Severe Acute Respiratory Syndrome and Particulate Matter Exposure: A Systematic Review.

BACKGROUND: Particulate matter (PM) exposure is responsible for seven million deaths annually and has been implicated in the pathogenesis of respiratory infections such as severe acute respiratory syndrome (SARS). Understanding modifiable risk factors of high mortality, resource burdensome C19 and exposure risks such as PM is key to mitigating their devastating effects. This systematic review focuses on the literature available, identifying the spatial and temporal variation in the role of quantified PM exposure in SARS disease outcome and planning our future experimental studies. METHODS: The systematic review utilized keywords adhered to the PRISMA guidelines. We included original human research studies in English. RESULTS: Initial search yielded N = 906, application of eligibility criteria yielded N = 46. Upon analysis of risk of bias N = 41 demonstrated high risk. Studies found a positive association between elevated PM2.5, PM10 and SARS-related outcomes. A geographic and temporal variation in both PM and C19's role was observed. CONCLUSION: C19 is a high mortality and resource intensive disease which devastated the globe. PM exposure is also a global health crisis. Our systematic review focuses on the intersection of this impactful disease-exposure dyad and understanding the role of PM is important in the development of interventions to prevent future spread of viral infections.

State-specific fertility rate changes across the USA following the first two waves of COVID-19.

STUDY QUESTION: How did the first two coronavirus disease 2019 (COVID-19) waves affect fertility rates in the USA? SUMMARY ANSWER: States differed widely in how their fertility rates changed following the COVID-19 outbreak and these changes were influenced more by state-level economic, racial, political, and social factors than by COVID-19 wave severity. WHAT IS KNOWN ALREADY: The outbreak of the COVID-19 pandemic contributed to already declining fertility rates in the USA, but not equally across states. Identifying drivers of differential changes in fertility rates can help explain variations in demographic shifts across states in the USA and motivate policies that support families in general, not only during crises. STUDY DESIGN, SIZE, DURATION: This is an ecological study using state-level data from 50 US states and the District of Columbia (n = 51). The study period extends from 2020 to 2021 with historical data from 2016 to 2019. We identified Wave 1 as the first apex for each state after February 2020 and Wave 2 as the second apex, during Fall/Winter 2020-2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: State-level COVID-19 wave severity, defined as case acceleration during each 3-month COVID-19 wave (cases/100 000 population/month), was derived from 7-day weekly moving average COVID-19 case rates from the US Centers for Disease Control and Prevention (CDC). State-level fertility rate changes (change in average monthly fertility rate/100 000 women of reproductive age (WRA)/year) were derived from the CDC Bureau of Vital Statistics and from 2020 US Census and University of Virginia 2021 population estimates 9 months after each COVID-19 wave. We performed univariate analyses to describe national and state-level fertility rate changes following each wave, and simple and multivariable linear regression analyses to assess the relation of COVID-19 wave severity and other state-level characteristics with fertility rate changes. MAIN RESULTS AND THE ROLE OF CHANCE: Nationwide, fertility dropped by 17.5 births/month/100 000 WRA/year following Wave 1 and 9.2 births/month/100 000 WRA/year following Wave 2. The declines following Wave 1 were largest among majority-Democrat, more non-White states where people practiced greater social distancing. Greater COVID-19 wave severity was associated with steeper fertility rate decline post-Wave 1 in simple regression, but the association was attenuated when adjusted for other covariates. Adjusting for the economic impact of the pandemic (hypothesized mediator) also attenuated the effect. There was no relation between COVID-19 wave severity and fertility rate change following Wave 2. LIMITATIONS, REASONS FOR CAUTION: Our study harnesses state-level data so individual-level conclusions cannot be inferred. There may be residual confounding in our multivariable regression and we were underpowered to detect some effects. WIDER IMPLICATIONS OF THE FINDINGS: The COVID-19 pandemic initially impacted the national fertility rate but, overall, the fertility rate rebounded to the pre-pandemic level following Wave 2. Consistent with prior literature, COVID-19 wave severity did not appear to predict fertility rate change. Economic, racial, political, and social factors influenced state-specific fertility rates during the pandemic more than the severity of the outbreak alone. Future studies in other countries should also consider whether these factors account for internal heterogeneity when examining the impact of the COVID-19 pandemic and other crises on fertility. STUDY FUNDING/COMPETING INTEREST(S): L.G.K. received funding from the National Institute of Environmental Health Sciences (R00ES030403), M.C. from the National Science Foundation Graduate Research Fellowship Program (20-A0-00-1005789), and M.L. and E.S. from the National Institute of Environmental Health Sciences (R01ES032808). None of the authors have competing interests. TRIAL REGISTRATION NUMBER: N/A.

