Background and Objectives: Despite advancements in detection and treatment, cervical cancer remains a significant health concern, particularly among young women of reproductive age. Limited data exists in the literature regarding fertility-sparing treatment (FST) of cervical cancers with tumor sizes greater than 2 cm. The objective of this systematic review was to evaluate the reproductive outcomes of women diagnosed with cervical cancer greater than 2 cm who underwent FST. Materials and Methods: A comprehensive search of the literature was carried out on the following databases: MEDLINE, EMBASE, Global Health, The Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Cochrane Methodology Register), the Health Technology Assessment Database, and Web of Science. Only original studies (retrospective or prospective) that reported reproductive outcomes of patients with cervical cancer >2 cm were considered eligible for inclusion in this systematic review (CRD42024521964). Studies describing only the oncologic outcomes, involving FST for cervical cancers less than 2 cm in size, and case reports were excluded. Results: Seventeen papers that met the abovementioned inclusion criteria were included in the present systematic review. In total, 443 patients with a cervical cancer larger than 2 cm were included in this systematic review. Eighty pregnancies occurred, with 24 miscarriages and 54 live births. Conclusions: FST appears to be a viable option for women of childbearing age diagnosed with cervical cancer larger than 2 cm. However, careful consideration is advised in interpreting these encouraging results, as they are subject to limitations, such as variability in study designs and potential biases. In addition, reproductive outcomes should be further cross-referenced with oncologic outcomes to clarify the potential risk–benefit ratio. It is critical to conduct further research using standardized approaches and larger participant groups to strengthen the validity of the conclusions drawn.

Background: Poor ovarian response (POR) complicates a substantial proportion of in vitro fertilization (IVF) cycles, frequently causing cycle cancellation and suboptimal reproductive outcomes. Conventional follicular‐phase ovarian stimulation (FPOS) protocols often yield limited results, prompting the evaluation of alternative strategies such as luteal‐phase ovarian stimulation (LPOS). Objectives: This study assesses whether LPOS presents similar efficacy in terms of assisted reproductive technology (ART) outcomes compared with stimulation in the conventional follicular phase in women with POR according to Bologna criteria. Method: Comprehensive electronic searches were performed up to July 2024 across MEDLINE (via PubMed), EMBASE, SCOPUS, LILACS, SciELO, CINAHL, PsycINFO, AMED, Clinicaltrials.gov , WHO ICTRP, and Cochrane databases, with additional hand‐searching of reference lists and gray literature. Inclusion criteria were comparative studies evaluating LPOS versus FPOS in poor ovarian responders undergoing IVF/intracytoplasmic sperm injection. Studies involving DuoStim protocols, lacking control groups, or with incomplete data were excluded. Study selection, data extraction, and quality assessments (RoB 2 for randomized clinical trial (RCTs); ROBINS‐I for observational studies) were conducted independently by multiple reviewers. Meta‐analysis utilized random‐effects models to generate pooled mean differences (MD) and risk ratios (RR) with 95% confidence intervals (CI). Certainty of evidence was assessed using the GRADE methodology. Results: Five studies (312 patients; 114 LPOS vs. 198 FPOS) met the inclusion criteria. LPOS resulted in a non‐significant increase in cumulus–oocyte complexes retrieved (MD 0.56; 95% CI –0.12 to 1.23) and mature (MII) oocytes (MD 0.061; 95% CI –0.04 to 0.126), with moderate heterogeneity. The number of embryos reaching day 3 was significantly higher with LPOS (MD 0.77; 95% CI 0.29 to 1.25). No significant differences were found for clinical pregnancy rate (RR 1.26; 95% CI 0.78 to 2.02), fertilization rate (RR 1.04; 95% CI 0.91 to 1.20), pregnancy loss rate (RR 0.97; 95% CI 0.27 to 3.43), or cancellation rate (RR 0.89; 95% CI 0.34 to 2.30). Stimulation duration was significantly longer in LPOS, while total gonadotropin dose and serum estradiol on trigger day did not differ significantly. The overall certainty of evidence ranged from low to very low; therefore, findings should be interpreted as preliminary and might change as additional studies become available. Conclusion: Luteal‐phase ovarian stimulation appears to be an effective alternative to conventional FPOS for poor responders, demonstrating similar reproductive outcomes with possible quantitative benefits in embryo yield. However, the evidence is limited, and research is ongoing; therefore, results are pending and further large‐scale randomized controlled trials are required to confirm these findings. PROSPERO Registration: This review was prospectively registered in PROSPERO (ID: CRD420251010075; registration date: 12/05/2025).

