Last data update: May 06, 2024. (Total: 46732 publications since 2009)
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Query Trace: Smith ER[original query] |
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Protocol for a sequential, prospective meta-analysis to describe coronavirus disease 2019 (COVID-19) in the pregnancy and postpartum periods (preprint)
Smith ER , Oakley E , He S , Zavala R , Ferguson K , Miller L , Grandner GW , Abejirinde IO , Afshar Y , Ahmadzia H , Aldrovandi G , Akelo V , Tippett Barr BA , Bevilacqua E , Brandt JS , Broutet N , Fernández Buhigas I , Carrillo J , Clifton R , Conry J , Cosmi E , Delgado-López C , Divakar H , Driscoll AJ , Favre G , Flaherman V , Gale C , Gil MM , Godwin C , Gottlieb S , Hernandez Bellolio O , Kara E , Khagayi S , Kim CR , Knight M , Kotloff K , Lanzone A , Le Doare K , Lees C , Litman E , Lokken EM , Laurita Longo V , Magee LA , Martinez-Portilla RJ , McClure E , Metz TD , Money D , Mullins E , Nachega JB , Panchaud A , Playle R , Poon LC , Raiten D , Regan L , Rukundo G , Sanin-Blair J , Temmerman M , Thorson A , Thwin S , Tolosa JE , Townson J , Valencia-Prado M , Visentin S , von Dadelszen P , Adams Waldorf K , Whitehead C , Yang H , Thorlund K , Tielsch JM . medRxiv 2022 2020.11.08.20228056 We urgently need answers to basic epidemiological questions regarding SARS-CoV-2 infection in pregnant and postpartum women and its effect on their newborns. While many national registries, health facilities, and research groups are collecting relevant data, we need a collaborative and methodologically rigorous approach to better combine these data and address knowledge gaps, especially those related to rare outcomes. We propose that using a sequential, prospective meta-analysis (PMA) is the best approach to generate data for policy- and practice-oriented guidelines. As the pandemic evolves, additional studies identified retrospectively by the steering committee or through living systematic reviews will be invited to participate in this PMA. Investigators can contribute to the PMA by either submitting individual patient data or running standardized code to generate aggregate data estimates. For the primary analysis, we will pool data using two-stage meta-analysis methods. The meta-analyses will be updated as additional data accrue in each contributing study and as additional studies meet study-specific time or data accrual thresholds for sharing. At the time of publication, investigators of 25 studies, including more than 76,000 pregnancies, in 41 countries had agreed to share data for this analysis. Among the included studies, 12 have a contemporaneous comparison group of pregnancies without COVID-19, and four studies include a comparison group of non-pregnant women of reproductive age with COVID-19. Protocols and updates will be maintained publicly. Results will be shared with key stakeholders, including the World Health Organization (WHO) Maternal, Newborn, Child, and Adolescent Health (MNCAH) Research Working Group. Data contributors will share results with local stakeholders. Scientific publications will be published in open-access journals on an ongoing basis.Competing Interest StatementClare Whitehead declares a a relationship with the following entities, Ferring Pharmaceuticals COVID19 Investigational, Grant, NHMRC Fellowship (salary support). Alice Panchaud declares the following research grants to institution: H2020-Grant (Consortium member of Innovative medicine initiative call 13 topic 9) (ConcePTION), Efficacy and safety studies on Medicines EMA/2017/09/PE/11, Lot 4, WP 2 lead (CONSIGN: Study on impact of COVID-19 infection and medicines in pregnancy), Safety monitoring of COVID-19 vaccines in the EU Reopening of competition no. 20 under a framework contract following procurement procedure EMA/2017/09/PE (Lot 3) 4. Federal Office of Public Health (207000 CHF). (The COVI-Preg registry). Edward Mullins declares a relationship with the following entities National Institute for Health Research (Project grant for PAN COVID study) Deborah Money declares a relationship with the following entities, Canadian Institutes of Health Research (payments to my institution only), Public Health Agency of Canada (payments to my institution only), BC Womens Foundation (payments to my institution only) and