288: IMPACT OF AN IV BICARBONATE SHORTAGE IN A SAMPLE OF ADULT ICUS: INTERRUPTED TIME-SERIES ANALYSIS
Bibliographic record
Abstract
Introduction: Limited research exists to guide the use of sodium bicarbonate among adults admitted to ICUs. From June to October 2017, there was a global shortage of I.V. sodium bicarbonate. Institutions like ours enacted conservation measures during this time period. We assessed the effect of the 2017 shortage of I.V. sodium bicarbonate on the use of sodium bicarbonate, and the incidence of severe acidemia (pH ≥7.20), hyperkalemia (serum K ≥6 mmol/L), renal replacement therapy use, and ICU mortality. Methods: This was an interrupted time series analysis among adults admitted to ICUs in Alberta, Canada between June 1, 2015 and December 31, 2019. The primary data source was eCritical, a population-based electronic health record and data registry for all Alberta ICUs. Individual patient data were aggregated and examined at the ICU-level per month. We included admissions with blood gas pH < 7.3 at any time during their ICU stay. The exposure was a bolus or infusion I.V. bicarbonate prescription. The primary outcome was the proportion of the sample treated with I.V. bicarbonate. Results: 19,293 admissions met inclusion criteria among 19 ICUs in 15 sites. The median age was 63 years (IQR 52 – 72 years), 36% were female, and median APACHE II was 23 (IQR 18 – 30). Among all admissions, 31% received bicarbonate in the pre-shortage period, 22% during the shortage and 29% post-shortage. Among patients with severe acidemia, 51% received bicarbonate pre-shortage, which fell to 41% during the shortage and was maintained at 41% post-shortage. Among patients with hyperkalemia, 45% received bicarbonate pre-shortage, which fell to 34% during the shortage, and rose to 45% post-shortage. The proportion of patients with severe acidemia was 42% pre-shortage, 42% during shortage, and 40% post-shortage. The proportion of patients with hyperkalemia was 15% pre-shortage, 16% during shortage, and 17% post-shortage. The proportion of patients requiring renal replacement therapy was 16% pre-shortage, 17% during shortage, and 16% post-shortage. There was no difference in ICU mortality. Conclusions: The I.V. sodium bicarbonate shortage was associated with its reduced administration, including among patients with severe acidemia and hyperkalemia, two conditions where sodium bicarbonate administration is a common practice.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".