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Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response-line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System-to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. ( Am J Public Health . 2024;114(10):1071-1080. https://doi.org/10.2105/AJPH.2024.307743).

Few precise estimates of hospitalization and fatality rates from COVID-19 exist for naive populations, especially within demographic subgroups. We estimated rates among persons with SARS-CoV-2 infection in the United States during May 1-December 1, 2020, before vaccines became available. Both rates generally increased with age; fatality rates were highest for persons >85 years of age (24%) and lowest for children 1-14 years of age (0.01%). Age-adjusted case hospitalization rates were highest for African American or Black, not Hispanic persons (14%), and case-fatality rates were highest for Asian or Pacific Islander, not Hispanic persons (4.4%). Eighteen percent of hospitalized patients and 44.2% of those admitted to an intensive care unit died. Male patients had higher hospitalization (6.2% vs. 5.2%) and fatality rates (1.9% vs. 1.5%) than female patients. These findings highlight the importance of collecting surveillance data to devise appropriate control measures for persons in underserved racial/ethnic groups and older adults.

Background: SARS-CoV-2 Omicron variants have the potential to impact vaccine effectiveness and duration of vaccine-derived immunity. We analyzed U.S. multi-jurisdictional COVID-19 vaccine breakthrough surveillance data to examine potential waning of protection against SARS-CoV-2 infection for the Pfizer-BioNTech (BNT162b) primary vaccination series by age., Methods: Weekly numbers of SARS-CoV-2 infections during January 16, 2022-May 28, 2022 were analyzed by age group from 22 U.S. jurisdictions that routinely linked COVID-19 case surveillance and immunization data. A life table approach incorporating line-listed and aggregated COVID-19 case datasets with vaccine administration and U.S. Census data was used to estimate hazard rates of SARS-CoV-2 infections, hazard rate ratios (HRR) and percent reductions in hazard rate comparing unvaccinated people to people vaccinated with a Pfizer-BioNTech primary series only, by age group and time since vaccination., Results: The percent reduction in hazard rates for persons 2 weeks after vaccination with a Pfizer-BioNTech primary series compared with unvaccinated persons was lowest among children aged 5-11 years at 35.5% (95% CI: 33.3%, 37.6%) compared to the older age groups, which ranged from 68.7%-89.6%. By 19 weeks after vaccination, all age groups showed decreases in the percent reduction in the hazard rates compared with unvaccinated people; with the largest declines observed among those aged 5-11 and 12-17 years and more modest declines observed among those 18 years and older., Conclusions: The decline in vaccine protection against SARS-CoV-2 infection observed in this study is consistent with other studies and demonstrates that national case surveillance data were useful for assessing early signals in age-specific waning of vaccine protection during the initial period of SARS-CoV-2 Omicron variant predominance. The potential for waning immunity during the Omicron period emphasizes the importance of continued monitoring and consideration of optimal timing and provision of booster doses in the future., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Early during the COVID-19 pandemic, the Centers for Disease Control and Prevention (CDC) leveraged an existing surveillance system infrastructure to monitor COVID-19 cases and deaths in the United States. Given the time needed to report individual-level (also called line-level) COVID-19 case and death data containing detailed information from individual case reports, CDC designed and implemented a new aggregate case surveillance system to inform emergency response decisions more efficiently, with timelier indicators of emerging areas of concern. We describe the processes implemented by CDC to operationalize this novel, multifaceted aggregate surveillance system for collecting COVID-19 case and death data to track the spread and impact of the SARS-CoV-2 virus at national, state, and county levels. We also review the processes established to acquire, process, and validate the aggregate number of cases and deaths due to COVID-19 in the United States at the county and jurisdiction levels during the pandemic. These processes include time-saving tools and strategies implemented to collect and validate authoritative COVID-19 case and death data from jurisdictions, such as web scraping to automate data collection and algorithms to identify and correct data anomalies. This topical review highlights the need to prepare for future emergencies, such as novel disease outbreaks, by having an event-agnostic aggregate surveillance system infrastructure in place to supplement line-level case reporting for near-real-time situational awareness and timely data.

