Substantial health and economic burden of COVID-19 during the year after acute illness among US adults at high risk of severe COVID-19.

BACKGROUND: Post-COVID conditions encompass a range of long-term symptoms after SARS-CoV-2 infection. The potential clinical and economic burden in the United States is unclear. We evaluated diagnoses, medications, healthcare use, and medical costs before and after acute COVID-19 illness in US patients at high risk of severe COVID-19. METHODS: Eligible adults were diagnosed with COVID-19 from April 1 to May 31, 2020, had ≥ 1 condition placing them at risk of severe COVID-19, and were enrolled in Optum's de-identified Clinformatics® Data Mart Database for ≥ 12 months before and ≥ 13 months after COVID-19 diagnosis. Percentages of diagnoses, medications, resource use, and costs were calculated during baseline (12 months preceding diagnosis) and the post-acute phase (12 months after the 30-day acute phase of COVID-19). Data were stratified by age and COVID-19 severity. RESULTS: The cohort included 19,558 patients (aged 18-64 y, n = 9381; aged ≥ 65 y, n = 10,177). Compared with baseline, patients during the post-acute phase had increased percentages of blood disorders (16.3%), nervous system disorders (11.1%), and mental and behavioral disorders (7.7%), along with increases in related prescriptions. Overall, there were substantial increases in inpatient and outpatient healthcare utilization, along with a 23.0% increase in medical costs. Changes were greatest among older patients and those admitted to the intensive care unit for acute COVID-19 but were also observed in younger patients and those who did not require COVID-19 hospitalization. CONCLUSIONS: There is a significant clinical and economic burden of post-COVID conditions among US individuals at high risk for severe COVID-19.

Coronavirus Disease 2019 Severity and Risk of Subsequent Cardiovascular Events.

BACKGROUND: Little is known about the relationship between coronavirus disease 2019 (COVID-19) severity and subsequent risk of experiencing a cardiovascular event (CVE) after COVID-19 recovery. We evaluated this relationship in a large cohort of United States adults. METHODS: Using a claims database, we performed a retrospective cohort study of adults diagnosed with COVID-19 between 1 April 2020 and 31 May 2021. We evaluated the association between COVID-19 severity and risk of CVE >30 days after COVID-19 diagnosis using inverse probability of treatment-weighted competing risks regression. Severity was based on level of care required for COVID-19 treatment: intensive care unit (ICU) admission, non-ICU hospitalization, or outpatient care only. RESULTS: A total of 1 357 518 COVID-19 patients were included (2% ICU, 3% non-ICU hospitalization, and 95% outpatient only). Compared to outpatients, there was an increased risk of any CVE for patients requiring ICU admission (adjusted hazard ratio [aHR], 1.80 [95% confidence interval {CI}, 1.71-1.89]) or non-ICU hospitalization (aHR, 1.28 [95% CI, 1.24-1.33]). Risk of subsequent hospitalization for CVE was even higher (aHRs, 3.47 [95% CI, 3.20-3.76] for ICU and 1.96 [95% CI, 1.85-2.09] for non-ICU hospitalized vs outpatient only). CONCLUSIONS: COVID-19 patients hospitalized or requiring critical care had a significantly higher risk of experiencing and being hospitalized for post-COVID-19 CVE than patients with milder COVID-19 who were managed solely in the outpatient setting, even after adjusting for differences between these groups. These findings underscore the continued importance of preventing severe acute respiratory syndrome coronavirus 2 infection from progressing to severe illness to reduce potential long-term cardiovascular complications.

Utilization of nonguideline concordant antibiotic treatment following acute otitis media in children in the United States.

