Standardized Data Elements for Patients with Acute Pulmonary Embolism: A Consensus Report from the Pulmonary Embolism Research Collaborative
Notice bibliographique
Résumé
ABSTRACT Recent advances in therapy and the promulgation of multidisciplinary pulmonary embolism teams (PERTs) show great promise to improve management and outcomes of acute pulmonary embolism (PE). However, the absence of randomized evidence and lack of consensus leads to tremendous variations in treatment and compromises the wide implementation of new innovations. Moreover, the changing landscape of healthcare, where quality, cost, and accountability are increasingly relevant, dictates that a broad spectrum of outcomes of care must be routinely monitored to fully capture the impact of modern PE treatment. We set out to standardize data collection in PE patients undergoing evaluation and treatment, and thus establish the foundation for an expanding evidence base that will address gaps in evidence and inform future care for acute PE. To do so, over 100 international PE thought leaders convened in Washington, DC in April 2022 to form the Pulmonary Embolism Research Collaborative (PERC™). Participants included physician experts, key members of the United States Food and Drug Administration (FDA), patient representatives, and industry leaders. Recognizing the multi-disciplinary nature of PE care, the Pulmonary Embolism Research Collaborative (PERC™) was created with representative experts from stakeholder medical subspecialties, including cardiology, pulmonology, vascular medicine, critical care, hematology, cardiac surgery, emergency medicine, hospital medicine, and pharmacology. A list of critical evidence gaps was composed with a matching comprehensive set of standardized data elements; these data points will provide a foundation for productive research, knowledge enhancement, and advancement of clinical care within the field of acute PE, and contribute to answering urgent unmet needs in PE management. Evidence produced through PERC™, as it is applied to data collection, promises to provide crucial knowledge that will ultimately produce a robust evidence base that will lead to standardization and harmonization of PE management and improved outcomes. CLINICAL PERSPECTIVE 1) What is new? Recent advances have increased options for treatment of acute pulmonary embolism, yet there remain wide variations in management due to the lack of a reliable evidence base upon which to base therapeutic decisions. The PERT Consortium TM is a strong advocate of evidence based care for PE patients and therefore initiated the Pulmonary Embolism Research Collaborative (PERC TM ) to establish a foundation for advancing high quality research and improving clinical care. A novel comprehensive set of standardized data elements is proposed for collection in patients with acute pulmonary embolism, to provide a foundation for expanding the evidence base and enhancing care. 2) What are the clinical implications? Standardizing collection of data for acute pulmonary embolism will enable analyses that will inform optimal risk stratification, treatment, and follow-up of patients with pulmonary embolism, and provide evidence-based treatment algorithms that will improve outcomes. Registries created using the proposed standardized elements will enable benchmarking and quality assurance for clinicians caring for pulmonary embolism patients. Incorporation of comprehensive standardized data elements into FDA IDE trials will enable the Agency to better assess the safety and effectiveness of investigational devices.
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 | 0,528 | 0,576 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,007 | 0,010 |
| Bibliométrie | 0,020 | 0,019 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,013 | 0,012 |
| Science ouverte | 0,013 | 0,015 |
| Intégrité de la recherche | 0,008 | 0,019 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».