Fetal heart rate (FHR) deceleration is the most common change seen during labor. The role of the autonomic nervous system in regulating the fetal cardiovascular response during multiple uterine contractions has been well-established. However, the mechanism underlying the hemodynamic response remains unclear and the specific reflex that mediates the cardiovascular modifications is still controversial. This study aimed to determine the role of the sympathetic and parasympathetic systems on fetal hemodynamics in complete cord occlusion. Chronically instrumented fetal sheep were randomized to receive an intravenous injection of atropine 2.5 mg (n = 8), propranolol 5 mg (n = 7), atropine and propranolol (n = 7), or a control protocol (n = 9), followed by three episodes of 1-minute umbilical cord occlusion repeated every 5 minutes. Cord compression induces a rapid decrease in the FHR and a rapid increase in MAP. The decrease in FHR is caused by an increase in parasympathetic activity, (atropine and atropine-propranolol abolish the FHR response to the occlusion). The change in FHR during occlusion was not modified by propranolol injection, showing no effect of sympathetic tone. The increase in MAP during occlusion was similar in the four protocols. After releasing occlusion, the FHR was still lower than that at baseline due to a sustained parasympathetic tone. Suppression of the parasympathetic output to the cardiovascular system unmasks an increase in the FHR above baseline values. The lower FHR with the propranolol protocol further supports an increase in myocardial β-adrenoceptor stimulation after cord release. The increase in MAP after cord release was similar in the four protocols, except after the early stage of interocclusion period in atropine protocol. Four minutes after cord release, the FHR returned to baseline irrespective of the drugs that were infused, thereby showing recovery of ANS control. Blood gases (pH, PaCO2, PaO2) and plasma lactate concentrations was similar between the four protocols at the end of three applications of UCO. Complete cord compression-induced deceleration is likely due to acute activation of parasympathetic output. β-adrenoceptor activity is involved in the increase in FHR after cord release. Understanding the reflexes involved in FHR deceleration may help us understand the mechanisms underlying fetal autonomic adaptation during cord occlusion.
Although paper-based transmission of medical information might seem outdated, it has proven efficient, and remains structurally safe from massive data leaks. As part of the ICIPEMIR project for improving medical imaging report, we explored the idea of structured data storage within a medical report, by embedding the data themselves in a QR-Code (and no URL-to-the-data). Three different datasets from ICIPEMIR were serialized, then encoded in a QR-Code. We compared 4 compression algorithms to reduce file size before QR-Encoding. YAML was the most concise format (character sparing), and allowed for embedding of a 2633-character serialized file within a QR-Code. The best compression rate was obtained with gzip, with a compression ratio of 2.32 in 15.7ms. Data were easily extracted and decompressed from a digital QR-Code using a simple command line. YAML file was also successfully recovered from the printed QR-Code with both Android and iOS smartphone. Minimal detected size was 3*3cm.
Introduction: Although electronic health records have been facilitating the management of medical information, there is still room for improvement in daily production of medical report. Possible areas for improvement would be: to improve reports quality (by increasing exhaustivity), to improve patients’ understanding (by mean of a graphical display), to save physicians’ time (by helping reports writing), and to improve sharing and storage (by enhancing interoperability). We set up the ICIPEMIR project (Improving the completeness, interoperability and patients explanation of medical imaging reports) as an academic solution to optimize medical imaging reports production. Such a project requires two layers: one engineering layer to build the automation process, and a second medical layer to determine domain-specific data models for each type of report. We describe here the medical layer of this project. Methods: We designed a reproducible methodology to identify -for a given medical imaging exam- mandatory fields, and describe a corresponding simple data model using validated formats. The mandatory fields had to meet legal requirements, domain-specific guidelines, and results of a bibliographic review on clinical studies. An UML representation, a JSON Schema, and a YAML instance dataset were defined. Based on this data model a form was created using Goupile, an open source eCRF script-based editor. In addition, a graphical display was designed and mapped with the data model, as well as a text template to automatically produce a free-text report. Finally, the YAML instance was encoded in a QR-Code to allow offline paper-based transmission of structured data. Results: We tested this methodology in a specific domain: computed tomography for urolithiasis. We successfully extracted 73 fields, and transformed them into a simple data model, with mapping to a simple graphical display, and textual report template. The offline QR-code transmission of a 2,615 characters YAML file was successful with simple smartphone QR-Code scanner. Conclusion: Although automated production of medical report requires domain-specific data model and mapping, these can be defined using a reproducible methodology. Hopefully this proof of concept will lead to a computer solution to optimize medical imaging reports, driven by academic research.
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