Critical Care最新文献

{"title":"Net albumin leakage in patients in the ICU with suspected sepsis. A prospective analysis using mass balance calculations","authors":"Dag Seldén, Nicolas Tardif, Jan Wernerman, Olav Rooyackers, Åke Norberg","doi":"10.1186/s13054-025-05323-9","DOIUrl":"https://doi.org/10.1186/s13054-025-05323-9","url":null,"abstract":"Albumin kinetics in septic shock have been extensively studied, but clinical recommendations remain weak. An increased transcapillary escape rate (TER) of albumin has been demonstrated, though TER does not account for lymphatic return. Mass balance calculations, considering lymphatic return, have been used to assess net albumin leakage (NAL) in major surgery but not in sepsis. This study aimed to evaluate NAL in ten ICU patients with suspected sepsis, hypothesizing a net positive leakage. Secondary aims included investigating associations between NAL and fluid overload, glycocalyx shedding products, and cytokines, as well as identifying factors associated with it. This prospective, observational study included ten patients within twelve hours of ICU admission for suspected sepsis at Karolinska University Hospital Huddinge. Albumin, hematocrit, and hemoglobin levels were sampled at 0, 1, 2, 4, 8, and 24 h. NAL was estimated using mass balance calculations, comparing proportional changes in albumin and hemoglobin concentrations over time, adjusted for albumin and hemoglobin infusions and losses. A proportionally greater decrease or smaller increase in albumin compared to hemoglobin indicated NAL, representing the net leakage from the circulation to the interstitium minus lymphatic return. Over 24 h, patients exhibited a net positive albumin leakage to the interstitium of 8 ± 10 g (p = 0.029). NAL showed no correlation with glycocalyx shedding products or fluid overload but had a weak correlation with interleukin-6 and interleukin-8 in the first 4 h. Albumin infusions appeared to increase net leakage. This study demonstrated a net positive albumin leakage of 8 ± 10 g over 24 h in ICU patients with suspected sepsis, with a weak early correlation to pro-inflammatory cytokines but no significant link to fluid balance or glycocalyx shedding. Notably, albumin infusions were associated with increased net leakage.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"54 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Being an observer of one’s own life—a meta-synthesis on the experience of mechanically ventilated patients in intensive care units","authors":"Fritz Sterr, Mareike Hechinger, Lydia Bauernfeind, Christian Rester, Rebecca Palm, Sabine Metzing","doi":"10.1186/s13054-025-05326-6","DOIUrl":"https://doi.org/10.1186/s13054-025-05326-6","url":null,"abstract":"The experience of patients under mechanical ventilation in the intensive care unit is described as complex and multifaceted, but an overarching and in-depth understanding of the experience is still missing. To provide an in-depth analysis and synthesis of patients’ experience when being mechanically ventilated in intensive care units. We conducted a meta-synthesis according to the methodological recommendations of Sandelowski and Barroso. Our systematic literature search in Medline, CINAHL, and Cochrane was complemented by hand and citation searches. We included only qualitative studies with a rich description of conscious patients’ experience under mechanical ventilation. Studies on children, step-down units, noninvasive ventilation and non-scientific journal articles were excluded. After the title, abstract and full-text screening by three reviewers, we performed initial, axial and selective coding and in-depth analysis in MAXQDA. The synthesis was supported by multiple discussion rounds. Of the 2,563 records identified, 20 studies were included in our synthesis. This revealed the central phenomenon of patients being observers of their own lives. They are yearning for a stable picture of reality and developing various situation-specific needs. Finally, patients are finding ways to deal with the situation. These concepts are interwoven in time and are experienced repeatedly in different dimensions. Patients under mechanical ventilation are highly perceptive. Healthcare professionals are particularly responsible for patients. They should reflect on their role in intensive care and must be sensitized to patients’ differentiated experience. Registration, Protocol: https://doi.org/10.17605/OSF.IO/G8Q6X ","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"10 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143575187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning models compared with current clinical indices