Journal of intensive medicine最新文献

{"title":"Diagnostic approach in acute hypoxemic respiratory failure","authors":"Pierre Bay ,&nbsp;Nicolas de Prost","doi":"10.1016/j.jointm.2024.09.003","DOIUrl":"10.1016/j.jointm.2024.09.003","url":null,"abstract":"<div><div>Acute hypoxemic respiratory failure (AHRF) is the leading cause of intensive care unit (ICU) admissions. Of patients with AHRF, 40 %–50 % will require invasive mechanical ventilation during their stay in the ICU, and 30 %–80 % will meet the Berlin Criteria for Acute Respiratory Distress Syndrome (ARDS). Rapid identification of the underlying cause of AHRF is necessary before initiating targeted treatment. Almost 10 % of patients with ARDS have no identified classic risk factors however, and the precise cause of AHRF may not be identified in up to 15 % of patients, particularly in cases of immunosuppression. In these patients, a multidisciplinary, comprehensive, and hierarchical diagnostic work-up is mandatory, including a detailed history and physical examination, chest computed tomography, extensive microbiological investigations, bronchoalveolar lavage fluid cytological analysis, immunological tests, and investigation of the possible involvement of pneumotoxic drugs.</div></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 2","pages":"Pages 119-126"},"PeriodicalIF":0.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724786","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":"Risk factors and outcomes of pediatric non-invasive respiratory support failure in Latin America","authors":"Diana Paola Escobar-Serna ,&nbsp;Juan Sebastian Barajas-Romero ,&nbsp;Juan Javier Peralta-Palmezano ,&nbsp;Juan Camilo Jaramillo-Bustamante ,&nbsp;Nicolas Monteverde-Fernandez ,&nbsp;Jesus Alberto Serra ,&nbsp;Paula Caporal ,&nbsp;Soledad Menta ,&nbsp;Ruben Lasso-Palomino ,&nbsp;Eliana Zemanate ,&nbsp;Javier Martínez ,&nbsp;Hernan Herrera ,&nbsp;Luis Martínez ,&nbsp;Francisca Castro Zamorano ,&nbsp;Cristobal Carvajal ,&nbsp;Monica Decía ,&nbsp;Roberto Jabornisky ,&nbsp;Franco Diaz ,&nbsp;Sebastian Gonzalez-Dambrauskas ,&nbsp;Pablo Vasquez-Hoyos ,&nbsp;Jennifer Silva","doi":"10.1016/j.jointm.2024.09.001","DOIUrl":"10.1016/j.jointm.2024.09.001","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;Noninvasive respiratory support (NRS) is standard in pediatric intensive care units (PICUs) for respiratory diseases, but its failure can lead to complications requiring invasive mechanical ventilation (IMV). This study aimed to identify risk factors for NRS failure in children with acute respiratory failure (ARF) in PICUs, and compare complications and outcomes between IMV-only and NRS failure patients.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We conducted a cohort study using data from the LARed Network prospective registry (April 2017–November 2022), in children under 18 years admitted to PICUs for ARF. Cases were divided into subgroups: those managed with IMV only, those who experienced NRS failure requiring IMV, those who received NRS successfully, and those who did not require NRS or IMV. Exclusions included patients with home respiratory support prior to admission, patients without PICU discharge at the cutoff date of the analysis and those with incomplete data. Multivariate mixed models analyzed NRS failure risk factors, and complications between the IMV-only and NRS failure groups, using centers as a random effect.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;A total of 7374 children met the inclusion criteria, with 6208 in the NRS group and 1166 in the IMV-only group. The NRS success rate was 85.3 %. Risk factors for NRS failure included age (median of 4.6 months, interquartile range of 2.1–14.2 months), history of prematurity (adjusted odds ratio [aOR]=1.53, 95 % confidence interval [CI]: 1.20 to 1.95) or malnutrition (aOR=1.85, 95 % CI: 1.18 to 2.91), suspected bacterial infection (aOR=5.12, 95 % CI: 4.05to 6.49), FiO&lt;sub&gt;2&lt;/sub&gt; &gt;30 % (aOR=1.52, 95 % CI: 1.18 to 1.97), severe hypoxemia with SpO&lt;sub&gt;2&lt;/sub&gt;/FiO&lt;sub&gt;2&lt;/sub&gt; ≤150 (aOR=1.85, 95 % CI: 1.48 to 2.30), tachypnea (aOR=1.42, 95 % CI: 1.18 to 1.72), tachycardia (aOR=1.77, 95 % CI: 1.47 to 2.12), and lung consolidations (aOR=1.45, 95 % CI: 1.14 to 1.85) or interstitial infiltrates (aOR=1.29, 95 % CI: 1.05 to 1.58) on chest X-ray. There were no significant differences in morbidity, mortality, duration of IMV, or PICU length of stay between patients who received IMV only and those who experienced NRS failure. However, patients who experienced NRS failure were more likely to develop withdrawal symptoms related to sedative or opioid discontinuation and/or delirium (aOR=2.57, 95 % CI: 1.85 to 2.57).