Trends in COVID-19 Risk-Adjusted Mortality Rates.

Early reports showed high mortality from coronavirus disease 2019 (COVID-19). Mortality rates have recently been lower, raising hope that treatments have improved. However, patients are also now younger, with fewer comorbidities. We explored whether hospital mortality was associated with changing demographics at a 3-hospital academic health system in New York. We examined in-hospital mortality or discharge to hospice from March through August 2020, adjusted for demographic and clinical factors, including comorbidities, admission vital signs, and laboratory results. Among 5,121 hospitalizations, adjusted mortality dropped from 25.6% (95% CI, 23.2-28.1) in March to 7.6% (95% CI, 2.5-17.8) in August. The standardized mortality ratio dropped from 1.26 (95% CI, 1.15-1.39) in March to 0.38 (95% CI, 0.12-0.88) in August, at which time the average probability of death (average marginal effect) was 18.2 percentage points lower than in March. Data from one health system suggest that mortality from COVID-19 is decreasing even after accounting for patient characteristics.

Unravelling the broader complexity of IL-6 involvement in health and disease.

The classification of interleukin-6 (IL-6) as a pro-inflammatory cytokine undervalues the biological impact of this cytokine in health and disease. With broad activities affecting the immune system, tissue homeostasis and metabolic processes, IL-6 displays complex biology. The significance of these involvements has become increasingly important in clinical settings where IL-6 is identified as a prominent target for therapy. Here, clinical experience with IL-6 antagonists emphasises the need to understand the context-dependent properties of IL-6 within an inflammatory environment and the anticipated or unexpected consequences of IL-6 blockade. In this review, we will describe the immunobiology of IL-6 and explore the gamut of IL-6 bioactivity affecting the clinical response to biological drugs targeting this cytokine pathway.

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial.

BACKGROUND: We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown. OBJECTIVES: The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS). METHODS: We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention and control arms using a patient identifier passed to the model execution code. Intervention effect was assessed by comparing LOS between intervention and control groups. Adverse safety outcomes of death, hospice, and re-presentation were tested separately and as a composite indicator. We tracked adoption and sustained use through daily counts of score displays. RESULTS: Enrolling 1,010 patients from May 15, 2020 to December 7, 2020, the trial found no detectable difference in LOS. The intervention had no impact on safety indicators of death, hospice or re-presentation after discharge. The scores were displayed consistently throughout the study period but the study lacks a causally linked process measure of provider actions based on the score. Secondary analysis revealed complex dynamics in LOS temporally, by primary symptom, and hospital location. CONCLUSION: An AI-based COVID-19 risk score displayed passively to clinicians during routine care of hospitalized adults with COVID-19 was safe but had no detectable impact on LOS. Health technology challenges such as insufficient adoption, nonuniform use, and provider trust compounded with temporal factors of the COVID-19 pandemic may have contributed to the null result. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04570488.

Outcomes of Breast Cancer Patients Treated with Chemotherapy, Biologic Therapy, Endocrine Therapy, or Active Surveillance During the COVID-19 Pandemic.

PURPOSE: Provide real-world data regarding the risk for SARS-CoV-2 infection and mortality in breast cancer (BC) patients on active cancer treatment. METHODS: Clinical data were abstracted from the 3778 BC patients seen at a multisite cancer center in New York between February 1, 2020 and May 1, 2020, including patient demographics, tumor histology, cancer treatment, and SARS-CoV-2 testing results. Incidence of SARS-CoV-2 infection by treatment type (chemotherapy [CT] vs endocrine and/or HER2 directed therapy [E/H]) was compared by Inverse Probability of Treatment Weighting. In those diagnosed with SARS-CoV-2 infection, Mann-Whitney test was used to a assess risk factors for severe disease and mortality. RESULTS: Three thousand sixty-two patients met study inclusion criteria with 641 patients tested for SARS-COV-2 by RT-PCR or serology. Overall, 64 patients (2.1%) were diagnosed with SARS-CoV-2 infection by either serology, RT-PCR, or documented clinical diagnosis. Comparing matched patients who received chemotherapy (n = 379) with those who received non-cytotoxic therapies (n = 2343) the incidence of SARS-CoV-2 did not differ between treatment groups (weighted risk; 3.5% CT vs 2.7% E/H, P = .523). Twenty-seven patients (0.9%) expired over follow-up, with 10 deaths attributed to SARS-CoV-2 infection. Chemotherapy was not associated with increased risk for death following SARS-CoV-2 infection (weighted risk; 0.7% CT vs 0.1% E/H, P = .246). Advanced disease (stage IV), age, BMI, and Charlson's Comorbidity Index score were associated with increased mortality following SARS-CoV-2 infection (P ≤ .05). CONCLUSION: BC treatment, including chemotherapy, can be safely administered in the context of enhanced infectious precautions, and should not be withheld particularly when given for curative intent.

Efficacy and safety of N-acetyl-L-leucine in Niemann-Pick disease type C.

