Optimizing Subsequent CARdiovascular Medication Reintroduction in the Intensive Care Unit
Bibliographic record
Abstract
Importance: Hospital admission for a critical illness episode creates communication breakpoints and can lead to medication discrepancies during hospital stays. Due to the patient's underlying condition and the care setting, chronic medications such as cardiovascular medication are often held, discontinued, or changed to alternative administration routes. Unfortunately, data on the optimal timing of cardiovascular drug reinitiation among intensive care unit (ICU) survivors are lacking. Objective: The primary objective of this study was to describe the prevalence of chronic cardiovascular medication taken before hospital admission and discontinued at ICU discharge and hospital discharge for critically ill patients. A secondary objective was to assess factors associated with medication discontinuation. Design setting and participants: We conducted a multicentered retrospective cohort study at 2 tertiary academic hospitals in Canada. All adult patients taking cardiovascular medication before ICU admission and surviving to hospital discharge between April 1, 2016, and April 1, 2017, were eligible. Main outcomes and measures: The main outcome of the study was the discontinuation of cardiovascular medication prescribed before ICU admission. The outcome was assessed through participants' chart review. Results: We included 352 patients with a median age of 71.0 years. A total of 155 patients (44.03%) had at least 1 cardiovascular medication discontinued during their stay. Our adjusted model uncovered 3 factors associated with cardiovascular medication discontinuation: male sex (odds ratio [OR] = 0.564, 95% confidence interval [CI] = 0.346-0.919), number of cardiovascular medications taken preadmission (OR = 1.669, 95% CI = 1.003-2.777 for 2 medications and OR = 3.170, 95% CI = 1.325-7.583), and the use of vasopressors (OR = 1.770, 95% CI = 1.045-2.997). Conclusion: Our study uncovered that cardiovascular medication discontinuation for ICU patients is frequent, especially for renin-angiotensin system (RAS) blockers. Data from our study could be used to reinforce site-specific protocols of medication reconciliation and optimization, as well as inform future protocols aimed at RAS blocker reinitiation follow-up.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".