Evolving impact of the COVID-19 pandemic in chronic dialysis recipients over the course of pandemic waves and COVID-19 vaccination rollout: a French national study. (preprint)

BackgroundThis observational study aims to assess the impact of the pandemic on the evolving of kidney transplantations, survival, and vaccination in chronic dialysis recipients (CDR) over the COVID-19 pandemic subperiods. MethodsUsing the French national health claims database, incident persons with end stage kidney disease in years 2015 to 2021 treated with dialysis were followed-up until December 31, 2022. Kidney transplantion and survival over pandemic subperiods versus the prepandemic period were investigated using longitudinal models with time-dependent covariates. Moreover, the impact of cumulative doses of COVID-19 vaccine on hospitalization and survival were compared between CDR and matched-control individuals. FindingsFollow-up of the 71,583 CDR and 143,166 controls totalized 639,341 person-years (CDR: 184,909; controls: 454,432). The likelihood of receiving a kidney transplant decreased during all pandemic subperiods except one. Mortality in CDR increased during the 3 wave subperiods (hazard ratio (HR [95% confidence interval]): 1{middle dot}19 [1{middle dot}13-1{middle dot}27], 1{middle dot}19 [1{middle dot}15-1{middle dot}23], and 1{middle dot}12 [1{middle dot}07-1{middle dot}17], respectively). While vaccine coverage declined with each booster dose, receiving such doses was associated with lower risks of COVID-19-related hospitalization (0{middle dot}66 [0{middle dot}56-0{middle dot}77], 0{middle dot}83 [0{middle dot}72-0{middle dot}94] for 1st booster versus 2nd dose and 2nd booster versus 1st booster, respectively) and death (corresponding HR: 0{middle dot}55 [0{middle dot}51-0{middle dot}59], 0{middle dot}88 [0{middle dot}83-0{middle dot}95]). Evolving patterns in mortality and vaccination outcomes were similar in CDR and controls. InterpretationThe impact of the pandemic in CDR was not specific of the kidney disease per se. Study results also suggest future research aimed at increasing adherence to vaccine booster doses.

COVID-19-associated acute renal failure in critically ill patients correlates with microthrombosis and renal loss of thrombomodulin (preprint)

Critically ill COVID-19 patients have a high degree of acute kidney injury which develops in up to 85% of patients. We have previously shown that circulating levels of angiopoietin-2 increased in critically ill COVID-19 patients correlated to kidney injury, coagulopathy, and mortality. Furthermore, our experiments showed a causal effect on coagulopathy from angiopoietin-2 binding and inhibition of thrombomodulin mediated anticoagulation. In the current study we hypothesize that renal microthrombi may be a mechanism for reduced renal function in critically ill COVID-19 patients, and that local dysregulation of thrombomodulin and angiopoietin-2 may be involved. To investigate our hypothesis, we utilized postmortem kidney tissue from seven COVID-19 patients treated at the intensive care unit. We evaluated kidney function, thrombosis, tubular injury, fibrosis, glomerulosclerosis, glomerular size as well as renal expression of thrombomodulin and angiopoietin-2. Proximity ligation assay was utilized to evaluate the presence of angiopoietin-2 binding to thrombomodulin. Normal kidney tissue came from the healthy part of six nephrectomies due to cancer. Our experiments show renal thrombosis in 6/7 COVID-19 patients, on average 14.7 (6.9-22.5) thrombi per mm2. Most COVID-19 kidneys had extensive kidney injury, especially tubular necrosis, but also glomerular enlargement, glomerulosclerosis, and tubulointerstitial fibrosis which in some cases most likely resulted from underlying disease. Thrombomodulin expression was reduced in glomeruli and peritubular capillaries in kidneys from COVID-19 patients, whereas no change was found for angiopoietin-2. In summary, our study describes a high degree of acute renal failure, renal microthrombosis, and loss of thrombomodulin in postmortem tissue from critically ill COVID-19 patients.