Background: In the United States, national ecological studies suggest a positive impact of COVID-19 vaccination coverage on outcomes in adults. However, the national impact of the vaccination program on COVID-19 in children remains unknown. To determine the association of COVID-19 vaccination with U.S. case incidence, emergency department visits, and hospital admissions for pediatric populations during the Delta and Omicron periods., Methods: We conducted an ecological analysis among children aged 5-17 and compared incidence rate ratios (RRs) of COVID-19 cases, emergency department visits, and hospital admissions by pediatric vaccine coverage, with jurisdictions in the highest vaccine coverage quartile as the reference., Results: RRs comparing states with lowest pediatric vaccination coverage to the highest pediatric vaccination coverage were 2.00 and 0.64 for cases, 2.96 and 1.11 for emergency department visits, and 2.76 and 1.01 for hospital admissions among all children during the Delta and Omicron periods, respectively. During the 3-week peak period of the Omicron wave, only children aged 12-15 and 16-17 years in the states with the lowest versus highest coverage, had a significantly higher rate of emergency department visits (RR = 1.39 and RR = 1.34, respectively)., Conclusions: COVID-19 vaccines were associated with lower case incidence, emergency department visits and hospital admissions among children during the Delta period but the association was weaker during the Omicron period. Pediatric COVID-19 vaccination should be promoted as part of a program to decrease COVID-19 impact among children; however, vaccine effectiveness may be limited when available vaccines do not match circulating viral variants., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Background: Case-based surveillance of pediatric coronavirus disease 2019 (COVID-19) cases underestimates the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children and adolescents. Our objectives were to estimate monthly SARS-CoV-2 antibody seroprevalence and calculate ratios of SARS-CoV-2 infections to reported COVID-19 cases among children and adolescents in 8 US states., Methods: Using data from the Nationwide Commercial Laboratory Seroprevalence Survey, we estimated monthly SARS-CoV-2 antibody seroprevalence among children aged 0-17 years from August 2020 through May 2021. We calculated and compared cumulative incidence of SARS-CoV-2 infection extrapolated from population-standardized seroprevalence of antibodies to SARS-CoV-2, cumulative COVID-19 case reports since March 2020, and infection-to-case ratios among persons of all ages and children aged 0-17 years for each state., Results: Of 41 583 residual serum specimens tested, children aged 0-4, 5-11, and 12-17 years accounted for 1619 (3.9%), 10 507 (25.3%), and 29 457 (70.8%), respectively. Median SARS-CoV-2 antibody seroprevalence among children increased from 8% (range, 6%-20%) in August 2020 to 37% (range, 26%-44%) in May 2021. Estimated ratios of SARS-CoV-2 infections to reported COVID-19 cases in May 2021 ranged by state from 4.7-8.9 among children and adolescents to 2.2-3.9 for all ages combined., Conclusions: Through May 2021 in selected states, the majority of children with serum specimens included in serosurveys did not have evidence of prior SARS-CoV-2 infection. Case-based surveillance underestimated the number of children infected with SARS-CoV-2 more than among all ages. Continued monitoring of pediatric SARS-CoV-2 antibody seroprevalence should inform prevention and vaccination strategies., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2022.)

Previous reports of COVID-19 case, hospitalization, and death rates by vaccination status † indicate that vaccine protection against infection, as well as serious COVID-19 illness for some groups, declined with the emergence of the B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, and waning of vaccine-induced immunity (1-4). During August-November 2021, CDC recommended § additional primary COVID-19 vaccine doses among immunocompromised persons and booster doses among persons aged ≥18 years (5). The SARS-CoV-2 B.1.1.529 (Omicron) variant emerged in the United States during December 2021 (6) and by December 25 accounted for 72% of sequenced lineages (7). To assess the impact of full vaccination with additional and booster doses (booster doses), ¶ case and death rates and incidence rate ratios (IRRs) were estimated among unvaccinated and fully vaccinated adults by receipt of booster doses during pre-Delta (April-May 2021), Delta emergence (June 2021), Delta predominance (July-November 2021), and Omicron emergence (December 2021) periods in the United States. During 2021, averaged weekly, age-standardized case IRRs among unvaccinated persons compared with fully vaccinated persons decreased from 13.9 pre-Delta to 8.7 as Delta emerged, and to 5.1 during the period of Delta predominance. During October-November, unvaccinated persons had 13.9 and 53.2 times the risks for infection and COVID-19-associated death, respectively, compared with fully vaccinated persons who received booster doses, and 4.0 and 12.7 times the risks compared with fully vaccinated persons without booster doses. When the Omicron variant emerged during December 2021, case IRRs decreased to 4.9 for fully vaccinated persons with booster doses and 2.8 for those without booster doses, relative to October-November 2021. The highest impact of booster doses against infection and death compared with full vaccination without booster doses was recorded among persons aged 50-64 and ≥65 years. Eligible persons should stay up to date with COVID-19 vaccinations., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Leah Eisenstein reports ownership of 100 shares of Pfizer stock. No other potential conflicts of interest were disclosed.