to predict the outcome of high flow nasal cannula therapy in acute hypoxemic respiratory failure","authors":"Hang Yu, Sina Saffaran, Roberto Tonelli, John G. Laffey, Antonio M. Esquinas, Lucas Martins de Lima, Letícia Kawano-Dourado, Israel S. Maia, Alexandre Biasi Cavalcanti, Enrico Clini, Declan G. Bates","doi":"10.1186/s13054-025-05336-4","DOIUrl":"https://doi.org/10.1186/s13054-025-05336-4","url":null,"abstract":"Early identification of patients with acute hypoxemic respiratory failure (AHRF) who are at risk of failing high-flow nasal cannula (HFNC) therapy could facilitate closer monitoring, and timely adjustment/escalation of treatment. We aimed to establish whether machine learning (ML) models could predict HFNC outcome, early in the course of treatment, with greater accuracy than currently used clinical indices. We developed ML models trained using measurements made within the first 2 h of treatment from 184 AHRF patients (37% HFNC failures) treated at the respiratory ICU of the University Hospital of Modena between 2018 and 2023. For external validation, we used a dataset on 567 AHRF patients (22% failures) comprising 510 patients from the recent RENOVATE trial in Brazil and 57 from the MIMIC-IV and eICU databases in the US. Predictive performance of the ML models was benchmarked against optimized thresholds of the following clinical indices: respiratory rate oxygenation index (ROX) and variants, heart rate to saturation of pulse oxygen (SpO2) ratio, SpO2/FiO2 ratio, PaO2/FiO2 ratio, sequential organ failure assessment and heart rate, acidosis, consciousness, oxygenation and respiratory rate scores. Internal and external predictive performance of a Support Vector Machine (SVM) ML model was superior to all clinical indices across all scenarios tested. In external validation on the 567-patient dataset, a SVM model trained on non-invasive measurements had an accuracy of 73%, sensitivity of 73%, specificity of 73%, and AUC of 0.79. The ROX index had an accuracy of 64%, sensitivity of 79%, specificity of 60%, and AUC of 0.74. When arterial blood gasses (ABG’s) were also used for model training, the SVM model had an accuracy of 83%, sensitivity of 84%, specificity of 82%, and AUC of 0.82 in external validation on the MIMIC-IV/eICU dataset. The modified ROX index, which requires PaO2, achieved 70% accuracy, 63% sensitivity, 74% specificity, and AUC of 0.65. Decision support tools based on SVM models could provide clinicians with more accurate early predictions of HFNC outcome than currently available clinical indices. If available, ABG measurements could improve the capability to accurately identify patients at risk of failing HFNC therapy.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"17 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sodium azide (NaN3) intoxication, “the man who lived”: potential effective antidote and treatment strategy","authors":"Jasper X. Geerdink, Greetje van der Wal, Lutea A. A. de Jong, Erik J. H. Olyslager, Thomas W. van den Goorbergh, Leo A. J. Kluijtmans, Peter E. Spronk","doi":"10.1186/s13054-025-05330-w","DOIUrl":"https://doi.org/10.1186/s13054-025-05330-w","url":null,"abstract":"This case report describes the successful treatment of a suicide attempt involving the ingestion of a supralethal dose of sodium azide (NaN3), presenting a prospective novel antidote and therapeutic approach. Treatment encompassed the implementation of high-volume continuous veno-venous hemofiltration (HV-CVVH) alongside the administration of levocarnitine. The latter demonstrated a substantial mitigation of lactate concentration. Comprehensive analyses of serum, ultrafiltrate, and urine revealed the efficacy of HV-CVVH in elimination of NaN3. Our case report presents a potential therapeutic approach for managing otherwise fatal NaN3 intoxications.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"11 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143570343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardizing persistent and chronic critical illness: impact of definitions variability on prevalence and mortality","authors":"Toshinobu Nakai, Yuki Kotani, Yoshiro Hayashi","doi":"10.1186/s13054-025-05335-5","DOIUrl":"https://doi.org/10.1186/s13054-025-05335-5","url":null,"abstract":"<p>Standardization of terminology and definitions is essential for scientific communication. Without such standardization, some studies may use different terms to express similar conditions, and other studies may use the same term with different definitions. Such diversities in medical language creates inconsistencies in scientific reporting, thereby hindering us from properly understanding the condition.