The Association between COVID-19 Infection and Kidney Damage in a Regional University Hospital.

Background and Objectives: Kidneys are one of the main targets for SARS-CoV-2. Early recognition and precautionary management are essential in COVID-19 patients due to the multiple origins of acute kidney injury and the complexity of chronic kidney disease management. The aims of this research were to investigate the association between COVID-19 infection and renal injury in a regional hospital. Materials and Methods: The data of 601 patients from the Vilnius regional university hospital between 1 January 2020 and 31 March 2021 were collected for this cross-sectional study. Demographic data (gender, age), clinical outcomes (discharge, transfer to another hospital, death), length of stay, diagnoses (chronic kidney disease, acute kidney injury), and laboratory test data (creatinine, urea, C-reactive protein, potassium concentrations) were collected and analyzed statistically. Results: Patients discharged from the hospital were younger (63.18 ± 16.02) than those from the emergency room (75.35 ± 12.41, p < 0.001), transferred to another hospital (72.89 ± 12.06, p = 0.002), or who died (70.87 ± 12.83, p < 0.001). Subsequently, patients who died had lower creatinine levels on the first day than those who survived (185.00 vs. 311.17 µmol/L, p < 0.001), and their hospital stay was longer (Spearman's correlation coefficient = -0.304, p < 0.001). Patients with chronic kidney disease had higher first-day creatinine concentration than patients with acute kidney injury (365.72 ± 311.93 vs. 137.58 ± 93.75, p < 0.001). Patients with acute kidney injury and chronic kidney disease complicated by acute kidney injury died 7.81 and 3.66 times (p < 0.001) more often than patients with chronic kidney disease alone. The mortality rate among patients with acute kidney injury was 7.79 (p < 0.001) times higher than among patients without these diseases. Conclusions: COVID-19 patients who developed acute kidney injury and whose chronic kidney disease was complicated by acute kidney injury had a longer hospital stay and were more likely to die.

Development and validation of a prediction model based on comorbidities to estimate the risk of in-hospital death in patients with COVID-19.

Background: Most existing prognostic models of COVID-19 require imaging manifestations and laboratory results as predictors, which are only available in the post-hospitalization period. Therefore, we aimed to develop and validate a prognostic model to assess the in-hospital death risk in COVID-19 patients using routinely available predictors at hospital admission. Methods: We conducted a retrospective cohort study of patients with COVID-19 using the Healthcare Cost and Utilization Project State Inpatient Database in 2020. Patients hospitalized in Eastern United States (Florida, Michigan, Kentucky, and Maryland) were included in the training set, and those hospitalized in Western United States (Nevada) were included in the validation set. Discrimination, calibration, and clinical utility were evaluated to assess the model's performance. Results: A total of 17 954 in-hospital deaths occurred in the training set (n = 168 137), and 1,352 in-hospital deaths occurred in the validation set (n = 12 577). The final prediction model included 15 variables readily available at hospital admission, including age, sex, and 13 comorbidities. This prediction model showed moderate discrimination with an area under the curve (AUC) of 0.726 (95% confidence interval [CI]: 0.722-0.729) and good calibration (Brier score = 0.090, slope = 1, intercept = 0) in the training set; a similar predictive ability was observed in the validation set. Conclusion: An easy-to-use prognostic model based on predictors readily available at hospital admission was developed and validated for the early identification of COVID-19 patients with a high risk of in-hospital death. This model can be a clinical decision-support tool to triage patients and optimize resource allocation.

Nationwide analysis of hospital admissions and outcomes of patients with SARS-CoV-2 infection in Austria in 2020 and 2021.

