Frozen Plasma Transfusion Practices in Ontario-an Electronic Audit at Five Tertiary Care Hospitals to Inform a Knowledge Translation Strategy to Reduce Inappropriate Plasma Transfusions
Notice bibliographique
Résumé
Abstract Frozen plasma transfusions are blood components that are frequently transfused to patients who are bleeding or require an invasive procedure and have a deficiency of coagulation factors detected on abnormal coagulation testing as inferred by a prolonged prothrombin time (PT), partial thromboplastin time (PTT), or increased international normalized ratio (INR). Despite published guidelines, supporting optimal plasma use, two recent provincial audits have suggested that 50% of the plasma transfused in the Province of Ontario is inappropriate. Inappropriate utilization of plasma has numerous adverse consequences for the recipient, including transfusion associated lung overload, allergic reactions, and delays necessary procedures while awaiting completion of the transfusion. In addition to the direct risks that inappropriate utilization of plasma has on the patient, it also has adverse consequences for the health care system; Given 98,521 units transfused in Canada in 2017, of which 50% are unnecessary, the annual revenue loss is estimated to be CAN$1.7 million. We will include all adult Inpatients receiving plasma during the time period January 1, 2017 and December 31, 2017. The study population will be subdivided into 5 groups of inappropriate plasma use that include: (1) patients with a normal INR≤1.5 and who were not actively bleeding, as indicated by no RBC transfusion; (2) patients with normal INR≤1.5 with moderate bleeding only; (3) elevated INR>1.5, without active bleeding or procedures; (4) no INR drawn before or after plasma infusion; or, (5) transfused a non-therapeutic dose of plasma, defined by less than or equal to 2 units. RBC transfusion requirement and the quantitative drop in hemoglobin will be used as a surrogate marker for bleeding. We plan to analyze the number and proportion of unnecessary plasma transfusions at five tertiary care centres by patient demographics, by triggering INR, and by the presence or absence of bleeding. As part of preliminary work to facilitate future audits and monitor appropriate plasma utilization in Ontario, there has been an Ontario Blood Utilization Data Strategy (ONBUDS) data extraction project where preliminary data has been extracted from blood transfusion databases, laboratory databases, and the discharge abstract database (DAD) for four institutions. We expect to confirm previous findings that 50% of the plasma transfused in Ontario is transfused inappropriately. Based on the preliminary ONBUDS data, it was found that the majority of inappropriate plasma transfusions were in the areas of cardiac surgery, orthopedic surgery, intensive care and gastroenterology. This study will inform a large quality improvement study aimed at reducing unnecessary plasma transfusion. The long-term goal is to develop an alternative electronic auditing strategy that is more comprehensive, faster, and more cost efficient than the historical annual Provincial audit which requires manual chart reviews by physicians, nurses and technologists. Disclosures No relevant conflicts of interest to declare.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».