{"title":"[Weaning of Long-term ICU Patients: Potential of Physical Therapy].","authors":"Frieder Kiefer","doi":"10.1055/a-2539-8670","DOIUrl":"10.1055/a-2539-8670","url":null,"abstract":"<p><strong>Abstract: </strong>Physiotherapy plays an important role in intensive care medicine in restoring mobility, flexibility, coordination, and quality of life. But the data regarding its use in the weaning of long-term patients are inconsistent and provide little basis for structured approaches. There are no clear data on therapy volume, frequency, or stop signals, which makes it difficult to create structured weaning guidelines.Based on recent literature, aspects of physiotherapy that can be applied to ICU patients are explored and it is underlined that physiotherapy can be regarded as safe and efficient, yet quite unstructured. Furthermore, rational outcome expectations and parameters are discussed based on recent evidence.The article outlines how modern therapy and weaning concepts can be designed and why future research should focus on determining the correct therapy volume for different patient groups. Readers learn why integrating interdisciplinary teams with knowledge from sports and nutrition medicine makes sense and how this approach can help long-term patients.</p>","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 5","pages":"336-342"},"PeriodicalIF":0.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147978407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[Anesthesiological Concepts in Pediatric Oral and Maxillofacial Surgery].","authors":"Judith-Elisabeth Riemer, Tobias Piegeler","doi":"10.1055/a-2719-4280","DOIUrl":"10.1055/a-2719-4280","url":null,"abstract":"<p><strong>Abstract: </strong>Anesthesiological care in pediatric oral and maxillofacial (OMF) surgery is challenging due to the proximity of the surgical field to the airway, a high prevalence of craniofacial malformations, and a high frequency of associated syndromal conditions. This review outlines current perioperative strategies for managing complex cases, such as cleft lip and palate repair and craniosynostosis correction. A comprehensive evaluation of clinical practices and current guidelines, including the 2024 ESAIC airway management recommendations and the 2024 German S3-guideline on cleft lip and palate, was conducted to highlight essential safety protocols and common pitfalls. Preoperative evaluation should focus on identifying obstructive sleep apnea syndrome (OSAS), which affects 3-5% of children and significantly increases the risk of respiratory complications. Specialized syndromes like the Pierre-Robin-sequence or the Treacher-Collins syndrome often present with difficult airways requiring advanced techniques such as video laryngoscopy or fiberoptic intubation. For craniosynostosis repair, high-risk interventions necessitate patient blood management (PBM), including the use of tranexamic acid, cell salvage, and point-of-care viscoelastic coagulation monitoring to manage substantial blood loss. Effective pain management relies on multimodal concepts, integrating regional anesthesia (e.g., infraorbital nerve blocks) to reduce opioid consumption and the associated risk of respiratory depression. In summary, pediatric OMF surgery cases require specialized expertise, standardized algorithms for the difficult airway, and meticulous postoperative monitoring. High-risk patients should be treated in specialized centers with appropriate pediatric anesthetic infrastructure to minimize perioperative morbidity.</p>","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 5","pages":"322-335"},"PeriodicalIF":0.7,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147978414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Masoud Dehbozorgi, Nelly Zental, Jan Larmann, Linda Grüßer
{"title":"[AI Algorithms - Intraoperative Hemodynamic Monitoring of Tomorrow?]","authors":"Masoud Dehbozorgi, Nelly Zental, Jan Larmann, Linda Grüßer","doi":"10.1055/a-2617-6321","DOIUrl":"10.1055/a-2617-6321","url":null,"abstract":"<p><strong>Abstract: </strong>This article provides an overview of basic concepts of artificial intelligence (AI), AI-based approaches in intraoperative hemodynamic monitoring and management, their potential benefits and limitations, and possible future directions. AI is rapidly transforming perioperative medicine through the analysis of the large volumes of data generated during surgery. Intraoperative hypotension is associated with postoperative complications and organ injury, yet current management remains mostly reactive, with interventions typically initiated only after hypotension occurs. AI-based predictive tools are designed to enable anesthesiologists to act proactively before hypotension develops.Algorithms such as the Hypotension Prediction Index (HPI) analyze high-resolution arterial pressure waveforms and other physiological signals to identify patterns indicating imminent hypotensive events. First clinical studies in both cardiac and non-cardiac surgery suggest that AI-guided support can reduce the depth and duration of hypotensive episodes, although larger multicenter trials are needed to determine effects on patient outcomes.Beyond hypotension prediction, AI has potential in optimizing blood pressure measurement, supporting echocardiographic image interpretation, and classifying patients according to hemodynamic phenotypes to guide individualized therapy. Challenges to clinical implementation include data privacy and regulatory requirements, algorithmic bias, explainability, the risk of overreliance on automated recommendations and data-related challenges in model training and validation.Currently, AI does not replace clinical expertise but may complement intraoperative decision-making. Predictive models may allow earlier recognition of patients at risk of hypotension and thereby support a more anticipatory approach to hemodynamic management. The extent to which this translates into measurable clinical benefit requires further investigation.