This retrospective study evaluated temporal and regional trends of patient admissions to hospitals, intensive care units (ICU), and intermediate care units (IMCU) as well as outcomes during the COVID-19 pandemic in Austria. We analysed anonymous data from patients admitted to Austrian hospitals with COVID-19 between January 1st, 2020 and December 31st, 2021. We performed descriptive analyses and logistic regression analyses for in-hospital mortality, IMCU or ICU admission, and in-hospital mortality following ICU admission. 68,193 patients were included, 8304 (12.3%) were primarily admitted to ICU, 3592 (5.3%) to IMCU. Hospital mortality was 17.3%; risk factors were male sex (OR 1.67, 95% CI 1.60-1.75, p < 0.001) and high age (OR 7.86, 95% CI 7.07-8.74, p < 0.001 for 90+ vs. 60-64 years). Mortality was higher in the first half of 2020 (OR 1.15, 95% CI 1.04-1.27, p = 0.01) and the second half of 2021 (OR 1.11, 95% CI 1.05-1.17, p < 0.001) compared to the second half of 2020 and differed regionally. ICU or IMCU admission was most likely between 55 and 74 years, and less likely in younger and older age groups. We find mortality in Austrian COVID-19-patients to be almost linearly associated with age, ICU admission to be less likely in older individuals, and outcomes to differ between regions and over time.

Serum IL-23, IL-10, and TNF-α predict in-hospital mortality in COVID-19 patients.

Objective: The hyperinflammatory response, caused by severe acute respiratory syndrome-2 (SARS-CoV-2), is the most common cause of death in patients with coronavirus disease 2019 (COVID-19). The etiopathogenesis of this illness is not fully understood. Macrophages appear to play a key part in COVID-19's pathogenic effects. Therefore, this study aims to examine serum inflammatory cytokines associated with the activation state of macrophages in COVID-19 patients and attempt to find accurate predictive markers for disease severity and mortality risk in hospital. Methods: 180 patients with COVID-19 and 90 healthy controls (HCs) participated in this study. Patients were divided into three different subgroups, mild (n=81), severe (n=60), and critical groups (n=39). Serum samples were collected and IL (Interleukin)-10, IL-23, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), IL-17, monocyte chemoattractant protein-1 (MCP-1) and chemokine ligand 3 (CCL3) were determined by ELISA. In parallel, myeloperoxidase (MPO) and C-reactive protein (CRP) were measured using colorimetric and electrochemiluminescence methods, respectively. Data were collected, and their associations with disease progression and mortality were assessed using regression models and receiver operating characteristic (ROC) curves. Results: Compared to HCs, a significant increase in IL-23, IL-10, TNF-α, IFN-γ and MCP-1, were observed in COVID-19 patients. Serum levels of IL-23, IL-10, and TNF-α were significantly higher in COVID-19 patients with critical cases compared to mild and severe cases, and correlated positively with CRP level. However, non-significant changes were found in serum MPO and CCL3 among the studied groups. Moreover, significant positive association has been observed among increased IL-10, IL-23 and TNF-α in serum of COVID-19 patients. Furthermore, a binary logistic regression model was applied to predict death's independent factors. Results showed that IL-10 alone or in combination with IL23 and TNF-α are strongly linked with non-survivors in COVID-19 patients. Finally, ROC curve results uncovered that IL-10, IL-23 and TNF-α were excellent predictors for prognosing COVID-19. Conclusion: The elevations of IL-10, IL-23, and TNF-α levels were seen in severe and critical cases of COVID-19 patients and their elevations were linked to the in-hospital mortality of the disease. A prediction model shows that the determination of these cytokines upon admission is important and should be done on COVID-19 patients as a way of evaluating the prognosis of the disease. COVID-19 Patients with high IL-10, IL-23, and TNF-α on admission are more likely to experience a severe form of the disease; therefore, those patients should be cautionary monitored and treated.

BEHRTDAY: Dynamic Mortality Risk Prediction using Time-Variant COVID-19 Patient Specific Trajectories.

Incorporating repeated measurements of vitals and laboratory measurements can improve mortality risk-prediction and identify key risk factors in individualized treatment of COVID-19 hospitalized patients. In this observational study, demographic and laboratory data of all admitted patients to 5 hospitals of Mount Sinai Health System, New York, with COVID-19 positive tests between March 1st and June 8th, 2020, were extracted from electronic medical records and compared between survivors and non-survivors. Next day mortality risk of patients was assessed using a transformer-based model BEHRTDAY fitted to patient time series data of vital signs, blood and other laboratory measurements given the entire patients' hospital stay. The study population includes 3699 COVID-19 positive (57% male, median age: 67) patients. This model had a very high average precision score (0.96) and area under receiver operator curve (0.92) for next-day mortality prediction given entire patients' trajectories, and through masking, it learnt each variable's context.

