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How Doctors Judge Whether a Medical Study Can Be Trusted

1The Clinical Question and Why Study Design Follows From It2Randomization, Allocation, and the Logic of Comparison3Blinding, Follow-Up, and Who Actually Got Analyzed4Reading the Result: Effect Size, Uncertainty, and Significance5Applicability: Does This Result Fit My Patient?6Combining Studies and Forming a Verdict
Applicability: Does This Result Fit My Patient?

Who was in the trial, and who is in front of you

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The example is the whole point of this page. The trial excluded people over seventy-five, people with a prior stroke, and people with poor kidney function. The patient in front of you has all three features. That does not make the trial invalid, but it means the thirty percent relative reduction was measured in a group she does not belong to, so the benefit you expect for her is an extrapolation. The practical move is to ask how far outside the studied population she sits, and to let that distance, not the trial's quality, set how confident you are.
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Eligibility criteria are the inclusion and exclusion rules that defined the study population. They are the first thing to compare against your patient, because they determine whose result the trial actually reports. A patient who would have been excluded sits outside the evidence, and applying the result to them is an extrapolation rather than a direct application.

A trial that excluded the patient in front of you

A trial of a new anticoagulant for atrial fibrillation enrolls adults under 75 with normal kidney function and excludes anyone with a prior stroke or a creatinine clearance below 50 mL/min. Your patient is 81, has had a stroke, and has a creatinine clearance of 38 mL/min. The trial's relative risk reduction of 30% was measured in a population that does not include her. You can still consider the drug, but the expected benefit and the bleeding risk in her case are extrapolations from a lower-risk group, and the trial cannot tell you how large they are.

Exclusions are often reported in a flow diagram rather than the abstract. The number and reasons for exclusions after enrollment also matter, because a trial that screened 5,000 patients to enroll 200 describes a narrower population than the enrollment number alone suggests.

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