Background: With the emergence of the delta variant, the United States experienced a rapid increase in Covid-19 cases in 2021. We estimated the risk of breakthrough infection and death by month of vaccination as a proxy for waning immunity during a period of delta variant predominance., Methods: Covid-19 case and death data from 15 U.S. jurisdictions during January 3 to September 4, 2021 were used to estimate weekly hazard rates among fully vaccinated persons, stratified by age group and vaccine product. Case and death rates during August 1 to September 4, 2021 were presented across four cohorts defined by month of vaccination. Poisson models were used to estimate adjusted rate ratios comparing the earlier cohorts to July rates., Results: During August 1 to September 4, 2021, case rates per 100,000 person-weeks among all vaccine recipients for the January to February, March to April, May to June, and July cohorts were 168.8 (95% confidence interval [CI], 167.5 to 170.1), 123.5 (95% CI, 122.8 to 124.1), 83.6 (95% CI, 82.9 to 84.3), and 63.1 (95% CI, 61.6 to 64.6), respectively. Similar trends were observed by age group for BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) vaccine recipients. Rates for the Ad26.COV2.S (Janssen-Johnson & Johnson) vaccine were higher; however, trends were inconsistent. BNT162b2 vaccine recipients 65 years of age or older had higher death rates among those vaccinated earlier in the year. Protection against death was sustained for the mRNA-1273 vaccine recipients. Across age groups and vaccine types, people who were vaccinated 6 months ago or longer (January-February) were 3.44 (3.36 to 3.53) times more likely to be infected and 1.70 (1.29 to 2.23) times more likely to die from COVID-19 than people vaccinated recently in July 2021., Conclusions: Our study suggests that protection from SARS-CoV-2 infection among all ages or death among older adults waned with increasing time since vaccination during a period of delta predominance. These results add to the evidence base that supports U.S. booster recommendations, especially for older adults vaccinated with BNT162b2 and recipients of the Ad26.COV2.S vaccine. (Funded by the Centers for Disease Control and Prevention.).

Background: In the USA, COVID-19 vaccines became available in mid-December, 2020, with adults aged 65 years and older among the first groups prioritised for vaccination. We estimated the national-level impact of the initial phases of the US COVID-19 vaccination programme on COVID-19 cases, emergency department visits, hospital admissions, and deaths among adults aged 65 years and older., Methods: We analysed population-based data reported to US federal agencies on COVID-19 cases, emergency department visits, hospital admissions, and deaths among adults aged 50 years and older during the period Nov 1, 2020, to April 10, 2021. We calculated the relative change in incidence among older age groups compared with a younger reference group for pre-vaccination and post-vaccination periods, defined by the week when vaccination coverage in a given age group first exceeded coverage in the reference age group by at least 1%; time lags for immune response and time to outcome were incorporated. We assessed whether the ratio of these relative changes differed when comparing the pre-vaccination and post-vaccination periods., Findings: The ratio of relative changes comparing the change in the COVID-19 case incidence ratio over the post-vaccine versus pre-vaccine periods showed relative decreases of 53% (95% CI 50 to 55) and 62% (59 to 64) among adults aged 65 to 74 years and 75 years and older, respectively, compared with those aged 50 to 64 years. We found similar results for emergency department visits with relative decreases of 61% (52 to 68) for adults aged 65 to 74 years and 77% (71 to 78) for those aged 75 years and older compared with adults aged 50 to 64 years. Hospital admissions declined by 39% (29 to 48) among those aged 60 to 69 years, 60% (54 to 66) among those aged 70 to 79 years, and 68% (62 to 73), among those aged 80 years and older, compared with adults aged 50 to 59 years. COVID-19 deaths also declined (by 41%, 95% CI -14 to 69 among adults aged 65-74 years and by 30%, -47 to 66 among those aged ≥75 years, compared with adults aged 50 to 64 years), but the magnitude of the impact of vaccination roll-out on deaths was unclear., Interpretation: The initial roll-out of the US COVID-19 vaccination programme was associated with reductions in COVID-19 cases, emergency department visits, and hospital admissions among older adults., Funding: None., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Federal and state enforcement authorities have increasingly intervened on the criminal overprescribing of opioids. However, little is known about the health effects these enforcement actions have on patients experiencing disrupted access to prescription opioids or medication-assisted treatment/medication for opioid use disorder. Simultaneously, opioid death rates have increased. In response, the Maryland Department of Health (MDH) has worked to coordinate mitigation strategies with enforcement partners (defined as any federal, state, or local enforcement authority or other governmental investigative authority). One strategy is a standardized protocol to implement emergency