Acute Medicine & Surgery最新文献

{"title":"Pediatric pharyngeal foreign body with a difficult diagnosis","authors":"Hisataka Ominato,&nbsp;Tomoki Yoshizaki,&nbsp;Yui Hirata-Nozaki,&nbsp;Shota Sakaue,&nbsp;Miki Takahara","doi":"10.1002/ams2.70052","DOIUrl":"https://doi.org/10.1002/ams2.70052","url":null,"abstract":"<p>A 1-year-old boy with Down syndrome visited the emergency department of our hospital with complaints of displeasure and suspicion of pharyngeal foreign body obstruction. The parents noticed that a clothing price tag was missing at home. At the time of the initial examination, no foreign bodies were detected in the oral cavity of the patient. In addition, computed tomography did not reveal any foreign bodies (Figure 1A). The patient was referred to our department the next day. Endoscopic examination revealed a plastic foreign body at the posterior pharyngeal wall (Figure 1B). We could observe the foreign body from the oral cavity, and the foreign body was removed from the oral cavity using forceps, avoiding the huge tongue (Figure 1C).</p><p>Pharyngeal foreign body obstruction usually manifests as dysphagia, vomiting, and drooling.<span>¹</span> Typical pharyngeal foreign bodies include food, toys, balloons, and plastic bags. The patient had Down syndrome, and consequently, his enlarged tongue posed difficulties for oral observation. The foreign body was plastic and transparent, and it is difficult to see the foreign body in the emergency department. This case was characterized by the difficulty of diagnosis due to the presence of a transparent plastic foreign body and a large tongue, and there was a risk of the foreign body blocking and moving to the larynx. It was suggested that this case showed the need for early intervention by an otolaryngologist in the emergency outpatient department and the importance of performing an endoscopy as soon as possible. In addition, we should consider the possibility of performing an endoscopy before a CT scan to avoid radiation exposure.</p><p>None.</p><p>The authors declare no conflicts of interest.</p><p>Approval of the research protocol: N/A.</p><p>Informed consent: Informed consent was obtained from the patient's family.</p><p>Registry and the registration number of the study/trial: N/A.</p><p>Animal studies: N/A.</p>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of near-infrared spectroscopy in diagnosing skin and soft tissue infections: A single-center retrospective study","authors":"Marina Oi,&nbsp;Takaaki Maruhashi,&nbsp;Yasushi Asari","doi":"10.1002/ams2.70041","DOIUrl":"https://doi.org/10.1002/ams2.70041","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>Skin and soft tissue infection (SSTI) is classified as necrotizing fasciitis (NF) or cellulitis based on the invasion depth of the lesion. Cellulitis has a good prognosis and improves with conservative treatment, whereas NF has a poor prognosis with rapid progression requiring prompt debridement of the wound and intensive care control. Therefore, they should be differentiated quickly and accurately; however, a useful diagnostic method, except for the surgical test incision, remains to be established. This study aimed to verify the usefulness of near-infrared spectroscopy (NIRS) to measure regional oxygen saturation (rSO2) in diagnosing SSTI.