The clinical features of Schönlein-Henoch Purpura (SHP) consist of non-thrombocytopenic purpura in association with joint, gastrointestinal and renal involvements. Because it is uncommon in adults, there is little information on the effects of SHP on pregnancy in the literature. This report documents the clinical findings and outcome of an uncommon case of SHP affecting a woman who was 25 weeks pregnant. Prompt steroid-therapy induced a rapidly favorable course and successful vaginal delivery at 40 weeks gestation. If SHP develops during pregnancy, it is not always easy to distinguish from obstetrical complications such as pre-eclampsia. An early diagnosis is important especially if renal involvement exists, because the prognosis for this disease can include nephropathy and it therefore needs close monitoring.
Abstract. The objective of this study was to ascertain the evidence on ovarian cancer during pregnancy and compile recommendations derived from this information. This was a retrospective study, based on clinical histories from patients diagnosed and treated at 4 independent hospitals for ovarian cancer during pregnancy, between 1992 and 2009. The median age at diagnosis was 30 years (range, 24-41). Out of 10 cases of ovarian cancer, 2 patients showed either bleeding or abdominal pain, while 8 patients were asymptomatic. All 10 cases were diagnosed via ultrasound, and the masses were detected in the first trimester in 7 patients and in the second trimester in 2 patients. Of the diagnosed tumors, 8 cases were epithelial tumors including 6 adenocarcinomas and 2 borderline tumors, and 2 germ cell tumors. The primary ovarian malignancies were at stage I of the disease. Unilateral salpingo-oophorectomy was performed in 9 patients and cystectomy was performed in one patient. Chemotherapy was administered to 4 patients, in 1 case during pregnancy. Neonatal outcome analysis showed a full-or pre-term delivery in 6 cases, abortion in 1 case and therapeutic termination in 3 cases. The majority of cases of ovarian cancer in pregnancy were incidentally detected by ultrasound at an early stage, resulting in good prognosis for the mother and the neonate.
Abstract. To investigate endocrine responses of isolated premature goat fetuses during long-term extrauterine incubation with umbilical arteriovenous extracorporeal membrane oxygenation (A-V ECMO), we conducted experiments in seven goat fetuses (95-134 days gestation). The fetuses were cannulated from the umbilical vessels, and their blood-gas exchange was totally supported by A-V ECMO, while they were maintained in an isothermal incubator containing artificial amniotic fluid. The survival period was between 84 and 190 h. At 24-h intervals, fetal blood samples were collected, and plasma concentrations of catecholamines, ACTH, and cortisol were determined. After 24 h of incubation, fetal circulatory and respiratory variables remained stable, until evident circulatory failure occurred before their deaths.A similar pattern was observed in temporal changes in plasma concentrations of catecholamines, ACTH, and cortisol. Plasma levels were high during the initial 24 h of incubation, subsequently decreased, and then increased before death. Hormone levels during stable periods were equivalent to or slightly higher than values for fetuses in utero. These results suggest that conditions during the stable period of long-term extracorporeal fetal incubation are not highly stressful for the isolated fetuses.
Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-based diagnosis in patients with uterine sarcomas. Fifteen sequences of MRI for patients (uterine sarcoma group: n = 63; uterine leiomyoma: n = 200) were used to train the models. Six radiologists (three specialists, three practitioners) interpreted the same images for validation. The most important individual sequences for diagnosis were axial T2-weighted imaging (T2WI), sagittal T2WI, and diffusion-weighted imaging. These sequences also represented the most accurate combination (accuracy: 91.3%), achieving diagnostic ability comparable to that of specialists (accuracy: 88.3%) and superior to that of practitioners (accuracy: 80.1%). Moreover, radiologists’ diagnostic accuracy improved when provided with DNN results (specialists: 89.6%; practitioners: 92.3%). Our DNN models are valuable to improve diagnostic accuracy, especially in filling the gap of clinical skills between interpreters. This method can be a universal model for the use of deep learning in the diagnostic imaging of rare tumors.
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