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Introduction: Sickle cell disease is an uncommon cause of anemia and jaundice during pregnancy. However, SCD is expected in Maharashtra, especially the Vidarbha region. SCD in pregnancy can cause various maternal and fetal complications. This study was conducted to know maternal and fetal outcomes in pregnancy with sickle cell disease in the third trimester. Methodology: This retrospective data were collected from hospital records of medical colleges located in central India for one and a half years, from November 2019 to January 2021. Forty-two women were admitted with pregnancy with sickle cell disease in the third trimester during the study period. The baseline characteristics, frequency of sickle hemoglobin variants, and maternal and fetal pregnancy outcomes were collected. Results: Compiled data were analyzed by simple descriptive statistics and frequency tables. Majority were primigravida (59.52%). Type of sickle cell was determined based on HB electrophoresis; out of 42 patients, 36 had AS pattern, 5 had SS pattern SCD, and 1 had As+b thal minor. The most common medical complication was anemia [73.80%] and UTI 26.19%. The most common adverse obstetric outcomes observed were IUGR/Oligohydramnios 42.85% and pre-eclampsia 21.42%. Majority of patients delivered by LSCS 42.85%. An adverse outcome in the fetus was fetal distress 45.23% and meconium-stained amniotic fluid 42.86%. Discussion: Due to hematological changes, extra demands, and sickle crisis, complications in both mother and fetus are more common in sickle cell anemia. Conclusions: Early detection and management of sickle cell anemia during pregnancy can reduce the adverse outcome in both mother and baby.

BackgroundStriking similarities have been found between coronavirus disease 2019 (COVID-19) and anti-melanoma differentiation-associated gene 5 (MDA5) antibody (Ab)-related dermatomyositis, implying a shared autoinflammatory aberrance. Herein, we aim to investigate whether the anti-MDA5 Ab is present in COVID-19 and correlates with the severity and adverse outcome of COVID-19 patients.Methods and FindingsWe retrospectively recruited 274 adult inpatients with COVID-19 in this study, including 48, 164, and 62 cases of deaths, severe, and non-severe patients respectively. The anti-MDA5 Ab was determined by ELISA and verified by Western Blotting, which indicated that the positive rate of anti-MDA5 Ab in COVID-19 patients was 48.2% (132/274). The clinical and laboratory features, as well as outcomes between patients with positive and negative anti-MDA5 Ab were compared and we found that the anti-MDA5 Ab positive patients tended to represent severe disease (88.6% vs 66.9%, P<0.0001). We also demonstrated that the titer of anti-MDA5 Ab was significantly elevated in the non-survivals (5.95 ± 5.16 vs 8.22 ± 6.64, P=0.030) and the positive rate was also higher than that in the survivals (23.5% vs 12.0%, P=0.012). Regarding severe COVID-19 patients, we found that high titer of anti-MDA5 Ab (≥10.0 U/mL) was more prevalent in the non-survivals (31.2% vs 14.0%, P=0.006). Moreover, a dynamic analysis of anti-MDA5 Ab was conducted at different time-points of COVID-19, which revealed that early profiling of anti-MDA5 Ab could distinguish severe patients from those with non-severe ones.ConclusionsAnti-MDA5 Ab was prevalent in the COVID-19 patients and high titer of this antibody is correlated with severe disease and unfavorable outcomes.

Abstract Background: To establish the ability of shock index and the different vital signs to predict the adverse maternal outcomes in the cases of obstetric hemorrhage . Methods: This prospective - retrospective study comprised patients with primary PPH or hemorrhage due to obstetric cause who were referred to zagazig University hospital Egypt , from January 2018, to December 2019 Data of vital signs of them ; systolic and diastolic blood pressure, pulse rate, pulse pressure, mean arterial pressure and shock index (heart rate divided by systolic blood pressure) at time of arrival were investigated . Adverse outcome like ,death , admission to the intensive care unit , massive transfusion and invasive procedures were revised and analyzed. AUROC (area under the receiver operating characteristic curve ) was used for shock index in comparison to each vital sign for predicting the adverse maternal outcomes. Sensitivity, specificity, and negative and positive predictive values were assessed to detect the best predictor.Results: The mean age of participants years (SD)was 29.2 ( ±7.3) of admission and 44% had altered. The most Common cause of hemorrhage was Iatrogenic ; either misuse of uterotonic or traumatic 30.2% The mean value of HR 108.1±26.6 , SBP 101± 28.7 mmHg , DBP 58.9±21.3 mmHg , SI 1.153±0.541 and mean blood loss 1922 (0.862) .For death, SI and SBP had the highest AUC value at 0.88 (0.81–0.95) with P=0.213). For ICU blood transfusion ≥ 5iu , admission and invasive surgical interventions, SI had the uppermost AUROC value at 0.76, 0.78 and 0.61. Sensitivity for all adverse outcomes of SI ≥ 0.7,is h from 99 to 90.0 . For death prediction SI≥ 0.7 had very low specificity ;0.6{0.2-1.3}and of SI ≥ 0.9 ;6.4{2.8-7.1}Conclusion: Shock index is a strapping applicable predictor of adverse outcomes. for patients who suffering from hypovolemic shock due to obstetric hemorrhage,

Background: The chemical part of the exposome, including drugs, may explain the increase of health effects with outcomes such as infertility, allergies, metabolic disorders, which cannot be only explained by the genetic changes. To better understand how drug exposure can impact human health, the concepts of adverse outcome pathways (AOPs) and AOP networks (AONs), which are representations of causally linked events at different biological levels leading to adverse health, could be used for drug safety assessment.Methods: To explore the action of drugs across multiple scales of the biological organization, we investigated the use of a network-based approach in the known AOP space. Considering the drugs and their associations to biological events, such as molecular initiating event and key event, a bipartite network was developed. This bipartite network was projected into a monopartite network capturing the event–event linkages. Nevertheless, such transformation of a bipartite network to a monopartite network had a huge risk of information loss. A way to solve this problem is to quantify the network reduction. We calculated two scoring systems, one measuring the uncertainty and a second one describing the loss of coverage on the developed event–event network to better investigate events from AOPs linked to drugs.Results: This AON analysis allowed us to identify biological events that are highly connected to drugs, such as events involving nuclear receptors (ER, AR, and PXR/SXR). Furthermore, we observed that the number of events involved in a linkage pattern with drugs is a key factor that influences information loss during monopartite network projection. Such scores have the potential to quantify the uncertainty of an event involved in an AON, and could be valuable for the weight of evidence assessment of AOPs. A case study related to infertility, more specifically to “decrease, male agenital distance” is presented.Conclusion: This study highlights that computational approaches based on network science may help to understand the complexity of drug health effects, with the aim to support drug safety assessment.