response functions, including rapidly identifying health hazards with real-time data access, deploying resources locally, and providing credible messages to partners and the public. From January 2018 through October 2019, MDH used the protocol in response to 12 enforcement actions targeting 34 medical professionals. A total of 9624 patients received Schedule II-V controlled substance prescriptions from affected prescribers under investigation in the 6 months before the respective enforcement action; 9270 (96%) patients were residents of Maryland. Preliminary data indicate fatal overdose events and potential loss of follow-up care among the patient population experiencing disrupted health care as a result of an enforcement action. The success of the strategy hinged on endorsement by leadership; the establishment of federal, state, and local roles and responsibilities; and data sharing. MDH's approach, data sources, and lessons learned may support health departments across the country that are interested in conducting similar activities on the front lines of the opioid crisis.

COVID-19 vaccine breakthrough infection surveillance helps monitor trends in disease incidence and severe outcomes in fully vaccinated persons, including the impact of the highly transmissible B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19. Reported COVID-19 cases, hospitalizations, and deaths occurring among persons aged ≥18 years during April 4-July 17, 2021, were analyzed by vaccination status across 13 U.S. jurisdictions that routinely linked case surveillance and immunization registry data. Averaged weekly, age-standardized incidence rate ratios (IRRs) for cases among persons who were not fully vaccinated compared with those among fully vaccinated persons decreased from 11.1 (95% confidence interval [CI] = 7.8-15.8) to 4.6 (95% CI = 2.5-8.5) between two periods when prevalence of the Delta variant was lower (<50% of sequenced isolates; April 4-June 19) and higher (≥50%; June 20-July 17), and IRRs for hospitalizations and deaths decreased between the same two periods, from 13.3 (95% CI = 11.3-15.6) to 10.4 (95% CI = 8.1-13.3) and from 16.6 (95% CI = 13.5-20.4) to 11.3 (95% CI = 9.1-13.9). Findings were consistent with a potential decline in vaccine protection against confirmed SARS-CoV-2 infection and continued strong protection against COVID-19-associated hospitalization and death. Getting vaccinated protects against severe illness from COVID-19, including the Delta variant, and monitoring COVID-19 incidence by vaccination status might provide early signals of changes in vaccine-related protection that can be confirmed through well-controlled vaccine effectiveness (VE) studies., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Janelle Delgadillo reports grant support from the Utah Department of Health. Ruth Lynfield reports that she is president of the Council of State and Territorial Epidemiologists, Secretary of the National Foundation for Infectious Diseases, and Associate Editor of the American Academy of Pediatrics Red Book (the fee for which is donated to the Minnesota Department of Health). Rachel K. Herlihy reports funding from the Council of State and Territorial Epidemiologists for travel to meetings and conferences. No other potential conflicts of interest were disclosed.

Although COVID-19 generally results in milder disease in children and adolescents than in adults, severe illness from COVID-19 can occur in children and adolescents and might require hospitalization and intensive care unit (ICU) support (1-3). It is not known whether the B.1.617.2 (Delta) variant,* which has been the predominant variant of SARS-CoV-2 (the virus that causes COVID-19) in the United States since late June 2021, † causes different clinical outcomes in children and adolescents compared with variants that circulated earlier. To assess trends among children and adolescents, CDC analyzed new COVID-19 cases, emergency department (ED) visits with a COVID-19 diagnosis code, and hospital admissions of patients with confirmed COVID-19 among persons aged 0-17 years during August 1, 2020-August 27, 2021. Since July 2021, after Delta had become the predominant circulating variant, the rate of new COVID-19 cases and COVID-19-related ED visits increased for persons aged 0-4, 5-11, and 12-17 years, and hospital admissions of patients with confirmed COVID-19 increased for persons aged 0-17 years. Among persons aged 0-17 years during the most recent 2-week period (August 14-27, 2021), COVID-19-related ED visits and hospital admissions in the states with the lowest vaccination coverage were 3.4 and 3.7 times that in the states with the highest vaccination coverage, respectively. At selected hospitals, the proportion of COVID-19 patients aged 0-17 years who were admitted to an ICU ranged from 10% to 25% during August 2020-June 2021 and was 20% and 18% during July and August 2021, respectively. Broad, community-wide vaccination of all eligible persons is a critical component of mitigation strategies to protect pediatric populations from SARS-CoV-2 infection and severe COVID-19 illness., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Sapna Bamrah Morris serves on the data safety monitoring board for the PaTS COVID Cohort2 Trial (Africa). No other potential conflicts of interest were disclosed.

