Sentence examples for being coded as obese from inspiring English sources
As a second step, we assessed the relative impact of being coded as obese on outcomes, namely hospitalization, PCI or CABG, and mortality.
We further assessed whether BMI influenced the likelihood that a subject was coded as obese in the administrative database.
In the DAD, 414 patients were coded as being obese.
Maternal early pregnancy was coded as underweight (BMI <18.5 kg/m), normal (≥18.5 and <25 kg/m), overweight (≥25 and <30 kg/m), obese class I (≥30 and <35 kg/m) and obese classes 2 and 3 (≥35 kg/m).
Subjects were considered to be "correctly" coded as obese if they had a diagnosis code of obesity in the administrative database and a BMI ≥ 30 kg/m in the measured data contained in APPROACH.
These incorrectly coded subjects had a mean BMI of 26.9 kg/m (SD 3.6), were older (mean age 63.7 ± 10.8 years vs 62.7 ± 11.0, p-value = 0.3), less likely to be female (33.3% vs 55.3%, p < 0.0001), and more likely to be diabetic (35.5 vs 44.3%, p = 0.0827) than those who were correctly coded as obese in both administrative and clinical data (n = 273).
The same was demonstrated for those "correctly" coded as obese.
Of those 414 subjects coded as obese in the DAD, nearly a third (141) were not actually obese when compared to measured data.
Of those coded as obese within the administrative database, the large majority (72.9%) were Class I obese; of those not coded as obese, 84.3% were Class I obese, and 2.9% were Class III obese (Table 3).
