Here is the design of a clinical trial:

Official Title: Efficacy of Dexamethasone Treatment for Patients With ARDS Caused by COVID-19

Included conditions:
- Acute Respiratory Distress Syndrome Caused by COVID-19

Study Armgroups:
- {'label': 'Control group', 'type': 'NO_INTERVENTION', 'description': 'Patients will be treated with standard intensive care'}
- {'label': 'Dexamethasone', 'type': 'ACTIVE_COMPARATOR', 'description': 'Standard intensive care plus dexamethasone', 'interventionNames': ['Drug: Dexamethasone']}

Interventions:
- {'type': 'DRUG', 'name': 'Dexamethasone', 'description': 'Dexamethasone (20 mg/iv/daily/from Day 1 of randomization during 5 days, followed by 10 mg/iv/daily from Day 6 to 10 of randomization', 'armGroupLabels': ['Dexamethasone'], 'otherNames': ['dexamethasone Indukern']}

Primary Outcomes:
- {'measure': '60-day mortality', 'description': 'All-cause mortality at 60 days after enrollment', 'timeFrame': '60 days'}

Please estimate the sample size based on the assumption: 
Power of 80%, two-sided significance level of alpha = 0.05, up to 5% potential losses to follow-up, no formal interim analysis, conditional power analysis if conditional power is ≥ 70% but < 80%, no adjustment to alpha required.
Sample size calculations
        The trial was designed to be initiated in rapid response to the COVID-19 public health emergency. We estimated the sample size on the assumption that treatment with dexamethasone could reduce all-cause 60-day mortality by 20%. Our baseline reference was 50â55% based on recent observational studies from China [4]. Depending on the estimated 60-day mortality, we studied various group-size scenarios with cohorts of 93 to 100 patients in each arm to detect a 20% difference with a power of 80%, at a two-sided significance level of alphaâ=â0.05. The R function power.prop.test was used to estimate the sample size requirement which is based on a z test. A population size of 192 patients (96 in each arm) will provide 80% power to detect a 20% absolute reduction, from 55% on the control group to 35% in the experimental group. To account for up to 5% potential losses to follow-up, we will randomize 200 patients. We will only analyze patients that are enrolled and randomized to receive treatment. There will not be a formal interim analysis. However, after recruitment of 70% of the patients, an independent statistician will perform a conditional power analysis. If the conditional power at that time is â¥â70% but <â80%, the external Data and Safety Monitoring Board (DSMB) can recommend an increase in sample size to achieve 80% power. The conditional power analysis will be performed at the Applied Health Research Center, Li Ka Shing Knowledge Institute of St. Michaelâs Hospital, Toronto, Canada. Since the conditional power analysis will not be used to stop the trial early due to a treatment difference, no adjustment to alpha is required. The DSMB could decide to stop the trial at any point for safety reasons. Also, in a context of a pandemic, it is plausible to discontinue the trial if no new patients are enrolled during a prolonged period of time. The decisions of the DSMB will be communicated to the principal investigators in a letter (sent by email). If the DSMB reaches a decision that the trial must be terminated early for safety reasons, they will email and call either one of the PIs within 24âh of making this decision.