is a Member of the COVID-19 Immunity Task Force sponsored by the Canadian government. Torri D. Metz declares a relationship with the following entities, Pfizer (site Principal Investigator for SARS-CoV-2 vaccination in pregnancy study, money paid to institution and member of Medical Advisory Board for SARS-CoV-2 vaccination in pregnancy study, money paid to me), NICHD (subcommittee Chair for the NICHD Maternal-Fetal Medicine Units Network Gestational Research Assessments of COVID-19 (GRAVID) study), and Society for Maternal-Fetal Medicine (board member). Erica Lokken declares a relationship with the following entity, US NIH (paid institution). Karen L. Kotloff declares a relationship with the following entity, Bill and Melinda Gates Foundation. Siran He declares a relationship with the following entity, Bill and Melinda Gates Foundtion (payments made to my institution). Valerie Flaherman declares a relationship with the following entities, Bill and Melinda Gates Foundation (payments to my institution), Yellow Chair Foundati n (payments to my institution), Robert Woods Johnson Foundation (payments to my institution), CDC Foundation, California Health Care Foundation (payments to my institution), Tara Health Foundation (payments to my institution), UCSF Womens Health Center of Excellence (payments to my institution) and California Department of Health Care Services (payments made to my institution). Jose Sanin-Blair declares a relationship with the following entity, Ferring Pharmaceuticals which give a grant ($10,000) for the expenses of RECOGEST trial and is a part of the Columbian Federation of Perinatology Yalda Afshar declares a relationship with the following entities, Bill and Melinda Gates Foundation (payments made to my institution), CDC Foundation (payments made to my institution), Robert Woods Johnson Foundation (payments made to my institution), and UCLA Deans Office COVID-19 research (payments made to my institution). Rebecca Cliffton declares a relationship with the following entity, NIH HD36801 (MFMU Network DCC).Clinical TrialPROSPERO ID: 188955Funding StatementFunded by the Bill & Melinda Gates Foundation grant to Emily Smith (INV-022057) at George Washington University and a grant to Emily Smith via a grant from the Bill & Melinda Gates Foundation to Stephanie Gaw (INV-017035) at University of California San Francisco.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This is a protocol paper and thus exempt from ethical approval. Ultimately, the meta-analysis study is exempt from human research ethics approval as the study authors will be synthesizing de-identified or aggregate data.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThis is a protocol paper and there is no related data to share. |
Risk of Adverse Maternal and Fetal Outcomes Associated with COVID-19 Variants of Concern: A Sequential Prospective Meta-Analysis (preprint)
Farooq F , Oakley E , Kerchner D , Hee Kim JY , Akelo V , Tippett Barr BA , Bevilacqua E , Bracero N , del Mar Gil M , Delgado-Lopez C , Favre G , Buhigas IF , Hillary Leung HY , Longo VL , Panchaud A , Poon LC , Martinez-Portilla RJ , Valencia-Prado M , Tielsch JM , Smith ER , Omore R , Ouma G , Onyango C , Otieno K , Were ZA , Were J , Maisonneuve E , Poncelet C , de Tejada BM , Quibel T , Monod C , Yu FNY , Kong CW , Lo TK , So PL , Leung WC , Meli F , Bonanni G , Romanzi F , Torcia E , di Ilio C , Aquise A , Rayo MN , Santacruz B , Gonzalez-Gea L , Laiseca S , Ferrer LN , Huertas MM , Rosario GM , Ramos NA , Gonzalez SV . medRxiv 2023 04 Introduction The main objective of this study is to conduct an individual patient data meta-analysis with collaborators from various countries to identify SARS-CoV-2 variants of concern associated with adverse maternal and neonatal outcomes. Methods Eligible studies included registries and single- or multi-site cohort studies that recruited pregnant and recently postpartum women with confirmed COVID-19. Studies must have enrolled at least 25 women within a defined catchment area. Studies also had to have data that overlapped more than a single COVID-19 variant time period. We invited principal investigators already participating in an ongoing sequential, prospective meta-analysis of perinatal COVID-19. Investigators shared individual patient data (IPD) with the