Ivermectin Effect on In-Hospital Mortality and Need for Respiratory Support in COVID-19 Pneumonia: Propensity Score-Matched Retrospective Study.

INTRODUCTION: There is negligible evidence on the efficacy of ivermectin for treating COVID-19 pneumonia. This study aimed to assess the efficacy of ivermectin for pre-emptively treating Strongyloides stercoralis hyperinfection syndrome in order to reduce mortality and the need for respiratory support in patients hospitalized for COVID-19. METHODS: This single-center, observational, retrospective study included patients admitted with COVID-19 pneumonia at Hospital Vega Baja from 23 February 2020 to 14 March 2021. Because strongyloidiasis is endemic to our area, medical criteria support empiric administration of a single, 200 µg/kg dose of ivermectin to prevent Strongyloides hyperinfection syndrome. The outcome was a composite of all-cause in-hospital mortality and the need for respiratory support. RESULTS: Of 1167 patients in the cohort, 96 received ivermectin. After propensity score matching, we included 192 patients. The composite outcome of in-hospital mortality or need for respiratory support occurred in 41.7% of the control group (40/96) and 34.4% (33/96) of the ivermectin group. Ivermectin was not associated with the outcome of interest (adjusted odds ratio [aOR] 0.77, 95% confidence interval [CI] 0.35, 1.69; p = 0.52). The factors independently associated with this endpoint were oxygen saturation (aOR 0.78, 95% CI 0.68, 0.89, p < 0.001) and C-reactive protein at admission (aOR: 1.09, 95% CI 1.03, 1.16, p < 0.001). CONCLUSIONS: In hospitalized patients with COVID-19 pneumonia, ivermectin at a single dose for pre-emptively treating Strongyloides stercoralis is not effective in reducing mortality or the need for respiratory support measures.

Estimates of Bivalent mRNA Vaccine Durability in Preventing COVID-19-Associated Hospitalization and Critical Illness Among Adults with and Without Immunocompromising Conditions - VISION Network, September 2022-April 2023.

On September 1, 2022, CDC's Advisory Committee on Immunization Practices (ACIP) recommended a single bivalent mRNA COVID-19 booster dose for persons aged ≥12 years who had completed at least a monovalent primary series. Early vaccine effectiveness (VE) estimates among adults aged ≥18 years showed receipt of a bivalent booster dose provided additional protection against COVID-19-associated emergency department and urgent care visits and hospitalizations compared with that in persons who had received only monovalent vaccine doses (1); however, insufficient time had elapsed since bivalent vaccine authorization to assess the durability of this protection. The VISION Network* assessed VE against COVID-19-associated hospitalizations by time since bivalent vaccine receipt during September 13, 2022-April 21, 2023, among adults aged ≥18 years with and without immunocompromising conditions. During the first 7-59 days after vaccination, compared with no vaccination, VE for receipt of a bivalent vaccine dose among adults aged ≥18 years was 62% (95% CI = 57%-67%) among adults without immunocompromising conditions and 28% (95% CI = 10%-42%) among adults with immunocompromising conditions. Among adults without immunocompromising conditions, VE declined to 24% (95% CI = 12%-33%) among those aged ≥18 years by 120-179 days after vaccination. VE was generally lower for adults with immunocompromising conditions. A bivalent booster dose provided the highest protection, and protection was sustained through at least 179 days against critical outcomes, including intensive care unit (ICU) admission or in-hospital death. These data support updated recommendations allowing additional optional bivalent COVID-19 vaccine doses for certain high-risk populations. All eligible persons should stay up to date with recommended COVID-19 vaccines.

Has COVID-19 changed the spectrum of arrhythmias and the incidence of sudden cardiac death?

Arrhythmic manifestations of COVID-19 include atrial arrhythmias such as atrial fibrillation or atrial flutter, sinus node dysfunction, atrioventricular conduction abnormalities, ventricular tachyarrhythmias, sudden cardiac arrest, and cardiovascular dysautonomias including the so-called long COVID syndrome. Various pathophysiological mechanisms have been implicated, such as direct viral invasion, hypoxemia, local and systemic inflammation, changes in ion channel physiology, immune activation, and autonomic dysregulation. The development of atrial or ventricular arrhythmias in hospitalized COVID-19 patients has been shown to portend a higher risk of in-hospital death. Management of these arrhythmias should be based on published evidence-based guidelines, with special consideration of the acuity of COVID-19 infection, concomitant use of antimicrobial and anti-inflammatory drugs, and the transient nature of some rhythm disorders. In view of new SARS-CoV­2 variants that may evolve, the development and use of newer antiviral and immunomodulator drugs, and the increasing adoption of vaccination, clinicians must remain vigilant for other arrhythmic manifestations that may occur in association with this novel but potentially deadly disease.

