Steroids and COVID-19: We Need a Precision Approach, Not One Size Fits All

Waterer, Grant; Rello, Jordi

doi:10.1007/s40121-020-00338-x

Cited by 27 publications

(22 citation statements)

References 21 publications

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“…11 , 12 However, ambiguity remains about optimal dosing strategies, contraindications for treatment, and the effectiveness of corticosteroids for COVID-19 treatment in different subpopulations. 7 , 13 , 14 , 15 …”

Section: Introductionmentioning

confidence: 99%

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids

Lam

Siefkas

Zelin

et al. 2021

Clinical Therapeutics

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Purpose : Coronavirus Disease 2019 ( COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guidelines have supported the use of corticosteroids and remdesivir in the treatment of COVID-19. However, uncertainty remains about which patients are most likely to benefit from treatment with either drug; such knowledge is crucial for avoiding preventable side effects, minimizing costs, and effectively allocating resources. This study presents a machine learning system capable of identifying patients for whom treatment with corticosteroids or remdesivir is associated with improved survival time. Methods : Gradient boosted decision tree models to predict treatment benefit were trained and tested on data from patients hospitalized at 10 hospitals in the United States between December 18, 2019 and October 18, 2020. 893 patients were treated with remdesivir, and 1,471 were treated with corticosteroids. Models were evaluated for their ability to identify patients that exhibited longer survival times when treated with corticosteroids or remdesivir. Fine and Gray models for the proportional hazard were evaluated comparing treated and untreated patients in the full COVID-19 population, in patients receiving supplemental oxygen, and in patients identified by the algorithm. Inverse probability of treatment weights were used to adjust for confounding. Models for each treatment were trained and tested separately. Findings : .Adult patients (age ≥ 18) were included in this study, with men comprising slightly more than 50% of the sample. After adjusting for confounding, neither corticosteroids nor remdesivir were associated with increased survival time in the full hospitalized COVID-19 population or in the population receiving supplemental oxygen. However, in the populations identified by the algorithms, both corticosteroids and remdesivir were significantly associated with an increase in survival time, with hazard ratios of 0.56 (p = 0.04) and 0.40 (p = 0.04), respectively Implications : Machine learning methods are capable of identifying hospitalized COVID-19 patients for whom treatment with corticosteroids or remdesivir is associated with an increase in survival time. These methods may help improve patient outcomes and allocate resources during the COVID-19 crisis.

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Section: Introductionmentioning

confidence: 99%

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids

Lam

Siefkas

Zelin

et al. 2021

Clinical Therapeutics

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show abstract

“…Use of intravenous steroids is also recommended in the recent American Thoracic and European Respiratory Society guidance [45] for patients who underwent MV, require oxygen supplementation or require extracorporeal membrane oxygenation. It is also supported by recent meta-analyses [46] , although more research is required on the interaction with antivirals, anticoagulation, specific subsets like diabetes or older than 70 years, suggesting the need for a precision prescription approach [47] to be more selective in reducing potential harm and optimise benefits. Finally, interactions between IL-6R blocking therapy and steroids need to be elucidated.…”

Section: Covid-19 Managementmentioning

confidence: 87%

Update in COVID-19 in the intensive care unit from the 2020 HELLENIC Athens International symposium

Rello

Belliato

Dimopoulos

et al. 2020

Anaesthesia Critical Care & Pain Medicine

Self Cite

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Highlights Severe COVID-19 presents as multiple organ dysfunction syndrome (SARS-CoV-2 MODS) Less is more in ventilating critically ill patients with severe COVID-19 pneumonia European Medicines Agency released approval for administration of steroids Main therapeutic targets: anti-inflammatory; anticoagulation; protective ventilation

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“…Just as it has been well-established that a "one-size fits all" approach is insufficient for testing, treatment, and vaccination, social processes like school transmission benefit from locally tailored approaches. [18][19][20] Models that account for differences in underlying populations and social dynamics are a valuable tool for adopting a "precision medicine" approach to population health. 18 Finally, the model structure and dynamics are not limited to COVID-19.…”

Section: Discussionmentioning

confidence: 99%

Modeling infection dynamics and mitigation strategies to support K-6 in-person instruction during the COVID-19 pandemic

Morrison

Nianogo

Manuel

et al. 2021

Preprint

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ObjectiveTo support safer in-person K-6 instruction during the coronavirus disease 2019 (COVID- 19) pandemic by providing public health authorities and school districts with a practical model of transmission dynamics and mitigation strategies.MethodsWe developed an agent-based model of infection dynamics and preventive mitigation strategies such as distancing, health behaviors, surveillance and symptomatic testing, daily symptom and exposure screening, quarantine policies, and vaccination. The model parameters can be updated as the science evolves and are adjustable via an online user interface, enabling users to explore the effects of interventions on outcomes of interest to states and localities, under a variety of plausible epidemiological and policy assumptions.ResultsUnder default assumptions, secondary infection rates and school attendance are substantially affected by surveillance testing protocols, vaccination rates, class sizes, and effectiveness of safety education.ConclusionsOur model helps policymakers consider how mitigation options and the dynamics of school infection risks affect outcomes of interest. The model’s parameters can be immediately updated in response to changes in epidemiological conditions, science of COVID-19 transmission dynamics, testing and vaccination resources, and reliability of mitigation strategies.

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Steroids and COVID-19: We Need a Precision Approach, Not One Size Fits All

Cited by 27 publications

References 21 publications

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids

Update in COVID-19 in the intensive care unit from the 2020 HELLENIC Athens International symposium

Modeling infection dynamics and mitigation strategies to support K-6 in-person instruction during the COVID-19 pandemic

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