In patients on chronic hemodialysis, there is no standard protocol for maintenance iron supplementation. This study aimed to compare two fixed-dose intravenous (IV) iron protocols to reduce erythropoiesis-stimulating agents (ESA). We conducted a double-blinded, randomized controlled study on hemodialysis patients having ferritin levels between 200 and 700 ng/dl and transferrin saturation values between 20 and 40%. Patients were assigned to receive either 100 or 200 mg of IV iron each month. ESA was adjusted every month to keep Hb between 10 and 12 g/dl. ESA dose at 12 months was the primary outcome. The secondary outcomes were all-cause mortality, cardiovascular events, absolute iron deficiency anemia (IDA), blood transfusion, adverse events, and iron withholding rate. Of the 79 eligible patients, 40 received 100 mg of IV iron, while 39 received 200 mg. At month 12, the mean monthly ESA dose in the 100-mg IV iron group was 35,706 ± 21,637 IU, compared to 26,382 ± 14,983 IU in the 200-mg group (P = 0.03). IDA was found in twelve patients (30%) in the 100-mg group and four patients (10.5%) in the 200-mg group (P = 0.05). In each group, three patients died (P = 0.9). Hospitalization, venous access thrombosis, and infection rates were similar in both groups. The withholding rate of IV iron was higher in 200-mg group (25% vs. 64.1%), but the protocol compliance was found more in 100-mg group (50% vs. 28.2%) (P = 0.001). In conclusion, monthly 200-mg IV iron infusions significantly reduce ESA doses but have a higher withholding rate. (Funded by the Kidney Foundation of Thailand and the Research Group in Nephrology and Renal Replacement Therapy from the Faculty of Medicine, Thammasat University).Thai Clinical Trials Registry number, TCTR20190707001.
Background and Objectives: Osteoporosis results in increasing morbidity and mortality in hemodialysis patients. The medication for treatment has been limited. There is evidence that beta-blockers could increase bone mineral density (BMD) and reduce the risk of fracture in non-dialysis patients, however, a study in hemodialysis patients has not been conducted. This study aims to determine the association between beta-blocker use and bone mineral density level in hemodialysis patients. Materials and Methods: We conducted a cross-sectional study in hemodialysis patients at Thammasat University Hospital from January 2018 to December 2020. A patient receiving a beta-blocker ≥ 20 weeks was defined as a beta-blocker user. The association between beta-blocker use and BMD levels was determined by univariate and multivariate linear regression analysis. Results: Of the 128 patients receiving hemodialysis, 71 were beta-blocker users and 57 were non-beta-blocker users (control group). The incidence of osteoporosis in hemodialysis patients was 50%. There was no significant difference in the median BMD between the control and the beta-blocker groups of the lumbar spine (0.93 vs. 0.91, p = 0.88), femoral neck (0.59 vs. 0.57, p = 0.21), total hip (0.73 vs. 0.70, p = 0.38), and 1/3 radius (0.68 vs. 0.64, p = 0.40). The univariate and multivariate linear regression analyses showed that the beta-blocker used was not associated with BMD. In the subgroup analysis, the beta-1 selective blocker used was associated with lower BMD of the femoral neck but not within the total spine, total hip, and 1/3 radius. The multivariate logistic regression showed that the factors of age ≥ 65 years (aOR 3.31 (1.25–8.80), p = 0.02), female sex (aOR 4.13 (1.68–10.14), p = 0.002), lower BMI (aOR 0.89 (0.81–0.98), p = 0.02), and ALP > 120 U/L (aOR 3.88 (1.33–11.32), p = 0.01) were independently associated with osteoporosis in hemodialysis patients. Conclusions: In hemodialysis patients, beta-blocker use was not associated with BMD levels, however a beta-1 selective blocker used was associated with lower BMD in the femoral neck.
Background and Objectives: Patients receiving in-center hemodialysis are at a high risk of coronavirus disease 2019 (COVID-19) infection. A reduction in hemodialysis frequency is one of the proposed measures for preventing COVID-19 infection. However, the predictors for determining an unsuccessful reduction in hemodialysis frequency are still lacking. Materials and Methods: This retrospective observational study enrolled patients who were receiving long-term thrice-weekly hemodialysis at the Thammasat University Hospital in 2021 and who decreased their dialysis frequency to twice weekly during the COVID-19 outbreak. The outcomes were to determine the predictors and a prediction model of unsuccessful reduction in dialysis frequency at 4 weeks. Bootstrapping was performed for the purposes of internal validation. Results: Of the 161 patients, 83 patients achieved a dialysis frequency reduction. Further, 33% and 82% of the patients failed to reduce their dialysis frequency at 4 and 8 weeks, respectively. The predictors for unsuccessful reduction were diabetes, congestive heart failure (CHF), pre-dialysis overhydration, set dry weight (DW), DW from bioelectrical impedance analysis, and the mean pre- and post-dialysis body weight. The final model including these predictors demonstrated an AUROC of 0.763 (95% CI 0.654–0.866) for the prediction of an unsuccessful reduction. Conclusions: The prediction score involving diabetes, CHF, pre-dialysis overhydration, DW difference, and net ultrafiltration demonstrated a good performance in predicting an unsuccessful reduction in hemodialysis frequency at 4 weeks.
Background: The incidence and risk factors for acute kidney injury in COVID-19 patients vary across studies, and predicting models for AKI are limited. This study aimed to identify the risk factors for AKI in severe COVID-19 infection and develop a predictive model for AKI. Method: Data were collected from patients admitted to the ICU at Thammasat University Hospital in Thailand with PCR-confirmed COVID-19 between 1 January 2021, and 30 June 2022. Results: Among the 215 severe-COVID-19-infected patients, 102 (47.4%) experienced AKI. Of these, 45 (44.1%), 29 (28.4%), and 28 (27.4%) patients were classified as AKI stage 1, 2, and 3, respectively. AKI was associated with 30-day mortality. Multivariate logistic regression analysis revealed that prior diuretic use (odds ratio [OR] 7.87, 95% confidence interval [CI] 1.98–31.3; p = 0.003), use of a mechanical ventilator (MV) (OR 5.34, 95%CI 1.76–16.18; p = 0.003), and an APACHE II score ≥ 12 (OR 1.14, 95%CI 1.05–1.24; p = 0.002) were independent risk factors for AKI. A predictive model for AKI demonstrated good performance (AUROC 0.814, 95%CI 0.757–0.870). Conclusions: Our study identified risk factors for AKI in severe COVID-19 infection, including prior diuretic use, an APACHE II score ≥ 12, and the use of a MV. The predictive tool exhibited good performance for predicting AKI.
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