American Journal of Nephrology最新文献

Objective: To explore the clinical value of diffusion-weighted imaging (DWI) combined with T2 mapping for the early evaluation of delayed graft function (DGF) after renal transplantation.

Method: A total of 92 patients who underwent allogeneic renal transplantation were prospectively recruited. All patients underwent magnetic resonance imaging of the transplanted kidneys after the operation. Diffusion-weighted imaging and mapping of the T2-relaxation time (T2 mapping) were measured and analysed. According to the recovery of renal function within one week after surgery, the patients were divided into a normal graft function (NGF) group and a DGF group.

Results: The apparent diffusion coefficient (ADC) values of the cortex and medulla in the DGF group were significantly lower than in the NGF group (P < 0.05). The T2 values of the cortex and medulla in the DGF group were significantly higher than in the NGF group (P < 0.05). The eGFR was positively correlated with the cortical ADC value (P < 0001) and medullary ADC value (P < 0001) and negatively correlated with the medulla T2 value (P = 0.027). The results of the binary logistic regression analysis indicated that age, creatinine level, eGFR, cortical ADC value, medulla ADC value, cortical T2 value and medulla T2 value were independent factors related to DGF. Using these 7 indicators for joint prediction, the AUC was 0.895, and the prediction effect was good.

Conclusion: Diffusion-weighted imaging combined with T2 mapping has important differential diagnostic value for DGF after renal transplantation.

Introduction: Renin-angiotensin system inhibitors (RASi) are critical for cardiovascular diseases (CVD), but adverse effects sometimes lead to discontinuation, raising concerns about impacts on major outcomes. Although the observational studies have suggested continuation or restarting of RASi, the evidence from randomized controlled trials (RCTs) and systematic reviews based on RCTs are not sufficient.

Method: We performed a systematic review and meta-analysis including only RCTs. We searched MEDLINE, EMBASE, CENTRAL, ClinicalTrials.gov, and EU Clinical Trials Register for the full text review analysis. Primary outcomes included all-cause death and CVD events. Risk of bias was assessed using version 2 of the Cochrane Risk of bias tool (RoB2), and the certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation approach.

Results: Among the seven included RCTs (n = 928), three studies (n = 745) reported all-cause mortality and two studies (n = 697) reported CVD events. The meta-analysis did not show difference in all-cause mortality between intervention and control groups (RR 0.95, 95% CI: 0.54 to 1.65, I2 = 0%) and CVD events (RR 1.22, 95% CI: 1.00 to 1.50, I2 = 0%) between intervention and control groups. The certainty of evidence was rated as very low for both outcomes due to RoB, imprecision, and clinical heterogeneity.

Conclusion: In this systematic review and meta-analysis, there might not be deference in the risk of all-cause mortality or CVD events following RASi discontinuation compared with continuation. The number of enrolled studies was limited, and the certainty of evidence was very low, thus our results should be interpreted carefully.

Introduction: Cardiovascular-kidney-metabolic (CKM) syndrome significantly impacts clinical outcomes, though evidence linking integrated cardiometabolic-kidney biomarkers to prognosis remains sparse. This study evaluated prognostic associations of these biomarkers and developed machine learning (ML)-based mortality prediction models for CKM patients.

Methods: Using NHANES data (1999-2018) and death records from 10,616 stage 0-3 CKM patients, we analyzed cardiometabolic-kidney indices: cardiometabolic index (CMI), atherogenic index of plasma (AIP), estimated glomerular filtration rate (eGFR), and urinary albumin-creatinine ratio (uACR). Survival analysis incorporated the Kaplan-Meier curves, Cox regression, and restricted cubic splines to evaluate nonlinear associations. Risk reclassification was quantified via net reclassification index (NRI) and integrated discrimination improvement (IDI). Optimal mortality thresholds were determined using survival cut-point analysis, and inflammation's mediating role was explored. Seven ML models were trained, with performance assessed by area under the receiver operating characteristic curve (AUC-ROC), Brier score, and net clinical benefit.