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This was a single-center, retrospective, observational study. SSTI cases from October 2019 to April 2024 (4.5 years) were selected from medical records, and their characteristics, rSO2 levels, computed tomography findings, and Laboratory Risk Indicator for Necrotizing Fasciitis scores were collected. The primary endpoint was the rSO2 between cellulitis and NF lesions measured using NIRS, and the affected and unaffected sides in the same patient were compared.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Eighteen patients were included: six with NF and 12 with cellulitis. There were no significant differences in patient characteristics between the groups. The primary endpoint of NIRS on the affected/unaffected side was significantly lower in patients with NF (0.6 [interquartile range, 0.5–0.7] vs. 1.4 [1.2–1.6]; <i>p</i> &lt; 0.01).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>NIRS has the potential to be a non-invasive and quantitative diagnostic tool for SSTI.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical characteristics and outcomes of patients with out-of-hospital cardiac arrest treated by repeated extracorporeal cardiopulmonary resuscitation: A multicenter retrospective cohort study","authors":"Akira Suekane,&nbsp;Wataru Takayama,&nbsp;Koji Morishita,&nbsp;Akihiko Inoue,&nbsp;Toru Hifumi,&nbsp;Tetsuya Sakamoto,&nbsp;Yasuhiro Kuroda,&nbsp;the Save-J II Study Group","doi":"10.1002/ams2.70051","DOIUrl":"https://doi.org/10.1002/ams2.70051","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>Retrospective analysis of clinical characteristics and outcomes of patients with out-of-hospital cardiac arrest (OHCA) treated with extracorporeal cardiopulmonary resuscitation (ECPR) requiring extracorporeal membrane oxygenation (ECMO) reinsertion or not.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data from the Study of Advanced Life Support for Ventricular Fibrillation with Extracorporeal Circulation in the Japan II database were reviewed. Patients who received ECPR after OHCA between January 2015 and July 2021 and underwent ECPR weaning were divided into reinsertion and no-reinsertion groups. The primary outcome was the 30-day survival rate.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Data from 1011 patients who underwent ECMO weaning ≥1 time and survived were analyzed (12 [1.2%], reinsertion; 999 [98.8%] no-reinsertion). The reinsertion group had a longer time to first ECMO weaning (median [interquartile range, IQR]: 3.0 [2.0–5.0] vs. 4.5 [3.2–6.8] days; <i>p</i> = 0.02). The survival rates at 30 days (25.0% vs. 55.1%; <i>p</i> = 0.08) and favorable neurological outcomes at discharge (8.3% vs. 30.5%; <i>p</i> = 0.18) tended to be lower in the reinsertion group. Among patients who died within 30 days, medical costs were significantly higher in the reinsertion group (median [IQR]: $36,628.2 [26,012.9–45,885.6] vs. $16,456.6 [9341.2–24,880.6]; <i>p</i> &lt; 0.01). Intensive care unit (ICU) stay and mechanical ventilation duration were significantly longer in the reinsertion group.