Integrated multiomics implicates dysregulation of ECM and cell adhesion pathways as drivers of severe COVID-associated kidney injury (preprint)

COVID-19 has been a significant public health concern for the last four years; however, little is known about the mechanisms that lead to severe COVID-associated kidney injury. In this multicenter study, we combined quantitative deep urinary proteomics and machine learning to predict severe acute outcomes in hospitalized COVID-19 patients. Using a 10-fold cross-validated random forest algorithm, we identified a set of urinary proteins that demonstrated predictive power for both discovery and validation set with 87% and 79% accuracy, respectively. These predictive urinary biomarkers were recapitulated in non-COVID acute kidney injury revealing overlapping injury mechanisms. We further combined orthogonal multiomics datasets to understand the mechanisms that drive severe COVID-associated kidney injury. Functional overlap and network analysis of urinary proteomics, plasma proteomics and urine sediment single-cell RNA sequencing showed that extracellular matrix and autophagy-associated pathways were uniquely impacted in severe COVID-19. Differentially abundant proteins associated with these pathways exhibited high expression in cells in the juxtamedullary nephron, endothelial cells, and podocytes, indicating that these kidney cell types could be potential targets. Further, single-cell transcriptomic analysis of kidney organoids infected with SARS-CoV-2 revealed dysregulation of extracellular matrix organization in multiple nephron segments, recapitulating the clinically observed fibrotic response across multiomics datasets. Ligand-receptor interaction analysis of the podocyte and tubule organoid clusters showed significant reduction and loss of interaction between integrins and basement membrane receptors in the infected kidney organoids. Collectively, these data suggest that extracellular matrix degradation and adhesion-associated mechanisms could be a main driver of COVID-associated kidney injury and severe outcomes.

Kidney Outcomes and Trajectories of Tubular Injury and Function in Critically Ill Persons with and without Coronavirus-2019 (preprint)

Background Coronavirus disease-2019 (COVID-19) may injure the kidney tubules via activation of inflammatory host responses and/or direct viral infiltration. Most studies of kidney injury in COVID-19 lacked contemporaneous controls or measured kidney biomarkers at a single time point. To better understand mechanisms of AKI in COVID-19, we compared kidney outcomes and trajectories of tubular injury, viability, and function in prospectively enrolled critically ill adults with and without COVID-19.Methods The COVID-19 Host Response and Outcomes (CHROME) study prospectively enrolled patients admitted to intensive care units in Washington state with symptoms of lower respiratory tract infection, determining COVID-19 status by nucleic acid amplification on arrival. We evaluated major adverse kidney events (MAKE) defined as a doubling of serum creatinine, kidney replacement therapy, or death, in 330 patients after inverse probability weighting. In the 181 patients with available biosamples, we determined trajectories of urine kidney injury molecule-1 (KIM-1) and epithelial growth factor (EGF), and urine:plasma ratios of endogenous markers of tubular secretory clearance.Results At ICU admission, mean age was 55\(\pm\)16 years; 45% required mechanical ventilation; and mean serum creatinine concentration was 1.1 mg/dL. COVID-19 was associated with a 70% greater incidence of MAKE (95% CI 1.05, 2.74) and a 741% greater incidence of KRT (95% CI 1.69, 32.41). The biomarker cohort had a median of three follow-up measurements. Urine EGF, secretory clearance ratios, and eGFR increased over time in the COVID-19 negative group but remained unchanged in the COVID-19 positive group. In contrast, urine KIM-1 concentrations did not significantly change over the course of the study in either group.Conclusions Among critically ill adults, COVID-19 is associated with a more protracted course of proximal tubular dysfunction.

Bidirectional causal relationships between IgA nephropathy and COVID-19: genetic evidence from Mendelian randomization (preprint)

Purpose Previous studies have suggested that patients with IgA nephropathy (IgAN) was associated with an increased risk of coronavirus disease 2019 (COVID-19) infection. However, the findings were inconsistent, and whether there was a causality between IgAN and COVID-19 infection remains unknown. This study was performed to estimate the casual effect between IgAN and COVID-19 infection with the implementation of bidirectional Mendelian randomization (MR) analysis.Methods Genetic summary data of IgAN was derived from a large genome-wide association study (GWAS) that consisted of 14,361 cases and 43,923 controls. The genetic data of COVID-19 comprised of three phenotypes, including hospitalization, severity and infection, which had a population more than 20 million. The methods of inverse variance weighting (IVW), MR-Egger, weight median and weighted mode were applied for causal inference in MR analysis.Results In the forward direction, the IVW’s results proved that IgAN did not have causal relationships with hospitalization COVID-19 (OR = 1.077, 95%CI: 0.953–1.217, P = 0.236), severe COVID-19 (OR = 1.059, 95%CI: 0.878–1.278, P = 0.547) and COVID-19 infection (OR = 0.973, 95%CI: 0.929–1.109, P = 0.243). Furthermore, reverse MR analysis showed no evidence of causal associations of hospitalization COVID-19 (OR = 1.017, 95%CI: 0.968–1.069, P = 0.499), severe COVID-19 (OR = 1.005, 95%CI: 0.979–1.078, P = 0.781) and COVID-19 infection (OR = 1.030, 95%CI: 0.909–1.169, P = 0.641) with the risk of IgAN.Conclusion Our study does not support a casual association of IgAN with the risk of COVID-19 infection, nor does the causality between COVID-19 infection and IgAN risk.