</p><p>In this regard, persistent critical illness (PerCI) and chronic critical illness (CCI) are two terms used to describe prolonged critical conditions beyond the acute phase [1, 2]. However, the absence of standardized definitions leads to substantial variability in their clinical implications. Recently, <i>Critical Care</i> published a systematic scoping review highlighting the heterogeneity in definitions, epidemiology, and outcomes of PerCI and CCI [3]. We commend the authors for their comprehensive analysis, which synthesizes data obtained from numerous studies, performs a meta-analysis on specific patient populations (e.g., overall populations, sepsis, trauma, and COVID-19), and offers valuable recommendations for future research.</p><p>To further expand on the insights provided by Ohbe et al., we conducted an exploratory analysis to illustrate how different PerCI/CCI definitions impact reported prevalence and in-hospital mortality. From the 99 studies included in Ohbe et al.’s scoping review [3], we selected those explicitly reporting PerCI/CCI definitions, prevalence, and in-hospital mortality. We then created a scatter plot, where each dot represents a study, with PerCI/CCI prevalence on the x-axis and in-hospital mortality on the y-axis (Fig. 1), using Excel version 16.94. Dots were color-coded according to the PerCI/CCI definition applied in each study. This visualization underscores the substantial variability in prevalence and mortality based on the chosen definition.</p><figure><figcaption><b data-test=\"figure-caption-text\">Fig. 1</b></figcaption><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05335-5/MediaObjects/13054_2025_5335_Fig1_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure 1\" aria-describedby=\"Fig1\" height=\"400\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05335-5/MediaObjects/13054_2025_5335_Fig1_HTML.png\" width=\"685\"/></picture><p>Prevalence and hospital mortality according to the different persistent/chronic critical illness definitions</p><span>Full size image</span><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></figure><p>Studies defining PerCI/CCI as “ICU stay ≥ 14 days with persistent organ dysfunction” (orange) reported higher prevalence compared to other definitions. This trend may be attributed to the study populations, which predominantly consisted of septic","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"12 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: An updated “norepinephrine equivalent” score in intensive care as a marker of shock severity","authors":"Yuki Kotani, Annamaria Di Gioia, Giovanni Landoni, Alessandro Belletti, Ashish K. Khanna","doi":"10.1186/s13054-025-05250-9","DOIUrl":"https://doi.org/10.1186/s13054-025-05250-9","url":null,"abstract":"<p><b>Correction: Critical Care (2023) 27:29 </b><b>https://doi.org/10.1186/s13054-023-04322-y</b></p><p>Following publication of the original article [1], the authors would like to correct the correction rate for metaraminol which is 1/8 under the heading Proposed updated norepinephrine equivalent score, Figure 1 and Table 1.</p><p>The sentences currently reads:</p><br/><p>A randomized trial compared metaraminol and norepinephrine in septic shock [38]. Based on the findings of this trial suggesting 2.5 μg/kg/min of metaraminol corresponded to 0.3 μg/kg/min of norepinephrine, we defined a correction factor of 8 to metaraminol dose in μg/kg/min.</p><br/><p>The sentences should read:</p><br/><p>A randomized trial compared metaraminol and norepinephrine in septic shock [38]. Based on the findings of this trial suggesting 2.5 μg/kg/min of metaraminol corresponded to 0.3 μg/kg/min of norepinephrine, we defined a correction factor of 1/8 to metaraminol dose in μg/kg/min.</p><p>The incorrect Figure 1:</p><figure><figcaption><b data-test=\"figure-caption-text\">Fig. 1</b></figcaption><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05250-9/MediaObjects/13054_2025_5250_Fig1_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure 1\" aria-describedby=\"Fig1\" height=\"315\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05250-9/MediaObjects/13054_2025_5250_Fig1_HTML.png\" width=\"685\"/></picture><p>Visual summary of an updated norepinephrine equivalent score and need for using norepinephrine equivalence</p><span>Full size image</span><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></figure><p>The correct Figure 1:</p><figure><figcaption><b data-test=\"figure-caption-text\">Fig. 1</b></figcaption><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05250-9/MediaObjects/13054_2025_5250_Fig2_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure 