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  • 1
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 9, No. 7 ( 2022-07-04)
    Abstract: Patient-reported outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are an important measure of the full burden of coronavirus disease (COVID). Here, we examine how (1) infecting genotype and COVID-19 vaccination correlate with inFLUenza Patient-Reported Outcome (FLU-PRO) Plus score, including by symptom domains, and (2) FLU-PRO Plus scores predict return to usual activities and health. Methods The epidemiology, immunology, and clinical characteristics of pandemic infectious diseases (EPICC) study was implemented to describe the short- and long-term consequences of SARS-CoV-2 infection in a longitudinal, observational cohort. Multivariable linear regression models were run with FLU-PRO Plus scores as the outcome variable, and multivariable Cox proportional hazards models evaluated effects of FLU-PRO Plus scores on return to usual health or activities. Results Among the 764 participants included in this analysis, 63% were 18–44 years old, 40% were female, and 51% were White. Being fully vaccinated was associated with lower total scores (β = −0.39; 95% CI, −0.57 to −0.21). The Delta variant was associated with higher total scores (β = 0.25; 95% CI, 0.05 to 0.45). Participants with higher FLU-PRO Plus scores were less likely to report returning to usual health and activities (health: hazard ratio [HR] , 0.46; 95% CI, 0.37 to 0.57; activities: HR, 0.56; 95% CI, 0.47 to 0.67). Fully vaccinated participants were more likely to report returning to usual activities (HR, 1.24; 95% CI, 1.04 to 1.48). Conclusions Full SARS-CoV-2 vaccination is associated with decreased severity of patient-reported symptoms across multiple domains, which in turn is likely to be associated with earlier return to usual activities. In addition, infection with the Delta variant was associated with higher FLU-PRO Plus scores than previous variants, even after controlling for vaccination status.
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2757767-3
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  • 2
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 8, No. 12 ( 2021-12-01)
    Abstract: The inFLUenza Patient-Reported Outcome Plus (FLU-PRO Plus) is a patient-reported outcome data collection instrument assessing symptoms of viral respiratory tract infections across 8 body systems. This study evaluated the measurement properties of FLU-PRO Plus in a study enrolling individuals with coronavirus disease 2019 (COVID-19). Methods Data from a prospective cohort study (EPICC) in US Military Health System beneficiaries evaluated for COVID-19 was utilized. Adults with symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with FLU-PRO Plus survey information within 1 week of symptom onset were included. Reliability of FLU-PRO Plus was estimated using intraclass correlation coefficient (ICC; 2 days’ reproducibility). Known-groups validity was assessed using patient global assessment (PGA) of disease severity. Patient report of return to usual health was used to assess responsiveness (day 1–6/7). Results Two hundred twenty-six SARS-CoV-2–positive participants were included in the analysis. Reliability among those who reported no change in their symptoms from one day to the next was high for most domains (ICC range, 0.68–0.94 for day 1 to day 2). Construct validity was demonstrated by moderate to high correlation between the PGA rating of disease severity and domain and total scores (eg, total scores correlation: 0.69 [influenza-like illness severity], 0.69 [interference in daily activities] , and –0.58 [physical health]). In addition, FLU-PRO Plus demonstrated good known-groups validity, with increasing domain and total scores observed with increasing severity ratings. Conclusions FLU-PRO Plus performs well in measuring signs and symptoms in SARS-CoV-2 infection with excellent construct validity, known-groups validity, and responsiveness to change. Standardized data collection instruments facilitate meta-analyses, vaccine effectiveness studies, and other COVID-19 research activities.
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2757767-3
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  • 3
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 9, No. 3 ( 2022-03-01)
    Abstract: Nasopharyngeal (NP) swabs are the standard for SARS-CoV-2 diagnosis. If less invasive alternatives to NP swabs (eg, oropharyngeal [OP] or nasal swabs [NS] ) are comparably sensitive, the use of these techniques may be preferable in terms of comfort, convenience, and safety. Methods This study compared the detection of SARS-CoV-2 in swab samples collected on the same day among participants with at least one positive PCR test. Results Overall, 755 participants had at least one set of paired swabs. Concordance between NP and other swab types was 75% (NS), 72% (OP), 54% (rectal swabs [RS]), and 78% (NS/OP combined). Kappa values were moderate for the NS, OP, and NS/OP comparisons (0.50, 0.45, and 0.54, respectively). Highest sensitivity relative to NP (0.87) was observed with a combination of NS/OP tests (positive if either NS or OP was positive). Sensitivity of the non-NP swab types was hig hest in the first week postsymptom onset and decreased thereafter. Similarly, virus RNA quantity was highest in the NP swabs as compared with NS, OP, and RS within two weeks postsymptom onset. OP and NS performance decreased as virus RNA quantity decreased. No differences were noted between NS specimens collected at home or in clinic. Conclusions NP swabs detected more SARS-CoV-2 cases than non-NP swabs, and the sensitivity of the non-NP swabs decreased with time postsymptom onset. While other swabs may be simpler to collect, NP swabs present the best chance of detecting SARS-CoV-2 RNA, which is essential for clinical care as well as genomic surveillance.