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;This study identified key risk factors for predicting NRS failure in children with acute ARF in PICUs, including younger age, prematurity, malnutrition, suspected bacterial infection, FiO&lt;sub&gt;2&lt;/sub&gt; &gt;30 %, severe hypoxemia (SpO&lt;sub&gt;2&lt;/sub&gt;/FiO&lt;sub&gt;2&lt;/sub&gt; ≤150), tachypnea, tachycardia, and radiological findings such as lung consolidation and interstitial infiltrates. Compared to patients managed with IMV from the start, those who experienced NRS failure were more likely to develop withdrawal symptoms and/or delirium, although","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 2","pages":"Pages 176-184"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724778","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":"Redefining sepsis management: The comprehensive impact of artificial intelligence","authors":"Jamie Ghossein ,&nbsp;Brett N. Hryciw ,&nbsp;Kwadwo Kyeremanteng","doi":"10.1016/j.jointm.2024.08.002","DOIUrl":"10.1016/j.jointm.2024.08.002","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"5 2","pages":"Pages 134-136"},"PeriodicalIF":0.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724788","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":"Advancing understanding and management of invasive fungal diseases in the intensive care unit: Insights from FUNDICU consensus definitions","authors":"Ignacio Martin-Loeches","doi":"10.1016/j.jointm.2024.06.001","DOIUrl":"10.1016/j.jointm.2024.06.001","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 482-483"},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000720/pdfft?md5=0089500e6bd86bd20272d1703930bc85&pid=1-s2.0-S2667100X24000720-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141707272","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":"Investigating computational models for diagnosis and prognosis of sepsis based on clinical parameters: Opportunities, challenges, and future research directions","authors":"Jyotirmoy Gupta ,&nbsp;Amit Kumar Majumder ,&nbsp;Diganta Sengupta ,&nbsp;Mahamuda Sultana ,&nbsp;Suman Bhattacharya","doi":"10.1016/j.jointm.2024.04.006","DOIUrl":"10.1016/j.jointm.2024.04.006","url":null,"abstract":"<div><p>This study investigates the use of computational frameworks for sepsis. We consider two dimensions for investigation – early diagnosis of sepsis (EDS) and mortality prediction rate for sepsis patients (MPS). We concentrate on the clinical parameters on which sepsis diagnosis and prognosis are currently done, including customized treatment plans based on historical data of the patient. We identify the most notable literature that uses computational models to address EDS and MPS based on those clinical parameters. In addition to the review of the computational models built upon the clinical parameters, we also provide details regarding the popular publicly available data sources. We provide brief reviews for each model in terms of prior art and present an analysis of their results, as claimed by the respective authors. With respect to the use of machine learning models, we have provided avenues for model analysis in terms of model selection, model validation, model interpretation, and model comparison. We further present the challenges and limitations of the use of computational models, providing future research directions. This study intends to serve as a benchmark for first-hand impressions on the use of computational models for EDS and MPS of sepsis, along with the details regarding which model has been the most promising to date. We have provided details regarding all the ML models that have been used to date for EDS and MPS of sepsis.</p></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 468-477"},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000744/pdfft?md5=25f1779e49c9e98ed44a5c02345f8a85&pid=1-s2.0-S2667100X24000744-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141699597","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 hyperglycemia at ICU admission and postoperative acute kidney injury in patients undergoing cardiac surgery: Analysis of the MIMIC-IV database","authors":"Juan Ruan ,&nbsp;Weipeng Huang ,&nbsp;Jun Jiang ,&nbsp;Chang Hu ,&nbsp;Yiming Li ,&nbsp;Zhiyong Peng ,&nbsp;Shuhan Cai","doi":"10.1016/j.jointm.2024.04.004","DOIUrl":"10.1016/j.jointm.2024.04.004","url":null,"abstract":"<div><h3>Background</h3><p>This study aimed to explore the correlation between hyperglycemia at intensive care unit (ICU) admission and the incidence of acute kidney injury (AKI) in patients after cardiac surgery.