243. Prioritization of Antibiotic Administration for STAT Orders in the Septic Patient: A Retrospective Analysis
Bibliographic record
Abstract
Appropriate antibiotic (AB) therapy is crucial in sepsis and septic shock. Two central factors govern patient survival: adequate empiric coverage and rapid initiation of therapy. The administration of broad-spectrum antibiotics in sepsis and septic shock play an important role diminishing patient morbidity and mortality.1 The sequence of antibiotic administration has been suggested to affect patient outcomes.2 This is a retrospective study to assess the impact of a pictogram (Figure 1) in the emergency department medication rooms on nurses’ antibiotic administration order in the septic patient. The study population included patients prescribed at least two concomitant AB between January 2017 and January 2018. Each patient’s AB regimen, indication and administration sequence were reviewed using a standardized form. Sequence of administration was deemed appropriate if the sequence followed the pictogram: broad to narrower spectrum AB, and was deemed inappropriate if the sequence differed from the pictogram. Ethics approval was obtained before starting the chart review. A total of 120 patients were identified pre-/postintervention. 20% (10/51) had received AB in an incorrect sequence prior to the pictogram implementation compared with 11% (8/70) postintervention. AB prescribed were piperacillin/tazobactam (24%), azithromycin (24%) and vancomycin (18%), ceftriaxone (15%) for sepsis arising from pneumonia, urinary tract, and intra-abdominal infections. The availability of a pictogram to guide the sequence of antibiotic administration in the septic patient can assure its correct administration sequence and potentially affect patient outcomes. An improvement (45%,P = 0.2) was seen post implementation suggesting the pictogram to be a helpful visual aid for nurses. Although not statistically significant, the difference implies a tendency that may be explored in a larger sample size to search for a potential effect. References 1. Rhodes A, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock 2016. Crit Care Med 2017(45)486–552. 2. Roberts R, et al. Impact of Antibiotic Initiation Sequence on Outcomes in Patients with Septic Shock. Poster 652. Crit Care Med 2016(44) Suppl. All authors: No reported disclosures.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".