2\" aria-describedby=\"Fig2\" height=\"321\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05250-9/MediaObjects/13054_2025_5250_Fig2_HTML.png\" width=\"685\"/></picture><p>Visual summary of an updated norepinephrine equivalent score and need for using norepinephrine equivalence</p><span>Full size image</span><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></figure><p>The incorrect Table 1:</p><figure><figcaption><b data-test=\"table-caption\">Table 1 Summary of norepinephrine equivalent formulas</b></figcaption><span>Full size table</span><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-chevron-right-small\"","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"8 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of intracranial hypertension prediction models based on radiomic features in patients with traumatic brain injury: an exploratory study based on CENTER-TBI data","authors":"Yingchi Shan, Yajun Xue, Jun Zhu, Thijs Vande Vyvere, Dana Pisică, Andrew Maas, Shuo Zhang, Guoyi Gao","doi":"10.1186/s13054-025-05328-4","DOIUrl":"https://doi.org/10.1186/s13054-025-05328-4","url":null,"abstract":"Head computed tomography (CT) is a routinely performed examination to assess the intracranial condition of patients with traumatic brain injury (TBI), and radiological findings can help to indicate the presence of intracranial hypertension. At present, the prediction of intracranial hypertension is mainly based on manual discrimination of imaging characteristics. The aim of our study was to establish a model to predict intracranial hypertension via fully automatic CT image segmentation, rigorous radiomic feature extraction and reliable model development and validation. Patients admitted to the intensive care unit (ICU) who underwent intracranial pressure (ICP) monitoring were included in our study. For the development cohort, we extracted data from the CENTER-TBI database and randomly divided the data into a training group and a test group. For the validation cohort, we extracted data from patients admitted to the Shanghai General Hospital. Patients whose initial recorded ICP value was greater than or equal to 20 mmHg were defined as having intracranial hypertension. Radiological features, including imaging characteristics and three categories of radiomic features, were extracted from the head CT. Feature selection was performed for all radiological findings. A morphological model was built on the basis of selected imaging characteristics. First-order, second-order and third-order models were built on the basis of selected radiomic features. A comprehensive model was built on the basis of all selected radiological findings. The performances of these five models were assessed by four classifiers, including logistic regression (LR), random forest (RF), multilayer perceptron (MLP), and extreme gradient boosting (XGB), from which the best classifier was selected. After the process of model training and external validation, we ultimately used the optimal classifier to generate a prediction model with greater predictive power and stability. Five models were built, including a morphological model, first-order model, second-order model, third-order model and comprehensive model. The optimal classifier was the logistic regression (LR) classifier, with which the morphological, first-order, second-order, third-order and comprehensive models had AUCs of 0.75, 0.77, 0.76, 0.86, and 0.83 and F1 scores of 0.54, 0.73, 0.63, 0.72, and 0.75, respectively, in the external validation group. We successfully established a model for predicting intracranial hypertension on the basis of radiomic features. This model may serve as an approach for intracranial hypertension prediction in TBI patients. ","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"85 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alterations in the lipid profile of critically ill children in relation to outcome","authors":"Lauren De Bruyn, Sarah Vander Perre, Sascha Verbruggen, Koen Joosten, Greet Van den Berghe, Lies Langouche","doi":"10.1186/s13054-025-05327-5","DOIUrl":"https://doi.org/10.1186/s13054-025-05327-5","url":null,"abstract":"Critically ill adults typically develop hypocholesterolemia, associated with poor outcome. Whether similar alterations occur in critically ill children is less clear. In secondary analyses of the PEPaNIC RCT (n = 1440), we first documented the time course of plasma cholesterol and triglyceride concentrations, and the effect of randomization to early-parenteral-nutrition (early-PN) or late-PN hereon, for 96 matched critically ill children staying ≥ 5 days in PICU. Second, for 1165 children with available admission plasma