Mortality in patients with COVID-19 versus non-COVID-19- related acute respiratory distress syndrome: A single center retrospective observational cohort study.

The pathophysiology of coronavirus disease-2019 (COVID-19)-related acute respiratory distress syndrome (ARDS) varies from other pneumonia-related ARDS. We evaluated whether the mortality rates differed for COVID-19 and non-COVID-19-related ARDS in the Asian population in 2021. This single center retrospective observational cohort study included patients with COVID-19 and non-COVID-19-related ARDS that required invasive mechanical ventilation. The primary outcome was all-cause in-hospital mortality. The secondary outcomes included hospital length of stay, ICU length of stay, duration of mechanical ventilation, and ventilator-free days (VFDs) during the first 28 days. A 1:1 propensity score matching was performed to correct potential confounders by age, obesity or not, and ARDS severity. One-hundred-and-sixty-four patients fulfilled the inclusion criteria. After 1:1 propensity score matching, there were 50 patients in each group. The all-cause in-hospital mortality of all patients was 38 (38%), and no significant differences were found between COVID-19 and non-COVID-19-related ARDS (17 [34%) vs. 21 [42%], p = 0.410). Both groups had length of stay (30.0 [20.0-46.0] vs. 27.0 [13.0-45.0] days, p = 0.312), ICU length of stay (19.0 [13.0-35.0] vs. 16.0 [10.0-32.0] days, p = 0.249), length of mechanical ventilation (19.0 [10.0-36.0] vs. 14.0 [9.0-29.0] days, p = 0.488), and ventilator-free days during the first 28 days (5.5 [0.0-17.0] vs. 0.0 [0.0-14.0] days, p = 0.320). Immunocompromised status (Hazard ratio: 3.63; 95% CI: 1.51-8.74, p = 0.004) and progress to severe ARDS (Hazard ratio: 2.92; 95% CI: 1.18-7.22, p = 0.020) were significant in-hospital mortality-related confounders. There were no significant difference in mortality among both groups. Immunocompromised status and progression to severe ARDS are two possible risk factors for patients with ARDS; COVID-19 is not a mortality-related risk exposure.

Effect of P2Y12 Inhibitors on Organ Support-Free Survival in Critically Ill Patients Hospitalized for COVID-19: A Randomized Clinical Trial.

Importance: Platelet activation is a potential therapeutic target in patients with COVID-19. Objective: To evaluate the effect of P2Y12 inhibition among critically ill patients hospitalized for COVID-19. Design, Setting, and Participants: This international, open-label, adaptive platform, 1:1 randomized clinical trial included critically ill (requiring intensive care-level support) patients hospitalized with COVID-19. Patients were enrolled between February 26, 2021, through June 22, 2022. Enrollment was discontinued on June 22, 2022, by the trial leadership in coordination with the study sponsor given a marked slowing of the enrollment rate of critically ill patients. Intervention: Participants were randomly assigned to receive a P2Y12 inhibitor or no P2Y12 inhibitor (usual care) for 14 days or until hospital discharge, whichever was sooner. Ticagrelor was the preferred P2Y12 inhibitor. Main Outcomes and Measures: The primary outcome was organ support-free days, evaluated on an ordinal scale that combined in-hospital death and, for participants who survived to hospital discharge, the number of days free of cardiovascular or respiratory organ support up to day 21 of the index hospitalization. The primary safety outcome was major bleeding, as defined by the International Society on Thrombosis and Hemostasis. Results: At the time of trial termination, 949 participants (median [IQR] age, 56 [46-65] years; 603 male [63.5%]) had been randomly assigned, 479 to the P2Y12 inhibitor group and 470 to usual care. In the P2Y12 inhibitor group, ticagrelor was used in 372 participants (78.8%) and clopidogrel in 100 participants (21.2%). The estimated adjusted odds ratio (AOR) for the effect of P2Y12 inhibitor on organ support-free days was 1.07 (95% credible interval, 0.85-1.33). The posterior probability of superiority (defined as an OR > 1.0) was 72.9%. Overall, 354 participants (74.5%) in the P2Y12 inhibitor group and 339 participants (72.4%) in the usual care group survived to hospital discharge (median AOR, 1.15; 95% credible interval, 0.84-1.55; posterior probability of superiority, 80.8%). Major bleeding occurred in 13 participants (2.7%) in the P2Y12 inhibitor group and 13 (2.8%) in the usual care group. The estimated mortality rate at 90 days for the P2Y12 inhibitor group was 25.5% and for the usual care group was 27.0% (adjusted hazard ratio, 0.96; 95% CI, 0.76-1.23; P = .77). Conclusions and Relevance: In this randomized clinical trial of critically ill participants hospitalized for COVID-19, treatment with a P2Y12 inhibitor did not improve the number of days alive and free of cardiovascular or respiratory organ support. The use of the P2Y12 inhibitor did not increase major bleeding compared with usual care. These data do not support routine use of a P2Y12 inhibitor in critically ill patients hospitalized for COVID-19. Trial Registration: ClinicalTrials.gov Identifier: NCT04505774.

