Josipa Domjanović

Background and Objectives: The assessment of cardiac function in patients with end-stage renal disease (ESRD) is vital due to their high cardiovascular risk. However, contemporary echocardiographic indices and their association with hemodialysis-to-hemodiafiltration transfer are underreported in this population. Materials and Methods: This prospective cohort study enrolled 36 ESRD patients undergoing hemodialysis-to-hemodiafiltration transfer, with baseline and 3-month post-transfer comprehensive echocardiographic assessments. The key parameters included the global work index, global constructed work, global wasted work (GWW), global work efficiency (GWE), and global longitudinal strain (GLS), with secondary measures from conventional echocardiography. The baseline measures were compared to general population reference values and changes pre- to post-transfer were analyzed using the Mann–Whitney U test. Results: Patients exhibited significant deviations from reference ranges in GWW (179.0 vs. 53.0–122.2 mmHg%), GWE (90.0 vs. 53.0–122.2%), and GLS (−16.0 vs. −24.0–(−16.0)%). Post-transfer left ventricular myocardial work and longitudinal strain remained unchanged (p > 0.05), except for increased GWW (179.0, IQR 148.0–217.0 to 233.5, IQR 159.0-315.0 mmHg%, p = 0.037) and improved mid-inferior peak systolic longitudinal strain ((−17.0, IQR −19.0–(−11.0) to −18.7, IQR −20.0–(−18.0)%, p = 0.016). The enrolled patients also showed higher left atrial diameters, left ventricular volumes, and mass, with impaired systolic function in both ventricles compared to reference values. Conclusions: This study highlights baseline impairments in contemporary echocardiographic measures (GWW, GWE, GLS) in ESRD patients versus reference values, but found no association between hemodialysis-to-hemodiafiltration transfer and most myocardial work and strain parameters.

Background: Timely recognition of high-risk individuals with novel Coronavirus disease (COVID-19) is important. Yet, validated risk scores for kidney transplant recipients with COVID-19 are lacking. The present study aimed to externally validate the novel ImAgeS risk score in this population. Methods: A retrospective analysis of 65 kidney transplant recipients with COVID-19 was conducted. A robust external validation of the novel ImAgeS risk score with respect to 30-day all-cause mortality was performed using regression analysis, discrimination and calibration methods. Results: An overall mortality rate during the study follow-up was 18.5% (N = 12). The ImAgeS risk score showed a statistically significant association with 30-day all-cause mortality (HR 1.04 95% CI 1.00–1.08, p = 0.040). This risk score demonstrated a modest, statistically significant discrimination of all-cause mortality (AUC of 0.679 (95% CI 0.519–0.840, p = 0.027). The calibration of the model was acceptable with a Hosmer-Lemeshow value of 3.74, Harrell’s C concordance index of 0.699 and Somers’ D of 0.397. Conclusions: The ImAgeS risk score demonstrated a significant association with 30-day all-cause mortality in kidney transplant recipients with COVID-19. The model showed modest discrimination and satisfactory calibration, confirming the findings from the computational study. Further studies are needed to determine the utility of the ImAgeS score in this high-risk population.

Background and Objectives: Clinical risk scores were poorly examined in kidney transplant recipients (KTR) with COVID-19. Materials and Methods: This observational study compared the association and discrimination of clinical risk scores (MEWS, qCSI, VACO, PSI/PORT, CCI, MuLBSTA, ISTH-DIC, COVID-GRAM and 4C) with 30-day mortality in 65 hospitalized KTRs with COVID-19. Cox regression was used to derive hazard ratios (HR) and 95% confidence intervals (95% CI), and discrimination was assessed by Harrell’s C. Results: A significant association with 30-day mortality was demonstrated for MEWS (HR 1.65 95% CI 1.21–2.25, p = 0.002); qCSI (HR 1.32 95% CI 1.15–1.52, p < 0.001); PSI/PORT (HR 1.04 95% CI 1.02–1.07, p = 0.001); CCI (HR 1.79 95% CI 1.13–2.83, p = 0.013); MuLBSTA (HR 1.31 95% CI 1.05–1.64, p = 0.017); COVID-GRAM (HR 1.03 95% CI 1.01–1.06, p = 0.004); and 4C (HR 1.79 95% CI 1.40–2.31, p < 0.001). After multivariable adjustment, significant association persisted for qCSI (HR 1.33 95% CI 1.11–1.59, p = 0.002); PSI/PORT (HR 1.04 95% CI 1.01–1.07, p = 0.012); MuLBSTA (HR 1.36 95% CI 1.01–1.85, p = 0.046); and 4C Mortality Score (HR 1.93 95% CI 1.45–2.57, p < 0.001) risk scores. The best discrimination was observed with the 4C score (Harrell’s C = 0.914). Conclusions: Risk scores such as qCSI, PSI/PORT and 4C showed the best association with 30-day mortality amongst KTRs with COVID-19.

