The Application of Artificial Intelligence-Assisted Colposcopy in a Tertiary Care Hospital within a Cervical Pathology Diagnostic Unit.

The rising global incidence of cervical cancer is estimated to have affected more than 600,000 women, and nearly 350,000 women are predicted to have died from the disease in 2020 alone. Novel advances in cancer prevention, screening, diagnosis and treatment have all but reduced the burden of cervical cancer in developed nations. Unfortunately, cervical cancer is still the number one gynecological cancer globally. A limiting factor in managing cervical cancer globally is access to healthcare systems and trained medical personnel. Any methodology or procedure that may simplify or assist cervical cancer screening is desirable. Herein, we assess the use of artificial intelligence (AI)-assisted colposcopy in a tertiary hospital cervical diagnostic pathology unit. The study group consisted of 48 women (mean age 34) who were referred to the clinic for a routine colposcopy by their gynecologist. Cervical images were taken by an EVA-Visualcheck TM colposcope and run through an AI algorithm that gave real-time binary results of the cervical images as being either normal or abnormal. The primary endpoint of the study assessed the AI algorithm's ability to correctly identify histopathology results of CIN2+ as being abnormal. A secondary endpoint was a comparison between the AI algorithm and the clinical assessment results. Overall, we saw lower sensitivity of AI (66.7%; 12/18) compared with the clinical assessment (100%; 18/18), and histopathology results as the gold standard. The positive predictive value (PPV) was comparable between AI (42.9%; 12/28) and the clinical assessment (41.8%; 18/43). The specificity, however, was higher in the AI algorithm (46.7%; 14/30) compared to the clinical assessment (16.7%; 5/30). Comparing the congruence between the AI algorithm and histopathology results showed agreement 54.2% of the time and disagreement 45.8% of the time. A trained colposcopist was in agreement 47.9% and disagreement 52.1% of the time. Assessing these results, there is currently no added benefit of using the AI algorithm as a tool of speeding up diagnosis. However, given the steady improvements in the AI field, we believe that AI-assisted colposcopy may be of use in the future.

Polish Society of Gynecologists and Obstetricians recommendations on supplementation during pregnancy.

Polish Society of Gynecologists and Obstetricians recommendations on supplementation during pregnancy.

Postnatal condition of the second twin in respect to mode of delivery, chorionicity and type of fetal growth.

BACKGROUND: The increased use of assisted reproductive techniques (ART) contributes to the increased rate of twin pregnancies, which are burdened with a higher risk of complications. Factors that affect the condition of the second twin are understudied. OBJECTIVES: The objective of this study was to assess the impact of the delivery mode, chorionicity, amnionicity, and the type of fetal growth on the postnatal condition of the second twin. MATERIAL AND METHODS: The study included data from 475 pregnant women with twin pregnancies. Maternal age, parity, chorionicity, amnionicity, type of fetal growth, mode of delivery, gestational weeks at delivery, Apgar score, and umbilical arterial blood pH were retrospectively analyzed. Data normality was checked with the Kolmogorov-Smirnov test. The paired Wilcoxon signed-rank test and χ2 test were used for comparisons between groups. To check predictive value of the analyzed variables multiple linear regression was used. RESULTS: The mean maternal age was 29.22 (standard deviation (SD) ±5.19) years. The maternal age and gestational age at delivery did not differ significantly between women who delivered by cesarean section (CS) and vaginal delivery (VD). In the second twin, the Apgar score and values of arterial umbilical blood pH were lower in infants delivered by VD than in those delivered by CS (6.30 ±2.83 and 7.30 ±0.12; p = 0.0209 and 7.26 ±0.12 and 7.30 ±0.11; p = 0.0236, respectively). In monochorionic diamniotic twins with asymmetric growth, the second twin achieved significantly lower outcome than the first twin. Vaginal delivery was a predictive factor for a lower Apgar score and lower values of umbilical arterial blood pH in second twins, while not in first twins. Symmetrical fetal growth of twins was a predictive factor for better postnatal condition for both twins. CONCLUSIONS: In twin pregnancies, VD, but not CS, is associated with increased risk of worse postnatal condition of the second twin. In monochorionic diamniotic pregnancies complicated by growth discordance, CS seems to be a reasonable mode of delivery.