Results: Over a median 96-month follow-up, 847 deaths occurred. Elevated CMI, AIP, and uACR, along with reduced eGFR, independently predicted mortality (all p < 0.05), with nonlinear trends for CMI, eGFR, and uACR (p-nonlinearity < 0.05). High-risk thresholds for these indices increased mortality risk by 1.19-1.91-fold. Combining all indices improved risk stratification (NRI = 15.8%, IDI = 3.4%). Inflammation mediated 1.1-5.0% of biomarker-mortality associations. Among ML models, XGBoost achieved optimal performance (AUC = 0.852, 95% CI: 0.829-0.877), with Brier score of 0.063 (95% CI: 0.056-0.069) and provided clinical net benefits across risk thresholds from 0 to 0.6.

Conclusion: Cardiometabolic-kidney indices significantly associated with prognosis in CKM patients, highlighting the importance of heart-kidney-metabolism crosstalk. Combining easily accessible biomarkers with the XGBoost model may facilitate risk stratification.

Introduction: Urgent dialysis is labor-intensive and expensive because it requires specialized nursing staff. Most hospitals schedule a fixed number of nurses daily for urgent dialysis needs, but daily dialysis demand fluctuates, leading to inefficiencies.

Methods: We developed statistical, machine learning, and deep learning models to predict the next 7 days' dialysis needs. Our study included a retrospective (April 1, 2018, to March 31, 2023) and prospective component (November 1 to 30, 2023, and May 31 to June 27, 2024) across four hospitals (hospital A for one hospital and hospital B for three hospitals combined). To avoid model over-fitting, we divided our data into three sets: training, testing, and validation. The latter was performed prospectively during two silent deployment periods. The primary outcome measure was the mean absolute error (MAE).

Results: The mean daily dialysis volume in the retrospective data was 16.0 (standard deviation [SD], 5.7) for hospital A and 4.5 (SD, 2.3) for hospital B. The best performing models were autoregressive integrated moving average (ARIMA) and temporal convolutional network; both resulted in an MAE of 3.0 procedures for hospital A and 1.5 procedures for hospital B, compared to 4.4 and 1.9, respectively, for the benchmark. During our two prospective evaluations, the mean daily dialysis volume was 16.8 (SD, 4.5) for hospital A and 4.2 (SD, 2.5) for hospital B. The ARIMA model resulted in the lowest MAE at 2.2 and 1.5 procedures, respectively.

Conclusions: Our multicenter, 6-year study demonstrated that urgent in-hospital dialysis needs can be accurately forecasted.

Introduction: BK polyomavirus (BKPyV) in kidney transplant associated with adverse graft outcome. The aim of this study was to examine graft loss risk of BKPyV associated nephropathy (BKPyVAN) and BKPyV-DNAemia in relation with de novo donor-specific antibody (DSA) and rejection status.

Methods: Two hundred and forty patients from a multicentre cohort who had regular BKPyV and donor-DSA surveillance were retrospectively reviewed and stratified according to the presence of BKPyV-DNAemia and rejection.

Results: BKPyV-DNAemia did not associate with de novo DSA development (hazard ratio [HR] 1.15, 95% confidence interval [CI] 0.50-2.67, p = 0.74) but de novo DSA was more commonly observed in patients who developed rejection (BKV+/rejection- 4.3% (n = 2) vs. BKV+/rejection+ 57.1% (n = 4), p < 0.001). BKPyV-DNAemia (adjusted HR 4.02, 95% CI: 1.30-12.43, p = 0.016) and de novo DSA (adjusted HR 6.76, 95% CI: 2.51-18.24, p < 0.001) were independent factors associated with antibody-mediated rejection. Patients with BKPyV-DNAemia who were further complicated with rejection had approximately 6-fold risk of graft loss (adjusted HR 6.24, 95% CI: 2.04-19.09, p = 0.001), whereas patient with BKPyV-DNAemia alone did not experience significant increase graft loss risk (adjusted HR 1.76, 95% CI: 0.64-4.81, p = 0.27).

Conclusions: Our study suggested that DSA monitoring would be warranted during immunosuppressant reduction for BKPyV-DNAemia and less aggressive reduction of immunosuppressant when DSA emerges might be a reasonable strategy to avoid overzealous reduction of immunosuppressant that could precipitate allograft rejection.

Introduction: Intradialytic hypertension (IH) is associated with elevated ambulatory blood pressure (BP), volume overload, and endothelial dysfunction, which may contribute to its increased morbidity/mortality. There is a paucity of data on cardiac structural and functional abnormalities in IH patients.

