Cytokine storm syndrome in patients with COVID-19 is mediated by pro-inflammatory cytokines resulting in acute lung injury and multiorgan failure. Elevation in serum ferritin and D-dimer is observed in COVID-19 patients. To determine prognostic values of optimal serum cutoff with trajectory plots for both serum ferritin and D-dimer in COVID-19 patients with invasive ventilator dependence and in-hospital mortality. We used retrospective longitudinal data from the Cerner COVID-19 de-identified cohort. COVID-19 infected patients with valid repeated values of serum ferritin and D-dimer during hospitalization were used in mixed-effects logistic-regression models. Among 52,411 patients, 28.5% (14,958) had valid serum ferritin and 28.6% (15,005) D-dimer laboratory results. Optimal cutoffs of ferritin (714 ng/mL) and D-dimer (2.1 mg/L) revealed AUCs ≥ 0.99 for in-hospital mortality. Optimal cutoffs for ferritin (502 ng/mL) and D-dimer (2.0 mg/L) revealed AUCs ≥ 0.99 for invasive ventilator dependence. Optimal cutoffs for in-house mortality, among females, were lower in serum ferritin (433 ng/mL) and D-dimer (1.9 mg/L) compared to males (740 ng/mL and 2.5 mg/L, respectively). Optimal cutoffs for invasive ventilator dependence, among females, were lower in ferritin (270 ng/mL) and D-dimer (1.3 mg/L) compared to males (860 ng/mL and 2.3 mg/L, respectively). Optimal prognostic cutoffs for serum ferritin and D-dimer require considering the entire trajectory of laboratory values during the disease course. Females have an overall lower optimal cutoff for both serum ferritin and D-dimer. The presented research allows health professionals to predict clinical outcomes and appropriate allocation of resources during the COVID-19 pandemic, especially early recognition of COVID-19 patients needing higher levels of care.

Objectives The rate of drug overdose deaths in the USA has more than tripled since the turn of the century, and rates are disproportionately high among the American Indian/Alaska Native (AI/AN) population. Little is known about the overall historical trends in AI/AN opioid-only and opioid/polysubstance-related mortality. This study will address this gap. Design This is a retrospective longitudinal ecological study. Setting US death records from 1999 to 2019 using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research. Participants US non-Hispanic AI/AN people age 12 years and older. Measures The primary outcomes, identified via the 10th revision of the International Statistical Classification of Diseases and Related Health Problems codes, included overdose deaths due to (1) opioids only, opioids in combination with any other substance, all-opioid related overdoses; (2) combinations of opioids and alcohol, opioids and methamphetamine, opioids and cocaine, opioids and benzodiazepines; and (3) specific types of opioids. Results From 1999 to 2019, opioid-only mortality rates increased from 2.8 to 15.8 per 100 000 (p<0.001) for AI/AN women and 4.6 to 25.6 per 100 000 (p<0.001) for AI/AN men. All opioid-related mortality rates increased significantly (p<0.001) from 5.2 to 33.9 per 100 000 AI/AN persons, 3.9 to 26.1 for women and 6.5 to 42.1 for men. AI/AN also exhibited significant increases in mortality rates due to opioids and alcohol, opioids and benzodiazepines, opioids and methamphetamine, and AI/AN men experienced substantial increases in mortality due to opioids and cocaine. Mortality rates by individual opioid types increased significantly over time for heroin, natural and semi-synthetic (prescription), and synthetic opioids (fentanyl/fentanyl analogues) other than methadone. Conclusions These findings highlight magnification over time in opioid-related deaths and may point to broader systemic factors that may disproportionately affect members of AI/AN communities and drive inequities.

With the emergence of the novel SARS-CoV-2 and the disease it causes; COVID-19, compliance with/adherence to protective measures is needed. Information is needed on which measures are, or are not, being undertaken. Data collected from the COVID Impact Survey, conducted by the non-partisan and objective research organization NORC at the University of Chicago on April, May, and June of 2020, were analyzed through weighted Quasi-Poisson regression modeling to determine the association of demographics, socioeconomics, and health conditions with protective health measures taken at the individual level in response to COVID-19. The three surveys included data from 18 regional areas including 10 states (CA, CO, FL, LA, MN, MO, MT, NY, OR, and TX) and 8 Metropolitan Statistical Areas (Atlanta, GA; Baltimore, MD; Birmingham, AL; Chicago, IL; Cleveland and Columbus, OH; Phoenix, AZ; and Pittsburgh, PA). Individuals with higher incomes, insurance, higher education levels, large household size, age 60+, females, minorities, those who have asthma, have hypertension, overweight or obese, and those who suffer from mental health issues during the pandemic were significantly more likely to report taking precautionary protective measures relative to their counterparts. Protective measures for the three subgroups with a known relationship to COVID-19 (positive for COVID-19, knowing an individual with COVID-19, and knowing someone who had died from COVID-19) were strongly associated with the protective health measures of washing hands, avoiding public places, and canceling social engagements. This study provides first baseline data on the response to the national COVID-19 pandemic at the individual level in the US. The found heterogeneity in the response to this pandemic by different variables can inform future research and interventions to reduce exposure to the novel SARS-CoV-2 virus.

