COVID-19 in kidney transplant recipients.

There is minimal information on coronavirus disease 2019 (COVID-19) in immunocompromised individuals. We have studied 10 patients treated at 12 adult care hospitals. Ten kidney transplant recipients tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by polymerase chain reaction, and 9 were admitted. The median age was 57 (interquartile range [IQR] 47-67), 60% were male, 40% Caucasian, and 30% Black/African American. Median time from transplant to COVID-19 testing was 2822 days (IQR 1272-4592). The most common symptom was fever, followed by cough, myalgia, chills, and fatigue. The most common chest X-ray and computed tomography abnormality was multifocal patchy opacities. Three patients had no abnormal findings. Leukopenia was seen in 20% of patients, and allograft function was stable in 50% of patients. Nine patients were on tacrolimus and a mycophenolic antimetabolite, and 70% were on prednisone. Hospitalized patients had their antimetabolite agent stopped. All hospitalized patients received hydroxychloroquine and azithromycin. Three patients died (30%), and 5 (50%) developed acute kidney injury. Kidney transplant recipients infected with COVID-19 should be monitored closely in the setting of lowered immunosuppression. Most individuals required hospitalization and presenting symptoms were similar to those of nontransplant individuals.

Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients.

Clinical prognostic models can assist patient care decisions. However, their performance can drift over time and location, necessitating model monitoring and updating. Despite rapid and significant changes during the pandemic, prognostic models for COVID-19 patients do not currently account for these drifts. We develop a framework for continuously monitoring and updating prognostic models and apply it to predict 28-day survival in COVID-19 patients. We use demographic, laboratory, and clinical data from electronic health records of 34912 hospitalized COVID-19 patients from March 2020 until May 2022 and compare three modeling methods. Model calibration performance drift is immediately detected with minor fluctuations in discrimination. The overall calibration on the prospective validation cohort is significantly improved when comparing the dynamically updated models against their static counterparts. Our findings suggest that, using this framework, models remain accurate and well-calibrated across various waves, variants, race and sex and yield positive net-benefits.

Mortality of Mechanically Ventilated COVID-19 Patients in Traditional versus Expanded Intensive Care Units in New York.

Rationale: During the first wave of the coronavirus disease (COVID-19) pandemic in New York City, the number of mechanically ventilated COVID-19 patients rapidly surpassed the capacity of traditional intensive care units (ICUs), resulting in health systems utilizing other areas as expanded ICUs to provide critical care. Objectives: To evaluate the mortality of patients admitted to expanded ICUs compared with those admitted to traditional ICUs. Methods: Multicenter, retrospective, cohort study of mechanically ventilated patients with COVID-19 admitted to the ICUs at 11 Northwell Health hospitals in the greater New York City area between March 1, 2020 and April 30, 2020. Primary outcome was in-hospital mortality up to 28 days after intubation of COVID-19 patients. Results: Among 1,966 mechanically ventilated patients with COVID-19, 1,198 (61%) died within 28 days after intubation, 46 (2%) were transferred to other hospitals outside of the Northwell Health system, 722 (37%) survived in the hospital until 28 days or were discharged after recovery. The risk of mortality of mechanically ventilated patients admitted to expanded ICUs was not different from those admitted to traditional ICUs (hazard ratio [HR], 1.07; 95% confidence interval [CI], 0.95-1.20; P = 0.28), while hospital occupancy for critically ill patients itself was associated with increased risk of mortality (HR, 1.28; 95% CI, 1.12-1.45; P < 0.001). Conclusions: Although increased hospital occupancy for critically ill patients itself was associated with increased mortality, the risk of 28-day in-hospital mortality of mechanically ventilated patients with COVID-19 who were admitted to expanded ICUs was not different from those admitted to traditional ICUs.

Association of race/ethnicity with mortality in patients hospitalized with COVID-19.

OBJECTIVE: To evaluate racial and ethnic differences in mortality among patients hospitalized with coronavirus disease 2019 (COVID-19) after adjusting for baseline characteristics and comorbidities. METHODS: This retrospective cohort study at 13 acute care facilities in the New York City metropolitan area included sequentially hospitalized patients between March 1, 2020, and April 27, 2020. Last day of follow up was July 31, 2020. Patient demographic information, including race/ethnicity and comorbidities, were collected. The primary outcome was in-hospital mortality. RESULTS: A total of 10 869 patients were included in the study (median age, 65 years [interquartile range (IQR) 54-77; range, 18-107 years]; 40.5% female). In adjusted time-to-event analysis, increased age, male sex, insurance type (Medicare and Self-Pay), unknown smoking status, and a higher score on the Charlson Comorbidity Index were significantly associated with higher in-hospital mortality. Adjusted risk of hospital mortality for Black, Asian, Hispanic, multiracial/other, and unknown race/ethnicity patients were similar to risk for White patients. CONCLUSIONS: In a large diverse cohort of patients hospitalized with COVID-19, patients from racial/ethnic minorities experienced similar mortality risk as White patients.