PURPOSE: Acute otitis media (AOM) is a common indication for antibiotics in children. We sought to characterize the frequency of nonguideline concordant antibiotic therapy for AOM in the United States, by agent and duration. METHODS: Using national administrative claims data (2016-2019), we identified children aged 6 months to 17 years with an oral antibiotic dispensed within 3 days of a new diagnosis of suppurative AOM. Use of nonguideline concordant agents and durations, defined based on national treatment guidelines, were summarized by age, race, rurality, region, and insurance type. Subsequent oral antibiotic dispensing within the year after AOM diagnosis was also evaluated. We created sunburst diagrams to visualize longitudinal patterns of within-person antibiotic utilization for AOM, by agent and duration. RESULTS: We identified 789 424 eligible commercially-insured and 502 239 medicaid-insured children. Among commercially insured children, 35% received nonguideline concordant agents for AOM, including cefdinir (16%), amoxicillin-clavulanate (12%), and azithromycin (7%). Fewer children age <2 years received a nonguideline concordant initial agent (27%) compared to age ≥6 years (41%). More children age <2 years received three or more antibiotics over the following year (34% vs. 3% for children age ≥6 years). The most common treatment duration was 10 days for all ages; treatment duration for the initial antibiotic was nonguideline concordant for 95% and 89% of children age 2-5 years and ≥6 years, respectively. Patterns were similar for medicaid-insured children. CONCLUSIONS: Nonguideline concordant antibiotic use is common when treating AOM in children, including use of broad-spectrum agents and longer-than-recommended antibiotic durations.

Comparative Effectiveness of High-Dose Versus Standard-Dose Influenza Vaccine Among Patients Receiving Maintenance Hemodialysis.

RATIONALE & OBJECTIVE: Studies of patients on maintenance dialysis therapy suggest that standard-dose influenza vaccine (SDV) may not prevent influenza-related outcomes. Little is known about the comparative effectiveness of SDV versus high-dose influenza vaccine (HDV) in this population. STUDY DESIGN: Cohort study using data from the US Renal Data System. SETTING & PARTICIPANTS: 507,552 adults undergoing in-center maintenance hemodialysis between the 2010 to 2011 and 2014 to 2015 influenza seasons. EXPOSURES: SDV and HDV. OUTCOMES: All-cause mortality, hospitalization due to influenza or pneumonia, and influenza-like illness during the influenza season. ANALYTIC APPROACH: Patients were eligible for inclusion in multiple yearly cohorts; thus, our unit of analysis was the influenza patient-season. To examine the relationship between vaccine dose and effectiveness outcomes, we estimated risk differences and risk ratios using propensity score weighting of Kaplan-Meier functions, accounting for a wide range of patient- and facility-level characteristics. For nonmortality outcomes, we used competing-risk methods to account for the high mortality rate in the dialysis population. RESULTS: Within 225,215 influenza patient-seasons among adults 65 years and older, 97.4% received SDV and 2.6% received HDV. We observed similar risk estimates for HDV and SDV recipients for mortality (risk difference, -0.08%; 95% CI, -0.85% to 0.80%), hospitalization due to influenza or pneumonia (risk difference, 0.15%; 95% CI, -0.69% to 0.93%), and influenza-like illness (risk difference, 0.00%; 95% CI, -1.50% to 1.08%). Our findings were similar among adults younger than 65 years, as well as within other subgroups defined by influenza season, age group, dialysis vintage, month of influenza vaccination, and vaccine valence. LIMITATIONS: Residual confounding and outcome misclassification. CONCLUSIONS: The HDV does not appear to provide additional protection beyond the SDV against all-cause mortality or influenza-related outcomes for adults undergoing hemodialysis. The additional cost and side effects associated with HDV should be considered when offering this vaccine. Future studies of HDV and other influenza vaccine strategies are warranted.

Who are we missing? Underrepresentation of data sources used for pharmacoepidemiology research in the United States.

PURPOSE: Research using healthcare databases often includes patients frequently excluded from clinical trials; yet it is not known whether commonly used data represents the overall population or specific sub-populations of interest. We aimed to examine population representativeness from data sources in recent research studies in the United States (US). METHODS: We identified data sources from abstracts accepted to the 34th International Conference on Pharmacoepidemiology & Therapeutic Risk Management. The final sample included research studies using ≥1 data source from the US. We classified data sources broadly as claims, linkage, electronic health records (EHR), survey, distributed data network, and other. Studies using claims and EHRs were further classified into more specific categories, including special populations of interest (eg, children). RESULTS: We identified 356 abstracts. The majority used claims data (n = 201, 56.5%), followed by data linkages (n = 46, 12.9%), and EHR data (n = 39, 11.0%). Among EHR studies, most (n = 16, 41.0%) came from network data sources (eg, Kaiser Permanente). Almost half (49.4%) of claims-based studies used commercial claims data sources, followed by Medicare (22.1%), Medicaid (11.3%), and Medicare Supplemental (6.1%). Only 15% of studies included children in the study population (n = 53), with 8% focused on a pediatric topic (n = 27). CONCLUSIONS: We find that certain populations in the US are under-represented in pharmacoepidemiology, particularly Medicaid enrollees and children. Researchers should strive to utilize data sources that may be more representative of the US population, particularly vulnerable populations.

