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- Magnusson, Carl, 1976, et al.
(author)
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Prehospital lactate levels in blood as a seizure biomarker : A multi-center observational study.
- 2021
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In: Epilepsia. - : Wiley. - 0013-9580 .- 1528-1167. ; 62:2, s. 408-415
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Journal article (peer-reviewed)abstract
- OBJECTIVE: The objective of this study was to assess the value of prehospital measurement of lactate level in blood for diagnosis of seizures in cases of transient loss of consciousness.METHODS: Between March 2018 and September 2019, prehospital lactate was measured with a point-of-care device by the emergency medical services in an area serving a population of 900 000. A total of 383 cases of transient loss of consciousness were identified and categorized as tonic-clonic seizure (TCS), other seizure, syncope, or other cause, according to the final diagnosis in the electronic medical records system. Receiver operating characteristic curve analyses were used to identify the optimal lactate cut-off.RESULTS: A total of 383 cases were included (135 TCS, 42 other seizure, 163 syncope, and 43 other causes). The median lactate level in TCS was 7.0 mmol/L, compared to a median of 2.0 mmol/L in all other cases (P < .001). The area under the curve (AUC) of TCS vs nonepileptic causes was 0.87 (95% confidence interval [CI] 0.83-0.91). The optimal cut-off (Youden index, 67.8%) was 4.75 mmol/L, with 79% sensitivity (95% CI 71-85) and 89% specificity (95% CI 85-93) for TCS.SIGNIFICANCE: Prehospital lactate can be a valuable tool for identifying seizures in transient loss of consciousness. For acceptable specificity, a higher cut-off than that previously demonstrated for hospital-based measurements must be used when values obtained close to the time of the event are interpreted.
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| 2. |
- Ranta, Aarne, et al.
(author)
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A Mobile Language Interpreter App for Prehospital/Emergency Care
- 2017
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In: Medicinteknikdagarna 2017.
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Conference paper (other academic/artistic)abstract
- Lack of a shared language is a common communication situation in the globalizing world. Sometimes this can be mitigated by the use of machine translation technology, such as Google translate, but there are mission-critical tasks, like in health care, where one has to be sure about the correctness of the translation. In such situations, human interpreters are the best choice, but interpreters are scarce and in urgent situations they are not always available. This calls for improved and more reliable machine translation initiatives.The project to be presented is developing a mobile translator for ambulance personnel use. The translator uses a verifiable and controllable machine translation technology, which is based on semantics, grammars, and professional terminology. The technology has been developed in the international open source project Grammatical Framework (GF) and tested in numerous research projects as well as commercial applications. This project is the first one to apply GF in a healthcare setting. The aim is to develop a platform for a range of health care applications, provided this pilot project for ambulance/emergency care is successful.The translator works as a mobile app, in which the user can speak and write questions and other phrases, and get them translated to speech and text in other languages. The phrases cover the concepts used in the SBAR protocol (Situation-Bakgrund-Aktuellt tillstånd-Rekommendation) for ambulance use, as gathered from available documents and a questionnaire sent out to professionals at SU Ambulans. The SBAR protocol is also made available as a dynamic phrasebook, where the user can select appropriate phrases from menus. To help translate spontaneous speech and writing, the translator will also have a facility of suggesting nearest-matching phrases and ranking them by proximity to the verified standard phrases.The current prototype covers around 400 concepts, from which millions of phrases can be built. It will work for 7 languages and enable translation between any two of them, although the primary use case is translation from Swedish to another language and translating simple answers from the other language to Swedish. GF has potential for extending the application to over 30 languages.
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