The aim of this study was to evaluate the specific neurologic biomarkers, neuroimaging findings, and cognitive function in patients with persistent atrial fibrillation (AF) undergoing electrical cardioversion, compared to control subjects. This cross-sectional study included 25 patients with persistent AF undergoing electrical cardioversion and 16 age- and sex-matched control subjects. Plasma levels of glial fibrillary acidic protein (GFAP), neurofilament light protein (NFL), and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1), as well as parameters of neuroimaging and cognitive function, were compared between the groups. Neuroimaging was performed using the standard magnetic resonance imaging (MRI) protocol. Cognitive function was assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Cognitive Function Index. Further analysis of neurologic biomarkers was performed based on the subsequent electrical cardioversion. There was no significant difference in GFAP (median of 24.7 vs. 28.7 pg/mL, p = 0.347), UCH-L1 (median of 112.8 vs. 117.7 pg/mL, p = 0.885), and NFL (median of 14.2 vs. 15.4 pg/mL, p = 0.886) levels between AF patients and control subjects. Similarly, neuroimaging showed no between-group difference in large cortical and non-cortical lesions (n = 2, 8.0% vs. n = 0, 0.0%, p = 0.246), small non-cortical lesions (n = 5, 20.0% vs. n = 5, 31.3%, p = 0.413), white matter hyperintensity (n = 23, 92.0% vs. n = 14, 87.5%, p = 0.636), and thromboembolic lesions (n = 0, 0.0% vs. n = 1, 6.3%, p = 0.206). Cognitive assessment did not show any between-group difference in the PROMIS index (52.2 ± 9.6 vs. 51.2 ± 6.2, p = 0.706). Finally, there were no significant dynamics in neurologic biomarkers following electrical cardioversion (p > 0.05). This hypothesis-generating study did not find a significant difference in neurologic biomarkers, neuroimaging findings, or cognitive function between patients with persistent AF and controls. The restoration of sinus rhythm was not significantly associated with a change in neurologic biomarkers. Further powered longitudinal studies are needed to re-assess these findings in an AF population.

There are limited data on the performance of laboratory-derived biomarkers in kidney transplant recipients (KTR) with COVID-19. This observational study enrolled 65 KTR with COVID-19 who were treated at the University Hospital of Split up to March 2022. Laboratory-derived biomarkers (neutrophile-to-lymphocyte (NLR) ratio, platelet-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, De Ritis ratio, C-reactive protein (CRP)-to-albumin ratio, lactate dehydrogenase (LDH)-to-hemoglobin ratio, CRP-to-lymphocyte ratio, red cell distribution width-to-albumin ratio, platelet-to-albumin ratio, D-Dimer-to-albumin ratio, D-Dimer-to-NLR ratio, LDH-to-albumin ratio, and LDH-to-white blood cell (WBC) ratio) were calculated, and their performance with regard to 30-day mortality was determined. Mortality events occurred in 12 patients (18.5%), which was significantly associated with increased De Ritis (HR 3.83, 95% CI 1.57–9.35, p = 0.003), CRP-to-albumin (HR 1.36, 95% CI 1.13–1.64, p = 0.001), LDH-to-hemoglobin (HR 1.44, 95% CI 1.07–1.92, p = 0.015), CRP-to-lymphocyte (HR 1.03, 95% CI 1.01–1.07, p = 0.003), D-dimer-to-albumin (HR 4.94, 95% CI 1.38–7.24, p = 0.038), LDH-to-albumin (HR 1.20, 95% CI 1.05–1.36, p = 0.008), and LDH-to-WBC (HR 1.03 95% CI 1.01–1.05, p = 0.024) ratios. Out of these, the best area-under-the-curve (AUC) values were achieved with De Ritis (AUC 0.691), CRP-to-albumin (AUC 0.764), LDH-to-hemoglobin (AUC 0.877), CRP-to-lymphocyte (AUC 0.739), and LDH-to-albumin (AUC 0.827) ratios, while the best discrimination displayed LDH-to-hemoglobin ratio (Harrell’s C 0.808 and Somers’ D 0.616). The overall calibration was satisfactory for all models. Derived laboratory biomarkers such as the de Ritis, CRP-to-albumin, LDH-to-hemoglobin, CRP-to-lymphocyte, and LDH-to-albumin ratios show significant association and discrimination with all-cause mortality in KTR with COVID-19, suggesting its potential risk stratification role.

