Planning, Implementation, and Evaluation of a Glycoprotein IIb/IIIa Inhibitor Protocol for the Treatment of Acute Coronary Syndromes
Bibliographic record
Abstract
ABSTRACT The glycoprotein IIb/IIIa inhibitors (GPIs) represent a relatively new therapy for acute coronary syndromes. In this article the authors share their experience with planning, implementing, and evaluating a protocol for GPI use in a community hospital. A working group conducted a literature review and recommended tirofiban as the formulary GPI; the working group also developed guidelines for use of the drug, including patient selection criteria. Medical records for 68 patients with unstable angina, admitted to the hospital over a 3-month period, were used to characterize the hospital’s patient population. Patient selection criteria included refractory ischemia or presentation with high-risk features such as chest pain at rest of less than 24 h duration, electrocardiographic changes, and troponin I level above 4.9 μg/L. Based on the hospital’s patient population, the annual estimated cost of treatment was almost $50,000. Drug use was evaluated for the first 20 patients treated with the drug. Eighteen (80%) of the patients receiving tirofiban met the predefined patient selection criteria. An outcomes assessment revealed that readmission for any reason and for acute myocardial infarction (within 7 and 30 days of discharge after admission for unstable angina) declined over time, although introduction of tirofiban was not the only factor in this change. The approach described here could be applied by other institutions considering the implementation of high-cost drug therapies. RESUME Les inhibiteurs des glycoproteines IIb-IIIa (IGP) representent un traitement relativement nouveau des syndromes coronariens aigus. Dans cet article, les auteurs partagent leur experience de la planification, de la mise en oeuvre et de l’evaluation d’un protocole d’utilisation des IGP au sein d’un hopital communautaire. Un groupe de travail a passe en revue la litterature et a recommande d’inscrire le tirofiban au formulaire therapeutique; ce groupe a egalement emis des lignes directrices sur l’utilisation de cet agent, comprenant des criteres de selection des patients. Les dossiers medicaux de 68 patients souffrant d’angine de poitrine instable et hospitalises au cours d’une periode de trois mois ont servi a caracteriser la population de patients de l’hopital. Les criteres de selection des patients comprenaient l’ischemie refractaire ou des facteurs de risque eleve comme des douleurs thoraciques au repos d’une duree inferieure a 24 heures, des modifications du trace ECG ainsi qu’un taux de troponine I superieur a 4,9 μg/L. En se fondant sur la population de patients de l’hopital, on a estime les couts annuels du traitement a pres de 50 000 $. Une evaluation de l’utilisation du medicament a ete effectuee pour les 20 premiers patients traites ; 18 (80%) des patients qui ont recu le tirofiban ont satisfait aux criteres de selection predefinis. Une evaluation des resultats a revele que les rehospitalisations, peu importe la cause et pour un infarctus aigu du myocarde (survenant dans les 7 et 30 jours suivant la sortie du patient hospitalise pour une angine instable), ont diminue avec le temps, bien que l’introduction du tirofiban n’etait pas le seul facteur expliquant ce changement. La presente demarche pourrait etre mise en oeuvre par d’autres etablissements qui envisagent le recours a des traitements medicamenteux couteux.
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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 | 0.161 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".