21 female, aged 32-69 years; mean age, 51.4 [SD, 9.7] years). The eGFR was estimated using Cockcroft-Gault, Modification of Diet in Renal Disease 7, Modification of Diet in Renal Disease 4, Chronic Kidney Disease Epidemiology Collaboration, Mayo Clinic, Nankivell, Bjornsson, Davis-Chandler, Edward-Whyte, Walser, Gates, Hull, Jelliffe-1, Jelliffe-2, or Mawer formulas and correlated with CrCl. CT parameters (kidney dimensions, volume, vascularization) were compared with eGFR formulas.

RESULTS

The 25% to 34% (mean, 28.5% [SD, 2.3%]) decrease in eGFR after donation and its 1.5% to 5.0% (mean, 3.2% [SD, 1.0%]) increase over a year were observed. Cockcroft-Gault, Bjornsson, Hull, and Mawer equations (all including serum creatinine, age, sex, and body mass) correlated with predonation CrCl (r = 0.54, 0.53, 0.53, and 0.56, respectively; P < .001). From CT parameters, renal cortex volume correlated with CrCl (r = 0.48, P = .002) as well as the 4 abovementioned equations before donation (r = 0.65, 0.61, 0.64, and 0.74, respectively; P < .001) and during the postdonation period (12-month r = 0.59, 0.54, 0.57, and 0.70 respectively; P < .002).

CONCLUSIONS

The eGFR calculated with equations combining serum creatinine, age, sex, and body mass as well as renal cortex volume are predictive of pre- and postdonation kidney function.

Estimation of nephron number in living humans by combining unenhanced computed tomography with biopsy-based stereology

Methods for estimating nephron number in a clinical setting may be useful for predicting renal outcomes. This study aimed to establish such a method using unenhanced computed tomography (CT) and biopsy-based stereology. Patients or living kidney donors simultaneously subjected to enhanced and unenhanced CT examinations were randomly assigned to development and validation groups. The enhanced CT-measured arterial phase and the venous phase images of kidneys were regarded as the true values for cortical volume and parenchymal volume, respectively. Linear multiple regression analysis was used to create models for estimating cortical volume using explanatory variables including unenhanced CT-measured parenchymal volume. Nephron number was determined as the product of cortical volume and the glomerular density in biopsies of donors. Five equations for estimating cortical volume were created and verified. In donors, estimated nephron number by unenhanced CT was consistent with that by enhanced CT, with minimal errors in all models (636–655 ± 210–219 vs. 648 ± 224 × 10³/kidney). Clinical characteristics combined with parenchymal volume did not improve the equation over parenchymal volume alone. These results support the feasibility of estimating nephron number by a combination of unenhanced CT and biopsy-based stereology, with a possible application for renal disease patients who are often not suitable for contrast media.