Agreement among Health Care Professionals in Diagnosing Case Vignette-Based Surgical Site Infections

OBJECTIVE: To assess agreement in diagnosing surgical site infection (SSI) among healthcare professionals involved in SSI surveillance. METHODS: Case-vignette study done in 2009 in 140 healthcare professionals from seven specialties (20 in each specialty, Anesthesiologists, Surgeons, Public health specialists, Infection control physicians, Infection control nurses, Infectious diseases specialists, Microbiologists) in 29 University and 36 non-University hospitals in France. We developed 40 case-vignettes based on cardiac and gastrointestinal surgery patients with suspected SSI. Each participant scored six randomly assigned case-vignettes before and after reading the SSI definition on an online secure relational database. The intraclass correlation coefficient (ICC) was used to assess agreement regarding SSI diagnosis on a seven-point Likert scale and the kappa coefficient to assess agreement for superficial or deep SSI on a three-point scale. RESULTS: Based on a consensus, SSI was present in 21 of 40 vignettes (52.5%). Intraspecialty agreement for SSI diagnosis ranged across specialties from 0.15 (95% confidence interval, 0.00-0.59) (anesthesiologists and infection control nurses) to 0.73 (0.32-0.90) (infectious diseases specialists). Reading the SSI definition improved agreement in the specialties with poor initial agreement. Intraspecialty agreement for superficial or deep SSI ranged from 0.10 (-0.19-0.38) to 0.54 (0.25-0.83) (surgeons) and increased after reading the SSI definition only among the infection control nurses from 0.10 (-0.19-0.38) to 0.41 (-0.09-0.72). Interspecialty agreement for SSI diagnosis was 0.36 (0.22-0.54) and increased to 0.47 (0.31-0.64) after reading the SSI definition. CONCLUSION: Among healthcare professionals evaluating case-vignettes for possible surgical site infection, there was large disagreement in diagnosis that varied both between and within specialties

Using and Reporting the Delphi Method for Selecting Healthcare Quality Indicators: A Systematic Review

OBJECTIVE: Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi method to develop quality indicators, 2) to discuss specific methodological skills for quality indicators selection 3) to give guidance about this practice. METHODOLOGY AND MAIN FINDING: Three electronic data bases were searched over a 30 years period (1978-2009). All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. CONCLUSION: The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys

Real-time numerical forecast of global epidemic spreading: Case study of 2009 A/H1N1pdm

Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. Methods We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Results Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Conclusions Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models

Variability of the chronic obstructive pulmonary disease key epidemiological data in Europe: systematic review

<p>Abstract</p> <p>Background</p> <p>Chronic obstructive pulmonary disease (COPD) is predicted to become a major cause of death worldwide. Studies on the variability in the estimates of key epidemiological parameters of COPD may contribute to better assessment of the burden of this disease and to helpful guidance for future research and public policies. In the present study, we examined differences in the main epidemiological characteristics of COPD derived from studies across countries of the European Union, focusing on prevalence, severity, frequency of exacerbations and mortality, as well as on differences between the studies' methods.</p> <p>Methods</p> <p>This systematic review was based on a search for the relevant literature in the Science Citation Index database via the Web of Science and on COPD mortality rates issued from national statistics. Analysis was finally based on 65 articles and Eurostat COPD mortality data for 21 European countries.</p> <p>Results</p> <p>Epidemiological characteristics of COPD varied widely from country to country. For example, prevalence estimates ranged between 2.1% and 26.1%, depending on the country, the age group and the methods used. Likewise, COPD mortality rates ranged from 7.2 to 36.1 per 10⁵inhabitants. The methods used to estimate these epidemiological parameters were highly variable in terms of the definition of COPD, severity scales, methods of investigation and target populations. Nevertheless, to a large extent, several recent international guidelines or research initiatives, such as GOLD, BOLD or PLATINO, have boosted a substantial standardization of methodology in data collection and have resulted in the availability of more comparable epidemiological estimates across countries. On the basis of such standardization, severity estimates as well as prevalence estimates present much less variation across countries. The contribution of these recent guidelines and initiatives is outlined, as are the problems remaining in arriving at more accurate COPD epidemiological estimates across European countries.</p> <p>Conclusions</p> <p>The accuracy of COPD epidemiological parameters is important for guiding decision making with regard to preventive measures, interventions and patient management in various health care systems. Therefore, the recent initiatives for standardizing data collection should be enhanced to result in COPD epidemiological estimates of improved quality. Moreover, establishing international guidelines for reporting research on COPD may also constitute a major contribution.</p