The effect of routine inhalation therapy on ventilator-associated pneumonia (VAP) in mechanically ventilated patients with the coronavirus disease (COVID-19) has not been well-defined. This randomized controlled trial included 175 eligible adult patients with COVID-19 who were treated with mechanical ventilation at the University Hospital of Split between October 2020 and June 2021. Patients were randomized and allocated to a control group (no routine inhalation) or one of the treatment arms (inhalation of N-acetylcysteine; 5% saline solution; or 8.4% sodium bicarbonate). The primary outcome was the incidence of VAP, while secondary outcomes included all-cause mortality. Routine inhalation therapy had no effect on the incidence of bacterial or fungal VAP nor on all-cause mortality (p > 0.05). Secondary analyses revealed a significant reduction of Gram-positive and methicillin-resistant Staphylococcus aureus (MRSA) VAP in the treatment groups. Specifically, the bicarbonate group had a statistically significantly lower incidence of Gram-positive bacterial VAP (4.8%), followed by the N-acetylcysteine group (10.3%), 5% saline group (19.0%), and control group (34.6%; p = 0.001). This difference was driven by a lower incidence of MRSA VAP in the bicarbonate group (2.4%), followed by the N-acetylcysteine group (7.7%), 5% saline group (14.3%), and control group (34.6%; p < 0.001). Longer duration of ventilator therapy was the only significant, independent predictor of any bacterial or fungal VAP in the multivariate analysis (aOR 1.14, 95% CI 1.01–1.29, p = 0.038 and aOR 1.05, 95% CI 1.01–1.10, p = 0.028, respectively). In conclusion, inhalation therapy had no effect on the overall VAP incidence or all-cause mortality. Further studies should explore the secondary findings of this study such as the reduction of Gram-positive or MRSA-caused VAP in treated patients.

COVID-19 prediction models mostly consist of combined clinical features, laboratory parameters, and, less often, chest X-ray (CXR) findings. Our main goal was to propose a prediction model involving imaging methods, specifically ultrasound. This was a single-center, retrospective cohort observational study of patients admitted to the University Hospital Split from November 2020 to May 2021. Imaging protocols were based on the assessment of 14 lung zones for both lung ultrasound (LUS) and computed tomography (CT), correlated to a CXR score assessing 6 lung zones. Prediction models for the necessity of mechanical ventilation (MV) or a lethal outcome were developed by combining imaging, biometric, and biochemical parameters. A total of 255 patients with COVID-19 pneumonia were included in the study. Four independent predictors were added to the regression model for the necessity of MV: LUS score, day of the illness, leukocyte count, and cardiovascular disease (χ2 = 29.16, p < 0.001). The model accurately classified 89.9% of cases. For the lethal outcome, only two independent predictors contributed to the regression model: LUS score and patient’s age (χ2 = 48.56, p < 0.001, 93.2% correctly classified). The predictive model identified four key parameters at patient admission which could predict an adverse outcome.