Methods: In a cross-sectional analysis among 83 Veterans on maintenance hemodialysis with transthoracic echocardiograms (TTEs), we analyzed all intradialytic BP measurements from 3 treatments before and 3 treatments after the TTE and defined IH as an intradialytic BP slope >0 mm Hg/min averaged over these treatments. We compared systolic and diastolic dysfunction prevalence, ejection fraction (EF), left ventricular mass index (LVMI), left atrial volume index (LAVI), and early transmitral flow velocity to early diastolic mitral annular velocity ratio (E/e') and used logistic regression to determine if IH is independently associated with E/e' >14, a key criteria for diagnosing diastolic dysfunction and assessing elevated filling pressure.

Results: Mean age was 67.4 (±9.2) years. Most were men (n = 81), and 71% had diabetes. IH was present in 25 patients (30%), and they had higher prevalence of systolic dysfunction (52% vs. 17%, p = 0.003) and grade III diastolic dysfunction (16% vs. 2%, p = 0.03) reported on TTE compared to non-IH patients. IH patients had higher E/e' (18.5 [14-24] vs. 15.5 [11-19], p = 0.03), greater LVMI (137 [43] vs. 113 [38] mg/m2, p = 0.009), greater LAVI (52.7 [39-59] vs. 41.0 (33-48] mL/m2, p = 0.005), and lower EF (45.6% [17] vs. 55.7% [11], p = 0.002). IH associated with E/e' >14 in multiple models controlling for demographics, EF, mean intradialytic BP or CV comorbidities (OR 3.59-3.85, p < 0.05 for all); but in the model with LVMI, the association was blunted (OR 2.86, p = 0.1).

Conclusions: IH patients had a higher prevalence of TTE-reported systolic dysfunction and more severe diastolic dysfunction with more abnormalities than those without IH. IH independently associated with E/e' >14, even controlling for EF, intradialytic BP burden, and comorbid CV disease. Clinicians should consider TTE in IH patients to evaluate these abnormalities and optimize dialysis prescriptions and preventative pharmacologic therapies.

Introduction: Chronic kidney disease (CKD) is a public health and economic burden with serious adverse health outcomes and extremely low awareness. Current evidence on independent correlates of CKD awareness is inconsistent and recent data examining time trends of CKD awareness in the USA are dated. The aims of our study are to examine time trends in CKD awareness from 1999 to 2020 and examine independent correlates of CKD awareness in US adults with CKD.

Methods: We analyzed data from the National Health and Nutrition Examination Survey (1999-2020). The study sample consisted of 9,825 US adults with CKD. The primary outcome was CKD awareness. Independent correlates included sociodemographic, comorbidity and clinical variables. Unadjusted and adjusted logistic regression models were used to examine the association of CKD awareness and covariates.

Results: CKD awareness did not change significantly from 1999 (9.4%) to 2020 (10.8%). Fully adjusted model showed male sex (OR 1.41, 95% CI [1.09, 1.84]), non-Hispanic black race/ethnicity (OR 1.73, 95% CI [1.36, 2.20]), multimorbidity (OR 2.92, 95% CI [2.01, 4.25]), having high-risk CKD (OR 2.06, 95% CI [1.57, 2.70]), and very high-risk CKD (OR 5.38, 95% CI [3.99, 7.25]) were associated with higher likelihood of CKD awareness. However, age, education, and insurance were not significantly associated with CKD awareness.

Discussion: During the 2 decades examined in this study, CKD awareness remains extremely low. More prospective studies are needed to understand patient-level barriers to CKD awareness and provider-level barriers to CKD screening, CKD education, and knowledge transfer.

Background: Fluid monitoring is critical for patients on maintenance hemodialysis. Bioimpedance enables estimation of fluid volumes from measures of electrical tissue properties. However, empirical equations are needed to approximate key variables, especially in wrist-to-ankle bioimpedance measurements, introducing potential errors.

Summary: Here, we provide a technical overview of electrical impedance, derivation of fluid volumes from different bioimpedance methods and electrode setups, as well as sources of error including the assumption of constant resistivity, constant body temperature, and vendor-specific equations to derive fluid overload. We summarize the validity of bioimpedance methods in hemodialysis and conclude that irrespective of error sources reported above, segmental bioimpedance, where limbs and the trunk are measured separately, may be more accurate compared to the convenient wrist-to-ankle measurement. We argue that insufficient correction for variable body shape in wrist-to-ankle measurements jeopardizes this methodology, reporting here our analyses by means of theory and data simulation, where we found that conventional wrist-to-ankle bioimpedance underestimated extracellular fluid volume with increasing body fat percentage. The error could be reduced by using subject-specific body shape correction based on high-resolution 3D models. Finally, we attempt to provide guidance for identifying and mitigating common issues of wrist-to-ankle bioimpedance.