J Clin Immunol

We report a longitudinal analysis of the immune response associated with a fatal case of COVID-19 in Europe. This patient exhibited a rapid evolution towards multiorgan failure. SARS-CoV-2 was detected in multiple nasopharyngeal, blood, and pleural samples, despite antiviral and immunomodulator treatment. Clinical evolution in the blood was marked by an increase (2–3-fold) in differentiated effector T cells expressing exhaustion (PD-1) and senescence (CD57) markers, an expansion of antibody-secreting cells, a 15-fold increase in γδ T cell and proliferating NK-cell populations, and the total disappearance of monocytes, suggesting lung trafficking. In the serum, waves of a pro-inflammatory cytokine storm, Th1 and Th2 activation, and markers of T cell exhaustion, apoptosis, cell cytotoxicity, and endothelial activation were observed until the fatal outcome. This case underscores the need for well-designed studies to investigate complementary approaches to control viral replication, the source of the hyperinflammatory status, and immunomodulation to target the pathophysiological response. The investigation was conducted as part of an overall French clinical cohort assessing patients with COVID-19 and registered in clinicaltrials.gov under the following number: NCT04262921

High–temporal resolution profiling reveals distinct immune trajectories following the first and second doses of COVID-19 mRNA vaccines

Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here, we investigated responses to coronavirus disease 2019 (COVID-19) mRNA vaccination via high–temporal resolution blood transcriptome profiling. The first vaccine dose elicited modest interferon and adaptive immune responses, which peaked on days 2 and 5, respectively. The second vaccine dose, in contrast, elicited sharp day 1 interferon, inflammation, and erythroid cell responses, followed by a day 5 plasmablast response. Both post-first and post-second dose interferon signatures were associated with the subsequent development of antibody responses. Yet, we observed distinct interferon response patterns after each of the doses that may reflect quantitative or qualitative differences in interferon induction. Distinct interferon response phenotypes were also observed in patients with COVID-19 and were associated with severity and differences in duration of intensive care. Together, this study also highlights the benefits of adopting high-frequency sampling protocols in profiling vaccine-elicited immune responses

Nouvelles approches pour la segmentation et l'identification automatique des angiographies numérisées

L'analyse des angiographies numérisées en vue de la reconnaissance des principaux vaisseaux, nécessite une combinaison adéquate des techniques numériques et symboliques de traitement d'images. Une squelettisation qui tient compte de la transformation de distance et des propriétés topologiques des points, permet d'obtenir des primitives qui contiennent des informations sur le diamètre moyen des segments et sur leurs branchements. Les segments peuvent être regroupés en tenant compte des diamètres et des angles de déviation. Une approche heuristique permet de mettre en correspondance un modèle anatomique prédéfini décrivant la configuration bidimensionnelle des vaisseaux, avec les séquences de segments extraites de l'image. Les différents niveaux de représentation des données, l'application coordonnée des algorithmes et la mise en oeuvre d'une stratégie d'analyse sont pris en charge par une architecture de type tableau noir

[The evaluation of health care outcomes and hospital performance indicators].

International audienceINTRODUCTION: The assessment of the performance of health care establishments has undergone a considerable development over the past 15 years in the United States and to a lesser extent in other developed countries. BACKGROUND: The aim of measurement of performance indicators is to improve the quality of care (outcomes), patient information and the contractual arrangements with purchasers. However, this approach poses numerous methodological problems in the choice of performance indicators as well as the collection and interpretation of data. Specific structural patterns such as social and geographic environment, research and educational assignments, are often inadequately considered. In terms of public health the impact of the publication of these measurements has not been well studied. Based on the data in the literature this revue defines the measures of hospital performance and describes the main studies, their impacts and limitations. VIEWPOINT: It seems likely that the French public authorities will, in the short term, ask health care establishments to undertake this approach. CONCLUSIONS: Complimentary studies are needed to clarify the links between performance indicators and health care outcomes