THU293 Enhancement Of Best Practices In Diabetic Ketoacidosis Management Using Standardized Order-sets vs Individual Practitioner Orders
Bibliographic record
Abstract
Abstract Disclosure: C. Yim: None. Q. Li: None. T.G. Arnason: None. Diabetic ketoacidosis (DKA) is a hyperglycemic emergency occurring in diabetics due to insulin deficiency. This results in urinary losses of water and electrolytes (sodium, potassium, chloride) and ultimately extracellular fluid volume depletion. Hallmark features of DKA include ketoacidosis, arterial pH < 7.3, bicarbonate <15 mmol/L and an anion gap of >12 mmol/L. The 2018 Diabetes Canada (DC) guidelines outline the key steps of DKA management including fluid resuscitation, resolution of ketoacidosis, correction of electrolytes and management of precipitating factors. Its detailed algorithm identifies three pillars to DKA treatment: IV fluids, serum potassium and acidosis. A 2016 DKA outcome audit at the Royal University Hospital (RUH) in Saskatoon identified that practitioners diverged considerably from (2013) Canadian Diabetes Association guidelines. Subsequently, two standardized preprinted DKA order sets were developed incorporating the 2018 DC recommendations for i) INITIAL and ii) MAINTENANCE DKA management. Their rollout overlapped with annual academic half day sessions on DKA management for postgraduate year 1 residents in internal medicine. These order-sets were initially implemented at RUH in November 2018 and subsequently adopted by some practitioners at St. Paul’s Hospital (SPH). To ensure the order-sets were promoting improved outcomes and adhering to best practices, a retrospective chart review was conducted of all adult DKA admissions at RUH and SPH from Nov. 13, 2018 to December 31, 2020. In total, 279 hospital admissions were reviewed: 99 used practitioners’ own orders, 115 used both initial and maintenance order-sets, 26 used only the initial order-set and 38 used only the maintenance order-set. Use of the INITIAL order set significantly improved compliance (p < 0.0001) with DC 2018 guidelines for recommended insulin dose and timing, fluid resuscitation as well as potassium, sodium and dextrose replacement. Use of the MAINTENANCE order set consistently enhanced outcomes for intravenous fluid selection, subcutaneous insulin overlap, and ensuring a closed anion gap at transition (p < 0.0001). Additionally, the chart review revealed that there were hospital differences for uptake of order sets and compliance to DC 2018 guidelines. There was a significant uptake of order sets at RUH versus SPH (p < 0.0001). RUH consistently met outcomes for appropriate insulin dosing, potassium and dextrose replacement (p < 0.0001). RUH also consistently overlapped IV and SC insulin and ensured a closed insulin gap. The anion gap remained consistently closed post-transition at RUH versus SPH (p = 0.035). These results suggest that utilization of a DKA order set does significantly promote adherence to key best practices outlined in the DC 2018 guidelines. Presentation: Thursday, June 15, 2023
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.210 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".