International Journal of Women's Health最新文献

Objective: To explore the value of the ThinPrep cytology test (TCT) combined with human papillomavirus (HPV) DNA detection in the screening and triage of cervical lesions.

Methods: A total of 1671 patients with cervical inflammation or lesions who underwent colposcopy and biopsy between April 2020 and December 2022 were analyzed. The data included TCT, HPV DNA, and pathological findings.

Results: The incidence of high-grade squamous intraepithelial lesions (HSILs) or above significantly increased with TCT severity: 25.9% in the negative for intraepithelial lesion or malignancy (NILM) group, 39.4% in the atypical squamous cells of undetermined significance (ASCUS) and low-grade SIL (LSIL) groups, and 76.5% in the HSIL+ group (P<0.001 for all pairwise comparisons). The incidence also varied significantly by HPV status: 58.2% in the HPV 16 or 18 group, 28.6% in the other high-risk groups, and 17.6% in the low-risk and negative groups (P<0.001 for all pairwise comparisons). Multivariate analysis revealed independent risk factors for HSIL+: younger age (OR=0.972), HSIL and above cytology (OR=10.154), ASCUS and LSIL cytology (OR=2.250), HPV 16/18 infection (OR=8.061), and other high-risk HPV infections (OR=2.578). Patients with concurrent HPV 16/18 infection and HSIL or above cytology presented a substantially elevated risk (OR=41.517). Among the cohort, 35 cases of cervical squamous cell carcinoma were identified.

Conclusion: TCT combined with HPV DNA testing provides an effective strategy for risk stratification in cervical screening. Our findings support that patients with HPV16 or 18 should be referred directly for colposcopy, and patients with other high-risk HPV types and TCT results of ASCUS and above are also recommended for colposcopy referrals. These referral suggestions warrant further validation in larger, multicenter studies.

Purpose: To evaluate fetal interventricular septum (IVS) volume in pregnant women with gestational diabetes mellitus (GDM) and compare it with that of healthy pregnant women using 4D ultrasound with spatiotemporal image correlation (STIC) and virtual organ computer-aided analysis (VOCAL) methods.

Patients and methods: This prospective cross-sectional study was conducted at Bhumibol Adulyadej Hospital, Royal Thai Airforce, Bangkok, Thailand, from November 2024 to March 2025. Pregnant women with a gestational age (GA) between 29 and 34 weeks were enrolled and divided into two groups: GDM and healthy controls. Fetal IVS volume was measured using 4D ultrasonography with STIC and VOCAL. Maternal, fetal, and demographic data were collected and analyzed.

Results: A total of 111 participants were included: 63 in the GDM group and 48 in the control group. The GDM group was significantly older (33.0 vs 27.9 years) and had a higher BMI (31.1 vs 26.8 kg/m²). Mean fetal IVS volume was significantly greater in the GDM group (347.1 mm³ vs 221.5 mm³). Adverse neonatal outcomes were comparable. The cut-off fetal IVS volume for predicting neonatal hyperbilirubinemia (HBB) and respiratory distress syndrome (RDS) was 419.8 mm³. Sensitivity for predicting HBB and RDS was 55.0 and 56.0%, with negative predictive values of 94.0 and 95.2%, respectively.

Conclusion: Fetal IVS volume was significantly higher in GDM pregnancies. A cut-off value of 419.8 mm³ may be useful in predicting HBB and RDS risk, with high negative predictive value, suggesting its potential as a screening tool during the early third trimester.

Purpose: This study was conducted to evaluate the effects of epilepsy on pregnancy and delivery outcomes. It aimed to assess the relationship of seizure type, the presence of seizures during pregnancy, and the timing of the last seizure before conception on perinatal outcomes for pregnant women with epilepsy (WWE).

Methods: The research included 300 participants, comprising 100 pregnant WWE and a control group of 200 healthy pregnant women. The study analyzed demographic and clinical data for all subjects. Perinatal outcomes were evaluated according to seizure type, seizure status during pregnancy, and the last seizure before pregnancy.