</p></div><div><h3>Methods</h3><p>We conducted a retrospective cohort study, in which clinical data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Adults (≥18 years) in the database who were admitted to the cardiovascular intensive care unit after cardiac surgery were enrolled. The primary outcome was the incidence of AKI within 7 days following ICU admission. Secondary outcomes included ICU mortality, hospital mortality, ICU length of stay, and the 28-day and 90-day mortality. Multivariable Cox regression analysis was used to assess the association between ICU-admission hyperglycemia and AKI incidence within 7 days of ICU admission. Different adjustment strategies were used to adjust for potential confounders. Patients were divided into three groups according to their highest blood glucose levels recorded within 24 h of ICU admission: no hyperglycemia (&lt;140 mg/dL), mild hyperglycemia (140–200 mg/dL), and severe hyperglycemia (≥200 mg/dL).</p></div><div><h3>Results</h3><p>Of the 6905 included patients, 2201 (31.9%) were female, and the median (IQR) age was 68.2 (60.1–75.9) years. In all, 1836 (26.6%) patients had severe hyperglycemia. The incidence of AKI within 7 days of ICU admission, ICU mortality, and hospital mortality was significantly higher in patients with severe admission hyperglycemia than those with mild hyperglycemia or no hyperglycemia (80.3% <em>vs</em>. 73.6% and 61.2%, respectively; 2.8% <em>vs</em>. 0.9% and 1.9%, respectively; and 3.4% <em>vs</em>. 1.2% and 2.5%, respectively; all <em>P</em> &lt;0.001). Severe hyperglycemia was a risk factor for 7-day AKI (Model 1: hazard ratio [HR]=1.4809, 95% confidence interval [CI]: 1.3126 to 1.6707; Model 2: HR=1.1639, 95% CI: 1.0176 to 1.3313; Model 3: HR=1.2014, 95% CI: 1.0490 to 1.3760; all <em>P</em> &lt;0.050). Patients with normal glucose levels (glucose levels &lt;140 mg/dL) had a higher 28-day mortality rate than those with severe hyperglycemia (glucose levels ≥200 mg/dL) (4.0% <em>vs</em>. 3.8%, <em>P</em> &lt;0.001).</p></div><div><h3>Conclusions</h3><p>In post-cardiac surgery patients, severe hyperglycemia within 24 h of ICU admission increases the risk of 7-day AKI, ICU mortality, and hospital mortality. Clinicians should be extra cautious regarding AKI among patients with hyperglycemia at ICU admission after cardiac surgery.</p></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 526-536"},"PeriodicalIF":0.0,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000665/pdfft?md5=99d8c12a15a59d36251be0bccc5f7401&pid=1-s2.0-S2667100X24000665-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149510","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":"Adaptive platform trials in critical care","authors":"Muralie Vignarajah ,&nbsp;Bram Rochwerg","doi":"10.1016/j.jointm.2024.04.002","DOIUrl":"10.1016/j.jointm.2024.04.002","url":null,"abstract":"","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 478-479"},"PeriodicalIF":0.0,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000471/pdfft?md5=b264f1271456dd9d38292329b122ab17&pid=1-s2.0-S2667100X24000471-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149110","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":"Comparative study on the incidence of non-COVID-19 viral pneumonia before and after the COVID-19 pandemic: A retrospective analysis based on respiratory non-COVID viral nucleic acid results","authors":"","doi":"10.1016/j.jointm.2024.02.005","DOIUrl":"10.1016/j.jointm.2024.02.005","url":null,"abstract":"<div><h3>Background</h3><p>The impact of the coronavirus disease 2019 (COVID-19) pandemic on the etiology of non-COVID-19 viral pneumonia remains to be identified. We investigated the evolution of non-COVID-19 viral pneumonia in hospitalized patients before and after the COVID-19 pandemic.</p></div><div><h3>Methods</h3><p>This is a single-center retrospective study. Patients who came to West China Hospital of Sichuan University diagnosed with non-COVID-19 viral pneumonia from January 1, 2016 to December 31, 2021, were included and divided into pre- and post-COVID-19 groups according to the date of the COVID-19 outbreak in China. The results of 13 viral nucleic acid tests were compared between the two groups.