technical team for review and analysis. We examined 31 outcomes related to: i) COVID-19 severity (n=5); ii) maternal morbidities including adverse birth outcomes (n=14); iii) fetal and neonatal morbidity and mortality (n=5) and iv) adverse birth outcomes (n=8). SARS-CoV-2 strains that have been identified as variants of concern (VOC) by the WHO were analyzed using the publicly available strain frequency data by Nextstrain.org and strains were classified as dominant when they were more than half of sequences in a given geographic area. We applied a 2-stage IPD meta-analytic framework to generate pooled relative risks, with 95% CI for each dominant variant and outcome pair when there were one or more studies with available data. Results Our data show that the Delta wave, compared to Omicron, was associated with a higher risk of all adverse COVID-19 severity outcomes in pregnancy including risk of hospitalization [RR 4.02 (95% CI 1.10, 14.69), n=1 study], risk of ICU admissions [RR 2.59 (95% CI 1.26, 5.30, n=3 studies], risk of critical care admission [RR 2.52 (95% CI 1.25, 5.08, n=3 studies], risk of needing ventilation [RR 3.96 (95% CI 1.47, 10.71), n=3 studies] and risk of pneumonia [RR 6.73 (95% CI 2.17, 20.90), n=3 studies]. The majority of maternal morbidity and mortality indicators were not at increased risk during any of the COVID-19 variant waves except hemorrhage, any Cesarean section, intrapartum Cesarean section and maternal composite outcome, although data was limited. Risk of fetal and neonatal morbidity and mortality did not show significant increases in risks during any of the COVID-19 waves except stillbirth and perinatal death during the Delta wave ([RR 4.84 (95% CI 1.37, 17.05, n=3 studies], [RR 6.03 (95%CI 1.63, 22.34), n=3 studies], respectively) when compared to the Pre-alpha wave. Adverse birth outcomes including very low birthweight and very preterm birth also showed increased risks during the Delta wave compared to the Pre-alpha wave. Discussion During periods of Delta strain predominance, all COVID-19 severity outcomes were more severe among pregnant women, compared to periods when other COVID-19 strains predominated. In addition, there are limited data comparing the impact of different variants on pregnancy outcomes. This highlights the importance of ongoing genomic surveillance among special populations. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. |
Adverse maternal, fetal, and newborn outcomes among pregnant women with SARS-CoV-2 infection: an individual participant data meta-analysis
Smith ER , Oakley E , Grandner GW , Ferguson K , Farooq F , Afshar Y , Ahlberg M , Ahmadzia H , Akelo V , Aldrovandi G , Tippett Barr BA , Bevilacqua E , Brandt JS , Broutet N , Fernández Buhigas I , Carrillo J , Clifton R , Conry J , Cosmi E , Crispi F , Crovetto F , Delgado-López C , Divakar H , Driscoll AJ , Favre G , Flaherman VJ , Gale C , Gil MM , Gottlieb SL , Gratacós E , Hernandez O , Jones S , Kalafat E , Khagayi S , Knight M , Kotloff K , Lanzone A , Le Doare K , Lees C , Litman E , Lokken EM , Laurita Longo V , Madhi SA , Magee LA , Martinez-Portilla RJ , McClure EM , Metz TD , Miller ES , Money D , Moungmaithong S , Mullins E , Nachega JB , Nunes MC , Onyango D , Panchaud A , Poon LC , Raiten D , Regan L , Rukundo G , Sahota D , Sakowicz A , Sanin-Blair J , Söderling J , Stephansson O , Temmerman M , Thorson A , Tolosa JE , Townson J , Valencia-Prado M , Visentin S , von Dadelszen P , Adams Waldorf K , Whitehead C , Yassa M , Tielsch JM . BMJ Glob Health 2023 8 (1) INTRODUCTION: Despite a growing body of research on the risks of SARS-CoV-2 infection during pregnancy, there is continued controversy given heterogeneity in the quality and design of published studies. METHODS: We screened ongoing studies in our sequential, prospective meta-analysis. We pooled individual participant data to estimate the absolute and relative risk (RR) of adverse outcomes among pregnant women with SARS-CoV-2 infection, compared with confirmed negative pregnancies. We evaluated the risk of bias using a modified Newcastle-Ottawa Scale. RESULTS: We screened 137 studies and included 12 studies in 12 countries involving 13 136 pregnant women.Pregnant women with SARS-CoV-2 infection-as compared with uninfected pregnant women-were at significantly increased