A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation.

BACKGROUND: Predicting early respiratory failure due to COVID-19 can help triage patients to higher levels of care, allocate scarce resources, and reduce morbidity and mortality by appropriately monitoring and treating the patients at greatest risk for deterioration. Given the complexity of COVID-19, machine learning approaches may support clinical decision making for patients with this disease. OBJECTIVE: Our objective is to derive a machine learning model that predicts respiratory failure within 48 hours of admission based on data from the emergency department. METHODS: Data were collected from patients with COVID-19 who were admitted to Northwell Health acute care hospitals and were discharged, died, or spent a minimum of 48 hours in the hospital between March 1 and May 11, 2020. Of 11,525 patients, 933 (8.1%) were placed on invasive mechanical ventilation within 48 hours of admission. Variables used by the models included clinical and laboratory data commonly collected in the emergency department. We trained and validated three predictive models (two based on XGBoost and one that used logistic regression) using cross-hospital validation. We compared model performance among all three models as well as an established early warning score (Modified Early Warning Score) using receiver operating characteristic curves, precision-recall curves, and other metrics. RESULTS: The XGBoost model had the highest mean accuracy (0.919; area under the curve=0.77), outperforming the other two models as well as the Modified Early Warning Score. Important predictor variables included the type of oxygen delivery used in the emergency department, patient age, Emergency Severity Index level, respiratory rate, serum lactate, and demographic characteristics. CONCLUSIONS: The XGBoost model had high predictive accuracy, outperforming other early warning scores. The clinical plausibility and predictive ability of XGBoost suggest that the model could be used to predict 48-hour respiratory failure in admitted patients with COVID-19.

Acute Kidney Injury and Advanced Kidney Disease in the COVID-19 Pandemic: Proceedings From a National Kidney Foundation Symposium.

The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented and historic public health crisis that continues to expand and evolve. The National Kidney Foundation held a 2-part continuing medical education live virtual symposium on July 16 and July 24, 2020, to address the multiple challenges of COVID-19 in the context of advanced chronic kidney disease. Faculty addressed the pathophysiology, impact, risks, and management of COVID-19 as it relates to advanced kidney disease. Testing, risk mitigation, and inpatient and outpatient management were also addressed. This concise review addresses major findings of the symposium along with certain updates regarding vaccinations since then. These findings include: (1) severe COVID-19 infection has been associated with acute kidney injury, (2) it is essential to prevent and actively manage acute kidney injury to decrease mortality in these critically ill patients, (3) management of patients with advanced kidney disease should be geared toward minimizing their risk for exposure while making sure they are receiving adequate treatments, and (4) patients with kidney disease, especially ones in advanced stages, should be prioritized for vaccination.

External validation of the IMPROVE-DD risk assessment model for venous thromboembolism among inpatients with COVID-19.

There is a need to discriminate which COVID-19 inpatients are at higher risk for venous thromboembolism (VTE) to inform prophylaxis strategies. The IMPROVE-DD VTE risk assessment model (RAM) has previously demonstrated good discrimination in non-COVID populations. We aimed to externally validate the IMPROVE-DD VTE RAM in medical patients hospitalized with COVID-19. This retrospective cohort study evaluated the IMPROVE-DD VTE RAM in adult patients with COVID-19 admitted to one of thirteen Northwell Health hospitals in the New York metropolitan area between March 1, 2020 and April 27, 2020. VTE was defined as new-onset symptomatic deep venous thrombosis or pulmonary embolism. To assess the predictive value of the RAM, the receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Of 9407 patients who met study criteria, 274 patients developed VTE with a prevalence of 2.91%. The VTE rate was 0.41% for IMPROVE-DD score 0-1 (low risk), 1.21% for score 2-3 (moderate risk), and 5.30% for score ≥ 4 (high risk). Approximately 45.7% of patients were classified as high VTE risk, 33.3% moderate risk, and 21.0% low risk. Discrimination of low versus moderate-high VTE risk demonstrated sensitivity 0.971, specificity 0.215, PPV 0.036, and NPV 0.996. ROC AUC was 0.703. In this external validation study, the IMPROVE-DD VTE RAM demonstrated very good discrimination to identify hospitalized COVID-19 patients at low, moderate, and high VTE risk.