The Human Phospholipase B-II Precursor (HPLBII-P) in Urine as a Novel Biomarker of Glomerular Activity in COVID-19 and Diabetes Mellitus (preprint)

The human phospholipase B-II precursor (HPLBII-P) was originally purified from white blood cells but is also found in other cellular structures such as kidney glomeruli and tubuli. The objective of this report was to investigate the relationship of HPLBII-P in urine to acute kidney injury in patients with COVID-19 Methods Urine was collected at admission from 132 COVID-19 patients admitted to the intensive care units (ICU) because of respiratory failure. HPLBII-P was measured by a sensitive ELISA. For comparison, HNL was measured in urine, by the ELISA configured with mabs 763/8F, as a sign of tubular affection in addition to routine biomarkers of kidney disease Results Overall, the concentrations of urinary HPLBII-P were almost 3-fold higher in COVID-19 patients as compared to healthy controls (p

Investigating the correlation between demographic data, laboratory results, intubation, and mortality rate in hospitalized COVID-19 patients: A retrospective study (preprint)

Background COVID-19 is a highly contagious infectious disease that rapidly escalated into a pandemic. This coronavirus pandemic has been associated with considerable morbidity and mortality. Multiple risk factors for severe, critical illness and death due to COVID-19 have been identified. This study investigated associations between demographic traits, laboratory test results, intubation status, and mortality among hospitalized COVID-19 patients.Methods In this cross-sectional descriptive study, 181 patients infected with COVID-19 who were admitted to Imam Reza Hospital in Tabriz, Iran, between March and September 2020 were reviewed using the census sampling method. Demographic data, laboratory results, and intubation history were extracted from the records. The data were analyzed using Chi-square, the independent samples t-test, Mann-Whitney U tests, and logistic regression using SPSS 27. P < 0.05 and the odds ratio with a 95% confidence interval were considered significant.Results Out of 181 patients infected with COVID-19, there were 110 (60.8%) males with a median age of 66 (16–96) years. There was a significant direct relationship between outcome and intubation, chest X-ray, CT-Scan, renal diseases, age, WBC, K, P, urea, Cr, and LDH, respectively (P < 0.0001, < 0.0001, 0.02, 0.01, < 0.0001, 0.002, 0.002, 0.008, < 0.0001, < 0.0001, and 0.008). In contrast, there was a significant inverse relationship between outcome and PH, HCO3, and SaO2 (P = 0.005, 0.002, and < 0.0001).Conclusion This study found that several factors increase the risk of mortality in patients infected with COVID-19, including intubation, abnormal lung CT and chest X-ray findings, underlying kidney disease, advanced age, and high levels of white blood cells, potassium, phosphorus, urea, creatinine, and lactate dehydrogenase. On the other hand, increased pH, bicarbonate, and oxygen saturation were protective factors against mortality. These results highlight important risk and protective factors for mortality in COVID-19 patients. The findings can inform clinical decision-making and resource allocation during future COVID-19 outbreaks and pandemics involving similar respiratory viruses.

Acute kidney injury outcomes of COVID-19 confirmed patients in a Philippine tertiary hospital: A retrospective study (preprint)

The novel coronavirus (COVID-19) is known to be the fifth pandemic causing massive deaths worldwide. This virus has not only been deeply associated with acute respiratory distress, but also acute kidney injury (AKI). This study describes the baseline characteristics and various outcomes of AKI based on the KDIGO 2012 Clinical Practice Guidelines in patients hospitalized with COVID-19 at a Philippine tertiary hospital. A total of 195 patient records were retrospectively reviewed for the study. Of the 195 patients, 81(42%) patients developed AKI. Significant baseline characteristics included older age (56.28 + 14.12), presence of hypertension (p=0.004), diabetes mellitus (p=0.002), and cardiovascular disease (p=0.003). Also, the use of diuretics, inotropes and antibiotics were more prevalent in patients who developed AKI. Most of the patients who had AKI were categorized as stage 1 (49.38%).  Mechanical ventilation was significantly (p<0.001) more prevalent in patients with AKI (20.99%) compared to patients without AKI (5.26%). There was significantly higher rates (p<0.001) of renal replacement therapy in patients with AKI (30.86%). Lastly, higher mortality rates were observed in patients with AKI (50.62%) versus patients without AKI (12.28%). Our study demonstrated that patients with COVID-19 can develop AKI and tend to have a poorer prognosis.

