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The straw man algorithm allowed us to enrich a study population with type 1 diabetes.
We randomly selected 210 charts classified by the straw man algorithm for review: 70 patients classified as type 1, 60 classified as type 2, and 80 left unclassified by the straw man algorithm.
The straw man algorithm for classifying patients as type 1 versus type 2 flagged 1,095 patients as type 1 and 29,410 as type 2. The remaining patients were not classified.
Among 80 patients left unclassified by the straw man algorithm, 7 had type 1 diabetes, 65 had type 2 diabetes, 2 had gestational diabetes mellitus, 1 was being prescribed insulin but lacked sufficient data to classify diabetes type, and 5 did not have diabetes.
We started with a "straw man" algorithm designed to coarsely divide the population into pools of patients more likely to have type 1 and patients more likely to have type 2. We began with this preliminary algorithm in order to make chart reviews more efficient: type 1 diabetes is so rare compared with type 2 diabetes that random sampling of unselected patients yields very few type 1 cases.
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— — *I know — straw man.
In walks the straw man".
This is a straw man.
This was no straw man.
But that argument is a straw man.
The straw man is often a woman.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com