Development and Validation of a Treatment Benefit Index to Identify Hospitalized Patients With COVID-19 Who May Benefit From Convalescent Plasma.

Importance: Identifying which patients with COVID-19 are likely to benefit from COVID-19 convalescent plasma (CCP) treatment may have a large public health impact. Objective: To develop an index for predicting the expected relative treatment benefit from CCP compared with treatment without CCP for patients hospitalized for COVID-19 using patients' baseline characteristics. Design, Setting, and Participants: This prognostic study used data from the COMPILE study, ie, a meta-analysis of pooled individual patient data from 8 randomized clinical trials (RCTs) evaluating CCP vs control in adults hospitalized for COVID-19 who were not receiving mechanical ventilation at randomization. A combination of baseline characteristics, termed the treatment benefit index (TBI), was developed based on 2287 patients in COMPILE using a proportional odds model, with baseline characteristics selected via cross-validation. The TBI was externally validated on 4 external data sets: the Expanded Access Program (1896 participants), a study conducted under Emergency Use Authorization (210 participants), and 2 RCTs (with 80 and 309 participants). Exposure: Receipt of CCP. Main Outcomes and Measures: World Health Organization (WHO) 11-point ordinal COVID-19 clinical status scale and 2 derivatives of it (ie, WHO score of 7-10, indicating mechanical ventilation to death, and WHO score of 10, indicating death) at day 14 and day 28 after randomization. Day 14 WHO 11-point ordinal scale was used as the primary outcome to develop the TBI. Results: A total of 2287 patients were included in the derivation cohort, with a mean (SD) age of 60.3 (15.2) years and 815 (35.6%) women. The TBI provided a continuous gradation of benefit, and, for clinical utility, it was operationalized into groups of expected large clinical benefit (B1; 629 participants in the derivation cohort [27.5%]), moderate benefit (B2; 953 [41.7%]), and potential harm or no benefit (B3; 705 [30.8%]). Patients with preexisting conditions (diabetes, cardiovascular and pulmonary diseases), with blood type A or AB, and at an early COVID-19 stage (low baseline WHO scores) were expected to benefit most, while those without preexisting conditions and at more advanced stages of COVID-19 could potentially be harmed. In the derivation cohort, odds ratios for worse outcome, where smaller odds ratios indicate larger benefit from CCP, were 0.69 (95% credible interval [CrI], 0.48-1.06) for B1, 0.82 (95% CrI, 0.61-1.11) for B2, and 1.58 (95% CrI, 1.14-2.17) for B3. Testing on 4 external datasets supported the validation of the derived TBIs. Conclusions and Relevance: The findings of this study suggest that the CCP TBI is a simple tool that can quantify the relative benefit from CCP treatment for an individual patient hospitalized with COVID-19 that can be used to guide treatment recommendations. The TBI precision medicine approach could be especially helpful in a pandemic.

Association of Convalescent Plasma Treatment With Clinical Status in Patients Hospitalized With COVID-19: A Meta-analysis.

