132 research outputs found

    A qualitative analysis of a consensus process to develop quality indicators of injury care

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    Article deposited according to agreement with BMC, December 2, 2010 and according to publisher policies: http://www.biomedcentral.com/about/copyright [May 30, 2013].YesFunding provided by the Open Access Authors Fund

    Biomarkers for diagnosing serious bacterial infections in older outpatients: a systematic review

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    Background The value of biomarkers for diagnosing bacterial infections in older outpatients is uncertain and limited official guidance exists for clinicians in this area. The aim of this review is to critically appraise and evaluate biomarkers for diagnosing bacterial infections in older adults (aged 65 years and above). Methods We searched Medline, Embase, Web of Science and the Cochrane Library, from inception to January 2018. We included studies assessing the diagnostic accuracy of blood, urinary, and salivary biomarkers in diagnosing bacterial infections in older adults. The QUADAS-2 tool was used to assess study quality. Results We identified 11 eligible studies of moderate quality (11,034 participants) including 51 biomarkers at varying thresholds for diagnosing bacterial infections. An elevated Procalcitonin (≥ 0.2 ng/mL) may help diagnose bacteraemia in older adults [+ve LR range 1.50 to 2.60]. A CRP ≥ 50 mg/L only raises the probability of bacteraemia by 5%. A positive urine dipstick aids diagnosis of UTI (+ve LR range 1.23 to 54.90), and absence helps rule out UTI (−ve LR range 0.06 to 0.46). An elevated white blood cell count is unhelpful in diagnosing intra-abdominal infections (+ve LR range 0.75 to 2.62), but may aid differentiation of bacterial infection from other acute illness (+ve LR range 2.14 to 7.12). Conclusions The limited available evidence suggests that many diagnostic tests useful in younger patients, do not help to diagnose bacterial infections in older adults. Further evidence from high quality studies is urgently needed to guide clinical practice. Until then, symptoms and signs remain the mainstay of diagnosis in community based populations

    Heterogeneity in transmissibility and shedding SARS-CoV-2 via droplets and aerosols

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    Background: Which virological factors mediate overdispersion in the transmissibility of emerging viruses remains a longstanding question in infectious disease epidemiology. Methods: Here, we use systematic review to develop a comprehensive dataset of respiratory viral loads (rVLs) of SARS-CoV-2, SARS-CoV-1 and influenza A(H1N1)pdm09. We then comparatively meta-analyze the data and model individual infectiousness by shedding viable virus via respiratory droplets and aerosols. Results: The analyses indicate heterogeneity in rVL as an intrinsic virological factor facilitating greater overdispersion for SARS-CoV-2 in the COVID-19 pandemic than A(H1N1)pdm09 in the 2009 influenza pandemic. For COVID-19, case heterogeneity remains broad throughout the infectious period, including for pediatric and asymptomatic infections. Hence, many COVID-19 cases inherently present minimal transmission risk, whereas highly infectious individuals shed tens to thousands of SARS-CoV-2 virions/min via droplets and aerosols while breathing, talking and singing. Coughing increases the contagiousness, especially in close contact, of symptomatic cases relative to asymptomatic ones. Infectiousness tends to be elevated between 1-5 days post-symptom onset. Conclusions: Intrinsic case variation in rVL facilitates overdispersion in the transmissibility of emerging respiratory viruses. Our findings present considerations for disease control in the COVID-19 pandemic as well as future outbreaks of novel viruses.</p

    Timeliness of reporting of SARS-CoV-2 seroprevalence results and their utility for infectious disease surveillance

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    Seroprevalence studies have been used throughout the COVID-19 pandemic to monitor infection and immunity. These studies are often reported in peer-reviewed journals, but the academic writing and publishing process can delay reporting and thereby public health action. Seroprevalence estimates have been reported faster in preprints and media, but with concerns about data quality. We aimed to (i) describe the timeliness of SARS-CoV-2 serosurveillance reporting by publication venue and study characteristics and (ii) identify relationships between timeliness, data validity, and representativeness to guide recommendations for serosurveillance efforts. We included seroprevalence studies published between January 1, 2020 and December 31, 2021 from the ongoing SeroTracker living systematic review. For each study, we calculated timeliness as the time elapsed between the end of sampling and the first public report. We evaluated data validity based on serological test performance and correction for sampling error, and representativeness based on the use of a representative sample frame and adequate sample coverage. We examined how timeliness varied with study characteristics, representativeness, and data validity using univariate and multivariate Cox regression. We analyzed 1844 studies. Median time to publication was 154 days (IQR 64–255), varying by publication venue (journal articles: 212 days, preprints: 101 days, institutional reports: 18 days, and media: 12 days). Multivariate analysis confirmed the relationship between timeliness and publication venue and showed that general population studies were published faster than special population or health care worker studies; there was no relationship between timeliness and study geographic scope, geographic region, representativeness, or serological test performance. Seroprevalence studies in peer-reviewed articles and preprints are published slowly, highlighting the limitations of using the academic literature to report seroprevalence during a health crisis. More timely reporting of seroprevalence estimates can improve their usefulness for surveillance, enabling more effective responses during health emergencies

    SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies

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    Risk of bias (RoB) assessments are a core element of evidence synthesis but can be time consuming and subjective. We aimed to develop a decision rule-based algorithm for RoB assessment of seroprevalence studies. We developed the SeroTracker-RoB algorithm. The algorithm derives seven objective and two subjective critical appraisal items from the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence studies and implements decision rules that determine study risk of bias based on the items. Decision rules were validated using the SeroTracker seroprevalence study database, which included non-algorithmic RoB judgments from two reviewers. We quantified efficiency as the mean difference in time for the algorithmic and non-algorithmic assessments of 80 randomly selected articles, coverage as the proportion of studies where the decision rules yielded an assessment, and reliability using intraclass correlations comparing algorithmic and non-algorithmic assessments for 2070 articles. A set of decision rules with 61 branches was developed using responses to the nine critical appraisal items. The algorithmic approach was faster than non-algorithmic assessment (mean reduction 2.32 min [SD 1.09] per article), classified 100% (n = 2070) of studies, and had good reliability compared to non-algorithmic assessment (ICC 0.77, 95% CI 0.74–0.80). We built the SeroTracker-RoB Excel Tool, which embeds this algorithm for use by other researchers. The SeroTracker-RoB decision-rule based algorithm was faster than non-algorithmic assessment with complete coverage and good reliability. This algorithm enabled rapid, transparent, and reproducible RoB evaluations of seroprevalence studies and may support evidence synthesis efforts during future disease outbreaks. This decision rule-based approach could be applied to other types of prevalence studies

    Lack of evidence for interventions offered in UK fertility centres

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    Carl Heneghan and colleagues call for better quality evidence to help people seeking assisted reproduction make informed choices

    Serology assays used in SARS-CoV-2 seroprevalence surveys worldwide: a systematic review and meta-analysis of assay features, testing algorithms, and performance

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    Many serological assays to detect SARS-CoV-2 antibodies were developed during the COVID-19 pandemic. Differences in the detection mechanism of SARS-CoV-2 serological assays limited the comparability of seroprevalence estimates for populations being tested. We conducted a systematic review and meta-analysis of serological assays used in SARS-CoV-2 population seroprevalence surveys, searching for published articles, preprints, institutional sources, and grey literature between 1 January 2020, and 19 November 2021. We described features of all identified assays and mapped performance metrics by the manufacturers, third-party head-to-head, and independent group evaluations. We compared the reported assay performance by evaluation source with a mixed-effect beta regression model. A simulation was run to quantify how biased assay performance affects population seroprevalence estimates with test adjustment. Among 1807 included serosurveys, 192 distinctive commercial assays and 380 self-developed assays were identified. According to manufacturers, 28.6% of all commercial assays met WHO criteria for emergency use (sensitivity [Sn.] &gt;= 90.0%, specificity [Sp.] &gt;= 97.0%). However, manufacturers overstated the absolute values of Sn. of commercial assays by 1.0% [0.1, 1.4%] and 3.3% [2.7, 3.4%], and Sp. by 0.9% [0.9, 0.9%] and 0.2% [-0.1, 0.4%] compared to third-party and independent evaluations, respectively. Reported performance data was not sufficient to support a similar analysis for self-developed assays. Simulations indicate that inaccurate Sn. and Sp. can bias seroprevalence estimates adjusted for assay performance; the error level changes with the background seroprevalence. The Sn. and Sp. of the serological assay are not fixed properties, but varying features depending on the testing population. To achieve precise population estimates and to ensure the comparability of seroprevalence, serosurveys should select assays with high performance validated not only by their manufacturers and adjust seroprevalence estimates based on assured performance data. More investigation should be directed to consolidating the performance of self-developed assays

    Adherence of SARS‐CoV‐2 Seroepidemiologic Studies to the ROSES‐S Reporting Guideline During the COVID‐19 Pandemic

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    Background: Complete reporting of seroepidemiologic studies is critical to their utility in evidence synthesis and public health decision making. The Reporting of Seroepidemiologic studies—SARS‐CoV‐2 (ROSES‐S) guideline is a checklist that aims to improve reporting in SARS‐CoV‐2 seroepidemiologic studies. Adherence to the ROSES‐S guideline has not yet been evaluated. Objectives: This study aims to evaluate the completeness of SARS‐CoV‐2 seroepidemiologic study reporting by the ROSES‐S guideline during the COVID‐19 pandemic, determine whether guideline publication was associated with reporting completeness, and identify study characteristics associated with reporting completeness. Methods: A random sample from the SeroTracker living systematic review database was evaluated. For each reporting item in the guideline, the percentage of studies that were adherent was calculated, as well as median and interquartile range (IQR) adherence across all items and by item domain. Beta regression analyses were used to evaluate predictors of adherence to ROSES‐S. Results: One hundred and ninety‐nine studies were analyzed. Median adherence was 48.1% (IQR 40.0%–55.2%) per study, with overall adherence ranging from 8.8% to 72.7%. The laboratory methods domain had the lowest median adherence (33.3% [IQR 25.0%–41.7%]). The discussion domain had the highest median adherence (75.0% [IQR 50.0%–100.0%]). Reporting adherence to ROSES‐S before and after guideline publication did not significantly change. Publication source (p < 0.001), study risk of bias (p = 0.001), and sampling method (p = 0.004) were significantly associated with adherence. Conclusions: Completeness of reporting in SARS‐CoV‐2 seroepidemiologic studies was suboptimal. Publication of the ROSES‐S guideline was not associated with changes in reporting practices. Authors should improve adherence to the ROSES‐S guideline with support from stakeholders
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