Using negative control outcomes to assess the comparability of treatment groups among women with osteoporosis in the United States.

PURPOSE: In contrast to randomized clinical trials, comparative safety and effectiveness assessments of osteoporosis medications in clinical practice may be subject to confounding by indication. We used negative control outcomes to detect residual confounding when comparing osteoporosis medications. METHODS: Using MarketScan Commercial and Supplemental claims, we identified women aged ≥55 years who initiated an oral bisphosphonate (BP) (risedronate, alendronate, or ibandronate), denosumab (an injected biologic), or intravenous zoledronic acid (ZA) from October 1, 2010 to September 30, 2015. Women with Paget's disease or cancer were excluded. We compared individual oral BPs to each other, denosumab to ZA, denosumab to oral BPs, and ZA to oral BPs, with respect to 11 negative control outcomes identified by subject matter experts. We estimated the 12-month cumulative risk difference (RD) using inverse probability of treatment and censoring weights. RESULTS: Among 148 587 women, most initiated alendronate (57%), followed by ibandronate (12%), ZA (11%), risedronate (10%), and denosumab (10%). Compared with denosumab, patients initiating ZA had similar risks of all negative control outcomes. Compared with oral BPs, patients initiating denosumab had a higher risk of a wellness visit (RD = 1.2%, 95% CI: 0.4, 1.9) and a lower risk of receiving herpes zoster vaccine (RD = -0.6%, 95% CI: -1.1, -0.2). Comparing ZA with oral BP initiators resulted in two outcomes with positive associations. CONCLUSIONS: Caution is warranted when comparing injectable vs oral osteoporosis medications, given the potential for unmeasured confounding. Evaluating negative control outcomes could be a standard validity check prior to conducting comparative studies.

Restriction of Pharmacoepidemiologic Cohorts to Initiators of Medications in Unrelated Preventive Drug Classes to Reduce Confounding by Frailty in Older Adults.

Nonexperimental studies of the effectiveness of seasonal influenza vaccine in older adults have found 40%-60% reductions in all-cause mortality associated with vaccination, potentially due to confounding by frailty. We restricted our cohort to initiators of medications in preventive drug classes (statins, antiglaucoma drugs, and ß blockers) as an approach to reducing confounding by frailty by excluding frail older adults who would not initiate use of these drugs. Using a random 20% sample of US Medicare beneficiaries, we framed our study as a series of nonrandomized "trials" comparing vaccinated beneficiaries with unvaccinated beneficiaries who had an outpatient health-care visit during the 5 influenza seasons occurring in 2010-2015. We pooled data across trials and used standardized-mortality-ratio-weighted Cox proportional hazards models to estimate the association between influenza vaccination and all-cause mortality before influenza season, expecting a null association. Weighted hazard ratios among preventive drug initiators were generally closer to the null than those in the nonrestricted cohort. Restriction of the study population to statin initiators with an uncensored approach resulted in a weighted hazard ratio of 1.00 (95% confidence interval: 0.84, 1.19), and several other hazard ratios were above 0.95. Restricting the cohort to initiators of medications in preventive drug classes can reduce confounding by frailty in this setting, but further work is required to determine the most appropriate criteria to use.

Assessing Residual Bias in Estimating Influenza Vaccine Effectiveness: Comparison of High-dose Versus Standard-dose Vaccines.

