Cardiorenal Syndrome in COVID-19 Patients: A Systematic Review.

Aims: To perform a systematic review assessing the clinical manifestations and outcomes of cardiorenal syndrome or the presence of both cardiac and renal complications in the 2019 coronavirus disease (COVID-19) patients. Methods: All relevant studies about cardiorenal syndrome or both cardiac and renal complications in COVID-19 patients were retrieved on PUBMED, MEDLINE, and EMBASE from December 1, 2019 to February 20, 2022. Results: Our search identified 15 studies including 637 patients with a diagnosis of cardiorenal syndrome or evidence of both cardiac and renal complications followingSARS-CoV-2 infection. They were male predominant (66.2%, 422/637), with a mean age of 58 years old. Cardiac complications included myocardial injury (13 studies), heart failure (7 studies), arrhythmias (5 studies), or myocarditis and cardiomyopathy (2 studies). Renal complications manifested as acute kidney injury with or without oliguria. Patients with cardiorenal injury were often associated with significantly elevated levels of inflammatory markers (CRP, PCT, IL-6). Patients with a diagnosis of cardiorenal syndrome or evidence of both cardiac and renal complications had more severe disease and poorer prognosis (9 studies). Conclusion: The presence of either cardiorenal syndrome or concurrent cardiac and renal complications had a significant impact on the severity of the disease and the mortality rate among patients with COVID-19 infection. Therefore, careful assessment and management of potential cardiac and renal complications in patients with COVID-19 infection are important to improve their outcomes.

Kidney manifestations of mild, moderate and severe coronavirus disease 2019: a retrospective cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a pandemic that has affected more than 3 million patients globally. Previous data from Wuhan city showed that acute kidney injury (AKI), proteinuria and hematuria occurred frequently in patients with severe COVID-19. However, the prevalence of kidney injury in milder cases remains unclear. METHODS: This retrospective study included two major consecutive cohorts of COVID-19 patients in Sichuan Province. Baseline characteristics, laboratory data including renal function, proteinuria and dipstick hematuria, and other laboratory parameters were collected. A subgroup of patients was followed up for 2-4 weeks to evaluate the short-term outcome of renal impairment. RESULTS: Overall, 168 COVID-19-positive patients were included in the study. The majority of patients (79.7%) were diagnosed with mild or moderate disease. Half of patients presented with fever; however, in The Tibetan cohort, fever only occurred in 13.4% of patients. On hospital admission, proteinuria and dipstick hematuria were noted in 18.4% and 17.4% of patients, respectively, while AKI only occurred in one patient. Further analysis showed that severe or critical COVID-19 was associated with higher risk of proteinuria [relative risk (RR) 7.37, 95% confidence interval (CI) 2.45-22.18, P = 3.8 × 10-4] and dipstick hematuria (RR 8.30, 95% CI 2.69-25.56, P = 2.3 × 10-4). Proteinuria, dipstick hematuria, or the combination of proteinuria and hematuria could significantly predict severe or critical severe COVID-19. CONCLUSIONS: Proteinuria and dipstick hematuria are not uncommon in patients with COVID-19 infection, especially in severe or critical cases.

Survival Factors and Metabolic Pathogenesis in Elderly Patients (≥65) With COVID-19: A Multi-Center Study.