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2757767-3
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  • 4
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 8, No. Supplement_1 ( 2021-12-04), p. S24-S25
    Abstract: The long-term health effects after SARS-CoV-2 infection remain poorly understood. We evaluated health and healthcare usage after SARS-CoV-2 infection via surveys and longitudinal electronic medical record (EMR) review within the Military Health System (MHS). Methods We studied MHS beneficiaries enrolled in the Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) cohort from March to December 2020. COVID-19 illness symptom severity and duration were derived from surveys initiated in late 2020. In addition, multi-year healthcare encounter history before and after onset of COVID-19 symptoms was collected from the MHS EMR. Odds of organ-system clinical diagnoses within the 3 months pre- and post-symptom onset were calculated using generalized linear models, controlling for age, sex, and race, and including participant as a random effect. Results 1,015 participants were included who were SARS-CoV-2 positive, symptomatic, and had 3-month follow-up data available in the EMR (Table 1). 625 of these participants had survey data collected more than 28 days post-symptom onset, among whom 17% and 6% reported persistent symptoms at 28-84 days, and 85+ days, respectively. 9.6% had not resumed normal activities by one month. The most frequently reported symptoms persisting beyond 28 days were dyspnea, loss of smell and/or taste, fatigue, and exercise intolerance (Figure 1A). When compared with the period 61 to 90 days prior to symptom onset, the first month post-symptom onset period was associated with increases of pulmonary (aOR = 57, 95% CI 28-112), renal (aOR = 29, 95% CI 10-84), cardiovascular (aOR = 7, 95% CI 5-11), and neurological diagnoses (aOR = 3, 95% CI 2-4) (Figures 1B and 1C). Cardiovascular disease diagnoses remained elevated through 3 months (aOR = 2, 95% CI 1-3). Table 1. Characteristics of SARS-CoV-2+ EPICC participants, and illness duration among those with 28+ days post-symptom onset survey data collection. Figure 1 Fig1A. Symptoms reported by EPICC participants with illnesses longer than 28 days; 1B. Percent of participants with organ system specific diagnoses on each day, 90 days pre- and post-symptom onset; 1C. Odds of organ system specific diagnoses within each month, +/- 3 months of symptom onset, were calculated using generalized linear models, controlling for age, sex, and race and included participants as a random effect. Odds shown are relative to the earliest period included in the model, 61-90 days before onset. Conclusion In this MHS cohort, a significant proportion of participants had persistent symptoms and cardiovascular disease diagnoses 3 months after COVID-19 illness onset. These findings emphasize the long-term morbidity of COVID-19 and the importance of mitigating SARS-CoV-2 infections. Further analyses will evaluate demographic, clinical, and biomarker predictors of medium-to-long term organ-specific post-acute sequelae. Disclosures Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work)) Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R & D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2757767-3
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  • 5
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 8, No. Supplement_1 ( 2021-12-04), p. S273-S273
    Abstract: The risk factors of venous thromboembolism (VTE) in COVID-19 warrant further study. We leveraged a cohort in the Military Health System (MHS) to identify clinical and virological predictors of incident deep venous thrombosis (DVT), pulmonary embolism (PE), and other VTE within 90-days after COVID-19 onset. Methods PCR or serologically-confirmed SARS-CoV-2 infected MHS beneficiaries were enrolled via nine military treatment facilities (MTF) through April 2021. Case characteristics were derived from interview and review of the electronic medical record (EMR) through one-year follow-up in outpatients and inpatients. qPCR was performed on upper respiratory swab specimens collected post-enrollment to estimate SARS-CoV-2 viral load. The frequency of incident DVT, PE, or other VTE by 90-days post-COVID-19 onset were ascertained by ICD-10 code. Correlates of 90-day VTE were determined through multivariate logistic regression, including age and sampling-time-adjusted log10-SARS-CoV-2 GE/reaction as a priori predictors in addition to other demographic and clinical covariates which were selected through stepwise regression. Results 1473 participants with SARS-CoV-2 infection were enrolled through April 2021. 21% of study participants were inpatients; the mean age was 41 years (SD = 17.0 years). The median Charlson Comorbidity Index score was 0 (IQR = 0 - 1, range = 0 - 13). 