Intubated COVID-19 predictive (ICOP) score for early mortality after intubation in patients with COVID-19.

Patients with coronavirus disease 2019 (COVID-19) can have increased risk of mortality shortly after intubation. The aim of this study is to develop a model using predictors of early mortality after intubation from COVID-19. A retrospective study of 1945 intubated patients with COVID-19 admitted to 12 Northwell hospitals in the greater New York City area was performed. Logistic regression model using backward selection was applied. This study evaluated predictors of 14-day mortality after intubation for COVID-19 patients. The predictors of mortality within 14 days after intubation included older age, history of chronic kidney disease, lower mean arterial pressure or increased dose of required vasopressors, higher urea nitrogen level, higher ferritin, higher oxygen index, and abnormal pH levels. We developed and externally validated an intubated COVID-19 predictive score (ICOP). The area under the receiver operating characteristic curve was 0.75 (95% CI 0.73-0.78) in the derivation cohort and 0.71 (95% CI 0.67-0.75) in the validation cohort; both were significantly greater than corresponding values for sequential organ failure assessment (SOFA) or CURB-65 scores. The externally validated predictive score may help clinicians estimate early mortality risk after intubation and provide guidance for deciding the most effective patient therapies.

In-Hospital 30-Day Survival Among Young Adults With Coronavirus Disease 2019: A Cohort Study.

BACKGROUND: Our objective was to characterize young adult patients hospitalized with coronavirus disease 2019 (COVID-19) and identify predictors of survival at 30 days. METHODS: This retrospective cohort study took place at 12 acute care hospitals in the New York City area. Patients aged 18-39 hospitalized with confirmed COVID-19 between March 1 and April 27, 2020 were included in the study. Demographic, clinical, and outcome data were extracted from electronic health record reports. RESULTS: A total of 1013 patients were included in the study (median age, 33 years; interquartile range [IQR], 28-36; 52% female). At the study end point, 940 (92.8%) patients were discharged alive, 18 (1.8%) remained hospitalized, 5 (0.5%) were transferred to another acute care facility, and 50 (4.9%) died. The most common comorbidities in hospitalized young adult patients were obesity (51.2%), diabetes mellitus (14.8%), and hypertension (13%). Multivariable analysis revealed that obesity (adjusted hazard ratio [aHR], 2.71; 95% confidence interval [CI], 1.28-5.73; P = .002) and Charlson comorbidity index score (aHR, 1.20; 95% CI, 1.07-1.35; P = .002) were independent predictors of in-hospital 30-day mortality. CONCLUSIONS: Obesity was identified as the strongest negative predictor of 30-day in-hospital survival in young adults with COVID-19.

Asthma and COVID-19: An early inpatient and outpatient experience at a US children's hospital.

BACKGROUND: Initially, persistent asthma was deemed a risk factor for severe COVID-19 disease. However, data suggests that asthmatics do not have an increased risk of COVID-19 infection or disease. There is a paucity of data describing pediatric asthmatics with COVID-19. OBJECTIVE: The objectives of this study were to determine the prevalence of asthma among hospitalized children with acute symptomatic COVID-19, compare demographic and clinical outcomes between asthmatics and nonasthmatics, and characterize behaviors of our outpatient pediatric population. METHODS: We conducted a single-center retrospective study of pediatric patients admitted to the Cohen Children's Medical Center at Northwell Health with symptomatic COVID-19 within 4 months of the surge beginning in March 2020 and a retrospective analysis of pediatric asthma outpatients seen in the previous 6 months. Baseline demographic variables and clinical outcomes for inpatients, and medication compliance, health behaviors, and asthma control for outpatients were collected. RESULTS: Thirty-eight inpatients and 95 outpatients were included. The inpatient prevalence of asthma was 34.2%. Asthmatics were less likely to have abnormal chest x-rays (CXRs), require oxygen support, and be treated with remdesivir. Among outpatients, 41% reported improved asthma control and decreased rescue medication use, with no COVID-19 hospitalizations, despite six suspected infections. CONCLUSIONS: Among children hospitalized for acute symptomatic COVID-19 at our institution, 34.2% had a diagnosis of asthma. Asthmatics did not have a more severe course and required a lower level of care. Outpatients had improved medication compliance and control and a low risk of hospitalization. Biological and behavioral factors may have mitigated against severe disease.

Sex-Based Differences in COVID-19 Outcomes.

