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Enregistrement W4403018285 · doi:10.52054/fvvo.16.3.042

Achieving successful outcomes with endometrial ablation needs better case selection

2024· article· en· W4403018285 sur OpenAlexaboutno aff
T. Justin Clark

Notice bibliographique

RevueFacts Views and Vision in ObGyn · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueUterine Myomas and Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEndometrial ablationSelection (genetic algorithm)AblationCase selectionComputer scienceMedicineInternal medicineSurgeryArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

When uterine sparing techniques that destroyed the endometrium were introduced in the 1990s, the demise of hysterectomy for heavy menstrual bleeding seemed probable with the introduction of this effective, less invasive alternative method of surgery (O'Connor et al., 1997).With the introduction of rapid, semiautomated ways of cooking the endometrium, surgical proficiency in hysteroscopy became surplus to requirements as did the absolute necessity for an anaesthetist (Clark et al., 2011).However, endometrial ablation, as with pretty much all new health care innovations, is now seeing the initial euphoria that greeted its arrival on the health care scene, tempered by a healthy scepticism as longer-term prognostic data are inexorably accumulated.Hysterectomy has not disappeared and in fact remains in rude health, especially with the popularity of laparoscopic approaches and day-case models of care (Antoun et al., 2021).Moreover, it has long been known that a substantial proportion of women will have their uterus removed following the index ablative procedure.Recent reviews of the evidence base suggest the rates are around 12% within 5 years of this 'uterine sparing' ablative procedure (Oderkerk et al., 2023).In this issue of Facts, Views and Vision, McGee and colleagues (McGee et al., 2024) present the largest and longest longitudinal prognostic cohort of patients having undergone some form of endometrial destruction.The authors should he congratulated for their endeavour, interrogating a variety of large electronic datasets in Ontario, Canada and tracking whether these patients required subsequent uterine surgery and in particular hysterectomy.Their findings are generally in keeping with those of previous cohorts (Bansi-Matharu et al., 2013;Oderkerk et al., 2023), with 16% of women having a hysterectomy at five years, 23% at 10 years and 29% at 15 years.Whilst the rate of hysterectomy slows over time, this evaluation does not show any 'plateau' effect, where "treatment failures" no longer exist.However, is it rational to use hysterectomy as a surrogate for failure of endometrial ablative treatment?The indication for subsequent surgery could not be extracted from the routinely collected healthcare databases by the authors of the current paper.Despite this deficiency, it seems reasonable to assume that hysterectomy within two, and possibly five years, is most likely due to ongoing uterine symptoms, such as bleeding or pain.However, is it fair to assume this when judged more than five, and especially more than 10, years later because the indication for hysterectomy may very well not relate to menstrual bleeding and / or pain?If most re-interventions are indicated for ongoing or new bleeding symptoms and / or pain then the concomitant use of levonorgesterol-releasing intrauterine systems (LNG-IUS) (Oderkerk et al., 2021), as highlighted by the authors in their write up, may help reduce subsequent hysterectomy for these indications.The MIRA2 trial, randomising women to endometrial ablation with or without LNG-IUS, has recently completed recruitment and we await these results with interest to see if this synergy can improve the outcomes following endometrial ablation (Oderkerk et al., 2022).Interrogation of large, routinely collected health datasets delivers precision around outcomes but such evaluations lack granularity.This is because these 'big data' resources do not generally collect detailed additional demographic and clinical information that may aid our understanding.For example, clinical data such as pain, pre-existing gynaecological diagnoses like endometriosis, and ultrasonic data of structural uterine pathologies such as adenomyosis and fibroids, would allow an analysis of the effect on prognosis of these variables.Furthermore, all forms of endometrial destruction whether they were first Achieving successful outcomes with endometrial ablation needs better case selection

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,239
Score d'incertitude au seuil0,349

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,025
Tête enseignante GPT0,346
Écart entre enseignants0,321 · 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 tête enseignante, 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 présentoui

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