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Patients requiring ECMO reinsertion tended to have poor clinical outcomes and higher healthcare costs, highlighting the need for large-scale studies to develop ECPR protocols and optimize clinical benefits and resource allocation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical validity and layperson interpretation of emergency visit recommendations by the GPT model: A cross-sectional study","authors":"Chie Tanaka,&nbsp;Takahiro Kinoshita,&nbsp;Yohei Okada,&nbsp;Kasumi Satoh,&nbsp;Yosuke Homma,&nbsp;Kensuke Suzuki,&nbsp;Shoji Yokobori,&nbsp;Jun Oda,&nbsp;Yasuhiro Otomo,&nbsp;Takashi Tagami,&nbsp;Special Committee on the Utilization of Advanced Technology in Emergency Medicine, Japanese Association for Acute Medicine","doi":"10.1002/ams2.70042","DOIUrl":"https://doi.org/10.1002/ams2.70042","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>In Japan, emergency ambulance dispatches involve minor cases requiring outpatient services, emphasizing the need for improved public guidance regarding emergency care. This study evaluated both the medical plausibility of the GPT model in aiding laypersons to determine the need for emergency medical care and the laypersons' interpretations of its outputs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This cross-sectional study was conducted from December 10, 2023, to March 7, 2024. We input clinical scenarios into the GPT model and evaluated the need for emergency visits based on the outputs. A total of 314 scenarios were labeled with red tags (emergency, immediate emergency department [ED] visit) and 152 with green tags (less urgent). Seven medical specialists assessed the outputs' validity, and 157 laypersons interpreted them via a web-based questionnaire.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Experts reported that the GPT model accurately identified important information in 95.9% (301/314) of red-tagged scenarios and recommended immediate ED visits in 96.5% (303/314). However, only 43.0% (135/314) of laypersons interpreted those outputs as indicating urgent hospital visits. The model identified important information in 99.3% (151/152) of green-tagged scenarios and advised against immediate visits in 88.8% (135/152). However, only 32.2% (49/152) of laypersons considered them routine follow-ups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Expert evaluations revealed that the GPT model could be highly accurate in advising on emergency visits. However, laypersons frequently misinterpreted its recommendations, highlighting a substantial gap in understanding AI-generated medical advice.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143595569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between neurological outcomes and prehospital time in patients with out-of-hospital cardiopulmonary arrest","authors":"Kazuhide Yoshikawa,&nbsp;Akira Endo,&nbsp;Wataru Takayama,&nbsp;Tomohisa Shoko,&nbsp;Yasuhiro Otomo,&nbsp;Koji Morishita","doi":"10.1002/ams2.70025","DOIUrl":"https://doi.org/10.1002/ams2.70025","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Out-of-hospital cardiac arrest (OHCA) remains an important health care issue. Considering the importance of such a time course after cardiac arrest, detailed evaluation of the prehospital time (i.e., time from EMS contact to a patient to hospital arrival) is essential to improve the mortality and neurologic outcome of OHCA. In this study, we aimed to evaluate the impact of prehospital time on neurological outcomes in patients with OHCA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective observational study included adult non-traumatic OHCA patients who were transported to 2 emergency centers in Tokyo from January 2015 to December 2020. The following data were obtained retrospectively from medical records.