Background: Smaller studies suggest lower morbidity and mortality associated with coronavirus disease 2019 (COVID-19) in women. Our aim is to assess the impact of female sex on outcomes in a large cohort of patients hospitalized with COVID-19. Materials and Methods: This is a retrospective observational cohort study of 10,630 adult patients hospitalized with a confirmed COVID-19 polymerase chain reaction between March 1, 2020 and April 27, 2020, with follow-up conducted through June 4, 2020. Logistic regression was used to examine the relationship between sex and the primary outcomes, including length of stay, admission to intensive care unit (ICU), need for mechanical ventilation, pressor requirement, and all-cause mortality as well as major adverse events and in-hospital COVID-19 treatments. Results: In the multivariable analysis, women had 27% lower odds of in-hospital mortality (odds ratio [OR] = 0.73, 95% confidence interval [CI] 0.66-0.81; p < 0.001), 24% lower odds of ICU admission (OR = 0.76, 95% CI 0.69-0.84; p < 0.001), 26% lower odds of mechanical ventilation (OR = 0.74, 95% CI 0.66-0.82; p < 0.001), and 25% lower odds of vasopressor requirement (OR = 0.75, 95% CI 0.67-0.84; p < 0.001). Women had 34% less odds of having acute cardiac injury (OR = 0.66, 95% CI 0.59-0.74; p < 0.001; n = 7,289), 16% less odds of acute kidney injury (OR = 0.84, 95% CI 0.76-0.92; p < 0.001; n = 9,840), and 27% less odds of venous thromboembolism (OR = 0.73, 95% CI 0.56-0.96; p < 0.02; c-statistic 0.85, n = 9,407). Conclusions: Female sex is associated with lower odds of in-hospital outcomes, major adverse events, and all-cause mortality. There may be protective mechanisms inherent to female sex, which explain differences in COVID-19 outcomes.

Risk factors and outcomes for acute-on-chronic liver failure in COVID-19: a large multi-center observational cohort study.

OBJECTIVE: Coronavirus disease 2019 [COVID-19] infection in patients with chronic liver disease [CLD] may precipitate acute-on-chronic liver failure [ACLF]. In a large multi-center cohort of COVID-19-infected patients, we aim to analyze (1) the outcomes of patients with underlying CLD [with and without cirrhosis] and (2) the development and impact of ACLF on in-hospital mortality. DESIGN: We identified 192 adults with CLD from among 10,859 patients with confirmed COVID-19 infection (admitted to any of 12 hospitals in a New York health care system between March 1, 2020 and April 27, 2020). ACLF was defined using the EASL-CLIF Consortium definition. Patient follow-up was through April 30, 2020, or until the date of discharge, transfer, or death. RESULTS: Of the 84 patients with cirrhosis, 32 [38%] developed ACLF, with respiratory failure [39%] and renal failure [26%] being the most common. Hispanic/Latino ethnicity was particularly at higher risk of in-hospital mortality [adjusted HR 4.92, 95% 1.27-19.09, p < 0.02] in cirrhosis despite having lower risk of development of ACLF [HR 0.26, 95% CI 0.08-0.89, p = 0.03]. Hypertension on admission predicted development of ACLF [HR 3.46, 95% CI 1.12-10.75, p = 0.03]. In-hospital mortality was not different between CLD patients with or without cirrhosis [p = 0.24] but was higher in those with cirrhosis who developed ACLF [adjusted HR 9.06, 95% CI 2.63-31.12, p < 0.001] with a trend for increased mortality by grade of ACLF [p = 0.002]. There was no difference in in-hospital mortality between the CLD cohort compared to matched control without CLD (log rank, p = 0.98) and between the cirrhosis cohort compared to matched control without cirrhosis (log rank, p = 0.51). CONCLUSION: Development of ACLF is the main driver of increased in-hospital mortality in hospitalized patients with COVID-19 infection and cirrhosis.

Incidence of Venous Thromboembolism and Mortality in Patients with Initial Presentation of COVID-19.

