COVID-19: a novel coronavirus and a novel challenge for critical care

Arabi, Yaseen M.; Murthy, Srinivas; Webb, Steve

doi:10.1007/s00134-020-05955-1

Cited by 271 publications

(276 citation statements)

References 23 publications

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“…1 Despite public health responses aimed at containing the disease and delaying the spread, several countries have been confronted with a critical care crisis, and more countries will almost certainly follow. [2][3][4] Outbreaks lead to important increases in the demand for hospital beds and shortage of medical equipment, while medical staff themselves may also get infected.…”

Section: Introductionmentioning

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

167

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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: Introductionmentioning

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

167

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“…Ein Einsatz kann unter Umständen nach einer Benefit-Risiko-Abwägung als Einzelfallentscheidung erwogen werden. Therapieversuche sollten, wenn möglich, im Rahmen von "Compassionate-Use"-Programmen oder Studienprotokollen durchgeführt werden [10]. Die Universität Liverpool hat eine Aufstellung wahrscheinlicher PK-Interaktionen mit experimentellen Therapien von COVID-19 veröffentlicht [11].…”

Section: Medikamentöse Therapieunclassified

Empfehlungen zur intensivmedizinischen Therapie von Patienten mit COVID-19

Kluge

Janssens

Welte

et al. 2020

Med Klin Intensivmed Notfmed

102

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“…The coronavirus disease COVID- 19 [1], whose outbreak was detected in China in December 2019 [2], has become pandemic and as of March 2020 is putting national health systems of different countries into significant levels of stress [3][4][5][6] (see [7] and references therein for a fully detailed thread of reports including the effect of non-pharmaceutical interventions in a number of countries, severity analysis, symptom progression, etc, elaborated by the Imperial College COVID-19 Response Team). It is expected that the ICU demand of several hospitals across the UK will surpass their nominal capacity, as is already happening in Spain [8].…”

Section: I-backgroundmentioning

confidence: 99%

A flexible method for optimising sharing of healthcare resources and demand in the context of the COVID-19 pandemic

Lacasa

Challen

Brooks-Pollock

et al. 2020

Preprint

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As the number of cases of COVID-19 continues to grow exponentially, local health services are likely to be overwhelmed with patients requiring intensive care. We develop and implement an algorithm to provide optimal re-routing strategies to either transfer patients requiring Intensive Care Units (ICU) or ventilators, constrained by feasibility of transfer. We validate our approach with realistic data extracted from UK and Spain. For the UK case, we coarse-grain the NHS system at the level of NHS trusts and, subsequently cover the whole set of geopositioned trusts to extract a 4-regular geometric graph which indicates, for a given trust, its four nearest neighbors. The Spanish case is analysed at the autonomous community level, and we extract a contact network where nodes correspond to autonomous communities and links indicate adjacent communities. Estimates of weekly ICU demand could be extrapolated from an age structured epidemiological model by considering contagion-to-ICU likelihood estimates or alternatively from available data. Through random search optimisation we identify the best load sharing strategy, where the cost function to minimise is based on the total number of ICU units above capacity and we implement and test two optimisation strategies. Our framework is flexible allowing for additional criteria, different cost functions, and this methodology is general enough that it can easily be extended to optimise other resources beyond ICU units or ventilators. Assuming a uniform ICU demand across trusts, we show that using our method it is possible to enable access to ICU treatment to up to 1000 cases in the UK in a single step of the algorithm, and with more realistic demand the algorithm is able to balance about 600 beds per step in the Spanish system -leading to potentially saving a large percentage of these lives that would otherwise not have access to ICU if no load sharing was implemented.

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COVID-19: a novel coronavirus and a novel challenge for critical care

Cited by 271 publications

References 23 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

Empfehlungen zur intensivmedizinischen Therapie von Patienten mit COVID-19

A flexible method for optimising sharing of healthcare resources and demand in the context of the COVID-19 pandemic

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