Background: Nomogram, a visual clinical predictive model, provides a scientific basis for clinical decision making. Herein, we investigated 20 years of nomogram research responses, focusing on current and future trends and analytical challenges.Methods: We mined data of scientific literature from the Core Collection of Web of Science, searching for the original articles with title “Nomogram^*/Parton Table^*/Parton Nomogram^*”, published within January 1st, 2000 to December 30th, 2021. Data records were validated using HistCite Version and analyzed with a transformable statistical method, the Bibliometrix 3.0 package of R Studio.Results: In total, 4,176 original articles written by 19,158 authors were included from 915 sources. Annually, Nomogram publications are continually produced, which have rapidly grown since 2018. China published the most articles; however, its total citations ranked second after the United States. Both total citations and average article citations in the United States rank first globally, and a high degree of cooperation exists between countries. Frontiers in Oncology published the most papers (238); this number has grown rapidly since 2019. Journal of Urology had the highest H-index, with an average increase in publications over the past 20 years. Most research topics were tumor-related, among which tumor risk prediction and prognostic evaluation were the main contents. Research on prognostic assessment is more published and advanced, while risk prediction and diagnosis have good developmental prospects. Furthermore, nomogram of the urinary system has been highly developed. Following advancements in nomogram modeling, it has recently been applied to non-oncological subjects.Conclusion: This bibliometric analysis provides a comprehensive overview of the current nomogram status, which could enable better understanding of its development over the years, and provide global researchers a comprehensive analysis and structured information to help identify hot spots and gaps in future research.

Rapid Cycle Deliberate Practice (RCDP) has gained prominence in recent years as an innovative teaching method in simulation-based training for adult and pediatric emergency medical skills. However, its application in the training of forceps delivery skills among obstetrics and gynecology residents remains unexplored. This study aimed to assess the impact of RCDP in this domain. Conducted in March 2021, this randomized controlled study involved 60 second-year obstetrics and gynecology residents undergoing standardized training. Participants were randomly assigned to the RCDP group or the traditional teaching method (TTM) group, each comprising 30 residents. The RCDP group followed the RCDP practice mode, while the TTM group adhered to conventional simulation teaching. Post-training assessment of operational proficiency was conducted immediately and after one year. Independent operational confidence and training satisfaction were evaluated through questionnaire surveys and the Satisfaction with Simulation Experience (SSE) scale. Data analysis utilized SPSS 23.0. The RCDP group displayed significantly higher immediate post-training forceps operation scores compared to the TTM group (92.00 [range: 90.00-94.00] vs. 88.00 [range: 86.75-92.00]; z = 3.79; p < .001). However, no significant difference emerged in forceps operation scores after one year (86.00 [range: 85.00-88.00] vs. 85.50 [range: 84.00-88.25]; z = 0.54; p = .59). The RCDP group exhibited notable performance improvement over the TTM group (z = 3.49; p < .001). Independent operation confidence showed no significant discrepancy (p > .05). Importantly, the RCDP group reported higher satisfaction scores, particularly in the Debriefing and Reflection subscale (44.00 [range: 43.00-45.00] vs. 41.00 [range: 41.50-43.00]; z = 5.24; p < .001), contributing to an overall superior SSE score (z = 4.74; p < .001). RCDP exhibits immediate efficacy in elevating forceps delivery skills among residents. However, sustained skill enhancement necessitates innovative approaches, while RCDP's value lies in tailored feedback and reflection for enriched medical education.

Objective: To explore the risk factors of postpartum hemorrhage (PPH) in patients with pernicious placenta previa (PPP) and to develop and validate a clinical and imaging-based predictive model.Methods: A retrospective analysis was conducted on patients diagnosed surgically and pathologically with PPP between January 2018 and June 2022. All patients underwent PPP magnetic resonance imaging (MRI) and ultrasound scoring in the second trimester and before delivery, and were categorized into two groups according to PPH occurrence. The total imaging score and sub-item prediction models of the MRI risk score/ultrasound score were used to construct Models A and B/Models C and D. Models E and F were the total scores of the MRI combined with the ultrasound risk and sub-item prediction model scores. Model G was based on the subscores of MRI and ultrasound with the introduction of clinical data. Univariate logistic regression analysis and the logical least absolute shrinkage and selection operator (LASSO) model were used to construct models. The receiver operating characteristic curve andision curve analysis (DCA) were drawn, and the model with the strongest predictive ability and the best clinical effect was selected to construct a nomogram. Internal sampling was used to verify the prediction model’s consistency.Results: 158 patients were included and the predictive power and clinical benefit of Models B and D were better than those of Models A and C. The results of the area under the curve of Models B, D, E, F, and G showed that Model G was the best, which could reach 0.93. Compared with Model F, age, vaginal hemorrhage during pregnancy, and amniotic fluid volume were independent risk factors for PPH in patients with PPP (p < 0.05). We plotted the DCA of Models B, D, E, F, and G, which showed that Model G had better clinical benefits and that the slope of the calibration curve of Model G was approximately 45°.Conclusion: LASSO regression nomogram based on clinical risk factors and multiple conventional ultrasound plus MRI signs has a certain guiding significance for the personalized prediction of PPH in patients with PPP before delivery.