risk of maternal mortality (10 studies; n=1490; RR 7.68, 95% CI 1.70 to 34.61); admission to intensive care unit (8 studies; n=6660; RR 3.81, 95% CI 2.03 to 7.17); receiving mechanical ventilation (7 studies; n=4887; RR 15.23, 95% CI 4.32 to 53.71); receiving any critical care (7 studies; n=4735; RR 5.48, 95% CI 2.57 to 11.72); and being diagnosed with pneumonia (6 studies; n=4573; RR 23.46, 95% CI 3.03 to 181.39) and thromboembolic disease (8 studies; n=5146; RR 5.50, 95% CI 1.12 to 27.12).Neonates born to women with SARS-CoV-2 infection were more likely to be admitted to a neonatal care unit after birth (7 studies; n=7637; RR 1.86, 95% CI 1.12 to 3.08); be born preterm (7 studies; n=6233; RR 1.71, 95% CI 1.28 to 2.29) or moderately preterm (7 studies; n=6071; RR 2.92, 95% CI 1.88 to 4.54); and to be born low birth weight (12 studies; n=11 930; RR 1.19, 95% CI 1.02 to 1.40). Infection was not linked to stillbirth. Studies were generally at low or moderate risk of bias. CONCLUSIONS: This analysis indicates that SARS-CoV-2 infection at any time during pregnancy increases the risk of maternal death, severe maternal morbidities and neonatal morbidity, but not stillbirth or intrauterine growth restriction. As more data become available, we will update these findings per the published protocol. |
Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: A sequential, prospective meta-analysis.
Smith ER , Oakley E , Grandner GW , Rukundo G , Farooq F , Ferguson K , Baumann S , Waldorf KA , Afshar Y , Ahlberg M , Ahmadzia H , Akelo V , Aldrovandi G , Bevilacqua E , Bracero N , Brandt JS , Broutet N , Carrillo J , Conry J , Cosmi E , Crispi F , Crovetto F , Gil MDM , Delgado-Lpez C , Divakar H , Driscoll AJ , Favre G , Buhigas IF , Flaherman V , Gale C , Godwin CL , Gottlieb S , Gratacs E , He S , Hernandez O , Jones S , Joshi S , Kalafat E , Khagayi S , Knight M , Kotloff K , Lanzone A , Longo VL , LeDoare K , Lees C , Litman E , Lokken EM , Madhi SA , Magee LA , Martinez-Portilla RJ , Metz TD , Miller ES , Money D , Moungmaithong S , Mullins E , Nachega JB , Nunes MC , Onyango D , Panchaud A , Poon LC , Raiten D , Regan L , Sahota D , Sakowicz A , Sanin-Blair J , Stephansson O , Temmerman M , Thorson A , Thwin SS , TippettBarr BA , Tolosa JE , Tug N , Valencia-Prado M , Visentin S , vonDadelszen P , Whitehead C , Wood M , Yang H , Zavala R , Tielsch JM . Am J Obstet Gynecol 2022 228 (2) 161-177 OBJECTIVE: This sequential, prospective meta-analysis (sPMA) sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to: disease severity, maternal morbidities, neonatal mortality and morbidity, adverse birth outcomes. DATA SOURCES: We prospectively invited study investigators to join the sPMA via professional research networks beginning in March 2020. STUDY ELIGIBILITY CRITERIA: Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. STUDY APPRAISAL AND SYNTHESIS METHODS: We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a two-stage meta-analysis. RESULTS: We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (pre-existing diabetes, hypertension, cardiovascular disease) versus those without were at higher risk for COVID-19 severity and pregnancy health outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% CI: 1.12, 2.71) more likely to be admitted to the ICU. Pregnant women who were underweight before pregnancy were at higher risk of ICU admission (RR 5.53, 95% CI: 2.27, 13.44), ventilation (RR 9.36, 95% CI: 3.87, 22.63), and pregnancy-related death (RR 14.10, 95% CI: 2.83, 70.36). Pre-pregnancy obesity was also a risk factor for severe COVID-19 outcomes including ICU admission (RR 1.81, 95% CI: 1.26,2.60), ventilation (RR 2.05, 95% CI: 1.20,3.51), any critical care (RR 1.89, 95% CI: 1.28,2.77), and pneumonia (RR 1.66, 95% CI: 1.18,2.33). Anemic pregnant women with COVID-19 also had increased risk of ICU admission (RR 1.63, 95% CI: 1.25, 2.11) and death (RR 2.36, 95% CI: 1.15, 4.81). CONCLUSION: We found that pregnant women with comorbidities including diabetes, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly-known risk factors, including HIV infection, pre-pregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors. |
Protocol for a sequential, prospective meta-analysis to describe coronavirus disease 2019 (COVID-19) in the pregnancy and postpartum periods.