Results: The results showed a high rate of cesarean sections in the epilepsy group, at 71%. The number of babies born small for gestational age (SGA) was also significantly higher among WWE (p = 0.001). While there was no significant difference in most maternal and fetal outcomes between women with generalized and non-generalized seizures, the study identified pre-conception presence of seizures as a critical factor. Women who had experienced a seizure within the year before becoming pregnant had babies born at an earlier gestational week (p = 0.021) and with a lower birth weight (p = 0.018) compared to those whose last seizure was more than a year ago. Furthermore, 45% of the WWE had seizures during their pregnancy.

Conclusion: The most important predictor of seizures during pregnancy is the presence of seizures before pregnancy. Presence of seizures during gestation is strongly associated with adverse perinatal outcomes, whereas the specific type of epilepsy is not.

Purpose: Premature ovarian insufficiency (POI) is a common late effect of chemotherapy among survivors of adolescent and young-adult cancer (AYAC). Given on the widespread use of Chinese herbal medicine (CHM) in restoring individual health, we performed a cohort-based nested patient-control study with the aim of exploring the effect of blending CHM into routine care on the reduction of chemotherapy-induced POIrisk among females with AYAC.

Methods: Females aged 20-39 years with a newly-diagnosed AYAC and being free of POI between 2002 and 2010 were recruited from a population-based claims data. From these enrollees, we identified those with POI occurring after AYAC onset by the end of 2013 (n = 1040). Corresponding controls were randomly selected from the remaining subjects using a pair-matched approach. We then adopted conditional logistic regression to clarify the association between CHM use and POI risk, shown as 95% confidence intervals (CI) and adjusted odds ratios (AOR).

Results: Patients who revived CHM in addition to standard treatment towards AYAC experienced a substantial lower risk of POI than did those who did not use CHM (AOR, 0.16; 95% CI, 0.13-0.19). Importantly, initiating CHM treatment within the first three years after AYAC onset had the greatest benefit, with a lower risk of POI by 92%.

Conclusion: The present study revealed that embedding CHM into routine care of AYAC acted to prevent subsequent POI incident, implying that interdisciplinary collaboration and timely treatment planning should be emphasized to reduce the chance of POI onset.

Objective: Second-trimester glycated hemoglobin (HbA1c) has been proposed as a marker of adverse pregnancy outcomes, yet its predictive value across gestational diabetes mellitus (GDM), pregestational diabetes mellitus (PGDM), and non-diabetic pregnancies remains unclear. This study assessed whether mid-pregnancy HbA1c predicts adverse perinatal outcomes and identified a clinically meaningful threshold.

Materials and methods: This retrospective cohort included 460 singleton pregnancies delivered between January 2021 and January 2025 at Bursa City Hospital. Participants were categorized as GDM (n = 203), PGDM (n = 58), or healthy controls (n = 199). HbA1c was measured at 24-28 gestational weeks. An ROC-derived cut-off of 5.3% for predicting macrosomia (>4000 g) was used for subgroup analyses. Perinatal outcomes included gestational age at delivery, delivery mode, birth weight, Apgar scores, and neonatal intensive care unit (NICU) admission. Correlation, ROC, and multivariate logistic regression analyses were performed.

Results: Median HbA1c levels were highest in the PGDM group (6.50%), followed by GDM (5.36%) and controls (4.93%) (p = 0.038). Women with HbA1c >5.3% had higher rates of preterm birth (p = 0.005), cesarean delivery (p = 0.012), and macrosomia (p = 0.004). ROC analysis showed moderate predictive ability for macrosomia (AUC = 0.642), preterm birth (AUC = 0.602), and cesarean delivery (AUC = 0.562). In multivariate analysis, maternal BMI independently predicted macrosomia (OR = 1.07; 95% CI: 1.01-1.14; p = 0.02), whereas HbA1c showed a positive but nonsignificant association (OR = 1.35; p = 0.13).

Conclusion: Second-trimester HbA1c values above 5.3% were associated with increased risks of preterm birth, cesarean delivery, and macrosomia. Although HbA1c did not independently predict adverse outcomes after adjustment, it may serve as a useful adjunct biomarker for perinatal risk stratification and could contribute to multivariable prediction models.

