PT - JOURNAL ARTICLE AU - Hafeez Shaka AU - Farah Wani AU - Zain El-Amir AU - Dushyant Singh Dahiya AU - Jagmeet Singh AU - Ehizogie Edigin AU - Precious Eseaton AU - Asim Kichloo TI - Comparing patient characteristics and outcomes in type 1 versus type 2 diabetes with diabetic ketoacidosis: a review and a propensity-matched nationwide analysis AID - 10.1136/jim-2021-001901 DP - 2021 Aug 01 TA - Journal of Investigative Medicine PG - 1196--1200 VI - 69 IP - 6 4099 - http://hw-f5-jim.highwire.org/content/69/6/1196.short 4100 - http://hw-f5-jim.highwire.org/content/69/6/1196.full SO - J Investig Med2021 Aug 01; 69 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.