Smith ER , Oakley E , He S , Zavala R , Ferguson K , Miller L , Grandner GW , Abejirinde IO , Afshar Y , Ahmadzia H , Aldrovandi G , Akelo V , Tippett Barr BA , Bevilacqua E , Brandt JS , Broutet N , Fernández Buhigas I , Carrillo J , Clifton R , Conry J , Cosmi E , Delgado-López C , Divakar H , Driscoll AJ , Favre G , Flaherman V , Gale C , Gil MM , Godwin C , Gottlieb S , Hernandez Bellolio O , Kara E , Khagayi S , Kim CR , Knight M , Kotloff K , Lanzone A , Le Doare K , Lees C , Litman E , Lokken EM , Laurita Longo V , Magee LA , Martinez-Portilla RJ , McClure E , Metz TD , Money D , Mullins E , Nachega JB , Panchaud A , Playle R , Poon LC , Raiten D , Regan L , Rukundo G , Sanin-Blair J , Temmerman M , Thorson A , Thwin S , Tolosa JE , Townson J , Valencia-Prado M , Visentin S , von Dadelszen P , Adams Waldorf K , Whitehead C , Yang H , Thorlund K , Tielsch JM . PLoS One 2022 17 (6) e0270150 We urgently need answers to basic epidemiological questions regarding SARS-CoV-2 infection in pregnant and postpartum women and its effect on their newborns. While many national registries, health facilities, and research groups are collecting relevant data, we need a collaborative and methodologically rigorous approach to better combine these data and address knowledge gaps, especially those related to rare outcomes. We propose that using a sequential, prospective meta-analysis (PMA) is the best approach to generate data for policy- and practice-oriented guidelines. As the pandemic evolves, additional studies identified retrospectively by the steering committee or through living systematic reviews will be invited to participate in this PMA. Investigators can contribute to the PMA by either submitting individual patient data or running standardized code to generate aggregate data estimates. For the primary analysis, we will pool data using two-stage meta-analysis methods. The meta-analyses will be updated as additional data accrue in each contributing study and as additional studies meet study-specific time or data accrual thresholds for sharing. At the time of publication, investigators of 25 studies, including more than 76,000 pregnancies, in 41 countries had agreed to share data for this analysis. Among the included studies, 12 have a contemporaneous comparison group of pregnancies without COVID-19, and four studies include a comparison group of non-pregnant women of reproductive age with COVID-19. Protocols and updates will be maintained publicly. Results will be shared with key stakeholders, including the World Health Organization (WHO) Maternal, Newborn, Child, and Adolescent Health (MNCAH) Research Working Group. Data contributors will share results with local stakeholders. Scientific publications will be published in open-access journals on an ongoing basis. |
Vaccine effectiveness against influenza-associated hospitalizations among adults, 2018-2019, US Hospitalized Adult Influenza Vaccine Effectiveness Network
Ferdinands JM , Gaglani M , Ghamande S , Martin ET , Middleton D , Monto AS , Silveira F , Talbot HK , Zimmerman R , Smith ER , Patel M . J Infect Dis 2020 224 (1) 151-163 We estimated vaccine effectiveness for prevention of influenza-associated hospitalizations among adults during the 2018-2019 influenza season. Adults admitted with acute respiratory illness to 14 hospitals of the US Hospitalized Adult Influenza Vaccine Effectiveness Network and testing positive for influenza were cases; patients testing negative were controls. Vaccine effectiveness was estimated using logistic regression and inverse probability of treatment weighting. We analyzed data from 2863 patients with mean age of 63 years. Adjusted