Intensivist physician-to-patient ratios and mortality in the intensive care unit.

PURPOSE: A high daily census may hinder the ability of physicians to deliver quality care in the intensive care unit (ICU). We sought to determine the relationship between intensivist-to-patient ratios and mortality among ICU patients. METHODS: We performed a retrospective cohort study of intensivist-to-patient ratios in 29 ICUs in 10 hospitals in the United States from 2018 to 2020. We used meta-data from progress notes in the electronic health record to determine an intensivist-specific caseload for each ICU day. We then fit a multivariable proportional hazards model with time-varying covariates to estimate the relationship between the daily intensivist-to-patient ratio and ICU mortality at 28 days. RESULTS: The final analysis included 51,656 patients, 210,698 patient days, and 248 intensivist physicians. The average caseload per day was 11.8 (standard deviation: 5.7). There was no association between the intensivist-to-patient ratio and mortality (hazard ratio for each additional patient: 0.987, 95% confidence interval: 0.968-1.007, p = 0.2). This relationship persisted when we defined the ratio as caseload over the sample-wide average (hazard ratio: 0.907, 95% confidence interval: 0.763-1.077, p = 0.26) and cumulative days with a caseload over the sample-wide average (hazard ratio: 0.991, 95% confidence interval: 0.966-1.018, p = 0.52). The relationship was not modified by the presence of physicians-in-training, nurse practitioners, and physician assistants (p value for interaction term: 0.14). CONCLUSIONS: Mortality for ICU patients appears resistant to high intensivist caseloads. These results may not generalize to ICUs organized differently than those in this sample, such as ICUs outside the United States.

Emergency Department Visits and Deaths from Cardiovascular Diseases at a Referral Center for Cardiology During the COVID-19 Pandemic

Abstract Background The COVID-19 pandemic has imposed measures of social distancing and, during this time, there has been an elevation in cardiovascular mortality rates and a decrease in the number of emergency visits. Objectives To assess and compare in-hospital mortality for cardiovascular diseases and emergency department visits during the COVID-19 pandemic and the same period in 2019. Methods Retrospective, single-center study that evaluated emergency visits and in-hospital deaths between March 16, 2020 and June 16, 2020, when the steepest fall in the number of emergency admissions for COVID-19 was registered. These data were compared with the emergency visits and in-hospital deaths between March 16 and June 16, 2019. We analyzed the total number of deaths, and cardiovascular deaths. The level of significance was set at p < 0.05. Results There was a 35% decrease in the number of emergency visits and an increase in the ratio of the number of deaths to the number of emergency visits in 2020. The increase in the ratio of the number of all-cause deaths to the number of emergency visits was 45.6% and the increase in the ratio of the number of cardiovascular deaths to the number of emergency visits was 62.1%. None of the patients who died in the study period in 2020 tested positive for COVID-19. Conclusion In-hospital mortality for cardiovascular diseases increased proportionally to the number of emergency visits during the COVID-19-imposed social distancing compared with the same period in 2019. (Int J Cardiovasc Sci. 2020; [online].ahead print, PP.0-0)

Artificial neural network based prediction of the lung tissue involvement as an independent in-hospital mortality and mechanical ventilation risk factor in COVID-19.

