RT Journal Article SR Electronic T1 Comparing patient characteristics and outcomes in type 1 versus type 2 diabetes with diabetic ketoacidosis: a review and a propensity-matched nationwide analysis JF Journal of Investigative Medicine JO J Investig Med FD BMJ Publishing Group Ltd SP 1196 OP 1200 DO 10.1136/jim-2021-001901 VO 69 IS 6 A1 Hafeez Shaka A1 Farah Wani A1 Zain El-Amir A1 Dushyant Singh Dahiya A1 Jagmeet Singh A1 Ehizogie Edigin A1 Precious Eseaton A1 Asim Kichloo YR 2021 UL http://hw-f5-jim.highwire.org/content/69/6/1196.abstract AB Diabetic ketoacidosis (DKA) is a known complication of patients with type 1 diabetes mellitus (T1DM), but less common in type 2 diabetes mellitus (T2DM). The aim of this study was to compare the outcomes of patients admitted to the hospital with DKA in T1DM versus T2DM. This was a population-based, retrospective, cohort study using data from the Nationwide Inpatient Sample. The group of patients hospitalized for DKA was divided based on a secondary diagnosis of either T1DM or T2DM. The primary outcome was inpatient mortality, and the secondary outcomes were rate of complications, length of hospital stay (LOS) and total hospital charge (THC). The inpatient mortality for DKA was 0.27% (650 patients). In T2DM, the adjusted OR (aOR) for mortality was 2.13 (95% CI 1.38 to 3.28, p=0.001) with adjusted increase in mean THC of $6035 (95% CI 4420 to 7652, p<0.001) and mean LOS of 0.5 day (95% CI 0.3 to 0.6, p<0.001) compared with T1DM. Patients with T2DM had significantly higher odds of having septic shock (aOR 2.02, 95% CI 1.160 to 3.524, p=0.013) compared with T1DM. T2DM was associated with higher inpatient mortality, septic shock and increase in healthcare utilization costs compared with T1DM.Data are available in a public, open-access repository. We used and/or analyzed the NIS database 2016 and 2017, available online at http://www.hcup-us.ahrq.gov. The NIS is a large publicly available all-payer inpatient care database in the USA, containing data on more than 7 million hospital stays yearly. Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, uncommon treatments, and special populations.