Population-based analyses of COVID-19 data, by race and ethnicity can identify and monitor disparities in COVID-19 outcomes and vaccination coverage. CDC recommends that information about race and ethnicity be collected to identify disparities and ensure equitable access to protective measures such as vaccines; however, this information is often missing in COVID-19 data reported to CDC. Baseline data collection requirements of the Office of Management and Budget's Standards for the Classification of Federal Data on Race and Ethnicity (Statistical Policy Directive No. 15) include two ethnicity categories and a minimum of five race categories (1). Using available COVID-19 case and vaccination data, CDC compared the current method for grouping persons by race and ethnicity, which prioritizes ethnicity (in alignment with the policy directive), with two alternative methods (methods A and B) that used race information when ethnicity information was missing. Method A assumed non-Hispanic ethnicity when ethnicity data were unknown or missing and used the same population groupings (denominators) for rate calculations as the current method (Hispanic persons for the Hispanic group and race category and non-Hispanic persons for the different racial groups). Method B grouped persons into ethnicity and race categories that are not mutually exclusive, unlike the current method and method A. Denominators for rate calculations using method B were Hispanic persons for the Hispanic group and persons of Hispanic or non-Hispanic ethnicity for the different racial groups. Compared with the current method, the alternative methods resulted in higher counts of COVID-19 cases and fully vaccinated persons across race categories (American Indian or Alaska Native [AI/AN], Asian, Black or African American [Black], Native Hawaiian or Other Pacific Islander [NH/PI], and White persons). When method B was used, the largest relative increase in cases (58.5%) was among AI/AN persons and the largest relative increase in the number of those fully vaccinated persons was among NH/PI persons (51.6%). Compared with the current method, method A resulted in higher cumulative incidence and vaccination coverage rates for the five racial groups. Method B resulted in decreasing cumulative incidence rates for two groups (AI/AN and NH/PI persons) and decreasing cumulative vaccination coverage rates for AI/AN persons. The rate ratio for having a case of COVID-19 by racial and ethnic group compared with that for White persons varied by method but was <1 for Asian persons and >1 for other groups across all three methods. The likelihood of being fully vaccinated was highest among NH/PI persons across all three methods. This analysis demonstrates that alternative methods for analyzing race and ethnicity data when data are incomplete can lead to different conclusions about disparities. These methods have limitations, however, and warrant further examination of potential bias and consultation with experts to identify additional methods for analyzing and tracking disparities when race and ethnicity data are incomplete., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Throughout the COVID-19 pandemic, older U.S. adults have been at increased risk for severe COVID-19-associated illness and death (1). On December 14, 2020, the United States began a nationwide vaccination campaign after the Food and Drug Administration's Emergency Use Authorization of Pfizer-BioNTech COVID-19 vaccine. The Advisory Committee on Immunization Practices (ACIP) recommended prioritizing health care personnel and residents of long-term care facilities, followed by essential workers and persons at risk for severe illness, including adults aged ≥65 years, in the early phases of the vaccination program (2). By May 1, 2021, 82%, 63%, and 42% of persons aged ≥65, 50-64, and 18-49 years, respectively, had received ≥1 COVID-19 vaccine dose. CDC calculated the rates of COVID-19 cases, emergency department (ED) visits, hospital admissions, and deaths by age group during November 29-December 12, 2020 (prevaccine) and April 18-May 1, 2021. The rate ratios comparing the oldest age groups (≥70 years for hospital admissions; ≥65 years for other measures) with adults aged 18-49 years were 40%, 59%, 65%, and 66% lower, respectively, in the latter period. These differential declines are likely due, in part, to higher COVID-19 vaccination coverage among older adults, highlighting the potential benefits of rapidly increasing vaccination coverage., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Creatine is one of the most studied and popular ergogenic aids for athletes and recreational weightlifters seeking to improve sport and exercise performance, augment exercise training adaptations, and mitigate recovery time. Studies consistently reveal that creatine supplementation exerts positive ergogenic effects on single and multiple bouts of short-duration, high-intensity exercise activities, in addition to potentiating exercise training adaptations. In this respect, supplementation consistently demonstrates the ability to enlarge the pool of intracellular creatine, leading to an amplification of the cell's ability to resynthesize adenosine triphosphate. This intracellular expansion is associated with several performance outcomes, including increases in maximal strength (low-speed strength), maximal work output, power production (high-speed strength), sprint performance, and fat-free mass. Additionally, creatine supplementation may speed up recovery time between bouts of intense exercise by mitigating muscle damage and promoting the faster recovery of lost force-production potential. Conversely, contradictory findings exist in the literature regarding the potential ergogenic benefits of creatine during intermittent and continuous endurance-type exercise, as well as in those athletic tasks where an increase in body mass may hinder enhanced performance. The purpose of this review was to summarize the existing literature surrounding the efficacy of creatine supplementation on exercise and sports performance, along with recovery factors in healthy populations.

