Vaginal Hysterectomy: A Network Meta-Analysis Comparing Short-Term Outcomes of Surgical Techniques and Devices.

OBJECTIVE: To provide available evidence comparing surgical outcomes of different vaginal hysterectomy (VH) techniques and devices. DATA SOURCES: PubMed, Embase, and ClinicalTrials.gov databases were searched from inception to December 1, 2023, using relevant keywords. METHODS OF STUDY SELECTION: Studies comparing at least 2 surgical techniques and devices for VH were included. An arm-based random effect frequentist network meta-analysis was performed. All available surgical outcomes were evaluated. TABULATION, INTEGRATION, AND RESULTS: Ten randomized controlled trials and 7 observational studies were eligible reporting on 1577 women undergoing VH with different techniques and devices (50% conventional, 22.5% Ligasure, 17.3% BiClamp, and 9.2% transvaginal natural orifice transluminal endoscopic surgery [vNOTES]). All surgical techniques/devices had a comparable risk ratio (RR) in terms of intraoperative complications, but Clavien-Dindo grade III postoperative complications were significantly reduced in the vNOTES group (RR, 0.15; 95% confidence interval [CI], 0.03-0.82; I2 = 0%) compared with conventional VH. The pooled network analysis showed a lower standard mean deviation for blood loss when comparing energy-based vessel sealing technologies (Ligasure: standard mean deviation, -0.92; 95% CI, -1.47 to -0.37; BiClamp: standard mean deviation, -1.66; 95% CI, -2.77 to -0.55) with conventional VH. Total operative time, postoperative hemoglobin variation, and pain were significantly reduced only in the Ligasure group compared with conventional VH. Bilateral salpingectomy or bilateral salpingo-oophorectomy was most commonly performed in the vNOTES group (RR, 1.9; 95% CI, 1.17-3.10) compared with the conventional VH group. CONCLUSION: Modern surgical techniques/devices have the potential to improve anatomic exposure and to reduce morbidity of VH. This may drive resurgence of vaginal approach to hysterectomy.

Optimizing Performance of Transformer-based Models for Fetal Brain MR Image Segmentation.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To test transformer-based models' performance when manipulating pretraining weights, dataset size, input size and comparing the best-model with reference standard and state-of-the-art models for a resting-state functional (rs-fMRI) fetal brain extraction task. Materials and Methods An internal retrospective dataset (fetuses = 172; images = 519; collected from 2018-2022) was used to investigate influence of dataset size, pretraining approaches and image input size on Swin-UNETR and UNETR models. The internal and an external (fetuses = 131; images = 561) datasets were used to cross-validate and to assess generalization capability of the best model against state-of-the-art models on different scanner types and number of gestational weeks (GW). The Dice similarity coefficient (DSC) and the Balanced average Hausdorff distance (BAHD) were used as segmentation performance metrics. GEE multifactorial models were used to assess significant model and interaction effects of interest. Results Swin-UNETR was not affected by pretraining approach and dataset size and performed best with the mean dataset image size, with a mean DSC of 0.92 and BAHD of 0.097. The Swin-UNETR was not affected by scanner type. Generalization results on the internal dataset showed that Swin-UNETR had lower performances compared with reference standard models and comparable performances on the external dataset. Cross-validation on internal and external test sets demonstrated better and comparable performance of Swin-UNETR versus convolutional neural network architectures during the late-fetal period (GWs > 25) but lower performance during the midfetal period (GWs ≤ 25). Conclusion Swin-UNTER showed flexibility in dealing with smaller datasets, regardless of pretraining approaches. For fetal brain extraction of rs-fMRI, Swin-UNTER showed comparable performance with reference standard models during the late-fetal period and lower performance during the early GW period. ©RSNA, 2024.

Preterm birth in singleton pregnancies conceived by in vitro fertilization or intracytoplasmic sperm injection: an overview of systematic reviews.

BACKGROUND: The rate of preterm birth of singletons conceived through in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) is increased, being as high as 15% to 16% across Europe and the United States. However, the underlying etiology, phenotype, and mechanisms initiating preterm birth (PTB) are poorly understood. OBJECTIVE: To quantify the PTB risk and examine supposed etiology in IVF/ICSI singleton pregnancies compared to naturally conceived. STUDY DESIGN: Overview of reviews including all available systematic reviews with meta-analysis comparing PTB risk in IVF/ICSI and naturally conceived singletons. A comprehensive search of PubMed/MEDLINE, Embase, Scopus, and Cochrane Library databases was performed up to December 31, 2023. Information available on etiology, phenotype, initiation of PTB, and relevant moderators was retrieved and employed for subgroup analyses. Random-effects meta-analysis models were used for pooling effect measures. Estimates were presented as odds ratios (ORs) with 95% confidence intervals (CIs). The extent of overlap in the original studies was measured using the corrected covered area assessment. The quality of the included reviews was evaluated with the AMSTAR 2 tool. The Grading of Recommendations Assessment, Development and Evaluation approach was applied to rate evidence certainty. The protocol was registered on PROspective Register of Systematic Reviews (CRD42023411418). RESULTS: Twelve meta-analyses (16,522,917 pregnancies; ˃433,330 IVF/ICSI) were included. IVF/ICSI singletons showed a significantly higher PTB risk compared to natural conception (PTB ˂37 weeks: OR: 1.72, 95% CI: 1.57-1.89; PTB<32 weeks: OR: 2.19, 95% CI: 1.82-2.64). Influential analysis reinforced the strength of this association. Subgroup analyses investigating supposed etiology revealed a comparable risk magnitude for spontaneous PTB (OR: 1.79, 95% CI: 1.56-2.04) and a greater risk for iatrogenic PTB (OR: 2.28, 95% CI: 1.72-3.02). PTB risk was consistent in the subgroup of conventional IVF (OR: 1.95, 95% CI: 1.76-2.15) and higher in the subgroup of fresh only (OR: 1.79, 95% CI: 1.55-2.07) vs frozen-thawed embryo transfers (OR: 1.39, 95% CI: 1.34-1.43). There was minimal study overlap (13%). The certainty of the evidence was graded as low to very low. CONCLUSION: Singletons conceived through IVF/ICSI have a 2-fold increased risk of PTB compared to natural conception, despite the low certainty of the evidence. There is paucity of available data on PTB etiology, phenotype, or initiation. The greater risk increase is observed in fresh embryo transfers and involves iatrogenic PTB and PTB ˂32 weeks, likely attributable to placental etiology. Future studies should collect data on PTB etiology, phenotype, and initiation. IVF/ICSI pregnancies should undertake specialistic care with early screening for placental disorders, cervical length, and growth abnormalities, allowing appropriate timely follow-up, preventive measures, and therapeutic interventions strategies.

