The coronal incision is a useful approach to the upper and middle thirds of the facial skeleton, but injury of the frontal branch of the facial nerve can be possible. The authors experienced 56 cases from 31 patients in which trauma to the temporal fat pad and the facial nerve was avoided by dissecting beneath the deep layer of the deep temporal fascia during temporal dissection in subperiosteal face lift, frontofacial monobloc advancement, Le Fort III osteotomy, and open reduction of zygomatic arch fracture. The advantages of this approach include avoiding injury to the facial nerve and minimal bleeding, thereby allowing for an easy and more rapid procedure. Furthermore, there was no development of postoperative temporal depression. This approach is particularly useful for subperiosteal face lifts, procedures requiring exposure of the zygomatic arch, or procedures requiring access to the mid face.
Adipose Tissue* ; Depression ; Facial Nerve ; Fascia ; Hemorrhage ; Humans ; Osteotomy ; Rhytidoplasty ; Skeleton ; Zygoma

Objective: Commonly, brain temperature is estimated from measurements of body temperature. However, temperature difference between brain and body is still controversy.The objective of this study is to know temperature gradient between the brain and axilla according to body temperature in the patient with brain injury. Methods: A total of 135 patients who had undergone cranial operation and had the thermal diffusion flow meter (TDF) insert were included in this analysis. The brain and axilla temperatures were measured simultaneously every 2 hours with TDF (2 kinds of devices:SABER 2000 and Hemedex) and a mercury thermometer. Saved data were divided into 3 groups according to axillary temperature. Three groups are hypothermia group (less than 36.4°C), normothermia group (between 36.5°C and 37.5°C), and hyperthermia group (more than 37.6°C). Results: The temperature difference between brain temperature and axillary temperature was 0.93±0.50°C in all data pairs, whereas it was 1.28±0.56°C in hypothermia, 0.87±0.43°C in normothermia, and 0.71±0.41°C in hyperthermia. The temperature difference was statistically significant between the hypothermia and normothermia groups (p=0.000), but not between the normothermia and hyperthermia group (p=0.201). Conclusion This study show that brain temperature is significantly higher than the axillary temperature and hypothermia therapy is associated with large brain-axilla temperature gradients. If you do not have a special brain temperature measuring device, the results of this study will help predict brain temperature by measuring axillary temperature.

Objectives: Although medical artificial intelligence (AI) systems that assist healthcare professionals in critical care settings are expected to improve healthcare, skepticism exists regarding whether their potential has been fully actualized. Therefore, we aimed to conduct a qualitative study with physicians and nurses to understand their needs, expectations, and concerns regarding medical AI; explore their expected responses to recommendations by medical AI that contradicted their judgments; and derive strategies to implement medical AI in practice successfully. Methods: Semi-structured interviews were conducted with 15 healthcare professionals working in the emergency room and intensive care unit in a tertiary teaching hospital in Seoul. The data were interpreted using summative content analysis. In total, 26 medical AI topics were extracted from the interviews. Eight were related to treatment recommendation, seven were related to diagnosis prediction, and seven were related to process improvement. Results: While the participants expressed expectations that medical AI could enhance their patients’ outcomes, increase work efficiency, and reduce hospital operating costs, they also mentioned concerns regarding distortions in the workflow, deskilling, alert fatigue, and unsophisticated algorithms. If medical AI decisions contradicted their judgment, most participants would consult other medical staff and thereafter reconsider their initial judgment. Conclusions Healthcare professionals wanted to use medical AI in practice and emphasized that artificial intelligence systems should be trustworthy from the standpoint of healthcare professionals. They also highlighted the importance of alert fatigue management and the integration of AI systems into the workflow.

Lance-Adams syndrome (LAS) is a rare neurological disorder that may occur after cardiopulmonary resuscitation. The LAS is usually caused by hypoxic changes.Neuroimaging studies show that the brain pathology of LAS patients is not uniform, and the pathophysiology of the myoclonus can vary from patient to patient. Our case study contributes to this etiological heterogeneity by neuroimaging and transcranial magnetic stimulation (TMS). In patients with rare brain conditions such as LAS, a combination of brain stimulation methods, such as TMS, and diffusion tensor imaging can provide insights into this condition's pathophysiology. These insights can facilitate the development of more effective therapies.