INTRODUCTION: During COVID-19 pandemic, artificial neural network (ANN) systems have been providing aid for clinical decisions. However, to achieve optimal results, these models should link multiple clinical data points to simple models. This study aimed to model the in-hospital mortality and mechanical ventilation risk using a two step approach combining clinical variables and ANN-analyzed lung inflammation data. METHODS: A data set of 4317 COVID-19 hospitalized patients, including 266 patients requiring mechanical ventilation, was analyzed. Demographic and clinical data (including the length of hospital stay and mortality) and chest computed tomography (CT) data were collected. Lung involvement was analyzed using a trained ANN. The combined data were then analyzed using unadjusted and multivariate Cox proportional hazards models. RESULTS: Overall in-hospital mortality associated with ANN-assigned percentage of the lung involvement (hazard ratio [HR]: 5.72, 95% confidence interval [CI]: 4.4-7.43, p < 0.001 for the patients with >50% of lung tissue affected by COVID-19 pneumonia), age category (HR: 5.34, 95% CI: 3.32-8.59 for cases >80 years, p < 0.001), procalcitonin (HR: 2.1, 95% CI: 1.59-2.76, p < 0.001, C-reactive protein level (CRP) (HR: 2.11, 95% CI: 1.25-3.56, p = 0.004), glomerular filtration rate (eGFR) (HR: 1.82, 95% CI: 1.37-2.42, p < 0.001) and troponin (HR: 2.14, 95% CI: 1.69-2.72, p < 0.001). Furthermore, the risk of mechanical ventilation is also associated with ANN-based percentage of lung inflammation (HR: 13.2, 95% CI: 8.65-20.4, p < 0.001 for patients with >50% involvement), age, procalcitonin (HR: 1.91, 95% CI: 1.14-3.2, p = 0.14, eGFR (HR: 1.82, 95% CI: 1.2-2.74, p = 0.004) and clinical variables, including diabetes (HR: 2.5, 95% CI: 1.91-3.27, p < 0.001), cardiovascular and cerebrovascular disease (HR: 3.16, 95% CI: 2.38-4.2, p < 0.001) and chronic pulmonary disease (HR: 2.31, 95% CI: 1.44-3.7, p < 0.001). CONCLUSIONS: ANN-based lung tissue involvement is the strongest predictor of unfavorable outcomes in COVID-19 and represents a valuable support tool for clinical decisions.

Diabetes as a risk factor of death in hospitalized COVID-19 patients - an analysis of a National Hospitalization Database from Poland, 2020.

Introduction: Diabetes is one of the comorbidities associated with poor prognosis in hospitalized COVID-19 patients. In this nationwide retrospective study, we evaluated the risk of in-hospital death attributed to diabetes. Methods: We analyzed data from discharge reports of patients hospitalized with COVID-19 in 2020 as submitted to the Polish National Health Fund. Several multivariate logistic regression models were used. In each model, in-hospital death was estimated with explanatory variables. Models were built either on the whole cohorts or cohorts matched with propensity score matching (PSM). The models examined either the main effects of diabetes itself or the interaction of diabetes with other variables. Results: We included 174,621 patients with COVID-19 who were hospitalized in the year 2020. Among them, there were 40,168 diabetic patients (DPs), and the proportion of DPs in this group was higher than in the general population (23.0% vs. 9.5%, p<0.001). In this group of COVID-19 hospitalizations, 17,438 in-hospital deaths were recorded, and the mortality was higher among DPs than non-diabetics (16.3% vs. 8.1%, p<0.001). Multivariate logistic regressions showed that diabetes was a risk factor of death, regardless of sex and age. In the main effect analysis, odds of in-hospital death were higher by 28.3% for DPs than for non-diabetic patients. Similarly, PSM analysis including 101,578 patients, of whom 19,050 had diabetes, showed that the risk of death was higher in DPs regardless of sex with odds higher by 34.9%. The impact of diabetes differed among age groups and was the highest for patients aged 60-69. Conclusions: This nationwide study confirmed that diabetes was an independent risk factor of in-hospital death in the course of COVID-19 infection. However, the relative risk differed across the age groups.

