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Enregistrement W4402719596 · doi:10.1093/bjs/znae243

Service specification in aortic centres—UK Aortic Society survey

2024· article· en· W4402719596 sur OpenAlexaff
Giovanni Mariscalco, Riccardo Abbasciano, Karen Booth, Sunil Bhudia, Stefano Forlani, Michael Sabetai, Amit Modi, Graham Cooper, Manoj Kuduvalli

Notice bibliographique

RevueBritish journal of surgery · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueAortic Disease and Treatment Approaches
Établissements canadiensSt. Thomas Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineService (business)Internal medicineMarketing

Résumé

récupéré en direct d'OpenAlex

Aortic diseases are a growing concern1. In the UK, deaths registered as aortic aneurysm and dissection account for 3.2 and 7.5 per 100 000 inhabitants respectively, with half of diagnosed patients dying before reaching a hospital. Currently, in the UK, aortic surgeries are performed in cardiothoracic surgical units that treat patients within their designated region without interacting with other centres. The recent National Health System (NHS) launch of the ‘Acute Aortic Dissection toolkit’ provided an assessment framework and recommendations, describing key principles and actions to improve the care for emergency aortic syndromes2. This study aimed to understand the current state of aortic disease treatment in the UK and its compliance with best practices. A survey commissioned by the executive team of the UK-Aortic Society (https://uk-as.org) was sent to all aortic surgeons in the UK, obtaining a response from 65% of the aortic centres. The survey assessed service provision, surgeon qualifications, and adherence to national guidelines and the NHS ‘Acute Aortic Dissection toolkit’ (Fig. 1). Visual abstract of relevant outcomes derived from the survey Most centres perform a mix of elective and emergency aortic surgeries, with an average ratio between elective cases and acute aortic syndromes of 34% (±21%). Hybrid endovascular techniques are widely available (89% of the centres), but some complex procedures (Ross procedure, open treatment of thoraco-abdominal diseases) are less common (58% and 47% of the centres respectively). The ratio of urgent versus elective cases in centres with a larger volume (more than 80 aortic cases per year) was significantly lower (23%) when compared to smaller centres. Dedicated aortic surgeons are present in most centres (20 of 23 respondents), but co-located hybrid theatres (10 of 23) and on-call rotas are less frequent (13 of 23). Aortic multidisciplinary teams involving various specialists are present in most centres (18 of 23). Standardized protocols for imaging, transfer and follow-up care are not universally available (79%, 58% and 63% respectively). Only a third of centres participate in regional rotas for managing acute aortic syndromes. Educational programmes for aortic diseases are limited (37% of centres). There is no consensus on the definition of an aortic surgeon (48% of the respondents selected a figure between 10 and 20 and 52% a figure above 30 aortic operations performed per year). According to the responses provided, a ‘dedicated/specialized’ aortic surgeon should be able to perform aortic root replacement for 100% of the respondents, valve-sparing aortic root replacement for 83% and hybrid endovascular approaches for 61%. All participants agree on the volume–outcome relationship in aortic surgery and support the creation of a national aortic surgery database. The survey revealed significant variations in how aortic services are provided across the UK. Whereas some centres offer advanced treatments, others lack crucial resources like dedicated rotas and standardized protocols. The findings highlight the need for improvement in several areas. Concentrating complex aortic surgeries in high-volume centres with dedicated expertise could improve outcomes, as well known from previous publications3. Also, establishing regional rotas and implementing standardized protocols could ensure faster diagnosis, safer transfers and better long-term care for patients, whereas investing in regional educational programs for aortic diseases could improve awareness and early diagnosis. A dedicated database for aortic surgeries would allow for outcome tracking and continuous improvement. The authors have no funding to declare. The authors declare no conflict of interest. Supplementary material is available at BJS online. The data collected for the manuscript will be made available upon pertinent request to the corresponding author. Giovanni Mariscalco (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Visualization, Writing—original draft, Writing—review & editing), Riccardo Giuseppe Abbasciano (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing—original draft, Writing—review & editing), Karen Booth (Conceptualization, Writing—original draft, Writing—review & editing), Sunil Bhudia (Conceptualization, Writing—original draft, Writing—review & editing), Stefano Forlani (Conceptualization, Writing—original draft, Writing—review & editing), Michael Sabetai (Conceptualization, Writing—original draft, Writing—review & editing), Amit Modi (Conceptualization, Writing—original draft, Writing—review & editing), Graham Cooper (Conceptualization, Writing—original draft, Writing—review & editing), and Manoj Kuduvalli (Conceptualization, Writing—original draft, Writing—review & editing)

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,112
Score d'incertitude au seuil0,223

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,015
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0030,008
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,003
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0140,002

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.

Tête enseignante Opus0,071
Tête enseignante GPT0,286
Écart entre enseignants0,215 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentnon

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