The paper from the New England Journal of Medicine that reports azithromycin might cause cardiovascular death is not new to electrophysiologists tasked with deciding antibiotic choices in patients with Long QT syndrome or in those who take other antiarrhythmic drugs. Heck, even the useful Arizona CERT QTDrugs.org website could have told us that.
What was far scarier to me, though, was how the authors of this week’s paper reached their estimates of the magnitude of azithromycin’s cardiovascular risk.
Welcome to the underworld of Big Data Medicine.
Careful review of the Methods section of this paper reveals that “persons enrolled in the Tennessee Medicaid program” were the subjects, and that the data collected were “Computerized Medicaid data, which were linked to death certificates and to a state-wide hospital discharge database” and “Medicaid pharmacy files.” Anyone with azithromycin prescribed from 1992-2006 who had “not had a diagnosis of drug abuse or resided in a nursing home in the preceding year and had not been hospitalized in the prior 30 days.” Also, they had to be “Medicaid enrollees for at least 365 days and have regular use of medical care.”
Hey, no selection bias introduced with those criteria, right? But the authors didn’t stop there.