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of the 3120 OHCA patients who were transported during the study period, 2215 patients were evaluated via the inclusion and exclusion criteria. Sixty-nine patients were alive at hospital discharge with a good neurological outcome (i.e., CPC 1 or 2). The multivariate logistic regression model showed that prehospital time (time from EMS contact to hospital arrival) was an independent predictor for hospital discharge with good neurological outcome, in addition to age, bystander CPR, initial rhythm, and cause of cardiac arrest. The GAM plot showed that the adjusted odds ratio of prehospital time for the good neurological outcome was decreased linearly according to time, and the threshold was approximately 30 min.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The threshold of allowable prehospital time, including field activity and transport, for OHCA patients might be 30 min at least in a Japanese urban setting.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Difficult-to-transport cases and neurological outcomes of out-of-hospital cardiac arrest: A population-based nationwide study in Japan","authors":"Azusa Taguchi,&nbsp;Shotaro Aso,&nbsp;Hiroshi Yamagami,&nbsp;Hideo Yasunaga","doi":"10.1002/ams2.70050","DOIUrl":"https://doi.org/10.1002/ams2.70050","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>In Japan, emergency medical service personnel often have difficulty obtaining hospitals' acceptance of emergency cases owing to congestion in the emergency unit; such cases are called difficult-to-transport cases. Increased difficult-to-transport cases at a regional level may be associated with the prognosis of out-of-hospital cardiac arrest (OHCA). This study aimed to investigate the association between the proportion of difficult-to-transport cases at a regional level and neurological outcomes in patients with OHCA, using the nationwide Utstein database linked to ambulance records in Japan.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this retrospective cohort study from 2017 to 2021 in Japan, the proportion of difficult-to-transport cases was calculated as the number of difficult-to-transport cases divided by the number of emergency calls in each district on each day. Patients with OHCA were categorized into no, low, and high difficult-to-transport cases groups. The primary outcome was a Cerebral Performance Category 1 or 2 at 1 month. The secondary outcome was transportation time intervals. Multivariate regression analyses were conducted to assess the association between difficult-to-transport cases and patient outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 592,021 eligible patients, the no, low, and high difficult-to-transport case groups included 282,747 (48%), 155,167 (26%), and 154,107 (26%) patients, respectively. The high difficult-to-transport cases group was associated with decreased favorable neurological outcomes (adjusted odds ratio, 0.91; 95% confidence interval, 0.86–0.95) and longer total transportation time (difference, 4.1 min; 95% confidence interval, 3.8–4.4).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A higher proportion of difficult-to-transport cases was associated with poorer neurological outcomes and longer total transportation times in patients with OHCA.