Here is the design of a clinical trial:

Official Title: Intérêt du Traitement de la fièvre Par Refroidissement Externe Pour la Survie Des Patients ventilés en Choc Septique

Included conditions:
- Septic Shock

Study Armgroups:
- {'label': 'Fever Control by external cooling', 'type': 'EXPERIMENTAL', 'description': 'External cooling during 48 hours to obtain normothermia', 'interventionNames': ['Other: External Cooling']}
- {'label': 'Fever respected, no cooling', 'type': 'NO_INTERVENTION', 'description': 'Fever respect without any antipyretic therapy'}

Interventions:
- {'type': 'OTHER', 'name': 'External Cooling', 'description': 'External Cooling', 'armGroupLabels': ['Fever Control by external cooling']}

Primary Outcomes:
- {'measure': 'Mortality', 'description': 'All causes mortality', 'timeFrame': 'Day 60 from randomization'}

Please estimate the sample size based on the assumption: 
For a two-sided alpha of 5%, a power of 80%, and a cooling-to-no cooling ratio of 1:1, the sample size calculation was performed using the nQuery V.8 software.
Sample size calculation
        
          Justification of estimations
          The Sepsis-3 definition of septic shock will select patients with a higher mortality risk than those reported in older studies.35 39 The expected mortality has been extracted from the results of the pilot study and from the databases of two RCTs performed in France (ie, âHYPER2Sâ and âSEPSISPAMâ) among patients meeting the Sepsis-3 criteria (n=698 patients).15 40 41 Half of the patients had ARDS and the observed mortality was 54%; mortality was similar among patient with and without ARDS.
          In a meta-analysis of personal data, the RR of death using fever control among patients requiring mechanical ventilation and vasopressors was 22% (OR 0.72, 95%âCI 0.50 to 1.04).23 The RR difference estimation in large RCTs comparing two treatments for sepsis was 22% in the âHYEPR2Sâ, âSEPSISPAMâ, âCASSâ and âAPROACCHSSâ studies. The RR difference estimations in large RCTs comparing treatments for ARDS were 19% in the âPETALâ study and 33% in âEPVent-2â study.13 40â44
        
        
          Hypotheses
          An expected mortality of 52% with an expected RR of death of 19% is assumed. The hypothesis is to reduce mortality at day 60 from 52% to 42%. For a two-sided alpha of 5%, a power of 80% and a cooling-to-no cooling ratio of 1:1, 780 evaluable patients are needed. Due to lost to follow-up or other reasons, the final sample size of 820 patients is planned. The calculation was performed using the nQuery V.8 software (PTT0).
        
        
          Randomisation
          ICU medical investigators complete the process of informed consent and randomise the patients during their ICU stay. The treatment arm allocation will be provided by an interactive web response system (IWRS). After randomisation, cooling will be initiated immediately in patients allocated to the experimental group (figure 1). Allocation will be performed by stratification based on ARDS and by covariate-adaptive procedures. The ARDS criteria and the following patient characteristicsâknown to be strong predictors of mortalityâwill be recorded and added to the IWRS at randomisation to power the algorithm and ensure to the groups are balanced:
          
            
              Immunosuppression (ie, cancer chemotherapy, HIV, corticosteroids >1âmg/kg and/or >1âmonth, solid organ transplant, bone marrow transplant, immunosuppressant drugs for autoimmune disease).
            
            
              Arterial oxygen partial pressure to fractional inspired oxygen PaO2/FiO2 ratio (â¤4âhours before randomisation).
            
            
              Lactate level (â¤4âhours before randomisation).
            
            
              Age.
            
            
              Vasopressors (epinephrine+norepinephrine).
            
            
              Clinical centre of randomisation.
            
          
          
            Figure 1
            
              SEPSISCOOL-II trial design. ARDS, acute respiratory distress syndrome.
            
            
          
          The aforementioned characteristics are routinely monitored: their real-time availability guarantees the feasibility and the robustness of the real-time successful randomisation. These variables will be monitored and recorded in the study database. Hence, the distribution of covariates will be continually updated as the trial progresses.
          Dynamic hierarchical randomisation will be used to tackle the challenges of balancing a large number of stratification variables.45 The minimal sufficient balance randomisation method developed by Zhao et al46 will be implemented. As recommended by regulators, a random component will be incorporated to reduce the predictability of the allocation.47 48 The imbalance control limit will be set to pâ¥0.3 for all covariates, and the covariate-adaptive allocation procedure will start after 20 patients have been randomised in each ARDS stratum.46 For each covariate (either continuous or categorical), a vote is conducted to decide whether this covariate should be selected for the randomisation and how to reach balance. The algorithm then allocate the definitive arm, with a predefined probability, according to the results of the votes for the selected covariates. This process is performed for each new participant.
        
        
          Development and test of the algorithm
          The proposed algorithm for randomisation has been tested internally and widely on simulated data (>10 000 datasets simulated). Nineteen scenarios were computed and included worst-case and best-case schemes. Once we will have fully implemented the randomisation in this study, a separate research paper will provide a comprehensive overview of all relevant developments (ie, simulations and real-world data) used for assessing and validating the performances of the proposed algorithm.