Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis

Background The public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority

Understanding the potential impact of different drug properties on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and disease burden: a modelling analysis

Background The public health impact of the coronavirus disease 2019 (COVID-19) pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R = 1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalization) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focused on hospitalized-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority

Understanding the Potential Impact of Different Drug Properties On SARS-CoV-2 Transmission and Disease Burden: A Modelling Analysis

Background The public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods Using a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care, we explore the public-health impact of different potential therapeutics, under a range of scenarios varying healthcare capacity, epidemic trajectories; and drug efficacy in the absence of supportive care. Results The impact of drugs like dexamethasone (delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in high-income countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions Advances in the treatment of COVID-19 to date have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics delivered earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priority

Global Survey of Outcomes of Neurocritical Care Patients: Analysis of the PRINCE Study Part 2

BACKGROUND: Neurocritical care is devoted to the care of critically ill patients with acute neurological or neurosurgical emergencies. There is limited information regarding epidemiological data, disease characteristics, variability of clinical care, and in-hospital mortality of neurocritically ill patients worldwide. We addressed these issues in the Point PRevalence In Neurocritical CarE (PRINCE) study, a prospective, cross-sectional, observational study. METHODS: We recruited patients from various intensive care units (ICUs) admitted on a pre-specified date, and the investigators recorded specific clinical care activities they performed on the subjects during their first 7 days of admission or discharge (whichever came first) from their ICUs and at hospital discharge. In this manuscript, we analyzed the final data set of the study that included patient admission characteristics, disease type and severity, ICU resources, ICU and hospital length of stay, and in-hospital mortality. We present descriptive statistics to summarize data from the case report form. We tested differences between geographically grouped data using parametric and nonparametric testing as appropriate. We used a multivariable logistic regression model to evaluate factors associated with in-hospital mortality. RESULTS: We analyzed data from 1545 patients admitted to 147 participating sites from 31 countries of which most were from North America (69%, N = 1063). Globally, there was variability in patient characteristics, admission diagnosis, ICU treatment team and resource allocation, and in-hospital mortality. Seventy-three percent of the participating centers were academic, and the most common admitting diagnosis was subarachnoid hemorrhage (13%). The majority of patients were male (59%), a half of whom had at least two comorbidities, and median Glasgow Coma Scale (GCS) of 13. Factors associated with in-hospital mortality included age (OR 1.03; 95% CI, 1.02 to 1.04); lower GCS (OR 1.20; 95% CI, 1.14 to 1.16 for every point reduction in GCS); pupillary reactivity (OR 1.8; 95% CI, 1.09 to 3.23 for bilateral unreactive pupils); admission source (emergency room versus direct admission [OR 2.2; 95% CI, 1.3 to 3.75]; admission from a general ward versus direct admission [OR 5.85; 95% CI, 2.75 to 12.45; and admission from another ICU versus direct admission [OR 3.34; 95% CI, 1.27 to 8.8]); and the absence of a dedicated neurocritical care unit (NCCU) (OR 1.7; 95% CI, 1.04 to 2.47). CONCLUSION: PRINCE is the first study to evaluate care patterns of neurocritical patients worldwide. The data suggest that there is a wide variability in clinical care resources and patient characteristics. Neurological severity of illness and the absence of a dedicated NCCU are independent predictors of in-patient mortality.status: publishe