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143533558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of aerosol generation and cooling effects of evaporative plus convective cooling in heat stroke treatment: A simulation study","authors":"Jun Kanda,&nbsp;Yasufumi Miyake,&nbsp;Yuzo Sakamoto,&nbsp;Shoichi Yoshiike,&nbsp;Tomohiko Takeuchi,&nbsp;Tomoki Kanda,&nbsp;Daiki Tanaka,&nbsp;Tadashi Umehara,&nbsp;Kaori Kono,&nbsp;Yasushi Mizutani,&nbsp;Ayumi Tomonaga,&nbsp;Masahiro Asami,&nbsp;Akifumi Yoshida,&nbsp;Maiko Yamazaki,&nbsp;Naoto Morimura,&nbsp;Tetsuya Sakamoto","doi":"10.1002/ams2.70023","DOIUrl":"https://doi.org/10.1002/ams2.70023","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study aimed to experimentally verify the safety and effectiveness of evaporative plus convective cooling used in heat stroke treatment using a doll simulating a patient with heat stroke.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Evaporative plus convective cooling was simulated by blowing air through a fan (speed: approximately 1.0 or 2.5 m/s) and using normal (20°C) or slightly warm (40°C) water on a doll whose surface body temperature was set at 40°C. We measured the change in surface body temperature using a surface heater attached to the back of the doll's chest cover and observed aerosol generation (size: ≥5 μm) using a particulate visualization system. Three particle counters were placed to measure the generated particles that were not captured by the particulate visualization system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The cooling effect of the 2.5 m/s wind speed was greater than that of the 1.0 m/s wind speed. No particles &gt;0.5 μm were observed, and no aerosol particles were generated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our results thus suggested that wind force has a significant effect, and there was no risk of aerosol-related viral infection in evaporative plus convective cooling. However, this does not rule out the risk of droplet infection.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated CT image prescription of the gallbladder using deep learning: Development, evaluation, and health promotion","authors":"Chien-Yi Yang,&nbsp;Hao-Lun Kao,&nbsp;Yu Cheng Chen,&nbsp;Chung-Feng Kuo,&nbsp;Chieh Hsing Liu,&nbsp;Shao-Cheng Liu","doi":"10.1002/ams2.70049","DOIUrl":"https://doi.org/10.1002/ams2.70049","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>Most previous research on AI-based image diagnosis of acute cholecystitis (AC) has utilized ultrasound images. While these studies have shown promising outcomes, the results were based on still images captured by physicians, introducing inevitable selection bias. This study aims to develop a fully automated system for precise gallbladder detection among various abdominal structures, aiding clinicians in the rapid assessment of AC requiring cholecystectomy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The dataset comprised images from 250 AC patients and 270 control participants. The VGG-16 architecture was employed for gallbladder recognition. Post-processing techniques such as the flood fill algorithm and centroid calculation were integrated into the model. U-Net was utilized for segmentation and features extraction. All models were combined to develop a fully automated AC detection system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The gallbladder identification accuracy among various abdominal organs was 95.3%, with the model effectively filtering out CT images lacking a gallbladder. In diagnosing AC, the model was tested on 120 cases, achieving an accuracy of 92.5%, sensitivity of 90.4%, and specificity of 94.1%. After integrating all components, the ensemble model achieved an overall accuracy of 86.7%. The automated process required 0.029 seconds of computation time per CT slice and 3.59 seconds per complete CT set.