Venous thromboembolism (VTE) has emerged as an important issue in patients with COVID-19. The purpose of this study is to identify the incidence of VTE and mortality in COVID-19 patients initially presenting to a large health system. Our retrospective study included adult patients (excluding patients presenting with obstetric/gynecologic conditions) across a multihospital health system in the New York Metropolitan Region from March 1-April 27, 2020. VTE and mortality rates within 8 h of assessment were described. In 10,871 adults with COVID-19, 118 patients (1.09%) were diagnosed with symptomatic VTE (101 pulmonary embolism, 17 deep vein thrombosis events) and 28 patients (0.26%) died during initial assessment. Among these 146 patients, 64.4% were males, 56.8% were 60 years or older, 15.1% had a BMI > 35, and 11.6% were admitted to the intensive care unit. Comorbidities included hypertension (46.6%), diabetes (24.7%), hyperlipidemia (14.4%), chronic lung disease (12.3%), coronary artery disease (11.0%), and prior VTE (7.5%). Key medications included corticosteroids (22.6%), statins (21.2%), antiplatelets (20.6%), and anticoagulants (20.6%). Highest D-Dimer was greater than six times the upper limit of normal in 51.4%. Statin and antiplatelet use were associated with decreased VTE or mortality (each p < 0.01). In COVID-19 patients who initially presented to a large multihospital health system, the overall symptomatic VTE and mortality rate was over 1.0%. Statin and antiplatelet use were associated with decreased VTE or mortality. The potential benefits of antithrombotics in high risk COVID-19 patients during the pre-hospitalization period deserves study.

Validation of the IMPROVE-DD risk assessment model for venous thromboembolism among hospitalized patients with COVID-19.

BACKGROUND: Antithrombotic guidance statements for hospitalized patients with coronavirus disease 2019 (COVID-19) suggest a universal thromboprophylactic strategy with potential to escalate doses in high-risk patients. To date, no clear approach exists to discriminate patients at high risk for venous thromboembolism (VTE). OBJECTIVES: The objective of this study is to externally validate the IMPROVE-DD risk assessment model (RAM) for VTE in a large cohort of hospitalized patients with COVID-19 within a multihospital health system. METHODS: This retrospective cohort study evaluated the IMPROVE-DD RAM on adult inpatients with COVID-19 hospitalized between March 1, 2020, and April 27, 2020. Diagnosis of VTE was defined by new acute deep venous thrombosis or pulmonary embolism by Radiology Department imaging or point-of-care ultrasound. The receiver operating characteristic (ROC) curve was plotted and area under the curve (AUC) calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using standard methods. RESULTS: A total of 9407 patients were included, with a VTE prevalence of 2.9%. The VTE rate was 0.4% for IMPROVE-DD score 0-1 (low risk), 1.3% for score 2-3 (moderate risk), and 5.3% for score ≥ 4 (high risk). Approximately 45% of the total population scored high VTE risk, while 21% scored low VTE risk. IMPROVE-DD discrimination of low versus medium/high risk showed sensitivity of 0.971, specificity of 0.218, PPV of 0.036, and NPV of 0.996. ROC AUC was 0.702. CONCLUSIONS: The IMPROVE-DD VTE RAM demonstrated very good discrimination to identify hospitalized patients with COVID-19 as low, moderate, and high VTE risk in this large external validation study with potential to individualize thromboprophylactic strategies.

Severity of liver test abnormalities in coronavirus disease 2019 depends on comorbidities and predicts early in-hospital mortality.

BACKGROUND AND AIMS: Liver chemistry abnormalities (LCA) are common in patients with coronavirus disease 2019 (COVID-19), but their causes and clinical impact have not been adequately studied. We assessed the associations between LCA and clinical characteristics, inflammatory serum markers, in-hospital mortality. METHODS: Ten thousand eight hundred fifty-six adult patients with COVID-19 hospitalized in 13 hospitals in New York (1 March to 27 April 2020) were analyzed retrospectively. Abnormalities of liver chemistries [aspartate aminotransferase (AST), alanine aminotransferase, alkaline phosphatase, or total bilirubin] were defined as absent, mild-moderate (at least one value up to four times elevated), or severe. RESULTS: LCA were mild-moderate in 63.9% and severe in 7.6% at admission. Risk factors for severe LCA were male sex and chronic liver disease. Conversely, hypertension and diabetes mellitus were less likely associated with severe LCA. AST elevation correlated weakly to modestly with inflammatory markers. On adjusted analysis, in-hospital mortality was 1.56 times and 1.87 times increased in patients with mild-to-moderate and severe LCA, respectively. Diabetes, hypertension, male sex, and age greater than 60 years was associated with incremental risk of mortality with increase severity of LCA, especially in the first week of hospitalization. HTN was not associated with increased in-hospital mortality unless LCA was present. CONCLUSION: Increasing severity of LCA on hospital admission predicts early in-hospital mortality in COVID-19 patients. Mortality associated with the known risk factors, hypertension, diabetes, male sex, and old age was accentuated in the presence of LCA. AST correlated modestly with inflammatory markers.