The task force emphasizes the need for precision and clarity in specifying the key policy questions to be addressed and that studies should be designed with a goal of drawing causal inferences whenever possible. If a study is being performed to support a policy decision, then it should be designed as hypothesis testing-this requires drafting a protocol as if subjects were to be randomized and that investigators clearly state the purpose or main hypotheses, define the treatment groups and outcomes, identify all measured and unmeasured confounders, and specify the primary analyses and required sample size. Separate from analytic and statistical approaches, study design choices may strengthen the ability to address potential biases and confounding in prospective observational studies. The use of inception cohorts, new user designs, multiple comparator groups, matching designs, and assessment of outcomes thought not to be impacted by the therapies being compared are several strategies that should be given strong consideration recognizing that there may be feasibility constraints. The reasoning behind all study design and analytic choices should be transparent and explained in study protocol. Execution of prospective observational studies is as important as their design and analysis in ensuring that results are valuable and relevant, especially capturing the target population of interest, having reasonably complete and nondifferential follow-up. Similar to the concept of the importance of declaring a prespecified hypothesis, we believe that the credibility of many prospective observational studies would be enhanced by their registration on appropriate publicly accessible sites (e.g., clinicaltrials.gov and encepp.eu) in advance of their execution.

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These findings indicate that in the 3-year period prior to the publication of the AAN Practice Parameter, many but not all patients received the care that is recommended in that parameter; there were deficiencies, particularly in the key areas of gastrostomy and noninvasive positive pressure ventilation.

The GRACE Freedom-from-Event score can predict the in-hospital course of NSTE-ACS, and identifies up to 30% of the admitted population at low risk of death or any adverse in-hospital event.

This observational database has been a useful tool in monitoring compliance with the standard of care for patients with ALS and may have resulted in greater adherence to guidelines.