Risk factors associated with acute kidney injury in a cohort of hospitalized patients with COVID-19.

BACKGROUND: Patients with COVID-19 have a high incidence of acute kidney injury (AKI), which is associated with mortality. The objective of the study was to determine the factors associated with AKI in patients with COVID-19. METHODOLOGY: A retrospective cohort was established in two university hospitals in Bogotá, Colombia. Adults hospitalized for more than 48 h from March 6, 2020, to March 31, 2021, with confirmed COVID-19 were included. The main outcome was to determine the factors associated with AKI in patients with COVID-19 and the secondary outcome was estimate the incidence of AKI during the 28 days following hospital admission. RESULTS: A total of 1584 patients were included: 60.4% were men, 738 (46.5%) developed AKI, 23.6% were classified as KDIGO 3, and 11.1% had renal replacement therapy. The risk factors for developing AKI during hospitalization were male sex (OR 2.28, 95% CI 1.73-2.99), age (OR 1.02, 95% CI 1.01-1.03), history of chronic kidney disease (CKD) (OR 3.61, 95% CI 2.03-6.42), High Blood Pressure (HBP) (OR 6.51, 95% CI 2.10-20.2), higher qSOFA score to the admission (OR 1.4, 95% CI 1.14-1.71), the use of vancomycin (OR 1.57, 95% CI 1.05-2.37), piperacillin/tazobactam (OR 1.67, 95% CI 1.2-2.31), and vasopressor support (CI 2.39, 95% CI 1.53-3.74). The gross hospital mortality for AKI was 45.5% versus 11.7% without AKI. CONCLUSIONS: This cohort showed that male sex, age, history of HBP and CKD, presentation with elevated qSOFA, in-hospital use of nephrotoxic drugs and the requirement for vasopressor support were the main risk factors for developing AKI in patients hospitalized for COVID-19.

Clinical predictors of Covid-19 mortality in a tertiary hospital in Lagos, Nigeria: A retrospective cohort study.

Background: The predictors of mortality among patients presenting with severe to critical disease in Nigeria are presently unknown. Aim: The aim of this study was to identify the predictors of mortality among patients with COVID-19 presenting for admission in a tertiary referral hospital in Lagos, Nigeria. Patients and Methods: The study was a retrospective study. Patients' sociodemographics, clinical characteristics, comorbidities, complications, treatment outcomes, and hospital duration were documented. Pearson's Chi-square, Fischer's Exact test, or Student's t-test were used to assess the relationship between the variables and mortality. To compare the survival experience across medical comorbidities, Kaplan Meir plots and life tables were used. Univariable and multivariable Cox-proportional hazard analyses were conducted. Results: A total of 734 patients were recruited. Participants' age ranged from five months to 92 years, with a mean ± SD of 47.4 ± 17.2 years, and a male preponderance (58.5% vs. 41.5%). The mortality rate was 9.07 per thousand person-days. About 73.9% (n = 51/69) of the deceased had one or more co-morbidities, compared to 41.6% (252/606) of those discharged. Patients who were older than 50 years, with diabetes mellitus, hypertension, chronic renal illness, and cancer had a statistically significant relationship with mortality. Conclusion: These findings call for a more comprehensive approach to the control of non-communicable diseases, the allocation of sufficient resources for ICU care during outbreaks, an improvement in the quality of health care available to Nigerians, and further research into the relationship between obesity and COVID-19 in Nigerians.

Evaluation of an Emergency Department-based Palliative Care Extender Program on Hospital and Patient Outcomes.

