Birth defects have brought about major public health problems, and studying the clinical outcomes of the most common prenatal central nervous system abnormality, namely, fetal ventriculomegaly (VM), is helpful for improving reproductive health and fertility quality. This is a retrospective cohort study from 2011 to 2020 in the West China Second University Hospital, Sichuan University, aiming to evaluate the short-term and long-term outcomes of VM over 37 weeks’ gestation to exclude the influence of preterm birth. The study analyzed data from 401 term pregnancies, with 179 VM and 222 controls. From the short-term outcomes, the rate of the neonatal intensive care unit (NICU) admission under the VM group (10.06%) was comparatively higher than the control (0.45%), but Apgar scores between both groups at 1 min, 5 min and 10 min were not significantly different. From the long-term outcomes, there were more infants with abnormal neurodevelopment under the VM group than control (14.53% vs. 2.25%, p < 0.001). In addition, NICU admission (p = 0.006), peak width of lateral ventricles (p = 0.030) and postnatal cranial ultrasound suggestive with VM (p = 0.002) were related to infants’ long-term outcomes. NICU admission during the perinatal period was an independent risk factor for the adverse long-term outcomes (OR = 3.561, 95% CI 1.029–12.320, p = 0.045). In conclusion, VM impairs short-term and long-term outcomes of term infants. Short-term outcome, especially NICU admission, could predict their adverse long-term outcomes.

Background: Combining traditional clinical parameters with neuroendocrine markers to construct a nomogram model to predict the postoperative recurrence of neuroendocrine carcinoma of cervix (NECC). Methods: A total of 257 patients were included in this study. Univariate and multivariate Cox regression analyses were used to establish a nomogram model in the training cohorts, which was further validated in the validation cohorts. The calibration curve was used to conduct the internal and external verification of the model. Results: Overall, 41 relapse cases were observed in the training (23 cases) and validation (18 cases) cohorts. The univariate analysis preliminarily showed that FIGO stage, stromal invasion, nerve invasion, lymph vascular space invasion, lymph node involvement, cervical–uterine junction invasion and CgA were correlated with NECC recurrence. The multivariate analysis further confirmed that FIGO stage (p = 0.023), stromal invasion (p = 0.002), lymph vascular space invasion (p = 0.039) and lymph node involvement (p = 0.00) were independent risk factors for NECC recurrence, which were ultimately included in the nomogram model. In addition, superior consistency indices were demonstrated in the training (0.863, 95% CI 0.784–0.942) and validation (0.884, 95% CI 0.758–1.010) cohorts. Conclusions: The established nomogram model combining traditional clinical parameters with neuroendocrine markers can reliably and accurately predict the recurrence risks in NECC patients.

Purpose Combining traditional clinical parameters with neuroendocrine markers to construct a nomogram model to predict the postoperative recurrence of neuroendocrine carcinoma of cervix (NECC). Methods 257 patients were included in this study, of which, 171 patients diagnosed with NECC who underwent surgery at West China Second Hospital of Sichuan University were considered as part of the training cohort. The univariate and multivariate Cox regression analyses were used in screening the high-risk factors related to cancer recurrence in the training cohort to establish a nomogram model which was further independently validated in the remaining 86 patients who underwent surgery at First Affiliated Hospital of Chongqing Medical University. The calibration curve was used to conduct the internal and external verification of the model. Results Overall, 41 relapse cases were observed in the training (23 cases) and validation (18 cases) cohorts. The univariate analysis preliminarily showed that FIGO stage, stromal invasion, nerve invasion, lymph vascular space invasion, lymph node involvement, cervical-uterine junction invasion and CgA were correlated with NECC recurrence. The multivariate analysis further confirmed that FIGO stage (P = 0.023), stromal invasion (P = 0.002), lymph vascular space invasion (P = 0.039) and lymph node involvement (P = 0.00) were independent risk factors for NECC recurrence, which were ultimately included in the nomogram model. In addition, superior consistency indices were demonstrated in the training (0.863, 95%CI 0.784–0.942) and validation (0.884, 95%CI 0.758–1.010) cohorts. Conclusion The established nomogram model combining traditional clinical parameters with neuroendocrine markers can reliably and accurately predict the recurrence risks in NECC patients.