Background: Prescription Drug Monitoring Programs (PDMPs) collect controlled substance prescriptions dispensed within a state. Many PDMP programs perform targeted outreach (i.e., "unsolicited reporting") for patients who exceed numerical thresholds, however, the degree to which patients at highest risk of fatal opioid overdose are identified has not been compared with one another or with a predictive model. Methods: A retrospective analysis was performed using statewide PDMP data for Maryland residents aged 18 to 80 years with an opioid fill between April to June 2015. The outcome was opioid-related overdose death in 2015 or 2016. A multivariable logistic regression model and three PDMP thresholds were evaluated: (1) multiple provider episodes; (2) high daily average morphine milligram equivalents (MME); and (3) overlapping opioid and benzodiazepine prescriptions. Results: The validation cohort consisted of 170,433 individuals and 244 deaths. The predictive model captured more individuals who died (46.3% of total deaths) and had a higher death rate (7.12 per 1000) when the risk score cutoff (0.0030) was selected for a comparable size of high-risk individuals ( n  = 15,881) than those meeting the overlapping opioid/benzodiazepine prescriptions ( n  = 17,440; 33.2% of total deaths; 4.64 deaths per 1000) and high MME ( n  = 14,675; 24.6% of total deaths; 4.09 deaths per 1000) thresholds. Conclusions: The predictive model identified more individuals at risk of fatal opioid overdose as compared with PDMP thresholds commonly used for unsolicited reporting. PDMP programs could improve their targeting of unsolicited reports to reach more individuals at risk of overdose by using predictive models instead of simple threshold-based approaches.

Background and Aims: Evidence from randomized controlled trials establishes that medication treatment with methadone and buprenorphine reduces opioid use and improves treatment retention. However, little is known about the role of such medications compared with non-medication treatments in mitigating overdose risk among US patient populations receiving treatment in usual care settings. This study compared overdose mortality among those in medication versus non-medication treatments in specialty care settings., Design: Retrospective cohort study using state-wide treatment data linked to death records. Survival analysis was used to analyze data in a time-to-event framework., Setting: Services delivered by 757 providers in publicly funded out-patient specialty treatment programs in Maryland, USA between 1 January 2015 and 31 December 2016., Participants: A total of 48 274 adults admitted to out-patient specialty treatment programs in 2015-16 for primary diagnosis of opioid use disorder., Measurements: Main exposure was time in medication treatment (methadone/buprenorphine), time following medication treatment, time exposed to non-medication treatments and time following non-medication treatment. Main outcome was opioid overdose death during and after treatment. Hazard ratios were calculated using Cox proportional hazard regression. Propensity score weights were adjusted for patient information on sex, age, race, region of residence, marital and veteran status, employment, homelessness, primary opioid, mental health treatment, arrests and criminal justice referral., Findings: The study population experienced 371 opioid overdose deaths. Periods in medication treatment were associated with substantially reduced hazard of opioid overdose death compared with periods in non-medication treatment [adjusted hazard ratio (aHR) = 0.18, 95% confidence interval (CI) = 0.08-0.40]. Periods after discharge from non-medication treatment (aHR = 5.45, 95% CI = 2.80-9.53) and medication treatment (aHR = 5.85, 95% CI = 3.10-11.02) had similar and substantially elevated risks compared with periods in non-medication treatments., Conclusions: Among Maryland patients in specialty opioid treatment, periods in treatment are protective against overdose compared with periods out of care. Methadone and buprenorphine are associated with significantly lower overdose death compared with non-medication treatments during care but not after treatment is discontinued., (© 2020 Society for the Study of Addiction.)