BACKGROUND: Boston Medical Center (BMC), a safety-net hospital, treated a substantial portion of the Boston cohort that was sick with COVID-19. Unfortunately, these patients experienced high rates of morbidity and mortality given the significant health disparities that many of BMC's patients face. Boston Medical Center launched a palliative care extender program to help address the needs of critically ill ED patients under crisis conditions. In this program evaluation our goal was to assess outcomes between those who received palliative care in the emergency department (ED) vs those who received palliative care as an inpatient or were admitted to an intensive care unit (ICU). METHODS: We used a matched retrospective cohort study design to assess the difference in outcomes between the two groups. RESULTS: A total of 82 patients received palliative care services in the ED, and 317 patients received palliative care services as an inpatient. After controlling for demographics, patients who received palliative care services in the ED were less likely to have a change in level of care (P<0.001) or be admitted to an ICU (P<0.001). Cases had an average length of stay of 5.2 days compared to controls who stayed 9.9 days (P<0.001). CONCLUSION: Within a busy ED environment, initiating palliative care discussions by ED staff can be challenging. This study demonstrates that consulting palliative care specialists early in the course of the patient's ED stay can benefit patients and families and improve resource utilization.

Artificial intelligence guided HRCT assessment predicts the severity of COVID-19 pneumonia based on clinical parameters.

BACKGROUND: The purpose of the study was to compare the results of AI (artificial intelligence) analysis of the extent of pulmonary lesions on HRCT (high resolution computed tomography) images in COVID-19 pneumonia, with clinical data including laboratory markers of inflammation, to verify whether AI HRCT assessment can predict the clinical severity of COVID-19 pneumonia. METHODS: The analyzed group consisted of 388 patients with COVID-19 pneumonia, with automatically analyzed HRCT parameters of volume: AIV (absolute inflammation), AGV (absolute ground glass), ACV (absolute consolidation), PIV (percentage inflammation), PGV (percentage ground glass), PCV (percentage consolidation). Clinical data included: age, sex, admission parameters: respiratory rate, oxygen saturation, CRP (C-reactive protein), IL6 (interleukin 6), IG - immature granulocytes, WBC (white blood count), neutrophil count, lymphocyte count, serum ferritin, LDH (lactate dehydrogenase), NIH (National Institute of Health) severity score; parameters of clinical course: in-hospital death, transfer to the ICU (intensive care unit), length of hospital stay. RESULTS: The highest correlation coefficients were found for PGV, PIV, with LDH (respectively 0.65, 0.64); PIV, PGV, with oxygen saturation (respectively - 0.53, -0.52); AIV, AGV, with CRP (respectively 0.48, 0.46); AGV, AIV, with ferritin (respectively 0.46, 0.45). Patients with critical pneumonia had significantly lower oxygen saturation, and higher levels of immune-inflammatory biomarkers on admission. The radiological parameters of lung involvement proved to be strong predictors of transfer to the ICU (in particular, PGV ≥ cut-off point 29% with Odds Ratio (OR): 7.53) and in-hospital death (in particular: AIV ≥ cut-off point 831 cm3 with OR: 4.31). CONCLUSIONS: Automatic analysis of HRCT images by AI may be a valuable method for predicting the severity of COVID-19 pneumonia. The radiological parameters of lung involvement correlate with laboratory markers of inflammation, and are strong predictors of transfer to the ICU and in-hospital death from COVID-19. TRIAL REGISTRATION: National Center for Research and Development CRACoV-HHS project, contract number SZPITALE-JEDNOIMIENNE/18/2020.

Factors associated with mortality in patients hospitalized for COVID-19 admitted to a tertiary hospital in Lambayeque, Peru, during the first wave of the pandemic.

INTRODUCTION: COVID-19 caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread worldwide, becoming a long-term pandemic. OBJECTIVES: To analyze the factors associated with mortality in patients hospitalized for COVID-19 in a tertiary hospital in the Lambayeque region of Peru. METHODS: A retrospective cohort study of patients with a diagnosis of COVID-19, hospitalized in a hospital in northern Peru, was conducted from March to September 2020. RESULTS: Of the 297 patients studied, 69% were women, the mean age was 63.99 years (SD = ±15.33 years). Hypertension was the most frequent comorbidity (36.67%), followed by diabetes mellitus (24.67%) and obesity (8.33%). The probability of survival at 3 days of ICU stay was 65.3%, at 7 days 24.2%, and 0% on day 14. Risk factors associated with mortality in patients hospitalized for COVID-19 are age, male sex, tachypnea, low systolic blood pressure, low peripheral oxygen saturation, impaired renal function, elevated IL-6 and elevated D-dimer. CONCLUSIONS: Mortality in hospitalized patients with COVID-19 was 51.18 per 100 persons, Mortality was found to be associated with hypertension, type of infiltrating, and sepsis.