Background: This study investigates the relationship between the Dietary Inflammation Index (DII) and the risk of infertility among women of childbearing age in the United States.

Methods: This cross-sectional study analyzed data from 3184 women aged 20 to 45 years, utilizing information from the National Health and Nutrition Examination Survey (NHANES, 2013-2020). Dietary intake was assessed using 24-hour recall interviews to calculate the DII score, which is based on 28 dietary components. The DII score is used to assess the inflammatory potential of diet, with higher scores indicating a greater likelihood of inducing inflammation. Multivariate logistic regression and restricted cubic splines (RCS) were employed to evaluate the association between DII and infertility risk, adjusting for potential confounders such as age, BMI, and lifestyle factors. LASSO regression was used to identify key predictors, and a nomogram for predicting infertility risk was developed.

Results: Among the participants, 12.41% were classified as infertile. Women with infertility had significantly higher DII scores compared to those without infertility (2.27 [1.09, 3.14] vs 1.99 [0.92, 2.97]; p =0.016). The analysis revealed a positive association between higher DII scores and increased infertility risk, even after adjusting for confounding variables. RCS analysis indicated no significant nonlinear relationship between DII and infertility (p for non-linearity = 0.118). Furthermore, DII was identified as a more effective predictor of infertility risk than the Healthy Eating Index (HEI). The nomogram prediction model, developed from the predictive factors identified via LASSO regression, exhibited robust predictive performance, achieving an AUC of 85.1% (95% CI: 74.7%-95.5%).

Conclusion: A pro-inflammatory diet, indicated by a high Dietary Inflammatory Index (DII) score, is associated with an elevated risk of infertility in American women, thereby supporting dietary interventions to reduce inflammation for improved fertility outcomes and highlighting the relevance of dietary counseling in fertility care.

Objective: To develop and validate a machine learning-based predictive model for assessing the risk of epidural-related maternal fever (ERMF)- a common complication during labor analgesia.

Methods: A prospective cohort study was conducted among 500 parturients with term singleton pregnancies who received epidural labor analgesia between September 2022 and August 2023. Key variables collected include maternal demographic characteristics, anesthesia-related indicators for complications, and obstetric features. Following application of exclusion criteria, 422 parturients were included and allocated into a modeling cohort (n = 337) and a validation cohort (n = 85) using stratified random sampling at an 8:2 ratio. Eleven machine learning algorithms were utilized to construct predictive models. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), accuracy, precision, recall, and F1-score.

Results: The incidence of ERMF was 28.1% (119/422). Among the evaluated algorithms, Categorical Boosting (CatBoost) demonstrated the highest performance, with an AUC of 0.94 (95% CI: 0.86-0.98), accuracy of 90.59%, precision of 0.88, and average precision (AP) of 0.86 in the validation cohort. Analysis using SHapley Additive exPlanations (SHAP)-an interpretable artificial intelligence method- identified prolonged duration of rupture of membranes, higher maternal body mass index, and nulliparity as the top predictors of ERMF risk. An interactive web-based interface was developed to facilitate real-time clinical risk evaluation.

Conclusion: A machine learning model with high discriminative ability was constructed to predict the risk of ERMF. The CatBoost algorithm effectively identified parturients at elevated risk, and the accompanying visual tool offers evidence-based support for stratified management of intrapartum fever in clinical practice.

Background: Hypertensive disorders of pregnancy (HDP) are major causes of maternal-neonatal morbidity/mortality. Emerging evidence links early pregnancy depression to HDP, but the interaction of social support, including its potential mediating and moderating roles remains understudied. This prospective cohort study explored the associations between early pregnancy depression, social support, and HDP risk in Xuzhou, China.

Methods: A cohort of 1,406 pregnant women at ≤12weeks gestation were recruited from a hospital in Xuzhou, China, between July 2024 and July 2025. Depression symptoms and social support were assessed using the Edinburgh Postnatal Depression Scale (EPDS) and the Social Support Rating Scale (SSRS), respectively. HDP was diagnosed according to ISSHP-2021 criteria following participants until delivery. Associations were evaluated using multivariate logistic regression, mediation, and interaction analyses.