</p>","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 4","pages":"239-249"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147731152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[From Goal-Directed Therapy to Personalized Hemodynamic Management].","authors":"Peter Wichmann, Sebastian Haas, Daniel Reuter","doi":"10.1055/a-2617-5579","DOIUrl":"10.1055/a-2617-5579","url":null,"abstract":"<p><strong>Abstract: </strong>The article describes the transition from traditional goal-directed therapy (GDT) to personalized hemodynamic management in the perioperative setting. The primary objective of hemodynamic optimization is to ensure adequate tissue oxygenation, determined by arterial oxygen content and cardiac output. The latter is mainly influenced by preload, afterload, and myocardial contractility. Static preload parameters such as central venous pressure have limited predictive value for fluid responsiveness, whereas dynamic indices (SVV, PPV) may provide superior guidance under specific conditions.Large randomized trials (e.g., OPTIMISE, iPEGASUS) failed to demonstrate consistent outcome benefits of standardized algorithms targeting fixed hemodynamic thresholds. In contrast, personalized hemodynamic management aims to define individual target values-such as mean arterial pressure or cardiac index-based on patient-specific risk factors and comorbidities. Some studies (e.g., INPRESS, TAPIR) suggest potential advantages of individualized strategies, whereas others (IMPROVE) did not confirm significant differences in major outcomes.Current guidelines recommend advanced hemodynamic monitoring in high-risk patients but do not define universal target values. A cardiac index-guided, individualized approach integrating clinical and metabolic indicators appears promising. However, rigid algorithm application and indiscriminate inotrope use should be avoided. Clinical judgment remains essential for delivering safe, patient-centered perioperative care.</p>","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 4","pages":"226-237"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147731162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[Pros/Cons: Airway Management for Separate-side Ventilation: Always Use a Video Laryngoscope?]","authors":"Marc Kriege, Jérôme Michel Defosse","doi":"10.1055/a-2595-3203","DOIUrl":"10.1055/a-2595-3203","url":null,"abstract":"<p><strong>Abstract: </strong>The optimal technique for airway management during intubation with a double-lumen tube (DLT) in thoracic anesthesia remains unclear. While efforts are now being made to use a video laryngoscope for routine use with single-lumen tubes, its use with DLTs remains a topic of debate. This article presents an analysis from two perspectives in the style of a debate, in this case with a slight wink as a plea in court, comparing video laryngoscopy (VL) with direct laryngoscopy (DL) for routine use. The \"defense position\" highlights evidence demonstrating improved visibility of the glottis, higher success rates on the first attempt, less mucosal trauma, lower DLT misplacement rates, and educational advantages associated with VL, especially when using Macintosh blades. In contrast, the \"prosecution\" emphasizes the limitations of VL, including longer intubation times, difficulty advancing the DLT due to anatomical conditions and the rigidity of the DLT, increased misplacement rates in certain studies, variability between VL devices, and the potential for dental injuries associated with certain blades. A comprehensive evaluation of randomized trials, meta-analyses, and observational studies shows that while VL offers clear advantages in difficult airway situations, DL can provide faster and more reliable results under routine conditions. This comparison is intended to encourage critical evaluation of the current evidence and support informed clinical decision-making regarding the standard of care in thoracic anesthesia.</p>","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 4","pages":"267-274"},"PeriodicalIF":0.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147731163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"[\"The Art of Judgment Lies in Knowing What to Ignore\"].","authors":"Berthold Bein, Jens Scholz","doi":"10.1055/a-2808-1672","DOIUrl":"https://doi.org/10.1055/a-2808-1672","url":null,"abstract":"","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 3","pages":"161-162"},"PeriodicalIF":0.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147505986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthias Heringlake, Simon Schemke, Lennart H Muras
{"title":"[Artificial Intelligence in Anesthesiology - Focus on Hemodynamics].","authors":"Matthias Heringlake, Simon Schemke, Lennart H Muras","doi":"10.1055/a-2683-2991","DOIUrl":"10.1055/a-2683-2991","url":null,"abstract":"<p><p>Artificial intelligence (AI) is increasingly finding its way into anesthesiology and intensive care medicine. In the context of hemodynamic assessment, the analysis of arterial blood pressure waveforms for the prediction of impending hypotension represents a prototypical application. Targeted use of such approaches has indeed been shown to reduce the severity and duration of hypotensive episodes. However, definitive evidence demonstrating a reduction in morbidity and mortality is still lacking and remains the subject of ongoing debate. Beyond this application, multiple additional potentially meaningful applications for AI in this field can be envisioned; however, most of these are still in early stages of development or evaluation. From the authors' perspective, a major limitation to the implementation of AI in anesthesiology and intensive care medicine is likely to be less the technology itself than the human factor. Clinicians must not only continuously monitor the validity of AI-generated information but also adapt their workflows to the requirements of modern technology. In addition, the currently unresolved issue of liability in the context of AI-assisted decision-making must be addressed and clarified in a legally robust manner through appropriate legislation.</p>","PeriodicalId":520554,"journal":{"name":"Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie : AINS","volume":"61 3","pages":"163-171"},"PeriodicalIF":0.7,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147505976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}