BACKGROUND: Estimating influenza vaccine effectiveness using an unvaccinated comparison group may result in biased effect estimates. OBJECTIVES: To explore the reduction of confounding bias in an active comparison of high-dose versus standard-dose influenza vaccines, as compared with vaccinated versus unvaccinated comparisons. METHODS: Using Medicare data from the United States end-stage renal disease program (2009-2013), we compared the risk of all-cause mortality among recipients of high-dose vaccine (HDV) versus standard-dose vaccine (SDV), HDV versus no vaccine, and SDV versus no vaccine. To quantify confounding bias, analyses were restricted to the preinfluenza season, when the protective effect of vaccination should not yet be observed. We estimated the standardized mortality ratio-weighted cumulative incidence functions using Kaplan-Meier methods and calculated risk ratios (RRs) and risk differences between groups. RESULTS: Among 350,921 eligible patients contributing 825,642 unique patient preinfluenza seasons, 0.8% received HDV, 70.5% received SDV, and 28.7% remained unvaccinated. Comparisons with unvaccinated patients yielded spurious decreases in mortality risk during the preinfluenza period, for HDV versus none [RR, 0.60; 95% confidence interval (CI), 0.51-0.70)] and SDV versus none (RR, 0.72; 95% CI, 0.70-0.75). The effect estimate was attenuated in the HDV versus SDV comparison (RR, 0.89; 95% CI, 0.77-1.03). Estimates on the absolute scale followed a similar pattern. CONCLUSIONS: The HDV versus SDV comparison yielded less-biased estimates of the all-cause mortality before influenza season compared to those with nonuser comparison groups. Vaccine effectiveness and safety researchers should consider the active comparator design to reduce bias due to differences in underlying health status between vaccinated and unvaccinated individuals.

Controlling confounding by frailty when estimating influenza vaccine effectiveness using predictors of dependency in activities of daily living.

PURPOSE: To improve control of confounding by frailty when estimating the effect of influenza vaccination on all-cause mortality by controlling for a published set of claims-based predictors of dependency in activities of daily living (ADL). METHODS: Using Medicare claims data, a cohort of beneficiaries >65 years of age was followed from September 1, 2007, to April 12, 2008, with covariates assessed in the 6 months before follow-up. We estimated Cox proportional hazards models of all-cause mortality, with influenza vaccination as a time-varying exposure. We controlled for common demographics, comorbidities, and health care utilization variables and then added 20 ADL dependency predictors. To gauge residual confounding, we estimated pre-influenza season hazard ratios (HRs) between September 1, 2007 and January 5, 2008, which should be 1.0 in the absence of bias. RESULTS: A cohort of 2 235 140 beneficiaries was created, with a median follow-up of 224 days. Overall, 52% were vaccinated and 4% died during follow-up. During the pre-influenza season period, controlling for demographics, comorbidities, and health care use resulted in a HR of 0.66 (0.64, 0.67). Adding the ADL dependency predictors moved the HR to 0.68 (0.67, 0.70). Controlling for demographics and ADL dependency predictors alone resulted in a HR of 0.68 (0.66, 0.70). CONCLUSIONS: Results were consistent with those in the literature, with significant uncontrolled confounding after adjustment for demographics, comorbidities, and health care use. Adding ADL dependency predictors moved HRs slightly closer to the null. Of the comorbidities, health care use variables, and ADL dependency predictors, the last set reduced confounding most. However, substantial uncontrolled confounding remained.

Controlling Time-Dependent Confounding by Health Status and Frailty: Restriction Versus Statistical Adjustment.

Nonexperimental studies of preventive interventions are often biased because of the healthy-user effect and, in frail populations, because of confounding by functional status. Bias is evident when estimating influenza vaccine effectiveness, even after adjustment for claims-based indicators of illness. We explored bias reduction methods while estimating vaccine effectiveness in a cohort of adult hemodialysis patients. Using the United States Renal Data System and linked data from a commercial dialysis provider, we estimated vaccine effectiveness using a Cox proportional hazards marginal structural model of all-cause mortality before and during 3 influenza seasons in 2005/2006 through 2007/2008. To improve confounding control, we added frailty indicators to the model, measured time-varying confounders at different time intervals, and restricted the sample in multiple ways. Crude and baseline-adjusted marginal structural models remained strongly biased. Restricting to a healthier population removed some unmeasured confounding; however, this reduced the sample size, resulting in wide confidence intervals. We estimated an influenza vaccine effectiveness of 9% (hazard ratio = 0.91, 95% confidence interval: 0.72, 1.15) when bias was minimized through cohort restriction. In this study, the healthy-user bias could not be controlled through statistical adjustment; however, sample restriction reduced much of the bias.