27 (1.8%) had a prior history of VTE. Mean maximum viral load observed was 1.65 x 107 genome equivalents/reaction. 36 (2.4%) of all SARS-CoV-2 cases (including inpatients and outpatients), 29 (9.5%) of COVID-19 inpatients, and 7 (0.6%) of outpatients received an ICD-10 diagnosis of any VTE within 90 days after COVID-19 onset. Logistic regression identified hospitalization (aOR = 11.1, p = 0.003) and prior VTE (aOR = 6.2 , p = 0.009) as independent predictors of VTE within 90 days of symptom onset. Neither age (aOR = 1.0, p = 0.50), other demographic covariates, other comorbidities, nor SARS-CoV-2 viral load (aOR = 1.1, p = 0.60) were associated with 90-day VTE. Conclusion VTE was relatively frequent in this MHS cohort. SARS-CoV-2 viral load did not increase the odds of 90-day VTE. Rather, being hospitalized for SARS-CoV-2 and prior VTE history remained the strongest predictors of this complication. Disclosures Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work)) Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R & D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support David Tribble, M.D., DrPH, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2757767-3
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    In: Open Forum Infectious Diseases, Oxford University Press (OUP), Vol. 8, No. Supplement_1 ( 2021-12-04), p. S331-S332
    Abstract: The novel coronavirus disease 2019 (COVID-19) pandemic remains a global challenge. Accurate COVID-19 prognosis remains an important aspect of clinical management. While many prognostic systems have been proposed, most are derived from analyses of individual symptoms or biomarkers. Here, we take a machine learning approach to first identify discrete clusters of early stage-symptoms which may delineate groups with distinct symptom phenotypes. We then sought to identify whether these groups correlate with subsequent disease severity. Methods The Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) study is a longitudinal cohort study with data and biospecimens collected from nine military treatment facilities over 1 year of follow-up. Demographic and clinical characteristics were measured with interviews and electronic medical record review. Early symptoms by organ-domain were measured by FLU-PRO-plus surveys collected for 14 days post-enrollment, with surveys completed a median 14.5 (Interquartile Range, IQR = 13) days post-symptom onset. Using these FLU-PRO-plus responses, we applied principal component analysis followed by unsupervised machine learning algorithm k-means to identify groups with distinct clusters of symptoms. We then fit multivariate logistic regression models to determine how these early-symptom clusters correlated with hospitalization risk after controlling for age, sex, race, and obesity. Results Using SARS-CoV-2 positive participants (n = 1137) from the EPICC cohort (Figure 1), we transformed reported symptoms into domains and identified three groups of participants with distinct clusters of symptoms. Logistic regression demonstrated that cluster-2 was associated with an approximately three-fold increased odds [3.01 (95% CI: 2-4.52); P & lt; 0.001] of hospitalization which remained significant after controlling for other factors [2.97 (95% CI: 1.88-4.69); P & lt; 0.001]. (A) Baseline characteristics of SARS-CoV-2 positive participants. (B) Heatmap comparing FLU-PRO response in each participant. (C) Principal component analysis followed by k-means clustering identified three groups of participants. (D) Crude and adjusted association of identified cluster with hospitalization. Conclusion Our findings have identified three distinct groups with early-symptom phenotypes. With further validation of the clusters’ significance, this tool could be used to improve COVID-19 prognosis in a precision medicine framework and may assist in patient triaging and clinical decision-making. Disclaimer Disclosures David A. Lindholm, MD, American Board of Internal Medicine (Individual(s) Involved: Self): Member of Auxiliary R & D Infectious Disease Item-Writer Task Force. No financial support received. No exam questions will be disclosed ., Other Financial or Material Support Ryan C. Maves, MD, EMD Serono (Advisor or Review Panel member)Heron Therapeutics (Advisor or Review Panel member) Simon Pollett, MBBS, Astra Zeneca (Other Financial or Material Support, HJF, in support of USU IDCRP, funded under a CRADA to augment the conduct of an unrelated Phase III COVID-19 vaccine trial sponsored by AstraZeneca as part of USG response (unrelated work))
    Type of Medium: Online Resource
    ISSN: 2328-8957
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2757767-3
    Library Location Call Number Volume/Issue/Year Availability
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