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Anesthesiology:
doi: 10.1097/ALN.0000000000000283
Correspondence

“Big Data” Has Not Come to Pediatric Anesthesia

Fisher, Dennis M. M.D.

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To the Editor:

Litman’s editorial “Complications of Laryngeal Masks in Children”1 is subtitled as “Big Data Comes to Pediatric Anesthesia.” Unfortunately, Litman repeatedly misuses the term “big data,” potentially misleading readers of the Journal.
Wikipedia defines big data as “the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. As of 2012, limits on the size of data sets that are feasible to process in a reasonable amount of time were on the order of exabytes of data.”*
Surely, a retrospective study of 11,910 patients does not involve exabytes (billions of gigabytes) of data. Although Mathis et al.2 deserve credit for undertaking a study involving a relatively large dataset, Litman should have considered using the term “Large Simple Safety Study,” a term used by the U.S. Food and Drug Administration to describe simple clinical trials involving at least 10,000 subjects (although the term usually implies a prospective analysis—a better term might be a Large Simple Retrospective Review).
Litman’s use of the term minimizes the challenges to those whose work involves big data, for example, meteorologists. Although words evolve, they must be clearly defined if scientists wish to communicate without ambiguity.
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Competing Interests

The author declares no competing interests.
Dennis M. Fisher, M.D.
, P Less Than, San Francisco, California. fisher@plessthan.com
* Available at: http://en.wikipedia.org/wiki/Big_data. Accessed March 26, 2014. Cited Here...
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References

1. Litman RS. Complications of laryngeal masks in children. ANESTHESIOLOGY. 2013;119:1239–40

2. Mathis MR, Haydar B, Taylor EL, Morris M, Malviya SV, Christensen RE, Ramachandran SK, Kheterpal S. Failure of the Laryngeal Mask Airway Unique™ and Classic™ in the pediatric surgical patient: A study of clinical predictors and outcomes. ANESTHESIOLOGY. 2013;119:1284–95

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