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The proposed system achieves promising performance in the automatic detection and diagnosis of gallbladder conditions in patients requiring cholecystectomy, with robust accuracy and computational efficiency. With further clinical validation, this computer-assisted system could serve as an auxiliary tool in identifying patients requiring emergency surgery.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AMS Reviewer Summary 2024","authors":"","doi":"10.1002/ams2.70043","DOIUrl":"https://doi.org/10.1002/ams2.70043","url":null,"abstract":"&lt;p&gt;The publication of invaluable papers in the Acute Medicine &amp; Surgery depends on the prompt, careful review of submitted manuscripts. We would like to thank the Editorial Board members and the following experts for reviewing manuscripts from January 1, 2024 to December 31, 2024.&lt;/p&gt;&lt;p&gt;Abe, Ryuzo&lt;/p&gt;&lt;p&gt;Abe, Yoshinobu&lt;/p&gt;&lt;p&gt;Akahoshi, Tomohiko&lt;/p&gt;&lt;p&gt;Akutsu, Hiroyoshi&lt;/p&gt;&lt;p&gt;Amagasa, Shunsuke&lt;/p&gt;&lt;p&gt;Amemiya, Yu&lt;/p&gt;&lt;p&gt;Aokage, Toshiyuki&lt;/p&gt;&lt;p&gt;Aoki, Makoto&lt;/p&gt;&lt;p&gt;Arimoto, Hideki&lt;/p&gt;&lt;p&gt;Ariyoshi, Koichi&lt;/p&gt;&lt;p&gt;Atagi, Kazuaki&lt;/p&gt;&lt;p&gt;Atsumi, Takahiro&lt;/p&gt;&lt;p&gt;Azuma, Kazunari&lt;/p&gt;&lt;p&gt;Chiba, Takuyo&lt;/p&gt;&lt;p&gt;Cho, Kosai&lt;/p&gt;&lt;p&gt;Doi, Kent&lt;/p&gt;&lt;p&gt;Doi, Tomoaki&lt;/p&gt;&lt;p&gt;Ebihara, Takayuki&lt;/p&gt;&lt;p&gt;Endo, Tomoyuki&lt;/p&gt;&lt;p&gt;Fernandez, Luis G.&lt;/p&gt;&lt;p&gt;Fujii, Tomoko&lt;/p&gt;&lt;p&gt;Fujiogi, Michimasa&lt;/p&gt;&lt;p&gt;Fujishima, Seitaro&lt;/p&gt;&lt;p&gt;Fujita, Motoki&lt;/p&gt;&lt;p&gt;Fujita, Satoshi&lt;/p&gt;&lt;p&gt;Fujizuka, Kenji&lt;/p&gt;&lt;p&gt;Fukushima, Hidetada&lt;/p&gt;&lt;p&gt;Funabiki, Tomohiro&lt;/p&gt;&lt;p&gt;Funakoshi, Hiraku&lt;/p&gt;&lt;p&gt;Furukawa, Makoto&lt;/p&gt;&lt;p&gt;Goto, Tadahiro&lt;/p&gt;&lt;p&gt;Goto, Yoshikazu&lt;/p&gt;&lt;p&gt;Goto, Yukari&lt;/p&gt;&lt;p&gt;Hanada, Hiroyuki&lt;/p&gt;&lt;p&gt;Hanajima, Tasuku&lt;/p&gt;&lt;p&gt;Hanaki, Nao&lt;/p&gt;&lt;p&gt;Hara, Yoshitaka&lt;/p&gt;&lt;p&gt;Harada, Masahiro&lt;/p&gt;&lt;p&gt;Hashiguchi, Naoyuki&lt;/p&gt;&lt;p&gt;Hatakeyama, Junji&lt;/p&gt;&lt;p&gt;Hattori, Noriyuki&lt;/p&gt;&lt;p&gt;Hayakawa, Katsura&lt;/p&gt;&lt;p&gt;Hayakawa, Koichi&lt;/p&gt;&lt;p&gt;Hayakawa, Mineji&lt;/p&gt;&lt;p&gt;Hayashi, Hiroyuki&lt;/p&gt;&lt;p&gt;Hayashida, Kei&lt;/p&gt;&lt;p&gt;Hibino, Seikei&lt;/p&gt;&lt;p&gt;Hifumi, Toru&lt;/p&gt;&lt;p&gt;Hiraide, Atsushi&lt;/p&gt;&lt;p&gt;Hirayama, Takahiro&lt;/p&gt;&lt;p&gt;Hirose, Tomoya&lt;/p&gt;&lt;p&gt;Homma, Hiroshi&lt;/p&gt;&lt;p&gt;Homma, Yosuke&lt;/p&gt;&lt;p&gt;Hongo, Takashi&lt;/p&gt;&lt;p&gt;Hosomi, Sanae&lt;/p&gt;&lt;p&gt;Ikeda, Hisato&lt;/p&gt;&lt;p&gt;Inamasu, Joji&lt;/p&gt;&lt;p&gt;Inokuchi, Koichi&lt;/p&gt;&lt;p&gt;Inoue, Shigeaki&lt;/p&gt;&lt;p&gt;Inoue, Takehiro&lt;/p&gt;&lt;p&gt;Inoue, Yoshiaki&lt;/p&gt;&lt;p&gt;Irahara, Takayuki&lt;/p&gt;&lt;p&gt;Ishida, Kenichiro&lt;/p&gt;&lt;p&gt;Ishihara, Satoshi&lt;/p&gt;&lt;p&gt;Ishihara, Tadashi&lt;/p&gt;&lt;p&gt;Isokawa, Shutaro&lt;/p&gt;&lt;p&gt;Iwashita, Yoshiaki&lt;/p&gt;&lt;p&gt;Izawa, Yoshimitsu&lt;/p&gt;&lt;p&gt;Jones, Daryl&lt;/p&gt;&lt;p&gt;Kajino, Kentaro&lt;/p&gt;&lt;p&gt;Kaneko, Tadashi&lt;