Articles: cations.
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The microlesion effect refers to the improvement of clinical symptoms after deep brain stimulation (DBS) lead placement and is suggested to indicate optimal lead placement. Very few studies have reported its implications in neuropsychiatric disorders. ⋯ This study shows that the microlesion effect may seem as an immediate improvement after optimal DBS lead placement in patients with Tourette syndrome.
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Observational Study
Carle's obstetric early warning score as a screening tool for critical care admission.
Early warning systems (EWS) involve serial observations (track) with criteria (trigger) to timely identify patients at risk of complications. Carle designed a statistically based clinically modified obstetric early warning score (Carle's OEWS). This study evaluated Carle's OEWS and its individual components for predicting admission to the obstetric critical care unit (OCCU). Maternal near-miss and maternal mortality were the secondary outcomes. ⋯ Carle's OEWS is a useful screening tool for predicting obstetric OCCU admission and can be routinely used in labour wards to ensure timely intervention.
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Semin Respir Crit Care Med · Oct 2023
Blood Gas Transport: Implications for O2 and CO2 Exchange in Lungs and Tissues.
The well-known ways in which O2 and CO2 (and other gases) are carried in the blood were presented in the preceding chapter. However, what the many available texts about O2 and CO2 transport do not emphasize is why knowing how gases are carried in blood matters, and this second, companion, article specifically addresses that critical aspect of gas exchange physiology. ⋯ Dissociation curve shape and slope differences explain most of the differences between O2 and CO2 in both diffusive exchange in the lungs and tissues and convective exchange/transport in, and between, the lungs and tissues. In fact, each of the chapters in this volume describes physiological behavior that depends more or less directly on the dissociation curves of O2 and CO2.
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J. Cardiothorac. Vasc. Anesth. · Oct 2023
CommentCon: Artificial Intelligence-Derived Algorithms to Guide Perioperative Blood Management Decision Making.
Artificial intelligence has the potential to improve the care that is given to patients; however, the predictive models created are only as good as the base data used in their design. Perioperative blood management presents a complex clinical conundrum in which significant variability and the unstructured nature of the required data make it difficult to develop precise prediction models. ⋯ Current systems created to predict perioperative blood transfusion are not generalizable across clinical settings, and there is a considerable cost implication required to research and develop artificial intelligence systems that would disadvantage resource-poor health systems. In addition, a lack of strong regulation currently means it is difficult to prevent bias.