Clinical impact of urinary CD11b and CD163 on the renal outcomes of anti-neutrophil cytoplasmic antibody-associated glomerulonephritis.

BACKGROUND: The detection of leukocyte-derived CD11b (α subunit of integrin Mac-1) and CD163 (scavenger receptor) in urine may reflect renal inflammation in antineutrophil cytoplasmic antibody-associated glomerulonephritis (ANCA-GN). The objective of this study was to evaluate the clinical significance of urinary CD11b (U-CD11b) and CD163 (U-CD163) in ANCA-GN. METHODS: U-CD11b and U-CD163 were examined using enzyme-linked immunosorbent assay in ANCA-GN urine samples from our institutional cohort (n = 88) and a nationwide cohort (n = 138), and their association with renal histology was subsequently analyzed. Logistic regression analyses were performed on a nationwide ANCA cohort to determine the associations of the two urinary molecules with renal remission failure at 6 months or with yearly estimated glomerular filtration rate (eGFR) slope over a 24-month observation period. RESULTS: U-CD11b and U-CD163 were significantly associated with cellular crescent formation and leukocyte accumulation in glomerular crescents. With regard to interstitial inflammation, both levels of U-CD11b and U-CD163 at diagnosis remarkably increased in ANCA-GN compared with the levels observed in nonglomerular kidney disorders including nephrosclerosis, immunoglobulin G4-related disease and tubulointerstitial nephritis; however, the presence of U-CD11b alone was significantly correlated with tubulointerstitial leukocyte infiltrates. Although neither U-CD11b nor U-CD163 at diagnosis was associated with remission failure at 6 months, multivariate analysis demonstrated that the baseline U-CD11b levels were significantly associated with the increase in eGFR following immunosuppressive therapy. CONCLUSIONS: Although both U-CD11b and U-CD163 reflect renal leukocyte accumulation, U-CD11b at diagnosis provides additional clinical value by predicting the recovery rate after the treatment of ANCA-GN.

Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.

Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes. In particular, chronic kidney disease (CKD) is problematic because it often progresses to end-stage kidney disease. However, the trajectories of kidney function depend on individual patients. In this study, we propose a machine learning-based model to predict the rapid decline in kidney function among CKD patients by using a big hospital database constructed from the information of 118,584 patients derived from the electronic medical records system. The database included the estimated glomerular filtration rate (eGFR) of each patient, recorded at least twice over a period of 90 days. The data of 19,894 patients (16.8%) were observed to satisfy the CKD criteria. We characterized the rapid decline of kidney function by a decline of 30% or more in the eGFR within a period of two years and classified the available patients into two groups-those exhibiting rapid eGFR decline and those exhibiting non-rapid eGFR decline. Following this, we constructed predictive models based on two machine learning algorithms. Longitudinal laboratory data including urine protein, blood pressure, and hemoglobin were used as covariates. We used longitudinal statistics with a baseline corresponding to 90-, 180-, and 360-day windows prior to the baseline point. The longitudinal statistics included the exponentially smoothed average (ESA), where the weight was defined to be 0.9*(t/b), where t denotes the number of days prior to the baseline point and b denotes the decay parameter. In this study, b was taken to be 7 (7-day ESA). We used logistic regression (LR) and random forest (RF) algorithms based on Python code with scikit-learn library (https://scikit-learn.org/) for model creation. The areas under the curve for LR and RF were 0.71 and 0.73, respectively. The 7-day ESA of urine protein ranked within the first two places in terms of importance according to both models. Further, other features related to urine protein were likely to rank higher than the rest. The LR and RF models revealed that the degree of urine protein, especially if it exhibited an increasing tendency, served as a prominent risk factor associated with rapid eGFR decline.

Extreme hyperuricemia is a risk factor for infection-related deaths in incident dialysis patients: a multicenter prospective cohort study.

INTRODUCTION: There are few studies on the association between serum uric acid (UA) level and mortality in incident dialysis patients. We aimed to clarify whether the serum UA level at dialysis initiation is associated with mortality during maintenance dialysis. METHODS: We enrolled 1486 incident dialysis patients who participated in a previous multicenter prospective cohort study in Japan. We classified the patients into the following five groups according to their serum UA levels at dialysis initiation: G1 with a serum UA level <6 mg/dL; G2, 6.0-8.0 mg/dL; G3, 8.0-10.0 mg/dL; G4, 10.0-12.0 mg/dL; and G5, ≥12.0 mg/dL. We created three models (Model 1: adjusted for age and sex, Model 2: adjusted for Model 1 + 12 variables, and Model 3: stepwise regression adjusted for Model 2 + 13 variables) and performed a multivariate Cox proportional hazard regression analysis to examine the association between the serum UA level and outcomes, including infection-related mortality. RESULTS: Hazard ratios (HRs) were calculated relative to the G2, because the all-cause mortality rate was the lowest in G2. For Models 1 and 2, the all-cause mortality rate was significantly higher in G5 than in G2 (HR: 1.63, 95% confidence interval [CI]: 1.14-2.33 and HR: 1.78, 95% CI: 1.19-2.68, respectively). For Models 1, 2, and 3, the infection-related mortality rate was significantly higher in G5 than in G2 (HR: 2.75, 95% CI: 1.37-5.54, HR: 3.09, 95% CI: 1.45-6.59, HR: 3.37, and 95% CI: 1.24-9.15, respectively). CONCLUSIONS: Extreme hyperuricemia (serum UA level ≥12.0 mg/dL) at dialysis initiation is a risk factor for infection-related deaths.