Importance: COVID-19 convalescent plasma (CCP) is a potentially beneficial treatment for COVID-19 that requires rigorous testing. Objective: To compile individual patient data from randomized clinical trials of CCP and to monitor the data until completion or until accumulated evidence enables reliable conclusions regarding the clinical outcomes associated with CCP. Data Sources: From May to August 2020, a systematic search was performed for trials of CCP in the literature, clinical trial registry sites, and medRxiv. Domain experts at local, national, and international organizations were consulted regularly. Study Selection: Eligible trials enrolled hospitalized patients with confirmed COVID-19, not receiving mechanical ventilation, and randomized them to CCP or control. The administered CCP was required to have measurable antibodies assessed locally. Data Extraction and Synthesis: A minimal data set was submitted regularly via a secure portal, analyzed using a prespecified bayesian statistical plan, and reviewed frequently by a collective data and safety monitoring board. Main Outcomes and Measures: Prespecified coprimary end points-the World Health Organization (WHO) 11-point ordinal scale analyzed using a proportional odds model and a binary indicator of WHO score of 7 or higher capturing the most severe outcomes including mechanical ventilation through death and analyzed using a logistic model-were assessed clinically at 14 days after randomization. Results: Eight international trials collectively enrolled 2369 participants (1138 randomized to control and 1231 randomized to CCP). A total of 2341 participants (median [IQR] age, 60 [50-72] years; 845 women [35.7%]) had primary outcome data as of April 2021. The median (IQR) of the ordinal WHO scale was 3 (3-6); the cumulative OR was 0.94 (95% credible interval [CrI], 0.74-1.19; posterior probability of OR <1 of 71%). A total of 352 patients (15%) had WHO score greater than or equal to 7; the OR was 0.94 (95% CrI, 0.69-1.30; posterior probability of OR <1 of 65%). Adjusted for baseline covariates, the ORs for mortality were 0.88 at day 14 (95% CrI, 0.61-1.26; posterior probability of OR <1 of 77%) and 0.85 at day 28 (95% CrI, 0.62-1.18; posterior probability of OR <1 of 84%). Heterogeneity of treatment effect sizes was observed across an array of baseline characteristics. Conclusions and Relevance: This meta-analysis found no association of CCP with better clinical outcomes for the typical patient. These findings suggest that real-time individual patient data pooling and meta-analysis during a pandemic are feasible, offering a model for future research and providing a rich data resource.

Efficacy and Safety of COVID-19 Convalescent Plasma in Hospitalized Patients: A Randomized Clinical Trial.

Importance: There is clinical equipoise for COVID-19 convalescent plasma (CCP) use in patients hospitalized with COVID-19. Objective: To determine the safety and efficacy of CCP compared with placebo in hospitalized patients with COVID-19 receiving noninvasive supplemental oxygen. Design, Setting, and Participants: CONTAIN COVID-19, a randomized, double-blind, placebo-controlled trial of CCP in hospitalized adults with COVID-19, was conducted at 21 US hospitals from April 17, 2020, to March 15, 2021. The trial enrolled 941 participants who were hospitalized for 3 or less days or presented 7 or less days after symptom onset and required noninvasive oxygen supplementation. Interventions: A unit of approximately 250 mL of CCP or equivalent volume of placebo (normal saline). Main Outcomes and Measures: The primary outcome was participant scores on the 11-point World Health Organization (WHO) Ordinal Scale for Clinical Improvement on day 14 after randomization; the secondary outcome was WHO scores determined on day 28. Subgroups were analyzed with respect to age, baseline WHO score, concomitant medications, symptom duration, CCP SARS-CoV-2 titer, baseline SARS-CoV-2 serostatus, and enrollment quarter. Outcomes were analyzed using a bayesian proportional cumulative odds model. Efficacy of CCP was defined as a cumulative adjusted odds ratio (cOR) less than 1 and a clinically meaningful effect as cOR less than 0.8. Results: Of 941 participants randomized (473 to placebo and 468 to CCP), 556 were men (59.1%); median age was 63 years (IQR, 52-73); 373 (39.6%) were Hispanic and 132 (14.0%) were non-Hispanic Black. The cOR for the primary outcome adjusted for site, baseline risk, WHO score, age, sex, and symptom duration was 0.94 (95% credible interval [CrI], 0.75-1.18) with posterior probability (P[cOR<1] = 72%); the cOR for the secondary adjusted outcome was 0.92 (95% CrI, 0.74-1.16; P[cOR<1] = 76%). Exploratory subgroup analyses suggested heterogeneity of treatment effect: at day 28, cORs were 0.72 (95% CrI, 0.46-1.13; P[cOR<1] = 93%) for participants enrolled in April-June 2020 and 0.65 (95% CrI, 0.41 to 1.02; P[cOR<1] = 97%) for those not receiving remdesivir and not receiving corticosteroids at randomization. Median CCP SARS-CoV-2 neutralizing titer used in April to June 2020 was 1:175 (IQR, 76-379). Any adverse events (excluding transfusion reactions) were reported for 39 (8.2%) placebo recipients and 44 (9.4%) CCP recipients (P = .57). Transfusion reactions occurred in 2 (0.4) placebo recipients and 8 (1.7) CCP recipients (P = .06). Conclusions and Relevance: In this trial, CCP did not meet the prespecified primary and secondary outcomes for CCP efficacy. However, high-titer CCP may have benefited participants early in the pandemic when remdesivir and corticosteroids were not in use. Trial Registration: ClinicalTrials.gov Identifier: NCT04364737.