VE against influenza A(H1N1)pdm09-associated hospitalization was 51% (95%CI 25, 68). Adjusted VE against influenza A(H3N2) virus-associated hospitalization was -2% (95%CI -65, 37) and differed significantly by age, with VE of -130% (95% CI -374, -27) among adults 18 to ≤56 years of age. Although vaccination halved the risk of influenza-A(H1N1)pdm09-associated hospitalizations, it conferred no protection against influenza A(H3N2)-associated hospitalizations. We observed negative VE for young-and middle-aged adults but cannot exclude residual confounding as a potential explanation. |
Reducing antibiotic use in ambulatory care through influenza vaccination
Smith ER , Fry AM , Hicks LA , Fleming-Dutra KE , Flannery B , Ferdinands J , Rolfes MA , Martin ET , Monto AS , Zimmerman RK , Nowalk MP , Jackson ML , McLean HQ , Olson SC , Gaglani M , Patel MM . Clin Infect Dis 2020 71 (11) e726-e734 BACKGROUND: Improving appropriate antibiotic use is crucial for combating antibiotic resistance and unnecessary adverse drug reactions. Acute respiratory illness (ARI) commonly causes outpatient visits and accounts for ~41% of antibiotics used in the United States (U.S.). We examined the influence of influenza vaccination on reducing antibiotic prescriptions among outpatients with ARI. METHODS: We enrolled outpatients aged >/=6 months with ARI from 50-60 U.S. clinics during five winters (2013-2018) and tested for influenza with RT-PCR; results were unavailable for clinical decision-making and clinical influenza testing was infrequent. We collected antibiotic prescriptions and diagnosis codes for ARI syndromes. We calculated vaccine effectiveness (VE) by comparing vaccination odds among influenza-positive cases to test-negative controls. We estimated ARI visits and antibiotic prescriptions averted by influenza vaccination using estimates of VE, coverage, and prevalence of antibiotic prescriptions and influenza. RESULTS: Among 37,487 ARI outpatients, 9,659 (26%) were influenza-positive. Overall, 36% of ARI and 26% of influenza-positive patients were prescribed antibiotics. The top three prevalent ARI syndromes included: viral upper respiratory tract infection (47%), pharyngitis (18%), and allergy or asthma (11%). Among patients testing positive for influenza, 77% did not receive an ICD-CM diagnostic code for influenza. Overall, VE against influenza-associated ARI was 35% (95%CI 32-39). Vaccination prevented 5.6% of all ARI syndromes, ranging from 2.8% (sinusitis) to 11% (clinical influenza). Influenza vaccination averted 1 in 25 (3.8%; 95%CI 3.6%-4.1%) antibiotic prescriptions among ARI outpatients during influenza seasons. CONCLUSION: Vaccination and accurate influenza diagnosis may curb unnecessary antibiotic use and reduce the global threat of antibiotic resistance. |
Influenza vaccine effectiveness in inpatient and outpatient settings in the United States, 2015 - 2018
Tenforde MW , Chung J , Smith ER , Talbot HK , Trabue CH , Zimmerman RK , Silveira FP , Gaglani M , Murthy K , Monto AS , Martin ET , McLean HQ , Belongia EA , Jackson LA , Jackson ML , Ferdinands JM , Flannery B , Patel MM . Clin Infect Dis 2020 73 (3) 386-392 BACKGROUND: Demonstration of influenza vaccine effectiveness (VE) against hospitalization for severe illness in addition to milder outpatient illness may strengthen vaccination messaging and improve suboptimal uptake in the U.S. Our objective was to compare patient characteristics and VE between U.S. inpatient and outpatient VE networks. METHODS: We tested adults >/=18-years with acute respiratory illness (ARI) for influenza within two VE networks, one outpatient- and the other hospital-based, from 