Efficacy and safety of treatment modalities for cesarean scar pregnancy: a systematic review and network meta-analysis
Notice bibliographique
Résumé
OBJECTIVE: Cesarean scar pregnancy may lead to varying degrees of complications. There are many treatment methods for it, but there are no unified or recognized treatment strategies. This systematic review and network meta-analysis aimed to observe the efficacy and safety of treatment modalities for patients with cesarean scar pregnancy. DATA SOURCES: MEDLINE, Embase, and Cochrane Central Register of Controlled Trials were searched from their inception to January 31, 2024. In addition, relevant reviews and meta-analyses were manually searched for additional references. STUDY ELIGIBILITY CRITERIA: Our study incorporated head-to-head trials involving a minimum of 10 women diagnosed with cesarean scar pregnancy through ultrasound imaging or magnetic resonance imaging, encompassing a detailed depiction of primary interventions and any supplementary measures. Trials with a Newcastle-Ottawa scale score <4 were excluded because of their low quality. METHODS: We conducted a random-effects network meta-analysis and review for cesarean scar pregnancy. Group-level data on treatment efficacy and safety, reproductive outcomes, study design, and demographic characteristics were extracted following a predefined protocol. The quality of studies was assessed using the Cochrane risk-of-bias tools for randomized controlled trials and the Newcastle‒Ottawa scale for cohort studies and case series. The main outcomes were efficacy (initial treatment success) and safety (complications), of which summary odds ratios and the surface under the cumulative ranking curve using pairwise and network meta-analysis with random effects. RESULTS: Seventy-three trials (7 randomized controlled trials) assessing a total of 8369 women and 17 treatment modalities were included. Network meta-analyses were rooted in data from 73 trials that reported success rates and 55 trials that reported complications. The findings indicate that laparoscopy, transvaginal resection, hysteroscopic curettage, and high-intensity focused ultrasound combined with suction curettage demonstrated the highest cure rates, as evidenced by surface under the cumulative ranking curve rankings of 91.2, 88.2, 86.9, and 75.3, respectively. When compared with suction curettage, the odds ratios (95% confidence intervals) for efficacy were as follows: 6.76 (1.99-23.01) for laparoscopy, 5.92 (1.47-23.78) for transvaginal resection, 5.00 (1.99-23.78) for hysteroscopic curettage, and 3.27 (1.08-9.89) for high-intensity focused ultrasound combined with suction curettage. Complications were more likely to occur after receiving uterine artery chemoembolization, suction curettage, methotrexate+hysteroscopic curettage, and systemic methotrexate; hysteroscopic curettage, high-intensity focused ultrasound combined with suction curettage, and Lap were safer than the other options derived from finite evidence; and the confidence intervals of all the data were wide. CONCLUSION: Our findings indicate that laparoscopy, transvaginal resection, hysteroscopic curettage, and high-intensity focused ultrasound combined with suction curettage procedures exhibit superior efficacy with reduced complications. The utilization of methotrexate (both locally guided injection and systemic administration) as a standalone medical treatment is not recommended.
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 | 0,024 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,020 | 0,048 |
| Bibliométrie | 0,010 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».