Evolving methods for inference in the presence of healthy worker survivor bias.

Healthy worker survivor bias may occur in occupational studies due to the tendency for unhealthy individuals to leave work earlier, and consequently accrue less exposure, compared with their healthier counterparts. If occupational data are not analyzed using appropriate methods, this bias can result in attenuation or even reversal of the estimated effects of exposures on health outcomes. Recent advances in computing power, coupled with state-of-the-art statistical methods, have greatly increased the ability of analysts to control healthy worker survivor bias. However, these methods have not been widely adopted by occupational epidemiologists. We update the seminal review by Arrighi and Hertz-Picciotto (Epidemiology.1994; 5: 186-196) of the sources and methods to control healthy worker survivor bias. In our update, we discuss methodologic advances since the publication of that review, notably with a consideration of how directed acyclic graphs can inform the choice of appropriate analytic methods. We summarize and discuss methods for addressing this bias, including recent work applying g-methods to account for employment status as a time-varying covariate affected by prior exposure. In the presence of healthy worker survivor bias, g-methods have advantages for estimating less biased parameters that have direct policy implications and are clearly communicated to decision-makers.

Occupational radon exposure and lung cancer mortality: estimating intervention effects using the parametric g-formula.

BACKGROUND: Traditional regression analysis techniques used to estimate associations between occupational radon exposure and lung cancer focus on estimating the effect of cumulative radon exposure on lung cancer. In contrast, public health interventions are typically based on regulating radon concentration rather than workers' cumulative exposure. Estimating the effect of cumulative occupational exposure on lung cancer may be difficult in situations vulnerable to the healthy worker survivor bias. METHODS: Workers in the Colorado Plateau Uranium Miners cohort (n = 4,134) entered the study between 1950 and 1964 and were followed for lung cancer mortality through 2005. We use the parametric g-formula to compare the observed lung cancer mortality to the potential lung cancer mortality had each of 3 policies to limit monthly radon exposure been in place throughout follow-up. RESULTS: There were 617 lung cancer deaths over 135,275 person-years of follow-up. With no intervention on radon exposure, estimated lung cancer mortality by age 90 was 16%. Lung cancer mortality was reduced for all interventions considered, and larger reductions in lung cancer mortality were seen for interventions with lower monthly radon exposure limits. The most stringent guideline, the Mine Safety and Health Administration standard of 0.33 working-level months, reduced lung cancer mortality from 16% to 10% (risk ratio = 0.67 [95% confidence interval = 0.61 to 0.73]). CONCLUSIONS: This work illustrates the utility of the parametric g-formula for estimating the effects of policies regarding occupational exposures, particularly in situations vulnerable to the healthy worker survivor bias.

Estimating the Population Newly Eligible for the Pneumococcal Conjugate Vaccine.

INTRODUCTION: Recommendations for adult pneumococcal vaccination in the U.S. were revised in 2022 after the introduction of 15- and 20-valent pneumococcal conjugate vaccines (PCV15 and PCV20) to call for routine PCV use among immunocompetent adults with risk conditions aged 19-64 years. The present study estimated the size of this newly recommended population. METHODS: A retrospective cohort study was conducted using the Optum de-identified electronic health record (EHR) dataset. Patients who were active in the EHR between January 2016 and June 2021 and had ≥1 condition included in the current pneumococcal recommendation without an immunocompromising condition were included. Data were weighted to account for potential differences between the EHR and U.S. POPULATION: Data analyses were conducted in 2022. RESULTS: Of 45.6 million adults aged 19-64 years in the database, 12.5 million met inclusion criteria and had ≥1 qualifying condition, primarily smoking, with chronic lung disease/asthma and/or diabetes also common. After weighting, the U.S. population aged 19-64 years newly eligible for PCVs was approximately 56 million. CONCLUSIONS: Approximately one in four U.S. adults aged <65 years is now recommended to receive PCV15 or PCV20, which highlights the need for providers to assess vaccination status, administer the vaccine, or refer patients as appropriate, as well as the need for tools to facilitate patient identification and vaccination.

Characterizing timeliness of recommended vaccinations among privately-insured children in the United States, 2009-2019.

