Anästhesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS
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Anasthesiol Intensivmed Notfallmed Schmerzther · Apr 2022
[Practice-guided Presentation of the German S3 Guideline "Strategies to Warrant Rational In-hospital Use of Antibiotics"].
The current S3 guideline entitled "Strategies to warrant rational in-hospital use of antibiotics" summarizes evidence-based antibiotic stewardship (ABS) measures that aim to improve clinical outcomes and prevent development and spread of microbial resistance in German hospitals. Most important prerequisite for efficiency and safety of ABS programs is sufficient staffing capacity as well as reliably operating surveillance of (i) pathogens, (ii) antimicrobial resistance and (iii) consumption of antimicrobials. ⋯ Clinicians should be regularly granted access to in-hospital training programs delivered by ABS experts. Finally yet importantly, the current S3 guideline also highlights future goals, e.g., the structured involvement for nurses in ABS-guided infection management or the promotion of ABS programs in the outpatient sector and in veterinary medicine.
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Anasthesiol Intensivmed Notfallmed Schmerzther · Apr 2022
[Hemodynamic Monitoring 2.0 - What is Possible on Normal Wards?]
Life threatening events after surgery often occur on the ward. These events could be prevented by early detection of clinical deterioration of patients' health status during ward care. Therefore, an adequate monitoring could help to identify patients at risk, since there is an imbalance of monitoring intensity and the occurrence of life-threatening events during hospital stay. ⋯ Future trends of developing wireless monitoring systems are of paramount importance in this respect. Controlling artefacts is crucial for the successful balance between false alarms and "missed events". An adequate reaction is needed when detecting adverse events to avoid a "failure to rescue".
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Anasthesiol Intensivmed Notfallmed Schmerzther · Mar 2022
Review[Usage of Artificial Intelligence in the Combat against the COVID-19 Pandemic].
The COVID-19 pandemic is a global health emergency of historic dimension. In this situation, researchers worldwide wanted to help manage the pandemic by using artificial intelligence (AI). ⋯ The addressed aspects encompass AI algorithms for analysis of thoracic X-rays or CTs, prediction models for severity and outcome of the disease, AI applications in development of new drugs and vaccines as well as forecasting models for spread of the virus. The review shows, which approaches were pursued, and which were successful.
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Anasthesiol Intensivmed Notfallmed Schmerzther · Mar 2022
Review[Update on Intensive Care Unit Management of Stroke].
In this review, we provide an update on the intensive care unit (ICU) management of ischemic stroke. Over the last decade, new evidence has led to rapid changes in the early management of patients admitted with acute ischemic stroke. Nevertheless, stroke remains a leading cause of disability. ⋯ The main goal in the ICU management of stroke patients is to prevent secondary brain injury. To this end, a comprehensive approach to optimize systemic physiological homeostasis, control intracranial pressure, cerebral perfusion, hemodynamic and respiratory parameters is needed. Here, we summarize recent advances in invasive and non-invasive neuro-monitoring, decision making in decompressive neurosurgery for large supratentorial or cerebellar infarction, specific cardiorespiratory management, nutrition, temperature management and mobilization strategies in ischemic stroke.
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Anasthesiol Intensivmed Notfallmed Schmerzther · Mar 2022
[Artificial Intelligence: Challenges and Applications in Intensive Care Medicine].
The high workload in intensive care medicine arises from the exponential growth of medical knowledge, the flood of data generated by the permanent and intensive monitoring of intensive care patients, and the documentation burden. Artificial intelligence (AI) is predicted to have a great impact on ICU work in the near future as it will be applicable in many areas of critical care medicine. These applications include documentation through speech recognition, predictions for decision support, algorithms for parameter optimisation and the development of personalised intensive care medicine. ⋯ Speech recognition has the potential to reduce this documentation burden. It is not yet precise enough to be usable in the clinic. The application of AI in medicine, with the help of large data sets, promises to identify diagnoses more quickly, develop individualised, precise treatments, support therapeutic decisions, use resources with maximum effectiveness and thus optimise the patient experience in the near future.