Both opioid use and COVID-19 affect respiratory and pulmonary health, potentially putting individuals with opioid use disorders (OUD) at risk for complications from COVID-19. We examine the relationship between OUD and subsequent hospitalization, length of stay, risk for invasive ventilator dependence (IVD), and COVID-19 mortality. Multivariable logistic and exponential regression models using electronic health records data from the Cerner COVID-19 De-Identified Data Cohort from January through June 2020. Out of 52,312 patients with COVID-19, 1.9% (n=1,013) had an OUD. COVID-19 patients with an OUD had higher odds of hospitalization (aOR=3.44, 95% CI=2.81–4.21), maximum length of stay (eβ^=1.16, 95% CI=1.09–1.22), and odds of IVD (aOR=1.26, 95% CI=1.06–1.49) than patients without an OUD, but did not differ with respect to COVID-19 mortality. However, OUD patients under age 45 exhibited greater COVID-19 mortality (aOR=3.23, 95% CI=1.59–6.56) compared to patients under age 45 without an OUD. OUD patients using opioid agonist treatment (OAT) exhibited higher odds of hospitalization (aOR=5.14, 95% CI=2.75–10.60) and higher maximum length of stay (eβ^=1.22, 95% CI=1.01–1.48) than patients without OUDs; however, risk for IVD and COVID-19 mortality did not differ. OUD patients using naltrexone had higher odds of hospitalization (aOR=32.19, 95% CI=4.29–4,119.83), higher maximum length of stay (eβ^=1.59, 95% CI=1.06–2.38), and higher odds of IVD (aOR=3.15, 95% CI=1.04–9.51) than patients without OUDs, but mortality did not differ. OUD patients who did not use treatment medication had higher odds of hospitalization (aOR=4.05, 95% CI=3.32–4.98), higher maximum length of stay (eβ^=1.14, 95% CI=1.08–1.21), and higher odds of IVD (aOR=1.25, 95% CI=1.04–1.50) and COVID-19 mortality (aOR=1.31, 95% CI=1.07–1.61) than patients without OUDs. This study suggests people with OUD and COVID-19 often require higher levels of care, and OUD patients who are younger or not using medication treatment for OUDs are particularly vulnerable to death due to COVID-19.

Background: Restorative reproductive medicine (RRM) seeks to identify and correct underlying causes and factors contributing to infertility and reproductive dysfunction. Many components of RRM are highly suitable for primary care practice. We studied the outcomes amongst couples who received restorative reproductive medicine treatment for infertility in a primary care setting. Methods: Two family physicians in Massachusetts trained in a systematic approach to RRM (natural procreative technology, or NaProTechnology) treated couples with infertility. We retrospectively reviewed the characteristics, diagnoses, treatments, and outcomes for all couples treated during the years 1989 to 2014. We compared pregnancy and live birth by clinical characteristics using Kaplan-Meier analysis. We employed the Fleming-Harrington weighted Renyi test or the logrank test to compare the cumulative proportion with pregnancy or with live birth. Results: Among 370 couples beginning treatment for infertility, the mean age was 34.8 years, the mean prior time trying to conceive was 2.7 years, and 27% had a prior live birth. The mean number of diagnoses per couple was 4.9. Treatment components included fertility tracking with the Creighton Model FertilityCare System (80%); medications to enhance cervical mucus production (81%), to stimulate ovulation (62%), or to support the luteal phase (75%); and referral to female laparoscopy by a surgeon specializing in endometriosis (46%). The cumulative live birth rate at 2 years was 29% overall; this was significantly higher for women under age 35 (34%), and for women with body mass index < 25 (40%). There were 2 sets of twins and no higher-order multiple gestations. Of the 63 births with data available, 58 (92%) occurred at term. Conclusions: Family physicians can provide a RRM approach for infertility to identify underlying causes and promote healthy term live births. Younger women and women with body mass index < 25 are more likely to have a live birth.