Renal consequences of the novel coronavirus disease 2019 (COVID-19) and hydrogen sulfide as a potential therapy (preprint)

The novel coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is a global pandemic which is primarily considered a respiratory illness. However, emerging reports show that the virus exhibits both pulmonary and extra-pulmonary manifestations in humans, with the kidney as a major extra-pulmonary target due to its abundant expression of angiotensin-converting enzyme 2 and transmembrane protease serine 2, which facilitate entry of the virus into cells. Acute kidney injury has become prevalent in COVID-19 patients without prior any history of kidney dysfunction. In addition, the virus also worsens kidney conditions and increases mortality of COVID-19 patients with pre-existing chronic kidney disease, renal cancer, diabetic nephropathy, end-stage kidney disease as well as dialysis and kidney transplant patients. In the search for antiviral agents for the treatment of COVID-19, hydrogen sulfide (H2S), the third established member of gasotransmitter family, is emerging as a potential candidate, possessing important therapeutic properties including antiviral, anti-inflammatory, anti-thrombotic and antioxidant properties. A recent clinical study revealed higher serum H2S levels in survivors of COVID-19 pneumonia with reduced interleukin-6 levels compared to fatal cases. In this review, we summarize the global impact of COVID-19 on kidney conditions and discuss the emerging role of H2S as a potential COVID-19 therapy.

Medical Comorbidities as Predictors of COVID-19 Short-Term Mortality: A Historical Cohort Study (preprint)

Background: While the coronavirus disease 2019 (COVID-19) is most commonly associated with the respiratory system, disorders in other organ systems, such as the cardiovascular, neurologic, or renal, can also contribute to disease fatality. This study aimed to evaluate the relation of comorbidities to COVID-19 short-term mortality. Method: This was a single-center observational study with a historical cohort method at Bethesda Hospital Yogyakarta, Indonesia. COVID-19 diagnosis was made by utilizing reverse transcriptase-polymerase chain reaction (RT-PCR) on nasopharyngeal swabs. Patient data were retrieved from electronic medical records and used for Charlson Comorbidity Index assessments. In-hospital mortality was monitored throughout their hospital stay. Results: This study enrolled 333 patients. According to the total number of comorbidities in Charlson, 11.7% (n=39) of patients had no comorbidities; 30.9% (n=103) of patients had one comorbidity; 20.1% (n=67) of patients had two comorbidities; and 37.2% (n=124) of patients had more than three comorbidities. In multivariate analysis, these variables were significantly related to short-term mortality in COVID-19 patients: older age (odds ratio [OR] per year 1.64; 95% confidence interval [CI] 1.23-2.19; p 0.001), myocardial infarction (OR 3.57 ; 95% CI 1.49-8.56; p: 0.004), diabetes mellitus (OR 2.41; 95 CI 1.17-4.97; p: 0.017), renal disease (OR 5.18 ; 95% CI 2.07-12.97; p <0.001), and longer duration of stay (OR 1.20; 95% CI 1.08-1.32; p <0.001). Conclusion: Our study revealed multiple risk factors for mortality in patients with COVID-19. The coexistence of cardiovascular disease, diabetes, and renal problem are significant predictors of short-term mortality in COVID-19 patients.

Demystifying COVID-19 Mortality Causes with Interpretable Data Mining (preprint)