Urinary levels of the leukocyte surface molecule CD11b associate with glomerular inflammation in lupus nephritis.

Noninvasive biomarkers of disease activity are needed to monitor response to therapy and predict disease recurrence in patients with glomerulonephritis. The leukocyte surface markers integrin Mac-1 and CD16b have been implicated in the pathogenesis of lupus nephritis (LN). Mac-1 comprises a unique α subunit (CD11b) complexed with a common ß2 subunit, which are released along with CD16b from specific leukocyte subsets under inflammatory conditions including glomerulonephritis. We investigated the association of urinary CD11b and CD16b with histopathological activity in 272 patients with biopsy-proven glomerular diseases, including 118 with LN. Urine CD11b and CD16b were measured via enzyme-linked immunosorbent assay. Urinary levels of both markers were increased in LN, but only urinary CD11b was correlated with the number of glomerular leukocytes and with overall histopathological activity. In a subset of patients with samples available from the time of biopsy and subsequent clinical remission of LN, urinary levels of CD11b decreased with successful glucocorticoid treatment. Receiver-operating characteristic curve analysis demonstrated that urinary CD11b was superior to CD16b, the scavenger receptor CD163, and monocyte chemotactic protein-1 for the prediction of proliferative LN. In anti-mouse nephrotoxic serum glomerulonephritis, urinary CD11b correlated with histologic damage and decreased with corticosteroid treatment. In vitro, CD11b levels were decreased on activated mouse neutrophils displaying Fcγ receptor clustering and transendothelial migration, suggesting that leukocyte activation and transmigration are required for CD11b shedding in urine. Together, our results suggest that urinary CD11b may be a useful biomarker to estimate histopathological activity, particularly glomerular leukocyte accumulation, in LN.

Intravenously administered darbepoetin alfa once a week could maintain hemoglobin level more efficiently than once every 2 weeks in patients on hemodialysis.

BACKGROUND: Darbepoetin alfa, which has a much longer half-life than recombinant human erythropoietin, is used to treat renal anemia. However, there are few reports investigating the efficacy of darbepoetin alfa administered every 2 weeks (Q2W). METHODS: We performed the single-center, prospective, and randomized study in chronic hemodialysis patients. Clinically stable patients on hemodialysis were recruited, and darbepoetin alfa 15-40 microg/week was administered intravenously once a week (QW) to achieve a hemoglobin (Hb) level of 10.5-12.0 g/dl for 8 weeks prior to randomization. The patients were randomly assigned to 2 different dosing frequency groups: once a week (QW) or every 2 weeks (Q2W). We switched to a double dose in the Q2W group. We measured Hb level every 2 weeks and administered darbepoetin alfa to achieve an Hb level of 10.5-11.5 g/dl. The primary endpoints were the weekly dose of darbepoetin alfa administered at week 24. RESULTS: We assigned 19 and 20 patients into QW and Q2W, respectively. There were no significant differences between the groups in Hb, transferrin saturation, ferritin, and weekly dose of darbepoetin alfa at end of the baseline period. There was no significant difference in Hb level at week 24, at which time the weekly dose requirement and dose per dry body weight were much higher in the Q2W than in the QW group. CONCLUSION: Administration of darbepoetin alfa Q2W could maintain Hb level similarly to to that obtained QW, but we did not confirm efficiency at a higher dose requirement or blood pressure elevation.

Administration of alfacalcidol for patients with predialysis chronic kidney disease may reduce cardiovascular disease events.

BACKGROUND: Besides its effect on calcium metabolism, vitamin D may play a part in preventing the onset and progression of cardiovascular disease (CVD) events. Only a few reports on the studies relating to whether vitamin D may reduce CVD events in patients with predialysis chronic kidney disease (CKD) are available, and many ambiguities remain. METHODS: We conducted a retrospective cohort study of 665 patients with predialysis CKD. With log-rank test using the Kaplan-Meyer survival curve, comparison of incidences of CVD events, CVD-related mortality, and all-cause mortality were made between patients in the alfacalcidol treatment group (107 patients) in the predialysis stage to whom alfacalcidol 0.25-0.5 microg/day was orally administered for at least 24 weeks, and patients in the nontreatment group (558 patients) who received no administration of alfacalcidol or other type of activated vitamin D and its analogues. Patients to whom alfacalcidol administration was discontinued within 24 weeks as well as initiation of dialysis of <24 weeks were excluded for this study. Factors relating to CVD events were examined using Cox's proportional hazards analysis. RESULTS: The mean follow-up period was 55.1 +/- 38.9 months in the alfacalcidol treatment group and 41.9 +/- 38.4 months in the nontreatment group. CVD events occurred in 172 patients during the follow-up period, and 74 of those occurred during the predialysis period. In the alfacalcidol treatment group, the incidence of cumulative CVD events was significantly lower. In relation to all-cause deaths and CVD-related deaths, the cumulative mortality rate was significantly lower in the alfacalcidol treatment group during the follow-up period. Throughout the follow-up period, the association between CVD events and alfacalcidol use was detected when adjusted for age, sex, diabetes, hypertension, use of renin-angiotensin system inhibitors, estimated glomerular filtration rate, and albumin and parathyroid hormone. CONCLUSION: These data showed that oral administration of alfacalcidol for predialysis CKD patients was associated with reduced risk for CVD.