Introduction: Coronavirus disease is associated with increased morbidity and mortality in maintenance hemodialysis (MHD) patients. Recent breakthrough infection in vaccinated people has led some authorities to recommend a booster dose for patients fully vaccinated 5–8 months ago. We aimed to assess the humoral response of MHD patients following a booster dose with the BNT162b2 vaccine. Methods: The study included 102 MHD patients vaccinated with 2 doses of the BNT162b2 (Pfizer-BioNTech) vaccine. A third dose (booster) was recommended to all MHD patients in our center and was given to those who opted to receive it, resulting in a booster group and a control group that did not receive the booster. Previous exposure was excluded by testing for the presence of the anti-nucleocapsid antibody (SARS-CoV-2) or positive PCR. We assessed the humoral response before and after the booster dose. Results: Of 66 patients in the booster group, 65 patients (98.5%) developed a positive antibody response, from 472.7 ± 749.5 to 16,336.8 ± 15,397.3, as compared to a sustained decrease in the control group (695.7 ± 642.7 to 383.6 ± 298.6), p < 0.0001. No significant adverse effects were reported. Prior antibody titers were positively correlated to IgG levels following the booster dose. There was a significant association between malnutrition-inflammation markers and the humoral response. Conclusions: Almost all MHD patients developed a substantial humoral response following the booster dose, which was significantly higher than levels reported for MHD patients following administration of 2 doses alone. Further studies and observations are needed to determine the exact timing and dosing schedule.

Introduction: Convolutional Neural Network (CNN) systems in healthcare are influenced by unbalanced datasets and varying sizes. This article delves into the impact of dataset size, class imbalance, and their interplay on CNN systems, focusing on the size of the training set versus imbalance—a unique perspective compared to the prevailing literature. Furthermore, it addresses scenarios with more than two classification groups, often overlooked but prevalent in practical settings. Methods: Initially, a CNN was developed to classify lung diseases using X-ray images, distinguishing between healthy individuals and COVID-19 patients. Later, the model was expanded to include pneumonia patients. To evaluate performance, numerous experiments were conducted with varied data sizes and imbalance ratios for both binary and ternary classifications, measuring various indices to validate the model’s efficacy. Results: The study revealed that increasing dataset size positively impacts CNN performance, but this improvement saturates beyond a certain size. A novel finding is that the data balance ratio influences performance more significantly than dataset size. The behavior of three-class classification mirrored that of binary classification, underscoring the importance of balanced datasets for accurate classification. Conclusions: This study emphasizes the fact that achieving balanced representation in datasets is crucial for optimal CNN performance in healthcare, challenging the conventional focus on dataset size. Balanced datasets improve classification accuracy, both in two-class and three-class scenarios, highlighting the need for data-balancing techniques to improve model reliability and effectiveness. Motivation: Our study is motivated by a scenario with 100 patient samples, offering two options: a balanced dataset with 200 samples and an unbalanced dataset with 500 samples (400 healthy individuals). We aim to provide insights into the optimal choice based on the interplay between dataset size and imbalance, enriching the discourse for stakeholders interested in achieving optimal model performance. Limitations: Recognizing a single model’s generalizability limitations, we assert that further studies on diverse datasets are needed.

The optimal SARS-CoV-2 vaccination schedule in dialysis patients and the potential need for a fourth vaccine dose are debatable. We prospectively assessed the humoral responses to three and four doses of BNT162b2 among dialysis patients. The study included 106 dialysis patients; 60 (56.6%) and 46 (43.4%) received 3 and 4 vaccine doses, respectively. Anti-spike (anti-S) antibody titers significantly increased after the third vaccine dose, followed by a decline, yet still remained higher than all previous measurements. The fourth vaccine dose led to another profound rise in anti-S titers. The absolute increase following the fourth dose correlated with response to the third dose. Infection risk however was similar between patients vaccinated with three or four doses.

Background: Tezepelumab, a monoclonal antibody targeting thymic stromal lymphopoietin, has demonstrated efficacy for severe asthma in clinical trials, but real-world evidence remains limited. We aimed to evaluate the characteristics and outcomes of patients initiating tezepelumab in a real-world setting. Methods: We conducted a retrospective, multicentre cohort study across four tertiary care centres to evaluate the real-world effectiveness of tezepelumab in patients with severe asthma. Eligible patients were adults with a confirmed diagnosis of severe asthma, treated with tezepelumab. Data on exacerbation rates, pulmonary function and corticosteroid use were collected and analysed at baseline and 1-year follow-up. Results: The study included 103 patients treated with tezepelumab with a median (interquartile range) duration of 323 (267–359) days. Overall, 39% had prior biologic therapy and 32% had an eosinophil count <300 cells·μL⁻¹. At follow-up, there was a 66.7% relative reduction in annual exacerbations. The most pronounced reduction was observed in biologic-naïve patients with peripheral eosinophil counts ≥300 cells·μL⁻¹ (78% reduction). A 62% relative reduction was found among patients with eosinophil counts <150 cells·μL⁻¹. There were significant improvements in forced expiratory volume in 1 s, with 51% of patients demonstrating a ≥10% relative increase. Of patients using maintenance oral corticosteroid (mOCS), 45% discontinued mOCS and 23% reduced their dose by more than 50%. Conclusions: In this real-world cohort, treatment with tezepelumab for a median of 46 weeks was associated with improved asthma control, reductions in exacerbations, mOCS and inhaled corticosteroid doses, and a low symptom burden. These findings were consistent in biologic-experienced or low-eosinophil patients.