Dataset Information

Surveillance and Correlation of Severe Acute Respiratory Syndrome Coronavirus 2 Viral RNA, Antigen, Virus Isolation, and Self-Reported Symptoms in a Longitudinal Study With Daily Sampling.

ABSTRACT: The novel coronavirus pandemic incited unprecedented demand for assays that detect viral nucleic acids, viral proteins, and corresponding antibodies. The 320 molecular diagnostics in receipt of US Food and Drug Administration emergency use authorization mainly focus on viral detection; however, no currently approved test can be used to infer infectiousness, that is, the presence of replicable virus. As the number of tests conducted increased, persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA positivity by reverse-transcription polymerase chain reaction (RT-PCR) in some individuals led to concerns over quarantine guidelines. To this end, we attempted to design an assay that reduces the frequency of positive test results from individuals who do not shed culturable virus. We describe multiplex quantitative RT-PCR assays that detect genomic RNA (gRNA) and subgenomic RNA (sgRNA) species of SARS-CoV-2, including spike, nucleocapsid, membrane, envelope, and ORF8. Viral RNA abundances calculated from these assays were compared with antigen presence, self-reported symptoms, and culture outcome (virus isolation) using samples from a 14-day longitudinal household transmission study. By characterizing the clinical and molecular dynamics of infection, we show that sgRNA detection has higher predictive value for culture outcome compared to detection of gRNA alone. Our findings suggest that sgRNA presence correlates with active infection and may help identify individuals shedding culturable virus.

SUBMITTER: Bonenfant G

PROVIDER: S-EPMC9213875 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Surveillance and Correlation of Severe Acute Respiratory Syndrome Coronavirus 2 Viral RNA, Antigen, Virus Isolation, and Self-Reported Symptoms in a Longitudinal Study With Daily Sampling.

Bonenfant Gaston G Deyoe Jessica E JE Wong Terianne T Grijalva Carlos G CG Cui Dan D Talbot H Keipp HK Hassell Norman N Halasa Natasha N Chappell James J Thornburg Natalie J NJ Rolfes Melissa A MA Wentworth David E DE Zhou Bin B

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 20221101 10

The novel coronavirus pandemic incited unprecedented demand for assays that detect viral nucleic acids, viral proteins, and corresponding antibodies. The 320 molecular diagnostics in receipt of US Food and Drug Administration emergency use authorization mainly focus on viral detection; however, no currently approved test can be used to infer infectiousness, that is, the presence of replicable virus. As the number of tests conducted increased, persistent severe acute respiratory syndrome coronavi ...[more]

PMID: 35442437

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Project description:BackgroundPatient reported outcome measures (PROM) can improve patient care and be crucial for symptom tracking especially during disease outbreaks. FLU-PRO Plus is a validated PROM used to track viral respiratory symptoms. Our study aimed to evaluate the feasibility of using FLU-PRO© Plus, to track symptoms across three healthcare systems.MethodsThe prospective, longitudinal study recruited adults between February-May 2021 from HealthPartners Institute (HP), Kaiser Permanente Georgia (KPGA), and Kaiser Permanente Mid-Atlantic States (KPMAS). Adult members were eligible if they had a positive lab or diagnosis for either COVID-19 or influenza-like illness (ILI) or exhibited 2 + viral respiratory symptoms. Descriptive statistics were calculated to describe the patient characteristics for participants that were eligible for FLU-PRO Plus, successfully contacted, attempted to log in to the FLU-PRO Plus website, and participants who completed FLU-PRO Plus Day 1. Bivariable and multivariable logistic regression using PROC GLIMMIXX investigated the patient characteristics associated with (1) successful contact and (2) FLU-PRO Plus Day 1 completion.ResultsWe identified a total of 15,650 eligible participants during the enrollment period: 9,582 from HP, 1,740 from KPGA, and 4,328 from KPMAS. Among the total of 409 eligible adults who attempted to participate in FLU-PRO Plus, 317 completed FLU-PRO Plus Day 1. Among the 317 individuals that completed FLU-PRO Plus Day 1, 205 (67.5%) were diagnosed with COVID-19; 112 adults diagnosed with COVID-19 completed FLU-PRO Plus Day 14. Among adults successfully contacted, adults aged 35-64 (OR = 1.40, 95% CI 1.05, 1.87), females (OR = 1.77, 95% CI 1.38, 2.27), and adults diagnosed with COVID-19 (OR = 1.66, 95% CI 1.27, 2.17) had higher odds of completing FLU-PRO Plus Day 1; Asian adults (OR = 0.38, 95% CI 0.19, 0.76) and Black and African American adults (OR = 0.33, 95% CI 0.19, 0.76) had lower odds compared to White adults.ConclusionOur study reports on the feasibility of patients across three integrated healthcare systems utilizing FLU-PRO Plus to monitor their respiratory symptoms. Patient reported outcome measures (PROM) can improve patient care, quality of life, and reduce the strain of limited resources on healthcare systems. Future FLU-PRO Plus studies should develop an implementation strategy to fully integrate FLU-PRO Plus within clinical care and patient management.