Results: Among the participants, 122 (8.6%) cases of HDP were diagnosed. After adjusting for confounders, early pregnancy depression (EPDS ≥13) significantly increased the risk of HDP (aOR = 2.63, CI: 1.67-4.09, p < 0.001). Conversely, high social support (SSRS ≥45) was a protective factor against HDP (aOR = 0.42, 95% CI: 0.20-0.85, p < 0.001). Mediation analysis further revealed that social support partially mediated the depression-HDP association, accounting for 13.6% of the total effect.

Conclusion: This prospective study demonstrates that first-trimester depressive symptoms increase the risk of HDP, and social support not only directly protects women but also partially mediates the adverse effect of depression. Our findings highlight that early psychological screening and enhancing social support during the first trimester could be crucial strategies for HDP prevention.

Purpose: This study primarily aimed to identify factors influencing the knowledge, attitudes, and practices (KAP) of pregnant women regarding dental diagnosis and treatment during pregnancy in Harbin, China.

Patients and methods: A cross-sectional study was conducted from May to July 2025, during which 383 pregnant women attending the Obstetrics Department of the Fourth Affiliated Hospital of Harbin Medical University were successfully recruited via convenience sampling. A self-designed, validated questionnaire based on the KAP model and the standardized Modified Dental Anxiety Scale (MDAS) was used for data collection. Data were analyzed using descriptive statistics, Pearson correlation, univariate analysis, and multiple linear regression.

Results: The mean KAP scores (standardized to a 100-point scale) were suboptimal: knowledge, 59.36 ± 14.10; attitude, 59.92 ± 13.60; practice, 64.66 ± 16.74; and total KAP, 60.33 ± 12.28. Knowledge gaps were most evident regarding oral medications and radiographic examinations. Dental anxiety was prevalent in 72.0% of participants. The primary barrier to seeking care was safety concerns (74.93%). Medical professionals and online new media were the most frequently reported sources of oral health information. Multiple linear regression identified medical background, pregnancy intention, educational attainment, and dental anxiety as significant predictors of total KAP score (p < 0.05).

Conclusion: Pregnant women's KAP toward dental diagnosis and treatment were influenced by educational attainment, Medical professional background, pregnancy intention, and dental anxiety. Developing national guidelines, enhancing multidisciplinary collaboration, and providing targeted education and psychological support may improve oral health outcomes.

Menopause characterized by estrogen deficiency and has various symptoms, including vasomotor, genitourinary, and psychological manifestations. Innovative drug delivery systems (IDDSs) offer targeted approaches that increase therapeutic efficacy, reduce side effects, and improve patient adherence. To update our knowledge about Drug Delivery Systems (DDS) for decrease menopausal symptoms and its benefits compare with conventional systems. This review systematically examines the application and clinical potential of IDDS for managing menopause-related symptoms, with a particular emphasis on improvements in efficacy, safety, and patient adherence. A comprehensive literature search across multiple databases (PubMed, Em-base, Cochran, Scopus; 2001-2024) yielded 23 studies, including RCTs and observational studies on trans dermal, intravaginal, and Nano-based DDS s (patches, vaginal rings, nano particles) and Neurokinin-3 (NK3) antagonists. Transdermal systems, such as estrogen patches, maintained stable hormone levels and reduced thromboembolism risk by 30% compared to oral hormone replacement therapy (HRT), by bypassing first-pass metabolism. Intravaginal DDS s, like estradiol rings, relieved genitourinary symptoms with less than 1% systemic absorption, thereby minimizing endometrial risks. Non-hormonal Neurokini3 antagonists like fezolinetant, decreased VMS by 60% and benefited high-risk patients. Emerging technologies, like hydro gels, showed preclinical potential but lack long-term safety data. Adherence to treatment was better with sustained-release formulations, such as pellet implants, compared to daily dosing regimens. DDSs offer personalized menopause management, balancing safety and efficacy. Future research should focus on pharmacogenomics, equity, and long-term safety of advanced DDSs, especially those using nanotechnology.