Key messages: While more convenient than segmental measurements, wrist-to-ankle bioimpedance may underestimate fluid volumes in obesity when body shape is not properly accounted for. Novel techniques, including smartphone-based 3D scans of the body, could potentially facilitate individualizing body shape correction to improve fluid volume estimates.

Introduction: Endothelin-1 (ET-1) is a potent vasoconstrictor and is implicated in the pathogenesis of proteinuria and progressive chronic kidney disease (CKD). With the development of ET-1 receptor antagonists, there is interest in whether higher ET-1 concentrations are associated with a greater risk of adverse cardio-kidney events among high-risk patients, e.g., those with established CKD and type 2 diabetes mellitus (T2DM).

Methods: ET-1 concentrations were measured in a random subset of TREAT (n = 997 [25%] of the original 4,038 patients with CKD, T2DM, and anemia) using an automated ELISA assay on the Ella analyzer (ProteinSimple). We used unadjusted and adjusted Cox regression models to explore the association of baseline serum ET-1 (log-transformed and quartiles) with kidney events (composite of kidney failure or doubling of serum creatinine), heart failure (HF), and cardiovascular and all-cause death.

Results: At baseline, mean age was 67 ± 10 years and 56% were female. The mean eGFR was 34 ± 11 mL/min/1.73 m2; median urine protein/creatinine ratio was 0.4 (0.1, 1.7) g/g; median ET-1 was 2.4 (1.9, 3.0) pg/mL. During a median follow-up of 2.4 years, there were 225 kidney events, 99 HF events, 124 cardiovascular deaths, and 188 all-cause deaths. Each log-unit higher ET-1 was associated with a higher adjusted risk of the kidney composite (HR: 1.61; 95% CI: 1.08, 2.39), HF (HR: 2.61; 95% CI: 1.42, 4.81), but not with cardiovascular death (HR: 1.06; 95% CI: 0.65, 1.75) or all-cause death (HR: 1.33; 95% CI: 0.86, 2.04). Compared with the lowest quartile, categorical analyses suggested a higher risk of kidney events (HR 1.69; 95% CI 1.08, 2.64), HF events (HR: 2.35; 95% CI: 1.16, 4.80), and all-cause death (HR: 1.81; 95% CI: 1.09, 3.00) for the highest quartile of ET-1.

Conclusions: Among patients with established CKD, T2DM, and anemia, higher baseline ET-1 was associated with a higher subsequent risk of kidney outcomes, HF events, and all-cause death. Whether higher ET-1 predicts responsiveness to ET receptor antagonism warrants further investigation.

Introduction: Immune checkpoint inhibitors (ICIs) have improved cancer treatment; however, their use can be limited by immune-mediated adverse events, such as kidney damage. Diagnostic limitations of nephrotoxicity may lead to worsening of the patient's prognosis. This study aimed to validate a panel of urinary biomarkers as diagnostic tools for kidney damage in patients treated with ICIs.

Methods: A prospective study was conducted on patients scheduled to receive ICIs. Those who subsequently developed kidney damage were considered cases; and those who did not were considered controls. A battery of biomarkers was assessed in urine samples at PRE-1, before the first treatment cycle; PRE-3, before the third cycle; and POST-3, 1 week after the third treatment cycle.

Results: A total of 46 patients participated in the study. At PRE-1, increased urinary excretion of IGFBP7, NAG, TIMP-2 × IGFBP7, and transferrin was observed in the case group, suggesting that these markers could be useful for early risk stratification of developing kidney damage. Furthermore, increased urinary excretion of albumin and NGAL was observed at PRE-3, suggesting that these markers could be of diagnostic utility to identify patients that could develop kidney damage once treatment is initiated. All of the aforementioned biomarkers demonstrated significant discriminatory ability between cases and controls, as verified by ROC curve analysis.

Conclusion: The proposed biomarker battery could be used as a preventive tool for decision-making in the management of oncology patients at risk for kidney damage associated with ICIs. Furthermore, its use would allow personalized adjustment of therapy that would minimize the probability of renal complications even before starting the first cycle of treatment.