No abstract

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.

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There is accumulating evidence on the perinatal aspects of COVID-19, but available data are still insufficient. The reports on perinatal aspects of COVID-19 have been published on a small group of patients. Vertical transmission has been noted. The SARS-CoV-2 genome can be detected in umbilical cord blood and at-term placenta, and the infants demonstrate elevated SARS-CoV-2-specific IgG and IgM antibody levels. In this work, the analysis of clinical characteristics of RT-PCR SARS-CoV-2-positive pregnant women and their infants, along with the placental pathology correlation results, including villous trophoblast immunoexpression status for SARS-CoV-2 antibody, is presented. RT-PCR SARS-CoV-2 amniotic fluid testing was performed. Neonatal surveillance of infection status comprised RT-PCR testing of a nasopharyngeal swab and the measuring of levels of anti-SARS-CoV-2 in blood serum. In the initial study group were 161 pregnant women with positive test results. From that group, women who delivered during the hospital stay were selected for further analysis. Clinical data, laboratory results, placental histomorphology results, and neonatal outcomes were compared in women with immunohistochemistry (IHC)-con SARS-CoV-2-positive and IHC SARS-CoV-2-negative placentas (26 cases). A positive placental immunoprofile was noted in 8% of cases (n = 2), whereas 92% of cases were negative (n = 24). Women with placental infection proven by IHC had significantly different pathological findings from those without. One infected neonate was noted (n = 1; 4%). Infection was confirmed in perinatal autopsy, as there was the intrauterine fetal demise. The potential course of the infection with the risk of vertical transmission and implications for fetal–neonatal condition is critical for proper clinical management, which will involve comprehensive, multidisciplinary perinatal care for SARS-CoV-2-positive patients.

The rate of cesarean sections (CS) around the world is increasing at an 'alarming' rate. In Poland the rate of CS is 43.85%. Increasing CS rates are associated with short-term and long-term maternal and perinatal consequences. Previous CS increases the risk of cesarean scar pregnancy (CSP), placenta previa, placenta accreta spectrum (PAS) disorders and a uterine rupture. According to the theory of professor Ilan Timor-Tritsch, placenta previa accreta in a woman after previous CS is a consequence of continuation of CSP that was not recognized or not treated in the first trimester.