Clinical characteristics of SARS-CoV-2 patients: a French cross-sectional study in primary care

Sebo, Paul; Tudrej, B.V.; Lourdaux, Julie; Cuzin, Clara; Floquet, Martin; Haller, Dagmar M.; Maisonneuve, Hubert

doi:10.21203/rs.3.rs-34635/v1

Cited by 4 publications

(9 citation statements)

References 19 publications

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“…Regarding our results of the reported symptoms, loss of smell (anosmia) was the strongest indicator of SARS-CoV-2, followed by fever, shortness of breath, myalgia, cough, nausea, diarrhea, and coryza. The significant influence of loss of smell and cough is in line with previous studies carried out in high-income countries such as the US and UK [2,12–14], and the influence of fever, myalgia, and nausea was pointed as significant in some studies [13,14], but others noted as not associated [2,12]. Regarding sore throat, diarrhea, and shortness of breath, previous studies observed that they are not significant predictors for the SARS-CoV-2 infection [2,12–14].…”

Section: Discussionsupporting

confidence: 89%

“…Sebo and colleagues [14] studied a sample of 1,543 primary care patients tested in two laboratories in the Lyon area (France) and found that the two symptoms most strongly associated with a positive test were loss of taste (ageusia) and loss of smell and that the combination of these symptoms resulted in an even stronger association (i.e., the odds of having a positive test were six times greater than the odds of having a negative test). A recent literature review of studies analyzing the presence of loss of taste and smell in SARS-CoV-2 infected patients concluded that, from a total of 10,818 patients, 8,823 presented ageusia (81.6%) and 8,088 presented anosmia (74.8%) [15].…”

Section: Discussionmentioning

confidence: 99%

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App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

Dantas

Peres

Bastos

et al. 2020

Preprint

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Background: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of symptoms to build a regression model as a screening tool to identify people and areas with a higher risk of SARS-CoV-2 infection to be prioritized for testing. Materials and Methods: We applied machine learning techniques and provided a visualization of potential regions with high densities of COVID-19 as a risk map. We performed a retrospective analysis of individuals registered in "Dados do Bem", an app-based symptom tracker in use in Brazil. Results: From April 28 to July 16, 2020, 337,435 individuals registered their symptoms through the app. Of these, 49,721 participants were tested for SARS-CoV-2 infection, being 5,888 (11.8%) positive. Among self-reported symptoms, loss of smell (OR[95%CI]: 4.6 [4.4 - 4.9]), fever (2.6 [2.5 - 2.8]), and shortness of breath (2.1 [1.6-2.7]) were associated with SARS-CoV-2 infection. Our final model obtained a competitive performance, with only 7% of false-negative users among the predicted as negatives (NPV = 0.93). From the 287,714 users still not tested, our model estimated that only 34.5% are potentially infected, thus reducing the need for extensive testing of all registered users. The model was incorporated by the "Dados do Bem" app aiming to prioritize users for testing. We developed an external validation in the state of Goias and found that of the 465 users selected, 52% tested positive. Conclusions: Our results showed that the combination of symptoms might predict SARS-Cov-2 infection and, therefore, can be used as a tool by decision-makers to refine testing and disease control strategies.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

Dantas

Peres

Bastos

et al. 2020

Preprint

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Section: Plos Onesupporting

confidence: 90%

“…influence of fever, myalgia, and nausea was pointed as significant in some studies [25,26]. However, other authors noted it as not associated [6,24].…”

Section: Plos Onementioning

confidence: 95%

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

et al. 2021

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Background Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of symptoms to build a predictive model as a screening tool to identify people and areas with a higher risk of SARS-CoV-2 infection to be prioritized for testing. Materials and methods We performed a retrospective analysis of individuals registered in "Dados do Bem," a Brazilian app-based symptom tracker. We applied machine learning techniques and provided a SARS-CoV-2 infection risk map of Rio de Janeiro city. Results From April 28 to July 16, 2020, 337,435 individuals registered their symptoms through the app. Of these, 49,721 participants were tested for SARS-CoV-2 infection, being 5,888 (11.8%) positive. Among self-reported symptoms, loss of smell (OR[95%CI]: 4.6 [4.4–4.9]), fever (2.6 [2.5–2.8]), and shortness of breath (2.1 [1.6–2.7]) were independently associated with SARS-CoV-2 infection. Our final model obtained a competitive performance, with only 7% of false-negative users predicted as negatives (NPV = 0.93). The model was incorporated by the "Dados do Bem" app aiming to prioritize users for testing. We developed an external validation in the city of Rio de Janeiro. We found that the proportion of positive results increased significantly from 14.9% (before using our model) to 18.1% (after the model). Conclusions Our results showed that the combination of symptoms might predict SARS-Cov-2 infection and, therefore, can be used as a tool by decision-makers to refine testing and disease control strategies.

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“…Dry nose, loss of taste and/or smell, and muscle pain are frequent complaints of COVID-19 patients who visit their family practitioner [41, 42], while hospitalised patients [4] usually complain of fever, dry cough, dyspnoea, chest pain, fatigue, and myalgia. Almost 95% of the infected people present mild or moderate symptoms that do not necessitate hospital-based care.…”

Section: Discussionmentioning

confidence: 99%

COVID-19: Can early home treatment with Azithromycin alone or with Zinc help prevent hospitalisation, death, and long-COVID-19? A review

Lepere

Escarguel

et al. 2021

Preprint

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IntroductionThe effects of the SARS-CoV-2 pandemic continues to disrupt health systems worldwide, leading to population lockdowns in many countries. Preventing hospitalisation, death and long-COVID-19 with repurposed drugs remains a priority. Hydroxychloroquine (HCQ) and azithromycin (AZM) are the most commonly used in ambulatory care, with divergent results. With the aim of decentralizing early treatment to family practitioners, we addressed the question: Can early home treatment with AZM alone or with zinc help prevent hospitalisation, death, and long-COVID-19?MethodologyWe conducted a scoping review of articles published from 31st December 2019 to 5th November 2020 in Pubmed, Google Scholar, MedRxiv, and BioRxiv databases, and a review of undergoing clinical trials published in the Clinicaltrial.gov database.ResultsMany studies report on outpatient treatment with a combination of AZM + HCQ versus AZM alone, and few studies propose the addition of Zinc (Zn) to AZM. In addition, we identified 5 clinical trials currently recruiting individuals for early outpatient treatment with AZM. However, we failed in identifying any study or clinical trial conducted with family practitioners responding to our question.DiscussionThe antiviral, anti-inflammatory, immunomodulatory benefits of AZM + Zn make this drugs combination a good candidate therapy to treat flu-like-COVID-19 and atypical pneumoniae. The antibacterial action of AZM can also help disrupting the bacteria/virus cooperation that is poorly documented. Considering pros and cons of macrolide use (including antimicrobial resistance), we call for early use of this therapy by family practitioners for home treatment of individuals presenting mild or moderate symptoms under rigorous scientific guidance to prevent hospitalisation, death and long-COVID.

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Clinical characteristics of SARS-CoV-2 patients: a French cross-sectional study in primary care

Cited by 4 publications

References 19 publications

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning

COVID-19: Can early home treatment with Azithromycin alone or with Zinc help prevent hospitalisation, death, and long-COVID-19? A review

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