A case series detailing the successful reversal of the effects of mifepristone using progesterone.

BACKGROUND: Some women who take mifepristone, a progesterone receptor antagonist, in order to terminate their pregnancies, change their minds and desire to stop the medical abortion process. There are only two articles in the medical literature documenting the reversal of the effects of mifepristone. OBJECTIVE: We present and analyze a series of women who attempted to reverse the effects of mifepristone by taking supplemental progesterone to determine if the reversal of the effects mifepristone with progesterone is possible and safe. Additionally, we compare different progesterone regimens to determine relative efficacies. METHODS: This is an observational case series of 754 patients who decided to attempt to reverse the medical abortion process after taking mifepristone but before taking the second drug in the protocol, misoprostol. We followed the patients, who were given progesterone in an effort to reverse the effects of mifepristone, and conducted statistical analyses to determine the efficacies of different protocols compared to a control mifepristone embryo survival rate, derived from the literature. RESULTS: Intramuscular progesterone and high dose oral progesterone were the most effective with reversal rates of 64% (P < 0.001) and 68% (P < 0.001), respectively. There was no apparent increased risk of birth defects. Conclusions: The reversal of the effects of mifepristone using progesterone is safe and effective.

An interoperable system for automated diagnosis of cardiac abnormalities from electrocardiogram data.

Electrocardiogram (ECG) data are stored and analyzed in different formats, devices, and computer platforms. As a result, ECG data from different monitoring devices cannot be displayed unless the user has access to the proprietary software of each particular device. This research describes an ontology and encoding for representation of ECG data that allows open exchange and display of ECG data in a web browser. The ontology is based on the Health Level Seven (HL7) medical device communication standard. It integrates ECG waveform data, HL7 standard ECG data descriptions, and cardiac diagnosis rules, providing a capability to both represent ECG waveforms as well as perform automated diagnosis of 37 different cardiac abnormalities. The ECG ontology is encoded in XML, thus allowing ECG data from any digital ECG device that maps to it to be displayed in a general-purpose Internet browser. An experiment was conducted to test the interoperability of the system (ability to openly share ECG data without error in a web browser) and also to assess the accuracy of the diagnosis model. Results showed 100% interoperability using 276 ECG data files and 93% accuracy in diagnosis of abnormal cardiac conditions.