While SARS-CoV-2 infection rates are declining, older adults remain vulnerable to severe disease with high mortality. Although there have been some studies on revealing different risk factors affecting the death of COVID-19 patients, such as bilirubin, organ failure, patient age, and underlying disease, they fail to provide a comprehensive analysis to reveal their relationships and interactive effects on the risk of death. Based on the demographic information, inspection indicators, and underlying diseases of 1917 patients (102 were dead) admitted to Xiangya Hospital over a 4-month period, we used the association rule mining method to identify the risk factors leading causes of death among elderly Omicron patients. Firstly, we used the Affinity Propagation clustering to extract key features such as blood parameters, liver function indicators, renal function indicators, coagulation function indicators, and underlying diseases affecting death from the dataset. Then, we applied the Apriori to obtain 7 groups of abnormal feature combinations with significant increments in mortality rate. The results showed a relationship between the number of abnormal feature combinations and mortality rates within different groups. For instance, patients with “C-reactive protein > 8 mg/L”, “neutrophils percentage > 75.0 %”, “lymphocytes percentage < 20 %”, and “albumin < 40 g/L” have a 2x mortality rate than the basic one. If the characteristics of “D-dimer > 0.5 mg/L” and “WBC > 9.5 * 10 9 /L” are continuously included in this foundation, the mortality rate can be increased to 3x or 4x. In addition, we also found that liver and kidney diseases significantly affect patient mortality. Given patients with liver and renal diseases associated with other abnormal features, their mortality rate can be as high as 100 %. These findings can support auxiliary diagnosis and treatment to, facilitate early intervention in patients, thereby reducing patient mortality.

Cytokine Storm Fatal Acute Kidney Infection Triggered by COVID-19 (SARS CoV-2) Infection: A Review (preprint)

Acute kidney infection (AKI) occurred by tubular necrosis and glomerular dysfunction caused by many factors. SARS CoV-2 infection identified to cause fatal AKI. This paper aims to review the effect of covid-19 infection on the failure of the kidney and its mechanism. It identified that the SARS-CoV-2 received by the targeted cell by Angiotensin-converting enzyme 2 (ACE2). After the virus received by the target cells, it induces the production of pro-inflammatory cytokines such as tumor necrosis factor (TNF), interleukin (IL)-1, and interferons (IFN) by immune cells and causes cytokine storm. The pro-inflammatory cytokines are again responsible to induce the secretion of cyclooxygenase‑2 (COX‑2), which causes inflammation and pain as well it stimulates the iNOS enzyme to produce NO which allows the vasodilation of renal arteries. The increased production of NO by iNO enhanced the vasodilation of arteries, and allows the adhesion of neutrophils to the artery, and causes damage to glomerulus and tubules. Hence, the most likely sustainable intervention could be the application of angiotensin-converting enzyme 2 (ACE2) inhibition by the receptors of the target cells in these vital organs to reduce sever destruction during treatment at the early stage of infection.

Development and validation of a federated learning framework for detection of subphenotypes of multisystem inflammatory syndrome in children (preprint)

Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection. The highly diverse clinical features of MIS-C necessities characterizing its features by subphenotypes for improved recognition and treatment. However, jointly identifying subphenotypes in multi-site settings can be challenging. We propose a distributed multi-site latent class analysis (dMLCA) approach to jointly learn MIS-C subphenotypes using data across multiple institutions. Methods We used data from the electronic health records (EHR) systems across nine U.S. childrens hospitals. Among the 3,549,894 patients, we extracted 864 patients < 21 years of age who had received a diagnosis of MIS-C during an inpatient stay or up to one day before admission. Using MIS-C conditions, laboratory results, and procedure information as input features for the patients, we applied our dMLCA algorithm and identified three MIS-C subphenotypes. As validation, we characterized and compared more granular features across subphenotypes. To evaluate the specificity of the identified subphenotypes, we further compared them with the general subphenotypes identified in the COVID-19 infected patients. Findings Subphenotype 1 (46.1%) represents patients with a mild manifestation of MIS-C not requiring intensive care, with minimal cardiac involvement. Subphenotype 2 (25.3%) is associated with a high risk of shock, cardiac and renal involvement, and an intermediate risk of respiratory symptoms. Subphenotype 3 (28.6%) represents patients requiring intensive care, with a high risk of shock and cardiac involvement, accompanied by a high risk of >4 organ system being impacted. Importantly, for hospital-specific clinical decision-making, our algorithm also revealed a substantial heterogeneity in relative proportions of these three subtypes across hospitals. Properly accounting for such heterogeneity can lead to accurate characterization of the subphenotypes at the patient-level. Interpretation Our identified three MIS-C subphenotypes have profound implications for personalized treatment strategies, potentially influencing clinical outcomes. Further, the proposed algorithm facilitates federated subphenotyping while accounting for the heterogeneity across hospitals.