Etiologically Based Functional Taxonomy of the Preterm Birth Syndrome.

Preterm birth (PTB) is a complex syndrome traditionally defined by a single parameter, namely, gestational age at birth (ie, ˂37 weeks). This approach has limitations for clinical usefulness and may explain the lack of progress in identifying cause-specific effective interventions. The authors offer a framework for a functional taxonomy of PTB based on (1) conceptual principles established a priori; (2) known etiologic factors; (3) specific, prospectively identified obstetric and neonatal clinical phenotypes; and (4) postnatal follow-up of growth and development up to 2 years of age. This taxonomy includes maternal, placental, and fetal conditions routinely recorded in data collection systems.

Commentary: Predicting adverse outcomes in pregnant patients positive for SARS-CoV-2 by a machine learning approach.

SARS-CoV-2 infection poses a significant risk increase for adverse pregnancy outcomes both from maternal and fetal sides. A recent publication in BMC Pregnancy and Childbirth presented a machine learning algorithm to predict this risk. This commentary will discuss potential implications and applications of this study for future global health policies.

Progesterone levels during ovarian stimulation in segmented ART cycles inversely correlate with normalized birthweight of neonates conceived through subsequent frozen-thawed embryo transfer.

PURPOSE: To evaluate the association between serum progesterone (P) at the day of ovulation trigger and neonatal birthweight in singletons born after frozen-thawed embryo transfer in segmented ART cycles. METHODS: A retrospective multicenter cohort study involving data from patients who achieved uncomplicated pregnancy and term delivery of ART-conceived singleton babies following a segmented GnRH antagonist cycle. The main outcome was birthweight's z-score of the neonate. Univariate and multivariate linear logistic regression analyses were made to investigate the relation of z-score with variables inherent to the patient and to the ovarian stimulation. The variable P per oocyte was created by dividing the value of progesterone at ovulation trigger by the number of oocytes retrieved at oocyte retrieval. RESULTS: A total of 368 patients were included in the analysis. At univariate linear regression, the birthweight z-score of the neonate appeared to be inversely related to both P levels at the ovulation trigger (- 0.101, p = 0.015) and P levels per oocyte at trigger (- 1.417, p = 0.001), while it was directly related to the height of the mother (0.026, p = 0.002) and to the number of previous live births (0.291, p = 0.016). In multivariate analysis, both serum P (- 0.1; p = 0.015) and P per oocyte (- 1.347, p = 0.002) maintained the significant inverse association with birthweight z-score after adjusting for height and parity. CONCLUSIONS: Serum progesterone level on the day of ovulation trigger inversely correlates with normalized birthweight of neonates in segmented GnRH antagonist ART cycles.

Endometriosis increases the risk of gestational diabetes: a meta-analysis stratified by mode of conception, disease localization and severity.

To review the current evidence on the risk of gestational diabetes mellitus (GDM) in women with endometriosis, taking into account relevant confounders such as the higher frequency of Assisted Reproductive Technologies (ART) conceptions. Database searches on PubMed, Medline, Embase and Scopus through June 2022, using combinations of relevant keywords. A total of 18 studies, involving N = 4,600,885 women, were included. The overall risk of GDM in endometriosis patients was significantly higher than in controls (OR, 1.23; 95% CI 1.07-1.51). This significant association persisted in natural pregnancies (OR, 1.08; 95% CI 1.04-1.12) but not in pregnancies conceived through ART (OR, 0.93;95% CI 0.70-1.24). Based on the limited number of studies that examined this association in relation to endometriosis phenotype, an increased risk was found in more severe stages (OR, 3.20; 95% CI 1.20-8.54) but independently from localization of the lesions. Endometriosis increases the risk of GDM, with a possible progressive effect in more advanced stages of the disease. Although the effect magnitude may be limited in some subgroups, this finding has a clinically relevant impact due to both the strong biological plausibility and to the relatively high incidence of both endometriosis and GDM.