STUDY QUESTION: How do the three most widely accessible large language models perform in terms of accuracy, consistency, and reliability when answering clinically relevant questions derived from the 2022 ESHRE guideline on endometriosis? SUMMARY ANSWER: Model A achieved the highest accuracy scores, model C demonstrated significantly superior consistency across repeated queries, and all three models showed comparable but suboptimal reliability under free-tier access, while under official API access median accuracy converged across providers and reliability increased. WHAT IS KNOWN ALREADY: Large language models are increasingly consulted by both clinicians and patients as readily accessible sources of medical information. In reproductive medicine, preliminary evidence suggests that individual platforms may retrieve endometriosis-related content with mixed fidelity. However, no study has simultaneously benchmarked multiple models against a single, internationally recognized endometriosis guideline. The extent to which these tools can be trusted to faithfully reproduce evidence-based recommendations on endometriosis diagnosis and management remains largely unexplored. STUDY DESIGN, SIZE, DURATION: Cross-sectional, multi-platform comparative study. Fifty clinically relevant questions covering the diagnostic and therapeutic domains of the 2022 ESHRE endometriosis guideline were simultaneously submitted to all three models during December 2025. Each question was entered in duplicate using independent sessions to assess response consistency and reliability. Subgroup analyses were carried out by submitting the questions to the API version and to the free-tier version of the platforms available in May 2026. PARTICIPANTS/MATERIALS, SETTING, METHODS: The three models were accessed through their respective free web interfaces using new accounts, without prompt engineering, prior training, or retrieval-augmented generation. A zero-shot prompting approach was adopted. Accuracy was evaluated by two independent experts using the Global Quality Score (GQS); consistency was defined as identical responses across the three iterations; reliability was defined as the alignment of each response with the ESHRE guideline. Discrepancies were settled by a third reviewer. MAIN RESULTS AND THE ROLE OF CHANCE: Significant differences in accuracy were observed across models (Kruskal–Wallis H = 37.10, P < 0.001). Model A achieved the highest median GQS (5, interquartile range [IQR] 4–5), followed by model C (4, IQR 3–5) and model B (3, IQR 3–4). Post-hoc analysis confirmed that model A significantly outperformed model B (P < 0.001) but not model C (P = 0.123), while model C also scored significantly higher than model B (P < 0.001). For consistency, model C demonstrated a significantly higher rate of reproducible responses (92.0%) compared with model A (72.0%, P = 0.028) and model B (68.0%, P = 0.008). No significant between-model differences were found for reliability (χ2 = 1.029, P = 0.598), with rates of 76.0% for model C, 68.0% for model A, and 68.0% for model B. In API and free-tier May 2026 subgroup analyses, median GQS converged to 4 across all three providers, and reliability rose to at least 76% for each provider. LIMITATIONS, REASONS FOR CAUTION: Model outputs may change with subsequent updates. GQS retains a degree of subjectivity despite expert adjudication. The study tested factual recall rather than complex clinical reasoning, limiting generalizability to real-world decision-making scenarios. WIDER IMPLICATIONS OF THE FINDINGS: These findings provide the first multi-platform benchmark of large language models against the latest endometriosis guideline. While models A and C retrieved guideline-concordant information with acceptable fidelity, none of the models achieved a level of reliability required for unsupervised clinical use. The dissociation between accuracy and consistency at the free tier, and its attenuation under API and more recent accesses, indicates that both model capability and commercial tier shape user-facing outputs. The dissociation between accuracy and consistency underscores that a model producing high-quality answers does not necessarily do so in a reproducible manner. Expert oversight remains crucial when interpreting their output regarding endometriosis care. Future research should extend this framework to additional endometriosis guidelines and to longitudinal monitoring of models’ performance with their upgrades. FUNDING: No external funding was received for this study. DISCLOSURES: The authors declare no competing interests. TRIAL REGISTRATION NUMBER: N/A.