BACKGROUND: The Advisory Committee on Immunization Practices (ACIP) recommends early childhood vaccinations, but knowledge is limited about the magnitude and timing of vaccine delay for each recommended dose on a population level. We sought to characterize longitudinal patient-level patterns of early childhood vaccination schedule adherence. METHODS: Using the Merative MarketScan Commercial Database (2009-2019), we identified commercially-insured infants who received at least one timely dose of a 2-month recommended vaccine. We categorized the number of recommended vaccines administered on the same date at 2, 4, 6, and 12-15 months of age (grace period: -7, +21 days). A Sankey diagram illustrated the number of vaccines received concomitantly during each age window and depicted transitions to different states over time (e.g., no vaccine delay to vaccine delay). For each vaccine dose, we estimated the cumulative incidence of receipt. RESULTS: Among 1,239,364 eligible children, 28% of infants aged 4 months and 38% of infants aged 6 months did not receive timely, concomitant administration of all recommended vaccines. The number of timely vaccines received concomitantly and age at receipt varied most for doses recommended during the second year of life. Children with a previously delayed (versus timely) dose consistently experienced longer time to subsequent dose. CONCLUSIONS: National coverage improved over time for all recommended vaccine doses under study, most notably for measles, mumps, and rubella. However, many children do not receive vaccines on schedule. Interventions to maintain adherence to the recommended schedule are needed early in life.

Increased disease severity during COVID-19 related hospitalization in black non-hispanic, hispanic and medicaid-insured young children.

Background: The COVID-19 pandemic has disproportionately affected marginalized groups in the United States. Although most children have mild or asymptomatic COVID-19, some experience severe disease and long-term complications. However, few studies have examined health disparities in severe COVID-19 outcomes among US children. Objective: To examine disparities in the clinical outcomes of infants and children aged <5 years hospitalized with COVID-19 by race/ethnicity and payer status. Methods: Children aged <5 years hospitalized with an admission diagnosis of COVID-19 (April 2021-February 2023) were selected from the PINC AI™ Healthcare Database. Hospital outcomes included length of stay (LOS), intensive care unit (ICU) admission, oxygen supplementation, invasive mechanical ventilation (IMV), and prolonged duration of each outcome. Multivariable logistic regression models compared hospitalization outcomes by race/ethnicity and payer status. Results: Among 10,190 children (mean age: 0.9 years, 56.5% male, 66.7% Medicaid-insured), race/ethnicity was distributed as follows: White non-Hispanic (35.1%), Hispanic (any or Unknown race; 28.3%), Black non-Hispanic (15.2%), Other race/ethnicity (8.9%) and Unknown (12.5%). Payer status varied by race/ethnicity. White non-Hispanic children had the highest proportion with commercial insurance (42.9%) while other racial/ethnic groups ranged between 13.8% to 26.1%. Black non-Hispanic children had the highest proportion with Medicaid (82.3%) followed by Hispanic children (76.9%). Black non-Hispanic children had higher odds of prolonged outcomes: LOS (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI]:1.05-1.38), ICU days (aOR = 1.44, 95% CI: 1.07-1.93), and IMV days (aOR = 1.80, 95% CI: 1.09-2.97) compared to White non-Hispanic children. Similar patterns were observed for Hispanic and children of Other race/ethnicity. Medicaid-insured and children with other insurance had higher odds of prolonged LOS and oxygen days than commercially insured patients. Conclusion: There were disparities in clinical outcomes of COVID-19 by race/ethnicity and insurance type, particularly for prolonged-duration outcomes. Further research is required to fully comprehend the causes and consequences of these disparities and develop strategies to reduce them while ensuring equitable healthcare delivery.

Using a data-driven approach to define post-COVID conditions in US electronic health record data.