2015-2018. We compared age, sex, and chronic high-risk conditions between populations. The test-negative design was used to compare vaccination odds in influenza-positive cases versus influenza-negative controls. We estimated VE using logistic regression adjusting for site, age, sex, race/ethnicity, peak influenza activity, time-to-testing from symptom-onset, season (overall VE) and underlying conditions. VE differences (DeltaVE) were assessed with 95% confidence intervals (CI) determined through bootstrapping with significance defined as excluding the null. RESULTS: The VE networks enrolled 14,573 (4144 influenza-positive) outpatients and 6769 (1452 influenza-positive) inpatients. Inpatients were older (median 62-years vs. 49-years) and had more high-risk conditions (median 4 vs. 1). Overall influenza VE across seasons was 31% (95%CI:26%-37%) among outpatients and 36% (27%-44%) among inpatients. Strain-specific VE among outpatients versus inpatients was 37% (25%-47%) vs. 53% (37%-64%) against H1N1pdm09, 19% (9%-27%) vs. 23% (8%-35%) against H3N2, and 46% (38%-53%) vs. 46% (31%-58%) against B-viruses. DeltaVE was not significant for any comparison across all sites. CONCLUSIONS: Inpatients and outpatients with ARI represent distinct populations. Despite comparatively poor health status among inpatients, influenza vaccination was effective in preventing hospitalizations associated with influenza. |
Relative and absolute effectiveness of high-dose and standard-dose influenza vaccine against influenza-related hospitalization among older adults - United States, 2015-2017
Doyle JD , Beacham L , Martin ET , Talbot HK , Monto A , Gaglani M , Middleton DB , Silveira FP , Zimmerman RK , Alyanak E , Smith ER , Flannery BL , Rolfes M , Ferdinands JM . Clin Infect Dis 2020 72 (6) 995-1003 BACKGROUND: Seasonal influenza causes substantial morbidity and mortality in older adults. High-dose inactivated influenza vaccine (HD-IIV), with increased antigen content compared to standard-dose influenza vaccines (SD-IIV), is licensed for use in people aged >/=65 years. We sought to evaluate the effectiveness of HD-IIV and SD-IIV for prevention of influenza-associated hospitalizations. METHODS: Hospitalized patients with acute respiratory illness were enrolled in an observational vaccine effectiveness study at eight hospitals in the United States Hospitalized Adult Influenza Vaccine Effectiveness Network during the 2015-2016 and 2016-2017 influenza seasons. Enrolled patients were tested for influenza, and receipt of influenza vaccine by type was recorded. Effectiveness of SD-IIV and HD-IIV was estimated using a test-negative design (comparing odds of influenza among vaccinated and unvaccinated patients). Relative effectiveness of SD-IIV and HD-IIV was estimated using logistic regression. RESULTS: Among 1487 enrolled patients aged >/=65 years, 1107 (74%) were vaccinated; 622 (56%) received HD-IIV and 485 (44%) received SD-IIV. Overall, 277 (19%) tested positive for influenza, including 98 (16%) who received HD-IIV, 87 (18%) who received SD-IIV, and 92 (24%) who were unvaccinated. After adjusting for confounding variables, effectiveness of SD-IIV was 6% (95% confidence interval [CI] -42%, 38%) and that of HD-IIV was 32% (95%CI -3%, 54%), for a relative effectiveness of HD-IIV versus SD-IIV of 27% (95%CI -1%, 48%). CONCLUSIONS: During two U.S. influenza seasons, vaccine effectiveness was low to moderate for prevention of influenza hospitalization among adults aged >/=65 years. High-dose vaccine offered greater effectiveness. None of these findings were statistically significant. |
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