Inflammation Patterns in Omicron Variant-Linked COVID-19: Assessing Biomarkers for Predicting Disease Severity (preprint)

The ongoing COVID-19 pandemic necessitates the identification of effective biomarkers to gauge disease severity. C-reactive protein (CRP), D-Dimer, and White Blood Cell counts (WBCs) have emerged as potential indicators of COVID-19 severity and prognosis. This research, conducted at Qalla Hospital, enrolled 112 confirmed COVID-19 patients and 35 healthy controls, employing comprehensive clinical and laboratory evaluations that included CRP, D-Dimer, and WBC measurements. The diagnosis of COVID-19 adhered to established clinical criteria and was confirmed through SARS-CoV-2 testing, with stringent assessments to ensure precise participant classification. The results unveiled significantly elevated CRP (p-value=0.0001), D-Dimer (p-value=0.0001), and WBCs in COVID-19 patients compared to healthy controls. Elevated CRP levels, indicative of inflammation, increased D-Dimer levels associated with coagulation abnormalities, and raised WBCs within the CRP level (0.943), indicative of an immune response, were prevalent in COVID-19 patients. Gender distribution was balanced, while comorbidities such as diabetes mellitus (25%), hypertension (34.8%), kidney disease (6.2%), and multiple concurrent diseases (34%) were prevalent in the COVID-19 cohort. The discussion underscores the substantial differences in CRP, D-Dimer, and WBCs, emphasizing their potential as valuable biomarkers for diagnosing and monitoring COVID-19 severity. These biomarkers could serve as critical tools in evaluating disease progression, predicting complications, and guiding tailored therapeutic interventions. In conclusion, CRP, D-Dimer, and WBCs exhibited marked disparities between healthy individuals and COVID-19 patients, indicating their potential as diagnostic and prognostic indicators. Continued investigation into the utility of these biomarkers may refine risk stratification and treatment strategies, ultimately enhancing patient outcomes in COVID-19 management. A deeper understanding of the clinical implications of CRP, D-Dimer, and WBC levels could profoundly impact disease management and patient care strategies.

Real-world Efficacy of Ensitrelvir in Hospitalized Patients with COVID-19 in Japan: A Retrospective Observational Study (preprint)

Background: The coronavirus disease 2019 (COVID-19) pandemic necessitates continuously evaluating antiviral treatments, especially for high-risk groups, including older individuals. This study aimed to compare the efficacy of three antiviral drugs, including remdesivir, molnupiravir, and ensitrelvir, in hospitalized patients, focusing on outcomes such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen levels, hospitalization duration, and fever resolution. Methods: This retrospective observational study was conducted at Yoshida Hospital, Asahikawa city, Japan, enrolling 154 patients who received antiviral treatment upon COVID-19 diagnosis from July 1, 2022 to September 15, 2023. The diagnosis was confirmed by proprietary antigen tests or loop-mediated isothermal amplification assays. Patients who received treatment outside the hospital or with consistently negative antigen results were excluded. Drug administration was determined by attending physicians, considering oral administration challenges and renal dysfunction. The data were statistically analyzed using an unpaired two-tailed Student’s t-test and one-way analysis of variance complemented by the Tukey post-hoc test for detailed group comparisons. Results: No significant differences were observed in the initial antigen levels among the treatment groups. By day 10, the ensitrelvir group showed lower antigen levels than did the other groups, but not significantly. The ensitrelvir group had a higher antigen-negative conversion rate and a significantly shorter hospital stay than did the molnupiravir group. However, no significant differences were noted in the fever resolution time among the groups. Conclusion: This study suggests the potential benefits of ensitrelvir in reducing antigen levels and hospitalization duration. However, the overall efficacy of the antiviral agents for symptomatic relief appears similar. These findings underscore the need for further research to optimize COVID-19 management by considering personalized treatment approaches and long-term outcomes.

Thrombotic microangiopathy with kidney involvement in a patient with coronavirus disease 2019: A case report and literature review (preprint)