OBJECTIVE: To create a data-driven definition of post-COVID conditions (PCC) by directly measure changes in symptomatology before and after a first COVID episode. MATERIALS AND METHODS: Retrospective cohort study using Optum® de-identified Electronic Health Record (EHR) dataset from the United States of persons of any age April 2020-September 2021. For each person with COVID (ICD-10-CM U07.1 "COVID-19" or positive test result), we selected up to 3 comparators. The final COVID symptom score was computed as the sum of new diagnoses weighted by each diagnosis' ratio of incidence in COVID group relative to comparator group. For the subset of COVID cases diagnosed in September 2021, we compared the incidence of PCC using our data-driven definition with ICD-10-CM code U09.9 "Post-COVID Conditions", first available in the US October 2021. RESULTS: The final cohort contained 588,611 people with COVID, with mean age of 48 years and 38% male. Our definition identified 20% of persons developed PCC in follow-up. PCC incidence increased with age: (7.8% of persons aged 0-17, 17.3% aged 18-64, and 33.3% aged 65+) and did not change over time (20.0% among persons diagnosed with COVID in 2020 versus 20.3% in 2021). For cases diagnosed in September 2021, our definition identified 19.0% with PCC in follow-up as compared to 2.9% with U09.9 code in follow-up. CONCLUSION: Symptom and U09.9 code-based definitions alone captured different populations. Maximal capture may consider a combined approach, particularly before the availability and routine utilization of specific ICD-10 codes and with the lack consensus-based definitions on the syndrome.

Persons diagnosed with COVID-19 in England in the Clinical Practice Research Datalink (CPRD): a cohort description.

OBJECTIVE: To create case definitions for confirmed COVID-19 diagnoses, COVID-19 vaccination status and three separate definitions of high risk of severe COVID-19, as well as to assess whether the implementation of these definitions in a cohort reflected the sociodemographic and clinical characteristics of COVID-19 epidemiology in England. DESIGN: Retrospective cohort study. SETTING: Electronic healthcare records from primary care (Clinical Practice Research Datalink, CPRD) linked to secondary care data (Hospital Episode Statistics) data covering 24% of the population in England. PARTICIPANTS: 2 271 072 persons aged 1 year and older diagnosed with COVID-19 in CPRD Aurum between 1 August 2020 and 31 January 2022. MAIN OUTCOME MEASURES: Age, sex and regional distribution of COVID-19 cases and COVID-19 vaccine doses received prior to diagnosis were assessed separately for the cohorts of cases identified in primary care and those hospitalised for COVID-19 (primary diagnosis code of ICD-10 U07.1 'COVID-19'). Smoking status, body mass index and Charlson Comorbidity Index were compared for the two cohorts, as well as for three separate definitions of high risk of severe disease used in the UK (National Health Service Highest Risk, PANORAMIC trial eligibility, UK Health Security Agency Clinical Risk prioritisation for vaccination). RESULTS: Compared with national estimates, CPRD case estimates under-represented older adults in both the primary care (age 65-84: 6% in CPRD vs 9% nationally) and hospitalised (31% vs 40%) cohorts, and over-represented people living in regions with the highest median wealth areas of England (20% primary care and 20% hospital admitted cases in South East vs 15% nationally). The majority of non-hospitalised cases and all hospitalised cases had not completed primary series vaccination. In primary care, persons meeting high-risk definitions were older, more often smokers, overweight or obese, and had higher Charlson Comorbidity Index score. CONCLUSIONS: CPRD primary care data are a robust real-world data source and can be used for some COVID-19 research questions, however, limitations of the data availability should be carefully considered. Included in this publication are supplemental files for a total of over 28 000 codes to define each of three definitions of high risk of severe disease.

Economic burden and secondary complications of influenza-related hospitalization among adults in the US: a retrospective cohort study.

OBJECTIVE: This study aims to describe the healthcare resource utilization (HCRU) and direct medical cost of influenza-related hospitalizations to illustrate the persistent economic burden of influenza among adults in the US. METHODS: A retrospective cohort study was conducted using the PINC AI Healthcare Database. Adults hospitalized with a diagnosis of influenza between August 1-May 31 from 2016-2023 were identified and stratified by age (18-49, 50-64 and ≥65 years). The index hospitalization was defined as the individual's first influenza-related hospitalization during each season. Patient demographics, comorbidities, and hospitalization characteristics were assessed during the index hospitalization. Index hospitalization length of stay (LOS), in-hospital mortality, intensive care unit (ICU) admissions, mechanical ventilation (MV) usage, and costs were evaluated overall and by MV usage, ICU admission, and secondary complication status. Pre-index influenza-related outpatient and emergency department (ED) visits (7 days prior) were also evaluated. RESULTS: Primarily initiated in the ED, the median LOS for influenza-related hospitalizations was 3-4 days. Inpatient mortality increased with age (2.2-4.4%). Combined mean hospitalization and initial ED visit costs were $12,556-$14,494 (2017/18; high severity season) and $11,384-$12,896 (2022/23; most recent season). Compared to other age groups, adults ≥65 years had higher proportions of hospitalization with no MV or ICU usage. Adults 18-49 years had the highest proportion of ICU admission only, whereas adults 50-64 years had the highest MV usage only and both MV and ICU admission. MV and/or ICU usage was associated with higher hospitalization costs. Increasing proportionally with age, the majority of influenza-related hospitalizations had a secondary complication diagnosis, which were associated with elevated costs. LIMITATIONS: Analysis of this hospital-based administrative database relied on coding accuracy. Only hospital system-associated outpatient/ED visits were captured; the full scope of HCRU was under-ascertained. CONCLUSIONS: The economic burden of influenza-related hospitalizations remains substantial, driven by underlying conditions, MV/ICU usage and secondary complications.