</p></div><div><h3>Results</h3><p>A total of 5937 patients (3954 in the pre-COVID-19 group and 1983 in the post-COVID-19 group) were analyzed. Compared with the pre-COVID-19 group, the proportion of patients tested for respiratory non-COVID-19 viral nucleic acid was significantly increased in the post-COVID-19 group (14.78% <em>vs.</em> 22.79%, <em>P</em> &lt;0.05). However, the non-COVID-19 virus-positive rates decreased from 37.9% to 14.6% after the COVID-19 outbreak (<em>P</em> &lt; 0.001). Notably, non-COVID-19 viral pneumonia caused by the influenza A virus H1N1 (InfAH1N1) (2009) dropped to 0% after the pandemic. The top three viruses were InfAH1N1 (2009) (13.9%), human rhinovirus (7.4%), and human adenovirus (3.4%) in the pre-COVID-19 group, and human rhinovirus (3.8%), human respiratory syncytial virus (2.0%), human parainfluenza virus (1.1%) and InfAH3N2 (1.1%) in the post-COVID-19 group.</p></div><div><h3>Conclusions</h3><p>The proportion of non-COVID-19 viral pneumonia decreased significantly after the COVID-19 outbreak, among which InfAH1N1 (2009) pneumonia decreased the most dramatically.</p></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 491-495"},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000446/pdfft?md5=812676a83d2438e72ec183cf02f110dd&pid=1-s2.0-S2667100X24000446-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140773937","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":"Severe respiratory syncytial virus disease","authors":"","doi":"10.1016/j.jointm.2024.03.001","DOIUrl":"10.1016/j.jointm.2024.03.001","url":null,"abstract":"<div><p>The burden of respiratory syncytial virus (RSV) disease is widely recognized. Main risk factors for severe disease, such as extreme ages, chronic cardiopulmonary conditions, and immunosuppression, typically coincide with poorer outcomes. While the majority of RSV hospitalizations involve healthy children, a higher proportion of hospitalized adults with underlying conditions need intensive care. Presently, treatment primarily consists of supportive measures. RSV-induced wheezing should be distinguished from respiratory tract thickening, without response to bronchodilators. Obstructive RSV disease frequently overlaps with viral pneumonia. Non-invasive mechanical ventilation and high-flow oxygen therapy represented significant advancements in the management of severe RSV disease in children and may also hold considerable importance in specific phenotypes of RSV disease in adults. Most severe infections manifest with refractory hypoxemia necessitating more advanced ventilatory support and/or extracorporeal membrane oxygenation therapy. Although bacterial co-infection rates are low, they have been associated with worse outcomes. Antibiotic prescription rates are high. Accurately diagnosing bacterial co-infections remains a challenge. Current evidence and antibiotic stewardship policies advise against indiscriminate antibiotic usage, even in severe cases. The role of currently developing antiviral therapies in severe RSV disease will be elucidated in the coming years, contingent upon the success of new vaccines and immune passive strategies involving nirsevimab.</p></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 405-416"},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000379/pdfft?md5=9128c3ed103a89fb48f7f35fd6f1e688&pid=1-s2.0-S2667100X24000379-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140788108","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":"How much tidal volume is sufficiently low to be called “protective lung ventilation”","authors":"","doi":"10.1016/j.jointm.2024.03.002","DOIUrl":"10.1016/j.jointm.2024.03.002","url":null,"abstract":"<div><p>Ultra-low tidal volume (ULT) is an appealing alternative for severe acute respiratory distress syndrome (ARDS) patients with the aim to alleviate excess lung stress and strain. A recent article showed that ULT without extracorporeal carbon dioxide removal did not improve prognosis in moderate-to-severe coronavirus disease 2019-related ARDS patients. However, several reasons should be considered before drawing the definite conclusion about the ULT strategy in severe ARDS.</p></div>","PeriodicalId":73799,"journal":{"name":"Journal of intensive medicine","volume":"4 4","pages":"Pages 480-481"},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667100X24000434/pdfft?md5=7d6000d11f2c91b19970146dc1a5ffdd&pid=1-s2.0-S2667100X24000434-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140761519","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}