/p&gt;&lt;p&gt;Kashiura, Masahiro&lt;/p&gt;&lt;p&gt;Katayama, Yusuke&lt;/p&gt;&lt;p&gt;Kikutani, Kazuya&lt;/p&gt;&lt;p&gt;Kiriu, Nobuaki&lt;/p&gt;&lt;p&gt;Kitamura, Tetsuhisa&lt;/p&gt;&lt;p&gt;Kiyota, Kazuya&lt;/p&gt;&lt;p&gt;Koami, Hiroyuki&lt;/p&gt;&lt;p&gt;Kobata, Hitoshi&lt;/p&gt;&lt;p&gt;Kohara, Saeko&lt;/p&gt;&lt;p&gt;Kotani, Joji&lt;/p&gt;&lt;p&gt;Kuboyama, Kazutoshi&lt;/p&gt;&lt;p&gt;Kudo, Daisuke&lt;/p&gt;&lt;p&gt;Kurihara, Tomohiro&lt;/p&gt;&lt;p&gt;Kuroda, Yasuhiro&lt;/p&gt;&lt;p&gt;Kurozumi, Taketo&lt;/p&gt;&lt;p&gt;Kuwana, Tsukasa&lt;/p&gt;&lt;p&gt;Matsui, Satoshi&lt;/p&gt;&lt;p&gt;Matsumura, Yosuke&lt;/p&gt;&lt;p&gt;Matsunaga, Hiroki&lt;/p&gt;&lt;p&gt;Matsushima, Asako&lt;/p&gt;&lt;p&gt;Matsuura, Hiroshi&lt;/p&gt;&lt;p&gt;Matsuyama, Tasuku&lt;/p&gt;&lt;p&gt;Mayumi, Toshihiko&lt;/p&gt;&lt;p&gt;Mitate, Eiji&lt;/p&gt;&lt;p&gt;Mitsunaga, Toshiya&lt;/p&gt;&lt;p&gt;Miyamoto, Kyohei&lt;/p&gt;&lt;p&gt;Mizobata, Yasumitsu&lt;/p&gt;&lt;p&gt;Mizushima, Yasuaki&lt;/p&gt;&lt;p&gt;Mori, Takaaki&lt;/p&gt;&lt;p&gt;Morishita, Koji&lt;/p&gt;&lt;p&gt;Morita, Masanori&lt;/p&gt;&lt;p&gt;Muronoi, Tomohiro&lt;/p&gt;&lt;p&gt;Muroya, Takashi&lt;/p&gt;&lt;p&gt;Naito, Hiromichi&lt;/p&gt;&lt;p&gt;Nakada, Taka-Aki&lt;/p&gt;&lt;p&gt;Nakae, Hajime&lt;/p&gt;&lt;p&gt;Nakagawa, Yuko&lt;/p&gt;&lt;p&gt;Nakamori, Yasushi&lt;/p&gt;&lt;p&gt;Nakao, Shunichiro&lt;/p&gt;&lt;p&gt;Nishida, Takeshi&lt;/p&gt;&lt;p&gt;Nishimura, Takeshi&lt;/p&gt;&lt;p&gt;Nishimura, Tetsuro&lt;/p&gt;&lt;p&gt;Nishiuchi, Tatsuya&lt;/p&gt;&lt;p&gt;Nishiyama, Kei&lt;/p&gt;&lt;p&gt;Nojima, Tsuyoshi&lt;/p&gt;&lt;p&gt;Nomura, Osamu&lt;/p&gt;&lt;p&gt;Ochiai, Hidenobu&lt;/p&gt;&lt;p&gt;Ogura, Takayuki&lt;/p&gt;&lt;p&gt;Ohshimo, Shinichiro&lt;/p&gt;&lt;p&gt;Ohta, Bon&lt;/p&gt;&lt;p","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2024","authors":"Nobuaki Shime,&nbsp;Taka-aki Nakada,&nbsp;Tomoaki Yatabe,&nbsp;Kazuma Yamakawa,&nbsp;Yoshitaka Aoki,&nbsp;Shigeaki Inoue,&nbsp;Toshiaki Iba,&nbsp;Hiroshi Ogura,&nbsp;Yusuke Kawai,&nbsp;Atsushi Kawaguchi,&nbsp;Tatsuya Kawasaki,&nbsp;Yutaka Kondo,&nbsp;Masaaki Sakuraya,&nbsp;Shunsuke Taito,&nbsp;Kent Doi,&nbsp;Hideki Hashimoto,&nbsp;Yoshitaka Hara,&nbsp;Tatsuma Fukuda,&nbsp;Asako Matsushima,&nbsp;Moritoki Egi,&nbsp;Shigeki Kushimoto,&nbsp;Takehiko Oami,&nbsp;Kazuya Kikutani,&nbsp;Yuki Kotani,&nbsp;Gen Aikawa,&nbsp;Makoto Aoki,&nbsp;Masayuki Akatsuka,&nbsp;Hideki Asai,&nbsp;Toshikazu Abe,&nbsp;Yu Amemiya,&nbsp;Ryo Ishizawa,&nbsp;Tadashi Ishihara,&nbsp;Tadayoshi Ishimaru,&nbsp;Yusuke Itosu,&nbsp;Hiroyasu Inoue,&nbsp;Hisashi Imahase,&nbsp;Haruki Imura,&nbsp;Naoya Iwasaki,&nbsp;Noritaka Ushio,&nbsp;Masatoshi Uchida,&nbsp;Michiko Uchi,&nbsp;Takeshi Umegaki,&nbsp;Yutaka Umemura,&nbsp;Akira Endo,&nbsp;Marina Oi,&nbsp;Akira Ouchi,&nbsp;Itsuki Osawa,&nbsp;Yoshiyasu Oshima,&nbsp;Kohei Ota,&nbsp;Takanori Ohno,&nbsp;Yohei Okada,&nbsp;Hiromu Okano,&nbsp;Yoshihito Ogawa,&nbsp;Masahiro Kashiura,&nbsp;Daisuke Kasugai,&nbsp;Ken-ichi Kano,&nbsp;Ryo Kamidani,&nbsp;Akira Kawauchi,&nbsp;Sadatoshi Kawakami,&nbsp;Daisuke Kawakami,&nbsp;Yusuke Kawamura,&nbsp;Kenji Kandori,&nbsp;Yuki Kishihara,&nbsp;Sho Kimura,&nbsp;Kenji Kubo,&nbsp;Tomoki Kuribara,&nbsp;Hiroyuki Koami,&nbsp;Shigeru Koba,&nbsp;Takehito Sato,&nbsp;Ren Sato,&nbsp;Yusuke Sawada,&nbsp;Haruka Shida,&nbsp;Tadanaga Shimada,&nbsp;Motohiro Shimizu,&nbsp;Kazushige Shimizu,&nbsp;Takuto Shiraishi,&nbsp;Toru Shinkai,&nbsp;Akihito Tampo,&nbsp;Gaku Sugiura,&nbsp;Kensuke Sugimoto,&nbsp;Hiroshi