Background: Elderly patients infected with COVID-19 are reported to be facing a substantially increased risk of mortality. Clinical characteristics, treatment options, and potential survival factors remain under investigation. This study aimed to fill this gap and provide clinically relevant factors associated with survival of elderly patients with COVID-19. Methods: In this multi-center study, elderly patients (age ≥65 years old) with laboratory-confirmed COVID-19 from 4 Wuhan hospitals were included. The clinical end point was hospital discharge or deceased with last date of follow-up on Jul. 08, 2020. Clinical, demographic, and laboratory data were collected. Univariate and multivariate analysis were performed to analyze survival and risk factors. A metabolic flux analysis using a large-scale molecular model was applied to investigate the pathogenesis of SARS-CoV-2 with regard to metabolism pathways. Results: A total of 223 elderly patients infected with COVID-19 were included, 91 (40.8%) were discharged and 132 (59.2%) deceased. Acute respiratory distress syndrome (ARDS) developed in 140 (62.8%) patients, 23 (25.3%) of these patients survived. Multivariate analysis showed that potential risk factors for mortality were elevated D-Dimer (odds ratio: 1.13 [95% CI 1.04 - 1.22], p = 0.005), high immune-related metabolic index (6.42 [95% CI 2.66-15.48], p < 0.001), and increased neutrophil-to-lymphocyte ratio (1.08 [95% 1.03-1.13], p < 0.001). Elderly patients receiving interferon atmotherapy showed an increased probability of survival (0.29 [95% CI 0.17-0.51], p < 0.001). Based on these factors, an algorithm (AlgSurv) was developed to predict survival for elderly patients. The metabolic flux analysis showed that 12 metabolic pathways including phenylalanine (odds ratio: 28.27 [95% CI 10.56-75.72], p < 0.001), fatty acid (15.61 [95% CI 6.66-36.6], p < 0.001), and pyruvate (12.86 [95% CI 5.85-28.28], p < 0.001) showed a consistently lower flux in the survivors vs. the deceased subgroup. This may reflect a key pathogenic mechanism of COVID-19 infection. Conclusion: Several factors such as interferon atmotherapy and recreased activity of specific metabolic pathways were found to be associated with survival of elderly patients. Based on these findings, a survival algorithm (AlgSurv) was developed to assist the clinical stratification for elderly patients. Dysregulation of the metabolic pathways revealed in this study may aid in the drug and vaccine development against COVID-19.

Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China.

Novel coronavirus 2019 (COVID-19) infection is a global public health issue, that has now affected more than 200 countries worldwide and caused a second wave of pandemic. Severe adult respiratory syndrome-CoV-2 (SARS-CoV-2) pneumonia is associated with a high risk of mortality. However, prognostic factors predicting poor clinical outcomes of individual patients with SARS-CoV-2 pneumonia remain under intensive investigation. We conducted a retrospective, multicenter study of patients with SARS-CoV-2 who were admitted to four hospitals in Wuhan, China from December 2019 to February 2020. Mortality at the end of the follow up period was the primary outcome. Factors predicting mortality were also assessed and a prognostic model was developed, calibrated and validated. The study included 492 patients with SARS-CoV-2 who were divided into three cohorts: the training cohort (n = 237), the validation cohort 1 (n = 120), and the validation cohort 2 (n = 135). Multivariate analysis showed that five clinical parameters were predictive of mortality at the end of follow up period, including advanced age [odds ratio (OR), 1.1/years increase (p < 0.001)], increased neutrophil-to-lymphocyte ratio [(NLR) OR, 1.14/increase (p < 0.001)], elevated body temperature on admission [OR, 1.53/°C increase (p = 0.005)], increased aspartate transaminase [OR, 2.47 (p = 0.019)], and decreased total protein [OR, 1.69 (p = 0.018)]. Furthermore, the prognostic model drawn from the training cohort was validated with validation cohorts 1 and 2 with comparable area under curves (AUC) at 0.912, 0.928, and 0.883, respectively. While individual survival probabilities were assessed, the model yielded a Harrell's C index of 0.758 for the training cohort, 0.762 for the validation cohort 1, and 0.711 for the validation cohort 2, which were comparable among each other. A validated prognostic model was developed to assist in determining the clinical prognosis for SARS-CoV-2 pneumonia. Using this established model, individual patients categorized in the high risk group were associated with an increased risk of mortality, whereas patients predicted to be in the low risk group had a higher probability of survival.

Social Determinants of Health and COVID-19 Among Patients in New York City.

Background: Covid-19 testing and disease outcomes according to demographic and neighborhood characteristics must be understood. Methods: Using aggregate administrative data from a multi-site academic healthcare system in New York from March 1 â€" May 14, 2020, we examined patient demographic and neighborhood characteristics according to Covid-19 testing and disease outcomes. Results: Among the 23,918 patients, higher proportions of those over 65 years old, male sex, Hispanic ethnicity, Medicare, or Medicaid insurance had positive tests, were hospitalized, or died than those with younger age, non-Hispanic ethnicity, or private insurance. Patients living in census tracts with more non-White individuals, Hispanic individuals, individuals in poverty, or housing crowding had higher proportions of Covid-19 positive tests, hospitalizations, and deaths than counterparts. Discussion: Variation exists in Covid-19 testing and disease outcomes according to patient and neighborhood characteristics. There is a need to monitor Covid-19 testing access and disease outcomes and resolve racist policies and practices.