Open peer-review platform for COVID-19 preprints

Johansson, Michael A.; Saderi, Daniela

doi:10.1038/d41586-020-00613-4

Cited by 53 publications

(40 citation statements)

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“…[43][44][45][46][47] The evidence base for the development and validation of prediction models related to COVID-19 will quickly increase over the coming months. Together with the increasing evidence from predictor finding studies [48][49][50][51][52][53][54] and open peer review initiatives for COVID-19 related publications, 55 data registries 56-60 are being set up. To maximize the new opportunities and to facilitate IPD meta-analyses, the WHO has recently released a new data platform to encourage sharing of anonymized COVID-19 clinical data.…”

Section: Covid-19 Prediction Problems Will Often Not Present As a Simmentioning

confidence: 99%

Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection

Wynants

Calster

Bonten

et al. 2020

Preprint

165

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words)Objective To review and critically appraise published and preprint reports of models that aim to predict either (i) presence of existing COVID-19 infection, (ii) future complications in individuals already diagnosed with COVID-19, or (iii) models to identify individuals at high risk for COVID-19 in the general population.Design Rapid systematic review and critical appraisal of prediction models for diagnosis or prognosis of COVID-19 infection. Data sourcesPubMed, EMBASE via Ovid, Arxiv, medRxiv and bioRxiv until 24 th March 2020. Study selectionStudies that developed or validated a multivariable COVID-19 related prediction model. Two authors independently screened titles, abstracts and full text. Data extractionData from included studies were extracted independently by at least two authors based on the CHARMS checklist, and risk of bias was assessed using PROBAST.Data were extracted on various domains including the participants, predictors, outcomes, data analysis, and prediction model performance.Results 2696 titles were screened. Of these, 27 studies describing 31 prediction models were included for data extraction and critical appraisal. We identified three models to predict hospital admission from pneumonia and other events (as a proxy for covid-19 pneumonia) in the general population; 18 diagnostic models to detect COVID-19 infection in symptomatic individuals (13 of which were machine learning utilising computed tomography (CT) results); and ten prognostic models for predicting mortality risk, progression to a severe state, or length of hospital stay. Only one of these studies used data on COVID-19 cases outside of China.Most reported predictors of presence of COVID-19 in suspected patients included age, body temperature, and signs and symptoms. Most reported predictors of severe prognosis in

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Section: Covid-19 Prediction Problems Will Often Not Present As a Simmentioning

confidence: 99%

Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection

Wynants

Calster

Bonten

et al. 2020

Preprint

165

View full text Add to dashboard Cite

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“…At present, a total of 70,547 cases have been cured and discharged in China. In this outbreak, the elderly population is generally susceptible with high incidence of severe disease and mortality [2]. Community-acquired pneumonia in the elderly population has been found to result in decreased activities of daily living (ADL) and QoL, accompanied by decreased physical and mental function [3].…”

Section: Introductionmentioning

confidence: 99%

Respiratory rehabilitation in elderly patients with COVID-19: A randomized controlled study

Liu

Zhang

Yang

et al. 2020

Complementary Therapies in Clinical Practice

586

798

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“…Dissemination of research findings via pre-publication (prior to peer-review) reduces delays, but carries risks for validation of methodology, accuracy of data, and interpretation of findings. The extraordinary number of COVID-19 articles being submitted to pre-publication servers 28 has led to a rapid, open, peer-review platform for COVID-19 preprints, 29 in an attempt to improve quality control.…”

Section: Discussionmentioning

confidence: 99%

Compassionate drug (mis)use during pandemics: lessons for COVID-19 from 2009

Rojek

Martin

Horby

2020

Preprint

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Open peer-review platform for COVID-19 preprints

Abstract: Correspondence© 2 0 2 0 S p r i n g e r N a t u r e L i m i t e d . A l l r i g h t s r e s e r v e d .

Cited by 53 publications

References 0 publications

Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection

Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection

Respiratory rehabilitation in elderly patients with COVID-19: A randomized controlled study

Compassionate drug (mis)use during pandemics: lessons for COVID-19 from 2009

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