Study Objective: Persons with substance use disorders frequently utilize emergency department (ED) services, creating an opportunity for intervention and referral to addiction treatment and harm-reduction services. However, EDs may not have the appropriate tools to distinguish which patients are at greatest risk for negative outcomes. We link hospital ED and medical examiner mortality databases in one state to identify individual-level risk factors associated with overdose death among ED patients with substance-related encounters., Methods: This retrospective cohort study linked Maryland statewide ED hospital claims records for adults with nonfatal overdose or substance use disorder encounters in 2014 to 2015 with medical examiner mortality records in 2015 to 2016. Logistic regression was used to identify factors in hospital records associated with risk of opioid overdose death. Predicted probabilities for overdose death were calculated for hypothetical patients with different combinations of overdose and substance use diagnostic histories., Results: A total of 139,252 patients had substance-related ED encounters in 2014 to 2015. Of these patients, 963 later experienced an opioid overdose death, indicating a case fatality rate of 69.2 per 10,000 patients, 6 times higher than that of patients who used the ED for any cause. Factors most strongly associated with death included having both an opioid and another substance use disorder (adjusted odds ratio 2.88; 95% confidence interval 2.04 to 4.07), having greater than or equal to 3 previous nonfatal overdoses (adjusted odds ratio 2.89; 95% confidence interval 1.54 to 5.43), and having a previous nonfatal overdose involving heroin (adjusted odds ratio 2.24; 95% confidence interval 1.64 to 3.05)., Conclusion: These results highlight important differences in overdose risk among patients receiving care in EDs for substance-related conditions. The findings demonstrate the potential utility of incorporating routine data from patient records to assess risk of future negative outcomes and identify primary targets for initiation and linkage to lifesaving care., (Copyright © 2019 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

Introduction: Prescription Drug Monitoring Program data can provide insights into a patient's likelihood of an opioid overdose, yet clinicians and public health officials lack indicators to identify individuals at highest risk accurately. A predictive model was developed and validated using Prescription Drug Monitoring Program prescription histories to identify those at risk for fatal overdose because of any opioid or illicit opioids., Methods: From December 2018 to July 2019, a retrospective cohort analysis was performed on Maryland residents aged 18-80 years with a filled opioid prescription (n=565,175) from January to June 2016. Fatal opioid overdoses were identified from the Office of the Chief Medical Examiner and were linked at the person-level with Prescription Drug Monitoring Program data. Split-half technique was used to develop and validate a multivariate logistic regression with a 6-month lookback period and assessed model calibration and discrimination., Results: Predictors of any opioid-related fatal overdose included male sex, age 65-80 years, Medicaid, Medicare, 1 or more long-acting opioid fills, 1 or more buprenorphine fills, 2 to 3 and 4 or more short-acting schedule II opioid fills, opioid days' supply ≥91 days, average morphine milligram equivalent daily dose, 2 or more benzodiazepine fills, and 1 or more muscle relaxant fills. Model discrimination for the validation cohort was good (area under the curve: any, 0.81; illicit, 0.77)., Conclusions: A model for predicting fatal opioid overdoses was developed using Prescription Drug Monitoring Program data. Given the recent national epidemic of deaths involving heroin and fentanyl, it is noteworthy that the model performed equally well in identifying those at risk for overdose deaths from both illicit and prescription opioids., (Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: Predicting which individuals who are prescribed buprenorphine for opioid use disorder are most likely to experience an overdose can help target interventions to prevent relapse and subsequent consequences., Methods: We used Maryland prescription drug monitoring data from 2015 to identify risk factors for nonfatal opioid overdoses that were identified in hospital discharge records in 2016. We developed a predictive risk model for prospective nonfatal opioid overdoses among buprenorphine patients (N = 25,487). We estimated a series of models that included demographics plus opioid, buprenorphine and benzodiazepine prescription variables. We applied logistic regression to generate performance measures., Results: About 3.24% of the study