Background and aim: Millions of people worldwide have suffered from coronavirus disease 2019 (COVID-19). COVID-19 can lead to coagulopathy and thrombosis, presenting as pulmonary artery thromboembolism, deep vein thrombosis, and thrombotic microangiopathy (TMA), the latter being a rare finding in affected patients’ kidneys. Prior reports have rarely addressed the pathophysiology, clinical presentations, and therapeutic options in patients with COVID-19-associated TMA. Case presentation: We herein described a case of renal biopsy-proven TMA after COVID-19 in a 36-year-old woman. Initial examination revealed inflammation, acute kidney injury (AKI), anemia, and thrombocytopenia. She was diagnosed with hemolytic uremic syndrome, pulmonary infection, and COVID-19. After treatment, her condition stabilized but remained hemodialysis-dependent after discharge. One week later, she was re-hospitalized, and physical examination showed anemia and bilateral lower extremity edema. Abdominal ultrasound showed increased bilateral kidney echogenicity. Whole-exome sequencing detected an unknown variant of the C3 gene associated with hemolytic uremic syndrome susceptibility type 5/complement C3 deficiency. Kidney biopsy showed renal artery lesions, including small arteriole endothelial swelling, intimal thickening, mucinous degeneration, luminal occlusion, and small arterial wall necrosis. She received plasma exchange and steroids with significant renal function recovery. Conclusion: TMA likely contributed to AKI after COVID-19,thus supporting the notion that TMA plays an important role in the pathogenesis of COVID-19-related kidney injury. When diagnosing and treating COVID-19 patients with abnormal renal function, clinicians should incorporate kidney biopsy and genetic testing for the complement system, identify renal-limited and systemic TMA, and treat accordingly, which can improve patient outcomes.

Use of immune-modulating agents to regulate hyperinflammation in severe COVID-19; the assessment of tocilizumab use in combination with steroids (preprint)

Introduction COVID-19 infection might lead to hyperinflammatory state in severe cases leading to devastating outcomes. Immune modulation using steroids or other immune modulators can regulate the intensity of inflammatory response; however, this theory has not been adequately assessed in practice. The current study aims to investigate the use of corticosteroids alone or in combination with tocilizumab for the treatment of patients with severe COVID-19. Methods The current retrospective cross-sectional study has been conducted on 168 patients with severe COVID-19 infection who were categorized into three treatment groups of A: primary treatment with high-dose methylprednisolone (> 1 mg/kg) continued with tocilizumab; B: primary treatment with low-dose methylprednisolone (< 1 mg/kg) continued with tocilizumab and C: treatment with high-dose methylprednisolone (> 1 mg/kg) only. The parameters including clinical outcome, laboratory parameters, length of hospitalization, intensive care unit (ICU) admission requirement and drug-related adverse events were compared between the groups. Results The outcomes were significantly better in group B considering the shorter length of ICU stay, lower CRP, LDH, and higher oxygen saturation and platelet count in group B than the other groups (P-value < 0.05). Logistic regression assessment in crude and adjusted models revealed increased risks of mortality, the incidence of nosocomial infection and the incidence of adverse effects, including hepatic dysfunction, renal dysfunction and GIB in both groups A and C compared with group B (P-value < 0.05). Conclusion Based on the findings of this study, low-dose steroid continued with tocilizumab was superior over high-dose steroid alone or in combination with tocilizumab in terms of all evaluated parameters.

Pulmonary Fibrosis Followed by Severe Pneumonia in Patients with COVID- 19 infection: A Prospective Multicentre Study (preprint)

Backgrounds : The management of lung complications, especially fibrosis, after coronavirus disease (COVID-19) pneumonia, is an important issue in the COVID-19 post-pandemic era. We aimed to investigate risk factors for pulmonary fibrosis development in patients with severe COVID-19 pneumonia.Methods Clinical and radiologic data were prospectively collected from 64 patients who required mechanical ventilation due to COVID-19 pneumonia and were enrolled from eight hospitals in South Korea. Fibrotic changes on chest computed tomography (CT) was evaluated by visual assessment, and extent of fibrosis (mixed disease score) was measured using automatic quantification system.Results Sixty-four patients were enrolled, and their mean age was 58.2 years (64.1% were males). On chest CT (median interval: 60 days [interquartile range, IQR; 41–78 days] from enrolment), 35 (54.7%) patients showed ≥ 3 fibrotic lesions. The most frequent fibrotic change was traction bronchiectasis (47 patients, 73.4%). Median extent of fibrosis measured by automatic quantification was 10.6% (IQR, 3.8–40.7%). In a multivariable Cox proportional hazard model, which included nine variables with a p-value of < 0.10 in an unadjusted analysis as well as age, sex, and body mass index, male sex (hazard ratio [HR], 3.01; 95% confidence interval [CI], 1.27–7.11) and higher initial sequential organ failure assessment (SOFA) score (HR, 1.18; 95% CI, 1.02–1.37) were independently associated with pulmonary fibrosis (≥ 3 fibrotic lesions).Conclusion Our data suggests that male gender and higher SOFA score at intensive care unit admission were associated with pulmonary fibrosis in patients with severe COVID-19 pneumonia requiring mechanical ventilation.