COVID-19 outcomes of patients with gynecologic cancer in New York City: An updated analysis from the initial surge of the pandemic.

BACKGROUND: Despite significant increase in COVID-19 publications, characterization of COVID-19 infection in patients with gynecologic cancer remains limited. Here we present an update of COVID-19 outcomes among people with gynecologic cancer in New York City (NYC) during the initial surge of severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019 [COVID-19]). METHODS: Data were abstracted from gynecologic oncology patients with COVID-19 infection among 8 NYC area hospital systems between March and June 2020. Multivariable logistic regression was utilized to estimate associations between factors and COVID-19 related hospitalization and mortality. RESULTS: Of 193 patients with gynecologic cancer and COVID-19, the median age at diagnosis was 65.0 years (interquartile range (IQR), 53.0-73.0 years). One hundred six of the 193 patients (54.9%) required hospitalization; among the hospitalized patients, 13 (12.3%) required invasive mechanical ventilation, 39 (36.8%) required ICU admission. Half of the cohort (49.2%) had not received anti-cancer treatment prior to COVID-19 diagnosis. No patients requiring mechanical ventilation survived. Thirty-four of 193 (17.6%) patients died of COVID-19 complications. In multivariable analysis, hospitalization was associated with an age ≥ 65 years (odds ratio [OR] 2.12, 95% confidence interval [CI] 1.11, 4.07), Black race (OR 2.53, CI 1.24, 5.32), performance status ≥2 (OR 3.67, CI 1.25, 13.55) and ≥ 3 comorbidities (OR 2.00, CI 1.05, 3.84). Only former or current history of smoking (OR 2.75, CI 1.21, 6.22) was associated with death due to COVID-19 in multivariable analysis. Administration of cytotoxic chemotherapy within 90 days of COVID-19 diagnosis was not predictive of COVID-19 hospitalization (OR 0.83, CI 0.41, 1.68) or mortality (OR 1.56, CI 0.67, 3.53). CONCLUSIONS: The case fatality rate among patients with gynecologic malignancy with COVID-19 infection was 17.6%. Cancer-directed therapy was not associated with an increased risk of mortality related to COVID-19 infection.

Partially linear single-index generalized mean residual life models.

Mean residual life (MRL) function defines the remaining life expectancy of a subject who has survived to a time point and is an important alternative to the hazard function for characterizing the distribution of a time-to-event variable. Existing MRL models primarily focus on studying the association between risk factors and disease risks using linear model specifications in multiplicative or additive scale. When risk factors have complex correlation structures, nonlinear effects, or interactions, the prefixed linearity assumption may be insufficient to capture the relationship. Single-index modeling framework offers flexibility in reducing dimensionality and modeling nonlinear effects. In this article, we propose a class of partially linear single-index generalized MRL models, the regression component of which consists of both a semiparametric single-index part and a linear regression part. Regression spline technique is employed to approximate the nonparametric single-index function, and parameters are estimated using an iterative algorithm. Double-robust estimators are also proposed to protect against the misspecification of censoring distribution or MRL models. A further contribution of this article is a nonparametric test proposed to formally evaluate the linearity of the single-index function. Asymptotic properties of the estimators are established, and the finite-sample performance is evaluated through extensive numerical simulations. The proposed models and inference approaches are demonstrated by a New York University Langone Health (NYULH) COVID-19 dataset.

Factors Associated With Changes in Pregnancy Intention Among Women Who Were Mothers of Young Children in New York City Following the COVID-19 Outbreak.