cohort had ≥1 nonfatal opioid overdoses. In the model with all predictors, odds of nonfatal overdoses among buprenorphine patients were higher among males (OR = 1.39, 95% CI:1.21-1.62) and those with more buprenorphine pharmacies (OR = 1.19, 95% CI:1.11-1.28), 1+ buprenorphine prescription paid by Medicaid (OR = 1.21, 95% CI:1.02-1.48), Medicare (OR = 1.93, 95% CI:1.63-2.43), or a commercial plan (OR = 1.98, 95% CI:1.30-2.89), 1+ opioid prescription paid by Medicare (OR = 1.30, 95% CI:1.03-1.68), and more benzodiazepine prescriptions (OR = 1.04, 95% CI:1.02-1.05). The odds were lower among those with longer days of buprenorphine (OR = 0.64, 95% CI:0.60-0.69) or opioid (OR = 0.79, 95% CI:0.65-0.95) supply. The model had moderate predictive ability (c-statistic = 0.69)., Conclusions: Several modifiable risk factors, such as length of buprenorphine treatment, may be targets for interventions to improve clinical care and reduce harms. This model could be practically implemented with common prescription-related information and allow payers and clinical systems to better target overdose risk reduction interventions, such as naloxone distribution., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Lyons, BC, Mayo, JJ, Tucker, WS, Wax, B, and Hendrix, RC. Electromyographical comparison of muscle activation patterns across 3 commonly performed kettlebell exercises. J Strength Cond Res 31(9): 2363-2370, 2017-The purpose of this study was to compare the muscle activation patterns of 3 different kettlebell (KB) exercises using electromyography (EMG). Fourteen resistance-trained subjects completed a 1-arm swing (Swing), 1-arm swing style snatch (Snatch), and a 1-arm clean (Clean) using a self-selected 8 to 10 repetition maximum load for each exercise. Trial sessions consisted of subjects performing 5 repetitions of each KB exercise. Mean EMG was used to assess the muscle activation of the biceps brachii, anterior deltoid, posterior deltoid, erector spinae (ES), vastus lateralis (VL), biceps femoris, contralateral external oblique (EO), and gluteus maximus during each lift using surface electrodes. The mean EMG was normalized using maximal voluntary contractions obtained from manual muscle testing. Repeated-measures analysis of variance revealed a significant difference in the muscle activation patterns of the ES (Swing > Snatch), EO (Snatch, Clean > Swing), and VL (Swing > Clean) across the 3 KB exercises. We conclude that although the KB Swing, Snatch, and Clean are total body exercises, they place different demands on the ES, contralateral EO, and the VL. Therefore, KBs represent an authentic alternative for lifters, and the Swing, Snatch, and Clean are not redundant exercises.

Bat velocity is considered to be an important factor for successful hitting. The relationship between grip strength and bat velocity has not been conclusively established. The purposes of this study were to determine the relationship of grip strength to bat velocity and to ascertain whether the performance of resistance training exercises designed to specifically target the forearms and grip would significantly alter bat velocity. The subjects for this study were 23 male members (mean +/- SD, age = 19.7 +/- 1.3 years, height = 182.5 +/- 5.9 cm, weight = 85.4 +/- 15.5 kg, experience = 14.4 +/- 1.7 years) of a varsity baseball team at a National Collegiate Athletic Association Division II school. The Jamar hand dynamometer was used to test grip strength, and the SETPRO Rookie was used to measure instantaneous bat velocity at the point of contact with the ball. Subjects were randomly divided into an experimental group and a control group. For 6 weeks, both groups participated in their usual baseball practice sessions, but the experimental group also performed extra forearm and grip strengthening exercises, whereas the control group did not. Pretest and posttest correlations between grip strength and bat velocity revealed no significant relationship between grip strength and bat velocity (pretest r = 0.054, p = 0.807; posttest r = 0.315, p = 0.145). A dependent t-test performed on all subjects revealed that a significant (p = 0.001) increase in bat velocity did occur over the course of the study. A covariate analysis, employing pretest bat velocity as the covariate, revealed no significant difference (p = 0.795) in posttest bat velocity scores between the experimental and control groups. Thus, increases in bat velocity occurred, but the differences were similar for both the experimental and control groups. The findings of this study suggest that grip strength and bat velocity are not significantly related, and that the allocation of time and energy for added training of the forearms in order to improve grip strength for the purpose of increasing bat velocity may not be warranted.