Analysis of Female Urogenital Tract Microenvironment Pre- and Post LEEP and Impact on Sexual Dysfunction
Notice bibliographique
Résumé
ABSTRACT Introduction The microbiome of the female urogenital tract (FUT), including the urinary tract, the vagina, and the cervix, contains different organisms which are essential for maintaining a stable microenvironment. Little is known about the interrelatedness of these three regions despite their close anatomical relationship. It is possible that dysbiosis in one region because of disease, such as cervical dysplasia (CD), can impact other FUT microbiomes. Electrocautery of the cervix during the Loop Electrosurgical Excision Procedure (LEEP) effectively treats CD yet is known to alter the local microbiome. The impact of CD and its treatment (LEEP) on the FUT microbiomes has yet to be investigated. Given the potential for tissue damage from electrocautery, it is likely that the cervical microbiome pre- and post-LEEP could have a bacterial profile that reflects a persistent pro-inflammatory environment. It is possible that persistent dysbiosis may be a mechanism of the FSD that has been reported in a subpopulation of post-LEEP patients, though this correlation has never been investigated. Objective This study examined the bacterial profile of the FUT in patients with CD before and after treatment with LEEP. It also evaluated the sexual function of patients pre-and post-LEEP using validated surveys and compared the survey responses to the patient bacterial profiles. Methods Twenty-five participants with CD undergoing LEEP were consented and recruited. Vaginal and cervical swabs as well as urine samples were collected to examine the FUT microbiomes. All participants completed an online self-report survey including full FSFI before LEEP and three months post-LEEP. 16S rRNA analysis was performed to determine the presence and relative abundance of bacteria in the samples. Qualitative and statistical analysis were performed on survey responses using NVivo12 and SPSS, respectively. Results The cervical, vaginal, and urethral microbiomes displayed significant similarity (beta diversity, p = <0.0001) likely demonstrating a functional relationship between these three regions for the first time. Notably, this study found the relative abundance of Prevotella in participants with CD pre-LEEP significantly increased (p = <0.001) in only the cervical microbiome. This showed that the cervix had unique bacterial proportions compared to the vagina, though existing studies often examine them together. There was a further significant increase (p = 0.0186) in Prevotella in the cervical microbiome of participants post-LEEP versus pre-LEEP. The findings suggest that on average, patients with CD have a cervical microbiome in dysbiosis. This study also identified a subset of participants with decreased sexual function post-LEEP and correlative microbiome dysbiosis. Further bacterial analysis regarding these profiles is ongoing. Conclusions This study was the first to determine the interrelatedness between regions of the FUT microbiomes, and importantly showed that patients with CD have a cervical microbiome in dysbiosis. It also showed that CD patients may have persistent inflammation after treatment with LEEP, which could result in FSD detected by self-report surveys. Information gained from characteristic FUT bacterial profiles may be translated into therapies to regulate the microbiome pre- and post-LEEP and may indicate that the environment of the FUT can be optimized to facilitate healing following electrocautery procedures. Disclosure No
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».