Importance: Early evidence shows a decrease in the number of US births during the COVID-19 pandemic, yet few studies have examined individual-level factors associated with pregnancy intention changes, especially among diverse study populations or in areas highly affected by COVID-19 in the US. Objective: To study changes in pregnancy intention following the outbreak of the COVID-19 pandemic and identify factors possibly associated with these changes. Design, Setting, and Participants: A cross-sectional, population-based study was conducted among women who were currently pregnant or had delivered a live infant and responded to a survey emailed to 2603 women (n = 1560). Women who were mothers of young children enrolled in the prospective New York University Children's Health and Environment Study birth cohort were included; women who were not currently pregnant or recently postpartum were excluded. Exposures: Demographic, COVID-19-related, stress-related, and financial/occupational factors were assessed via a survey administered from April 20 to August 31, 2020. Main Outcomes and Measures: Pregnancy intentions before the COVID-19 pandemic and change in pregnancy intentions following the outbreak. Results: Of the 2603 women who were sent the survey, 1560 (59.9%) who were currently pregnant or had delivered a live infant responded, and 1179 women (75.6%) answered the pregnancy intention questions. Mean (SD) age was 32.2 (5.6) years. Following the outbreak, 30 of 61 (49.2%) women who had been actively trying to become pregnant had ceased trying, 71 of 191 (37.2%) women who had been planning to become pregnant were no longer planning, and 42 of 927 (4.5%) women who were neither planning nor trying were newly considering pregnancy. Among those who ceased trying, fewer than half (13 [43.3%]) thought they would resume after the pandemic. Of those pre-COVID-19 planners/triers who stopped considering or attempting pregnancy, a greater proportion had lower educational levels, although the difference was not statistically significant on multivariable analysis (odds ratio [OR], 2.14; 95% CI, 0.92-4.96). The same was true for those with higher stress levels (OR, 1.09; 95% CI, 0.99-1.20) and those with greater financial insecurity (OR, 1.37; 95% CI, 0.97-1.92. Those who stopped considering or attempting pregnancy were more likely to respond to the questionnaire during the peak of the outbreak (OR, 2.04; 95% CI, 1.01-4.11). Of those pre-COVID-19 nonplanners/nontriers who reported newly thinking about becoming pregnant, a smaller proportion responded during the peak, although the finding was not statistically significant on multivariable analysis (OR, 0.52; 95% CI, 0.26-1.03). Likewise, fewer respondents who were financially insecure reported newly considering pregnancy, although the finding was not statistically significant (OR, 0.69; 95% CI, 0.46-1.03). They were significantly less likely to be of Hispanic ethnicity (OR, 0.27; 955 CI, 0.10-0.71) and more likely to have fewer children in the home (OR, 0.62; 95% CI, 0.40-0.98) or self-report a COVID-19 diagnosis (OR, 2.70; 95% CI, 1.31-5.55). Conclusions and Relevance: In this cross-sectional study of 1179 women who were mothers of young children in New York City, increased stress and financial insecurity owing to the COVID-19 pandemic paralleled a reduction in pregnancy intention in the early months of the pandemic, potentially exacerbating long-term decreases in the fertility rate.

COVID-19 outcomes of patients with gynecologic cancer in New York City: an updated analysis

