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Objective: The study was aimed at comparing intrapartum and postpartum outcomes between pregnant patients with and without antenatal COVID‐19 infection using aggregated, deidentified electronic health record (EHR) data. Design and Setting: This retrospective cohort study included data from over 80 health care organizations within the TriNetX Analytics Research Network. Population: Individuals admitted for delivery from Jan 2020 to May 2023 were studied. Methods: We studied individuals with ICD‐10 codes for delivery, COVID‐19 diagnosis, and primary outcomes. We compared the incidence of adverse intrapartum and 30‐day postpartum outcomes in those with and without antenatal COVID‐19. Main Outcome Measures: The main outcomes compared were obstetric, cardiovascular, neurovascular, and respiratory outcomes within 30 days postpartum. Results: Twenty‐six thousand nine hundred seventy‐four of 369,923 (7%) birthing parents with a delivery encounter had an antenatal COVID‐19 diagnosis. Compared to matched controls, having COVID‐19 was associated with an increased risk of postpartum hemorrhage (RR—1.24 (CI—1.16–1.33)), gestational hypertension (RR—1.27 (CI—1.27–1.34)), preeclampsia (RR—1.25 (CI—1.18–1.32)), eclampsia (RR—1.66 (CI—1.29–2.32)), preterm labor (RR—1.21 (CI—1.21–1.34)), cerebral infarction (RR—1.74 (CI—1.04–2.90)), cardiomyopathy (RR—2.08 (CI—1.30–3.32)), heart failure (RR—1.55 (CI—1.04–2.31)), sepsis (RR—2.21 (CI—1.54–3.19)), DVT (RR—2.32 (CI—1.45–3.71)), and pulmonary embolism (RR—2.68 (CI—1.74–2.90)). Conclusion: Individuals with antenatal COVID‐19 were more likely to have intrapartum and postpartum obstetric, cardiovascular, neurovascular, and respiratory complications. This data will inform risk stratification and screening for prenatal care providers. [ABSTRACT FROM AUTHOR]

In this paper, we present a simple spreadsheet based simulation activity that can be performed by students at the undergraduate level. This simulation is implemented in free open source software (FOSS) LibreOffice Calc, which is available for both Windows and Linux platform. This activity aims at building the probability distribution for the possible macro-states of a system. This has been achieved by randomly sampling the configuration space consisting of all the possible microstates and determining the corresponding macrostate for each of the samples, which is akin to Monte-Carlo simulation. This simulation could act as a very useful tool in engaging students for learning the concepts of microstates, macrostates and steady state equilibrium, once the ideas have been introduced in the classroom. Further, the effect of the number of particles on the quality of steady state equilibrium achieved demonstrates the idea of thermodynamic limit. [ABSTRACT FROM AUTHOR]