Sugimoto,&nbsp;Tomohiro Suhara,&nbsp;Motohiro Sekino,&nbsp;Kenji Sonota,&nbsp;Mahoko Taito,&nbsp;Nozomi Takahashi,&nbsp;Jun Takeshita,&nbsp;Chikashi Takeda,&nbsp;Junko Tatsuno,&nbsp;Aiko Tanaka,&nbsp;Masanori Tani,&nbsp;Atsushi Tanikawa,&nbsp;Hao Chen,&nbsp;Takumi Tsuchida,&nbsp;Yusuke Tsutsumi,&nbsp;Takefumi Tsunemitsu,&nbsp;Ryo Deguchi,&nbsp;Kenichi Tetsuhara,&nbsp;Takero Terayama,&nbsp;Yuki Togami,&nbsp;Takaaki Totoki,&nbsp;Yoshinori Tomoda,&nbsp;Shunichiro Nakao,&nbsp;Hiroki Nagasawa,&nbsp;Yasuhisa Nakatani,&nbsp;Nobuto Nakanishi,&nbsp;Norihiro Nishioka,&nbsp;Mitsuaki Nishikimi,&nbsp;Satoko Noguchi,&nbsp;Suguru Nonami,&nbsp;Osamu Nomura,&nbsp;Katsuhiko Hashimoto,&nbsp;Junji Hatakeyama,&nbsp;Yasutaka Hamai,&nbsp;Mayu Hikone,&nbsp;Ryo Hisamune,&nbsp;Tomoya Hirose,&nbsp;Ryota Fuke,&nbsp;Ryo Fujii,&nbsp;Naoki Fujie,&nbsp;Jun Fujinaga,&nbsp;Yoshihisa Fujinami,&nbsp;Sho Fujiwara,&nbsp;Hiraku Funakoshi,&nbsp;Koichiro Homma,&nbsp;Yuto Makino,&nbsp;Hiroshi Matsuura,&nbsp;Ayaka Matsuoka,&nbsp;Tadashi Matsuoka,&nbsp;Yosuke Matsumura,&nbsp;Akito Mizuno,&nbsp;Sohma Miyamoto,&nbsp;Yukari Miyoshi,&nbsp;Satoshi Murata,&nbsp;Teppei Murata,&nbsp;Hiromasa Yakushiji,&nbsp;Shunsuke Yasuo,&nbsp;Kohei Yamada,&nbsp;Hiroyuki Yamada,&nbsp;Ryo Yamamoto,&nbsp;Ryohei Yamamoto,&nbsp;Tetsuya Yumoto,&nbsp;Yuji Yoshida,&nbsp;Shodai Yoshihiro,&nbsp;Satoshi Yoshimura,&nbsp;Jumpei Yoshimura,&nbsp;Hiroshi Yonekura,&nbsp;Yuki Wakabayashi,&nbsp;Takeshi Wada,&nbsp;Shinichi Watanabe,&nbsp;Atsuhiro Ijiri,&nbsp;Kei Ugata,&nbsp;Shuji Uda,&nbsp;Ryuta Onodera,&nbsp;Masaki Takahashi,&nbsp;Satoshi Nakajima,&nbsp;Junta Honda,&nbsp;Tsuguhiro Matsumoto","doi":"10.1002/ams2.70037","DOIUrl":"https://doi.org/10.1002/ams2.70037","url":null,"abstract":"<p>The 2024 revised edition of the Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock (J-SSCG 2024) is published by the Japanese Society of Intensive Care Medicine and the Japanese Association for Acute Medicine. This is the fourth revision since the first edition was published in 2012. The purpose of the guidelines is to assist healthcare providers in making appropriate decisions in the treatment of sepsis and septic shock, leading to improved patient outcomes. We aimed to create guidelines that are easy to understand and use for physicians who recognize sepsis and provide initial management, specialized physicians who take over the treatment, and multidisciplinary healthcare providers, including nurses, physical therapists, clinical engineers, and pharmacists. The J-SSCG 2024 covers the following nine areas: diagnosis of sepsis and source control, antimicrobial therapy, initial resuscitation, blood purification, disseminated intravascular coagulation, adjunctive therapy, post-intensive care syndrome, patient and family care, and pediatrics. In these areas, we extracted 78 important clinical issues. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) method was adopted for making recommendations, and the modified Delphi method was used to determine recommendations by voting from all committee members. As a result, 42 GRADE-based recommendations, 7 good practice statements, and 22 information-to-background questions were created as responses to clinical questions. We also described 12 future research questions.</p>","PeriodicalId":7196,"journal":{"name":"Acute Medicine & Surgery","volume":"12 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ams2.70037","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}