Despite a growing body of literature, characterization of COVID-19 infection in patients with gynecologic cancer remains limited. Here we present an update of COVID-19 outcomes in New York City (NYC) from the initial surge of severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019 [COVID-19]). We sought to determine the hospitalization and mortality rates and their associated factors, specifically recent chemotherapy and immunotherapy use. Data were abstracted from gynecologic oncology patients with COVID-19 infection among 8 New York City (NYC) area hospital systems. Multivariable logistic regression was utilized to analyze COVID-19 related hospitalization and mortality. Of 193 patients with gynecologic cancer and COVID-19, the median age at diagnosis was 65.0 years (interquartile range, 53.0-73.0 years). A total of 106 of the 193 patients (54.9%) required hospitalization;among the hospitalized patients 13 (12.3%) required invasive mechanical ventilation and 39 (36.8%) required ICU admission. No patients requiring mechanical ventilation survived. A total of 34 of 193 (17.6%) patients died of COVID-19 complications. On multivariable analysis, hospitalization was associated with an age greater than or equal to 65 years (odds ratio [OR] 2.12, 95% confidence interval [CI] 1.11, 4.07), Black race (OR 2.53, CI 1.24, 5.32), performance status greater than or equal to 2 (OR 3.67, CI 1.25, 13.55) and greater than or equal to 3 comorbidities (OR 2.00, CI 1.05, 3.84). Only former or current history of smoking (OR 2.75, CI 1.21, 6.22) was associated with death due to COVID-19 on multivariable analysis. A total of 13 of 34 (38.23%) patients who died of COVID-19 complications received cytotoxic chemotherapy, while 4 of 34 (11.76%) patients received immunotherapy. However, recent cytotoxic chemotherapy use was not predictive of COVID-19 hospitalization or mortality on multivariable analysis. [Display omitted] The case fatality rate among gynecologic oncology patients with COVID-19 infection is 17.6%. Cancer-directed therapy, including immunotherapy use, is not associated with an increased risk of mortality related to COVID-19 infection in this larger cohort. [ABSTRACT FROM AUTHOR] Copyright of Gynecologic Oncology is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Prospective individual patient data meta-analysis: Evaluating convalescent plasma for COVID-19.

As the world faced the devastation of the COVID-19 pandemic in late 2019 and early 2020, numerous clinical trials were initiated in many locations in an effort to establish the efficacy (or lack thereof) of potential treatments. As the pandemic has been shifting locations rapidly, individual studies have been at risk of failing to meet recruitment targets because of declining numbers of eligible patients with COVID-19 encountered at participating sites. It has become clear that it might take several more COVID-19 surges at the same location to achieve full enrollment and to find answers about what treatments are effective for this disease. This paper proposes an innovative approach for pooling patient-level data from multiple ongoing randomized clinical trials (RCTs) that have not been configured as a network of sites. We present the statistical analysis plan of a prospective individual patient data (IPD) meta-analysis (MA) from ongoing RCTs of convalescent plasma (CP). We employ an adaptive Bayesian approach for continuously monitoring the accumulating pooled data via posterior probabilities for safety, efficacy, and harm. Although we focus on RCTs for CP and address specific challenges related to CP treatment for COVID-19, the proposed framework is generally applicable to pooling data from RCTs for other therapies and disease settings in order to find answers in weeks or months, rather than years.

Racial disparities in patients with coronavirus disease 2019 infection and gynecologic malignancy.

BACKGROUND: Mounting evidence suggests disproportionate coronavirus disease 2019 (COVID-19) hospitalizations and deaths because of racial disparities. The association of race in a cohort of gynecologic oncology patients with severe acute respiratory syndrome-coronavirus 2 infection is unknown. METHODS: Data were abstracted from gynecologic oncology patients with COVID-19 infection among 8 New York City area hospital systems. A multivariable mixed-effects logistic regression model accounting for county clustering was used to analyze COVID-19-related hospitalization and mortality. RESULTS: Of 193 patients who had gynecologic cancer and COVID-19, 67 (34.7%) were Black, and 126 (65.3%) were non-Black. Black patients were more likely to require hospitalization compared with non-Black patients (71.6% [48 of 67] vs 46.0% [58 of 126]; P = .001). Of 34 (17.6%) patients who died from COVID-19, 14 (41.2%) were Black. Among those who were hospitalized, compared with non-Black patients, Black patients were more likely to: have ≥3 comorbidities (81.1% [30 of 37] vs 59.2% [29 of 49]; P = .05), to reside in Brooklyn (81.0% [17 of 21] vs 44.4% [12 of 27]; P = .02), to live with family (69.4% [25 of 36] vs 41.6% [37 of 89]; P = .009), and to have public insurance (79.6% [39 of 49] vs 53.4% [39 of 73]; P = .006). In multivariable analysis, among patients aged <65 years, Black patients were more likely to require hospitalization compared with non-Black patients (odds ratio, 4.87; 95% CI, 1.82-12.99; P = .002). CONCLUSIONS: Although Black patients represented only one-third of patients with gynecologic cancer, they accounted for disproportionate rates of hospitalization (>45%) and death (>40%) because of COVID-19 infection; younger Black patients had a nearly 5-fold greater risk of hospitalization. Efforts to understand and improve these disparities in COVID-19 outcomes among Black patients are critical.

