Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care

BACKGROUND: There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP). OBJECTIVES: To develop and validate a risk prediction model for hospital admission with readily available predictors. METHODS: A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort. RESULTS: In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept -0.08, 95% CI -0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI -0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation). CONCLUSION: We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended

Panel 7: otitis media:treatment and complications

Objective: We aimed to summarize key articles published between 2011 and 2015 on the treatment of (recurrent) acute otitis media, otitis media with effusion, tympanostomy tube otorrhea, chronic suppurative otitis media and complications of otitis media, and their implications for clinical practice. Data Sources: PubMed, Ovid Medline, the Cochrane Library, and Clinical Evidence (BMJ Publishing). Review Methods: All types of articles related to otitis media treatment and complications between June 2011 and March 2015 were identified. A total of 1122 potential related articles were reviewed by the panel members; 118 relevant articles were ultimately included in this summary. Conclusions: Recent literature and guidelines emphasize accurate diagnosis of acute otitis media and optimal management of ear pain. Watchful waiting is optional in mild to moderate acute otitis media; antibiotics do shorten symptoms and duration of middle ear effusion. The additive benefit of adenoidectomy to tympanostomy tubes in recurrent acute otitis media and otitis media with effusion is controversial and age dependent. Topical antibiotic is the treatment of choice in acute tube otorrhea. Symptomatic hearing loss due to persistent otitis media with effusion is best treated with tympanostomy tubes. Novel molecular and biomaterial treatments as adjuvants to surgical closure of eardrum perforations seem promising. There is insufficient evidence to support the use of complementary and alternative treatments. Implications for Practice: Emphasis on accurate diagnosis of otitis media, in its various forms, is important to reduce overdiagnosis, overtreatment, and antibiotic resistance. Children at risk for otitis media and its complications deserve special attention

Strategies in a metallophyte species to cope with manganese excess

The effect of exposure to high Mn concentration was studied in a metallophyte species, Erica andevalensis, using hydroponic cultures with a range of Mn concentrations (0.06, 100, 300, 500, and 700 mg L-1). At harvest, biomass production, element uptake, and biochemical indicators of metal stress (leaf pigments, organic acids, amino acids, phenols, and activities of catalase, peroxidase, superoxide dismutase) were determined in leaves and roots. Increasing Mn concentrations led to a decrease in biomass accumulation, and tip leaves chlorosis was the only toxicity symptom detected. In a similar way, photosynthetic pigments (chlorophylls a and b, and carotenoids) were affected by high Mn levels. Among organic acids, malate and oxalate contents in roots showed a significant increase at the highest Mn concentration, while in leaves, Mn led to an increasing trend in citrate and malate contents. An increase of Mn also induced an increase in superoxide dismutase activity in roots and catalase activity in leaves. As well, significant changes in free amino acids were induced by Mn concentrations higher than 300 mg L-1, especially in roots. No significant changes in phenolic compounds were observed in the leaves, but root phenolics were significantly increased by increasing Mn concentrations in treatments. When Fe supply was increased 10 and 20 times (7–14 mg Fe L-1 as Fe-EDDHA) in the nutrient solutions at the highest Mn concentration (700 mg Mn L-1), it led to significant increases in photosynthetic pigments and biomass accumulation. Manganese was mostly accumulated in the roots, and the species was essentially a Mn excluder. However, considering the high leaf Mn concentration recorded without toxicity symptoms, E. andevalensis might be rated as a Mn-tolerant speciesinfo:eu-repo/semantics/publishedVersio

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care

BackgroundThere is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP).ObjectivesTo develop and validate a risk prediction model for hospital admission with readily available predictors.MethodsA retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort.ResultsIn the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept −0.08, 95% CI −0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI −0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation).ConclusionWe derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended

Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care

There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP). To develop and validate a risk prediction model for hospital admission with readily available predictors. A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort. In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept −0.08, 95% CI −0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI −0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation). We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended. A general practice prediction model based on signs and symptoms of COVID-19 patients reliably predicted hospitalisation. The model performed well in second-wave data with other dominant variants and changed testing and vaccination policies. In an emerging pandemic, GP data can be leveraged to develop prognostic models for decision support and to predict hospitalisation rates.</p

Diagnostic accuracy of SARS-CoV-2 rapid antigen self-tests in asymptomatic individuals in the Omicron period: cross sectional study.

OBJECTIVES: To assess the performances of three commonly used antigen rapid diagnostic tests used as self-tests in asymptomatic individuals in the Omicron period. METHODS: We performed a cross-sectional diagnostic test accuracy study in the Omicron period in three public health service COVID-19 test sites in the Netherlands, including 3600 asymptomatic individuals aged [Formula: see text] 16 years presenting for SARS-CoV-2 testing for any reason except confirmatory testing after a positive self-test. Participants were sampled for RT-PCR (reference test) and received one self-test (either Acon Flowflex [Flowflex], MP Biomedicals (MPBio), or Siemens-Healthineers CLINITEST [CLINITEST]) to perform unsupervised at home. Diagnostic accuracies of each self-test were calculated. RESULTS: Overall sensitivities were 27.5% (95% CI, 21.3–34.3%) for Flowflex, 20.9% (13.9–29.4%) for MPBio, and 25.6% (19.1–33.1%) for CLINITEST. After applying a viral load cut-off (≥5.2 log10 SARS-CoV-2 E-gene copies/mL), sensitivities increased to 48.3% (37.6–59.2%), 37.8% (22.5–55.2%), and 40.0% (29.5–51.2%), respectively. Specificities were >99% for all tests in most analyses. DISCUSSION: The sensitivities of three commonly used SARS-CoV-2 antigen rapid diagnostic tests when used as self-tests in asymptomatic individuals in the Omicron period were very low. Antigen rapid diagnostic test self-testing in asymptomatic individuals may only detect a minority of infections at that point in time. Repeated self-testing in case of a negative self-test is advocated to improve the diagnostic yield, and individuals should be advised to re-test when symptoms develop