Kidney Replacement Therapy in COVID-19-Related Acute Kidney Injury: the Importance of Timing (preprint)

The objective of this study was to evaluate two different criteria for deciding when KRT should be initiated in patients with COVID-19-related AKI, as well as to determine the impact of the timing of KRT, as defined by each criterion, on in-hospital mortality among such patients. This was a retrospective study involving 512 adult patients admitted to the ICU. All participants had laboratory-confirmed COVID-19 and a confirmed diagnosis of AKI. The potential predictors were the determination of the timing of KRT based on a temporal criterion (days since hospital admission) and that based on a serum creatinine cutoff criterion. Covariates included age, sex, and the SOFA score, as well as the need for mechanical ventilation and vasopressors. The main outcome measure was in-hospital mortality. We evaluated 512 patients, of whom 69.1% were men. The median age was 64 years. Of the 512 patients, 76.6% required dialysis after admission. The overall in-hospital mortality rate was 72.5%. When the timing of KRT was determined by the temporal criterion, the risk of in-hospital mortality was significantly higher for delayed KRT than for timely KRT--84% higher in the univariate analysis (OR=1.84, 95%, [CI]: 1.10-3.09) and 140% higher after adjustment for age, sex, and SOFA score (OR=2.40, 95% CI: 1.36-4.24). When it was determined by the creatinine cutoff criterion, there was no such difference between high and low creatinine at KRT initiation. In patients with COVID-19-related AKI, earlier KRT appears to be associated with lower in-hospital mortality.

Artificial Intelligence (AI) Based Prediction of Mortality, ICU Admission and Ventilation Support Requirement for COVID-19 Patients Using 122 Clinical and Demographic Parameters (preprint)

IntroductionCOVID-19 can rapidly lead to severe respiratory problems and can result in an overwhelming burden on healthcare systems worldwide, making it imperative to identify high-risk patients and predict survival and need for intensive care (ICU). Most of the proposed modes are not well reported making them less reproducible and prone to high risk of bias. MethodsIn this study, the performances of seven classical machine (Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), k-Nearest Neighbor (KNN), XGBoost, Linear Discriminant Analysis (LDA) and Gaussian Naive Bayes (NB)) and two deep leaning models (Deep Neural Network (DNN) and Long Short-Term Memory (LSTM)) in combination with two widely used feature selection methods (random forest and extra tree classifier) were investigated to predict "last status" representing mortality, "ICU requirement", and "ventilation days". Fivefold cross-validation was used for training and validation purposes. In each fold, 80% data were used for training the models and the rest 20% were preserved for validation. To minimize bias, the training and testing sets were split maintaining similar distributions. Before splitting, k-nearest neighbour (KNN) imputation algorithm was employed to resolve the issue of missing data. On the other hand, bootstrapping technique was used for both oversampling and undersampling to address the issue of data imbalance. Publicly available 122 demographic and clinical features of 1384 patients were used. The performances of the models were evaluated using accuracy, sensitivity, specificity, and AUC (Area Under the Curve) of Receiver operating characteristic curves (ROC). ResultsOnly 10 features out of 122 were found to be useful in prediction modelling with "Acute kidney injury during hospitalization" feature being the most important one. Blood pH presents a decent discrimination capability especially in predicting "ICU requirement", and "ventilated days", Whereas gender and age are found to be vital in predicting "last status". It was observed that selecting more than 10 features lower the prediction accuracy. The performances of different algorithms depend on number of features and data pre-processing techniques. LSTM with the with balanced data and 10 features performs the best in predicting "last status" as well as "ICU requirement" with an average of 90%, 92%, 86% and 95% accuracy, sensitivity, specificity, and AUC respectively. DNN performs the best in predicting "Ventilation days" with 88% accuracy. For "ICU requirement" which is a binary prediction task, data pre-processing technique does not have any influence in making prediction and performances of different methods are comparable (89%, 98%, 78% and 95% accuracy, sensitivity, specificity, and AUC respectively). However, the number of features selected vary with data pre-processing technique. ConclusionConsidering all the factors and limitations including absence of exact time point of clinical onset, LSTM with carefully selected features can accurately predict "last status" and "ICU requirement" with approximately 90% accuracy, sensitivity, and specificity. DNN performs the best in predicting "Ventilation days". Appropriate machine learning algorithm with carefully selected features and balance data can accurately predict mortality, ICU requirement and ventilation support. Such model can be very useful in emergency and pandemic where prompt and precise decision making is crucial.