Treatment with Zinc is Associated with Reduced In-Hospital Mortality Among COVID-19 Patients: A Multi-Center Cohort Study.

Background: Zinc impairs replication of RNA viruses such as SARS-CoV-1, and may be effective against SARS-CoV-2. However, to achieve adequate intracellular zinc levels, administration with an ionophore, which increases intracellular zinc levels, may be necessary. We evaluated the impact of zinc with an ionophore (Zn+ionophore) on COVID-19 in-hospital mortality rates. Methods: A multicenter cohort study was conducted of 3,473 adult hospitalized patients with reverse-transcriptase-polymerase-chain-reaction (RT-PCR) positive SARS-CoV-2 infection admitted to four New York City hospitals between March 10 through May 20, 2020. Exclusion criteria were: death or discharge within 24h, comfort-care status, clinical trial enrollment, treatment with an IL-6 inhibitor or remdesivir. Patients who received Zn+ionophore were compared to patients who did not using multivariable time-dependent cox proportional hazards models for time to in-hospital death adjusting for confounders including age, sex, race, BMI, diabetes, week of admission, hospital location, sequential organ failure assessment (SOFA) score, intubation, acute renal failure, neurological events, treatment with corticosteroids, azithromycin or lopinavir/ritonavir and the propensity score of receiving Zn+ionophore. A sensitivity analysis was performed using a propensity score-matched cohort of patients who did or did not receive Zn+ionophore matched by age, sex and ventilator status. Results: Among 3,473 patients (median age 64, 1947 [56%] male, 522 [15%] ventilated, 545[16%] died), 1,006 (29%) received Zn+ionophore. Zn+ionophore was associated with a 24% reduced risk of in-hospital mortality (12% of those who received Zn+ionophore died versus 17% who did not; adjusted Hazard Ratio [aHR] 0.76, 95% CI 0.60-0.96, P=0.023). More patients who received Zn+ionophore were discharged home (72% Zn+ionophore vs 67% no Zn+ionophore, P=0.003) Neither Zn nor the ionophore alone were associated with decreased mortality rates. Propensity score-matched sensitivity analysis (N=1356) validated these results (Zn+ionophore aHR for mortality 0.63, 95%CI 0.44-0.91, P=0.015). There were no significant interactions for Zn+ionophore with other COVID-19 specific medications. Conclusions: Zinc with an ionophore was associated with increased rates of discharge home and a 24% reduced risk of in-hospital mortality among COVID-19 patients, while neither zinc alone nor the ionophore alone reduced mortality. Further randomized trials are warranted.

Increased Metabolic Burden Among Blacks: A Putative Mechanism for Disparate COVID-19 Outcomes.

Mounting evidence shows a disproportionate COVID-19 burden among Blacks. Early findings indicate pre-existing metabolic burden (eg, obesity, hypertension and diabetes) as key drivers of COVID-19 severity. Since Blacks exhibit higher prevalence of metabolic burden, we examined the influence of metabolic syndrome on disparate COVID-19 burden. We analyzed data from a NIH-funded study to characterize metabolic burden among Blacks in New York (Metabolic Syndrome Outcome Study). Patients (n=1035) were recruited from outpatient clinics, where clinical and self-report data were obtained. The vast majority of the sample was overweight/obese (90%); diagnosed with hypertension (93%); dyslipidemia (72%); diabetes (61%); and nearly half of them were at risk for sleep apnea (48%). Older Blacks (age≥65 years) were characterized by higher levels of metabolic burden and co-morbidities (eg, heart disease, cancer). In multivariate-adjusted regression analyses, age was a significant (p≤.001) independent predictor of hypertension (OR=1.06; 95% CI: 1.04-1.09), diabetes (OR=1.03; 95% CI: 1.02-1.04), and dyslipidemia (OR=0.98; 95% CI: 0.97-0.99), but not obesity. Our study demonstrates an overwhelmingly high prevalence of the metabolic risk factors related to COVID-19 among Blacks in New York, highlighting disparate metabolic burden among Blacks as a possible mechanism conferring the greater burden of COVID-19 infection and mortality represented in published data.