This study described the healthcare resource utilization (HCRU) and costs for US adults ≥18 years old hospitalized with influenza and associated secondary complications such as pneumonia, asthma exacerbation and malignant hypertension between 2016­2023. The researchers analyzed a hospital admission database and found that, for the healthcare system, average cost per influenza-related hospitalization ranged from $11,384 to $14,494, depending on the influenza season and age of the patient. Over 96% of patients admitted to a hospital initially presented at the emergency department, 20­30% of patients required mechanical ventilation (MV) or intensive care unit (ICU) admission, and the median hospital length of stay was 3­4 days. This study adds to the existing evidence by providing economic burden estimates for the 2022/23 influenza season, the most recent influenza season after the COVID-19 pandemic, and found slightly lower HCRU and cost for influenza hospitalizations relative to prior seasons. Also, the study comprehensively analyzed economic burden by patient age groups and found lower HCRU and costs among patients ≥65 years compared to adults 18­49 years and 50­64 years consistently for all seasons. Additionally, the study found that the proportion of patients with MV usage alone, with MV usage and an ICU admission, and average hospitalization costs were greatest among patients 50­64 years, highlighting the potential benefit of increasing rates of seasonal influenza vaccination among this age group. Finally, the study found higher costs among patients with complications related to their influenza infection compared to patients without complications. Overall, the study found that influenza-related hospitalization can contribute to substantial economic burden in the US in the most recent time period.

Definition and measurement of post-COVID-19 conditions in real-world practice: a global systematic literature review.

Post-COVID-19 conditions (PCC) is an umbrella term that encompasses a range of signs, symptoms and conditions present weeks after the acute phase of a SARS-CoV-2 infection. This systematic literature review summarises the heterogeneous methodology used to measure PCC across real-world studies and highlights trends by region, age group, PCC follow-up period and data source. METHODS: Medline, EMBASE and the Cochrane Library were searched and supplemented with conference and grey literature searches. Eligible studies included individuals with (1) PCC or (2) a positive SARS-CoV-2 test or COVID-19 diagnosis who were followed over time. Included studies were published in English between 1 January 2020 and 14 November 2022. FINDINGS: Of 291 publications included, 175 (60%) followed individuals with confirmed COVID-19 over time for PCC and 116 (40%) used a prespecified PCC definition. There was substantial heterogeneity in study design, geography, age group, PCC conditions/symptoms assessed and their classification and duration of follow-up. Among studies using a prespecified PCC definition, author-defined criteria (51%) were more common than criteria recommended by major public health organisations (19%). Measurement periods for PCC outcomes from date of acute COVID-19 test were primarily 3 to <6 months (39.2%), followed by 6 to <12 months (27.5%) and <3 months (22.9%). When classified by organ/system, constitutional-related PCC were the most frequently assessed in adult (86%) and paediatric (87%) populations. Within constitutional symptoms, fatigue was most frequently assessed in adult (91.6%) and paediatric (95.0%) populations, followed by fever/chills (37.9% and 55%, respectively). CONCLUSIONS: PCC definitions are heterogenous across real-world studies, which limits reliable comparisons between studies. However, some similarities were observed in terms of the most frequently measured PCC-associated symptoms/conditions, which may aid clinical management of patients with PCC.CRD42022376111.