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Enregistrement W3214092784 · doi:10.1093/hropen/hoab041

Meta-analysis and systematic review to determine the optimal imaging modality for the detection of uterosacral ligaments/torus uterinus, rectovaginal septum and vaginal deep endometriosis

2021· article· en· W3214092784 sur OpenAlexaff
B. Gerges, Wentao Li, Mathew Leonardi, Ben W. Mol, G. Condous

Notice bibliographique

RevueHuman Reproduction Open · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueEndometriosis Research and Treatment
Établissements canadiensMcMaster University
Organismes subventionnairesNational Health and Medical Research Council
Mots-clésMedicineUterosacral ligamentEndometriosisVaginaMeta-analysisMEDLINEProspective cohort studyMagnetic resonance imagingLaparoscopyModality (human–computer interaction)GynecologyObstetricsRadiologySurgeryInternal medicine

Résumé

récupéré en direct d'OpenAlex

STUDY QUESTION: Is there an ideal imaging modality for the detection of uterosacral ligaments/torus uterinus (USL), rectovaginal septum (RVS) and vaginal deep endometriosis (DE) in women with a clinical history of endometriosis? SUMMARY ANSWER: The sensitivity for the detection of USL, RVS and vaginal DE using MRI seems to be better than transvaginal ultrasonography (TVS), whilst the specificity of both were excellent. WHAT IS KNOWN ALREADY: The surgical management of women with DE can be complex and requires advanced laparoscopic skills with maximal cytoreduction being vital at the first procedure to provide the greatest symptomatic benefit. Owing to a correlation of TVS findings with surgical findings, preoperative imaging has been used to adequately consent women and plan the appropriate surgery. However, until publication of the consensus statement by the International Deep Endometriosis Analysis Group in 2016, there were significant variations within the terms and definitions used to describe DE in the pelvis. STUDY DESIGN SIZE DURATION: A systematic review and meta-analysis was conducted using Embase, Google Scholar, Medline, PubMed and Scopus to identify studies published from inception to May 2020, of which only those from 2010 were included owing to the increased proficiency of the sonographers and advancements in technology. PARTICIPANTS/MATERIALS SETTING METHODS: All prospective studies that preoperatively assessed any imaging modality for the detection of DE in the USL, RVS and vagina and correlated with the reference standard of surgical data were considered eligible. Study eligibility was restricted to those including a minimum of 10 unaffected and 10 affected participants. MAIN RESULTS AND THE ROLE OF CHANCE: There were 1977 references identified from which 10 studies (n = 1188) were included in the final analysis. For the detection of USL DE, the overall pooled sensitivity and specificity for all TVS techniques were 60% (95% CI 32-82%) and 95% (95% CI 90-98%), respectively, and for all MRI techniques were 81% (95% CI 66-90%) and 83% (95% CI 62-94%), respectively. For the detection of RVS DE, the overall pooled sensitivity and specificity for all TVS techniques were 57% (95% CI 30-80%) and 100% (95% CI 92-100%), respectively. For the detection of vaginal DE, the overall pooled sensitivity and specificity for all TVS techniques were 52% (95% CI 29-74%) and 98% (95% CI 95-99%), respectively, and for all MRI techniques were 64% (95% CI 40-83%) and 98% (96% CI 93-99%). Pooled analyses were not possible for other imaging modalities. LIMITATIONS REASONS FOR CAUTION: There was a low quality of evidence given the high risk of bias and heterogeneity in the included studies. There are also potential biases secondary to the risk of misdiagnosis at surgery owing to a lack of either histopathological findings or expertise, coupled with the surgeons not being blinded. Furthermore, the varying surgical experience and the lack of clarity regarding complete surgical clearance, thereby also contributing to the lack of histopathology, could also explain the wide range of pre-test probability of disease. WIDER IMPLICATIONS OF THE FINDINGS: MRI outperformed TVS for the per-operative diagnosis of USL, RVS and vaginal DE with higher sensitivities, although the specificities for both were excellent. There were improved results with other imaging modalities, such as rectal endoscopy-sonography, as well as the addition of bowel preparation or ultrasound gel to either TVS or MRI, although these are based on individual studies. STUDY FUNDING/COMPETING INTERESTS: No funding was received for this study. M.L. reports personal fees from GE Healthcare, grants from the Australian Women's and Children's Foundation, outside the submitted work. B.W.M. reports grants from NHMRC, outside the submitted work. G.C. reports personal fees from GE Healthcare, outside the submitted work; and is on the Endometriosis Advisory Board for Roche Diagnostics. REGISTRATION NUMBER: Prospective registration with PROSPERO (CRD42017059872) was obtained.

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)0,010
score de la tête « metaresearch » (Gemma)0,036
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,990
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,036
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0210,033
Bibliométrie0,0060,007
Études des sciences et des technologies0,0010,001
Communication savante0,0040,003
Science ouverte0,0020,002
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,129
Tête enseignante GPT0,391
Écart entre enseignants0,262 · 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.

Devis d'étudeMéta-analyse
DomaineMéthodes
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

Citations50
Publié2021
Routes d'admission1
Résumé présentoui

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