OBJECTIVE: To investigate the safety and efficacy of N-acetyl-L-leucine (NALL) on symptoms, functioning, and quality of life in pediatric (≥ 6 years) and adult Niemann-Pick disease type C (NPC) patients. METHODS: In this multi-national, open-label, rater-blinded Phase II study, patients were assessed during a baseline period, a 6-week treatment period (orally administered NALL 4 g/day in patients ≥ 13 years, weight-tiered doses for patients 6-12 years), and a 6-week post-treatment washout period. The primary Clinical Impression of Change in Severity (CI-CS) endpoint (based on a 7-point Likert scale) was assessed by blinded, centralized raters who compared randomized video pairs of each patient performing a pre-defined primary anchor test (8-Meter Walk Test or 9-Hole Peg Test) during each study periods. Secondary outcomes included cerebellar functional rating scales, clinical global impression, and quality of life assessments. RESULTS: 33 subjects aged 7-64 years with a confirmed diagnosis of NPC were enrolled. 32 patients were included in the primary modified intention-to-treat analysis. NALL met the CI-CS primary endpoint (mean difference 0.86, SD = 2.52, 90% CI 0.25, 1.75, p = 0.029), as well as secondary endpoints. No treatment-related serious adverse events occurred. CONCLUSIONS: NALL demonstrated a statistically significant and clinical meaningfully improvement in symptoms, functioning, and quality of life in 6 weeks, the clinical effect of which was lost after the 6-week washout period. NALL was safe and well-tolerated, informing a favorable benefit-risk profile for the treatment of NPC. CLINICALTRIALS. GOV IDENTIFIER: NCT03759639.

Assessment of Racial/Ethnic Disparities in Hospitalization and Mortality in Patients With COVID-19 in New York City.

Importance: Black and Hispanic populations have higher rates of coronavirus disease 2019 (COVID-19) hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored. Objective: To compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics. Design, Setting, and Participants: This retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status. Exposures: Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients). Main Outcomes and Measures: The likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death). Results: Among 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9). Conclusions and Relevance: In this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have critical illness or die after adjustment for comorbidity and neighborhood characteristics. This supports the assertion that existing structural determinants pervasive in Black and Hispanic communities may explain the disproportionately higher out-of-hospital deaths due to COVID-19 infections in these populations.

Potential Role of Oral Rinses Targeting the Viral Lipid Envelope in SARS-CoV-2 Infection.

Emerging studies increasingly demonstrate the importance of the throat and salivary glands as sites of virus replication and transmission in early COVID-19 disease. SARS-CoV-2 is an enveloped virus, characterized by an outer lipid membrane derived from the host cell from which it buds. While it is highly sensitive to agents that disrupt lipid biomembranes, there has been no discussion about the potential role of oral rinsing in preventing transmission. Here, we review known mechanisms of viral lipid membrane disruption by widely available dental mouthwash components that include ethanol, chlorhexidine, cetylpyridinium chloride, hydrogen peroxide, and povidone-iodine. We also assess existing formulations for their potential ability to disrupt the SARS-CoV-2 lipid envelope, based on their concentrations of these agents, and conclude that several deserve clinical evaluation. We highlight that already published research on other enveloped viruses, including coronaviruses, directly supports the idea that oral rinsing should be considered as a potential way to reduce transmission of SARS-CoV-2. Research to test this could include evaluating existing or specifically tailored new formulations in well-designed viral inactivation assays, then in clinical trials. Population-based interventions could be undertaken with available mouthwashes, with active monitoring of outcome to determine efficacy. This is an under-researched area of major clinical need.

Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study.

OBJECTIVE: To describe outcomes of people admitted to hospital with coronavirus disease 2019 (covid-19) in the United States, and the clinical and laboratory characteristics associated with severity of illness. DESIGN: Prospective cohort study. SETTING: Single academic medical center in New York City and Long Island. PARTICIPANTS: 5279 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection between 1 March 2020 and 8 April 2020. The final date of follow up was 5 May 2020. MAIN OUTCOME MEASURES: Outcomes were admission to hospital, critical illness (intensive care, mechanical ventilation, discharge to hospice care, or death), and discharge to hospice care or death. Predictors included patient characteristics, medical history, vital signs, and laboratory results. Multivariable logistic regression was conducted to identify risk factors for adverse outcomes, and competing risk survival analysis for mortality. RESULTS: Of 11 544 people tested for SARS-Cov-2, 5566 (48.2%) were positive. After exclusions, 5279 were included. 2741 of these 5279 (51.9%) were admitted to hospital, of whom 1904 (69.5%) were discharged alive without hospice care and 665 (24.3%) were discharged to hospice care or died. Of 647 (23.6%) patients requiring mechanical ventilation, 391 (60.4%) died and 170 (26.2%) were extubated or discharged. The strongest risk for hospital admission was associated with age, with an odds ratio of >2 for all age groups older than 44 years and 37.9 (95% confidence interval 26.1 to 56.0) for ages 75 years and older. Other risks were heart failure (4.4, 2.6 to 8.0), male sex (2.8, 2.4 to 3.2), chronic kidney disease (2.6, 1.9 to 3.6), and any increase in body mass index (BMI) (eg, for BMI >40: 2.5, 1.8 to 3.4). The strongest risks for critical illness besides age were associated with heart failure (1.9, 1.4 to 2.5), BMI >40 (1.5, 1.0 to 2.2), and male sex (1.5, 1.3 to 1.8). Admission oxygen saturation of <88% (3.7, 2.8 to 4.8), troponin level >1 (4.8, 2.1 to 10.9), C reactive protein level >200 (5.1, 2.8 to 9.2), and D-dimer level >2500 (3.9, 2.6 to 6.0) were, however, more strongly associated with critical illness than age or comorbidities. Risk of critical illness decreased significantly over the study period. Similar associations were found for mortality alone. CONCLUSIONS: Age and comorbidities were found to be strong predictors of hospital admission and to a lesser extent of critical illness and mortality in people with covid-19; however, impairment of oxygen on admission and markers of inflammation were most strongly associated with critical illness and mortality. Outcomes seem to be improving over time, potentially suggesting improvements in care.