Project description:Seasonal influenza surveillance is usually carried out by sentinel general practitioners (GPs) who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This traditional practice for surveillance generally presents several issues, such as a delay of one week or more in releasing reports, population biases in the health-seeking behaviour, and the lack of a common definition of ILI case. On the other hand, the availability of novel data streams has recently led to the emergence of non-traditional approaches for disease surveillance that can alleviate these issues. In Europe, a participatory web-based surveillance system called Influenzanet represents a powerful tool for monitoring seasonal influenza epidemics thanks to aid of self-selected volunteers from the general population who monitor and report their health status through Internet-based surveys, thus allowing a real-time estimate of the level of influenza circulating in the population. In this work, we propose an unsupervised probabilistic framework that combines time series analysis of self-reported symptoms collected by the Influenzanet platforms and performs an algorithmic detection of groups of symptoms, called syndromes. The aim of this study is to show that participatory web-based surveillance systems are capable of detecting the temporal trends of influenza-like illness even without relying on a specific case definition. The methodology was applied to data collected by Influenzanet platforms over the course of six influenza seasons, from 2011-2012 to 2016-2017, with an average of 34,000 participants per season. Results show that our framework is capable of selecting temporal trends of syndromes that closely follow the ILI incidence rates reported by the traditional surveillance systems in the various countries (Pearson correlations ranging from 0.69 for Italy to 0.88 for the Netherlands, with the sole exception of Ireland with a correlation of 0.38). The proposed framework was able to forecast quite accurately the ILI trend of the forthcoming influenza season (2016-2017) based only on the available information of the previous years (2011-2016). Furthermore, to broaden the scope of our approach, we applied it both in a forecasting fashion to predict the ILI trend of the 2016-2017 influenza season (Pearson correlations ranging from 0.60 for Ireland and UK, and 0.85 for the Netherlands) and also to detect gastrointestinal syndrome in France (Pearson correlation of 0.66). The final result is a near-real-time flexible surveillance framework not constrained by any specific case definition and capable of capturing the heterogeneity in symptoms circulation during influenza epidemics in the various European countries.

Project description:Individuals with sickle cell disease (SCD) experience neurocognitive decline, low medication adherence, increased unemployment, and difficulty with instrumental activities of daily living (IADL). The relationship between self-perceived cognitive difficulties and IADLs, including employment, school enrollment, independence, engagement in leisure activities, and medication adherence is unknown. We hypothesized that self-reported difficulties across neurocognitive areas would predict lower IADL skills. Adolescent and adult participants of the multi-site Sickle Cell Disease Implementation Consortium (SCDIC) (n = 2436) completed patient-reported outcome (PRO) measures of attention, executive functioning, processing speed, learning, and comprehension. Cognitive symptoms were analyzed as predictors in multivariable modeling. Outcome variables included 1) an IADL composite that consisted of employment, participation in school, reliance on others, and leisure pursuits, and 2) hydroxyurea adherence. Participants reported cognitive difficulty across areas of attention (55%), executive functioning (51%), processing speed (57%), and reading comprehension (65%). Executive dysfunction (p < 0.001) and sometimes or often experiencing learning difficulties (p < 0.001 and p = 0.04) and poor comprehension (p = 0.000 and p = 0.001), controlled for age (p < 0.001), pain (p < 0.001), and hydroxyurea use (p = 0.001), were associated with poor IADL skills. Executive functioning difficulties (p = 0.021), controlled for age (p = 0.013 for ages 25-34), genotype (p = 0.001), and hemoglobin (p = 0.004), predicted hydroxyurea non-adherence. Analysis of PRO measures indicated that cognitive dysfunction is prevalent in adolescents and adults with SCD. Cognitive dysfunction translated into clinically meaningful outcomes. PRO of cognitive symptoms can be used as an important adjunct clinical tool to monitor symptoms that impact functional skills, including engagement in societal activities and medication adherence.

Project description:IntroductionDirectly recorded patient experience of symptoms and health-related quality of life (HRQoL) can complement lung function and exacerbation rate data in chronic obstructive pulmonary disease (COPD) clinical studies. The FULFIL study recorded daily symptoms and activity limitation together with additional patient-reported outcomes of dyspnea and HRQoL, as part of the prespecified analyses. FULFIL co-primary endpoint data have been previously reported.MethodsFULFIL was a phase III, 24-week, randomized, double-blind, double-dummy, multicenter study comparing once-daily single inhaler triple therapy [fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI)] 100 µg/62.5 µg/25 µg with twice-daily inhaled corticosteroid/long-acting β2-agonist therapy [budesonide/formoterol (BUD/FOR)] 400 µg/12 µg in patients with symptomatic COPD at risk of exacerbations. A subset participated for 52 weeks. Patient-reported assessments were: Evaluating Respiratory Symptoms in COPD™ (E-RS: COPD), St George's Respiratory Questionnaire (SGRQ) for COPD, COPD Assessment Test (CAT), baseline and transitional dyspnea indices (TDI) and daily and global anchor questions for activity limitation.ResultsFF/UMEC/VI showed greater reductions from baseline in 4-weekly mean E-RS: COPD total and all subscale scores compared with BUD/FOR; differences were statistically significant (P < 0.05) at each time period. FF/UMEC/VI also demonstrated greater improvements from baseline at weeks 4 and 24 in SGRQ domain scores and TDI focal score compared with BUD/FOR. At weeks 4 and 24, improvements greater than the minimal clinically important difference from baseline were observed in CAT score with FF/UMEC/VI, but not BUD/FOR; differences were statistically significant (P ≤ 0.003).ConclusionThese findings demonstrate sustained daily symptom and HRQoL benefits of FF/UMEC/VI versus BUD/FOR. The inclusion of the CAT may provide data that are readily generalizable to everyday clinical practice.Trial registrationClinicalTrials.gov number: NCT02345161.FundingGSK.

Dataset Information

Surveillance and Correlation of Severe Acute Respiratory Syndrome Coronavirus 2 Viral RNA, Antigen, Virus Isolation, and Self-Reported Symptoms in a Longitudinal Study With Daily Sampling.

Publications

Surveillance and Correlation of Severe Acute Respiratory Syndrome Coronavirus 2 Viral RNA, Antigen, Virus Isolation, and Self-Reported Symptoms in a Longitudinal Study With Daily Sampling.

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