samples, lipid profiles were determined and their independent associations with outcome (time to live PICU discharge, new infection and 90-day mortality) were assessed with Multivariable Cox proportional hazard and logistic regression, adjusting for baseline risk factors. Plasma HDL-cholesterol, LDL-cholesterol, total-cholesterol and triglycerides were low throughout the 5 PICU days, with only HDL-cholesterol further decreasing over time (P < 0.0001) and without effect of randomization to early-PN or late-PN, and with admission values lower in infants than older children and in patients with infection (P < 0.05). Lower admission HDL- and total-cholesterol concentrations were independently associated with a lower likelihood of an earlier live PICU discharge (P < 0.001) and with a higher risk of 90-day mortality (P ≤ 0.01), whereas higher plasma triglycerides were independently associated with higher risk of 90-day mortality (P = 0.004). Low admission plasma HDL-cholesterol was independently associated with a higher risk of acquiring a new infection (P = 0.05). Critically ill children presented with low circulating levels of lipids. Low plasma cholesterol concentrations were associated with poor outcomes, most robustly for HDL-cholesterol. Whether these associations are causal or casual requires further investigation.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"23 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the diagnostic role of exosome-derived miRNAs in postoperative septic shock and non-septic shock patients","authors":"Adrián García-Concejo, Belén Sánchez-Quirós, Esther Gómez-Sánchez, Laura Sánchez-de Prada, Álvaro Tamayo-Velasco, María Sherezade Tovar-Doncel, Mario Lorenzo, Estefanía Gómez-Pesquera, Rodrigo Poves-Álvarez, David Bernardo, Marta Martín-Fernández, Hugo Gonzalo-Benito, Paula Moreno-Portales, Rosa Prieto-Utrera, Miguel Bardají-Carrillo, Rocío López-Herrero, María Fernández Arranz, Rosario Calaveras-Fernández, Fé Tomillo-Cebrián, Teresa Aydillo, María Ángeles Jiménez-Sousa, Amanda Fernández-Rodríguez, Salvador Resino, María Heredia-Rodríguez, Pedro Martínez-Paz, Eduardo Tamayo","doi":"10.1186/s13054-025-05320-y","DOIUrl":"https://doi.org/10.1186/s13054-025-05320-y","url":null,"abstract":"Diagnosing septic shock promptly is essential but challenging, especially due to its clinical similarity to non-septic shock. Extracellular vesicle-derived miRNAs may serve as biomarkers to distinguish septic shock from non-septic shock, providing a more accurate diagnostic tool for postsurgical patients. This study aims to identify extracellular vesicle-derived miRNA signatures that differentiate septic shock from non-septic shock in postsurgical patients, potentially improving diagnostic accuracy and clinical decision-making. A multicentre, prospective study was conducted on miRNA profiles in shock patients. Two cohorts were recruited from the Intensive Care Units of two Spanish hospitals: a discovery cohort with 109 patients and a validation cohort with 52 patients. Plasma samples were collected within 24 h of shock diagnosis and subjected to miRNA sequencing. High-throughput sequencing data from the discovery cohort were analysed to identify differentially expressed miRNAs. These findings were validated via qPCR in the validation cohort. Thirty miRNAs were identified as significantly differentially expressed between septic and non-septic shock patients. Among these, six miRNAs—miR-100-5p, miR-484, miR-10a-5p, miR-148a-3p, miR-342-3p, and miR-451a—demonstrated strong diagnostic capabilities for septic shock. A combination of miR-100-5p, miR-148a-3p, and miR-451a achieved an area under the curve of 0.894, with qPCR validation in the validation cohort yielding an area under the curve of 0.960. This study highlights extracellular vesicle-derived miRNAs as promising biomarkers for differentiating septic from non-septic shock. The identified three-miRNA signature has significant potential to enhance septic shock diagnosis, thereby aiding in timely and appropriate treatment for postsurgical patients.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"117 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrical impedance tomography-guided the optimal awake prone position in a moderate ARDS patient","authors":"Yongzhen Sun, Jiale Tao, Jinjun Jiang, Shujing Chen","doi":"10.1186/s13054-025-05332-8","DOIUrl":"https://doi.org/10.1186/s13054-025-05332-8","url":null,"abstract":"&lt;p&gt;Awake prone positioning (APP) has gained prominence as a therapeutic intervention for acute respiratory distress syndrome (ARDS), particularly in COVID-19-related respiratory failure due to its proven survival benefits [1, 2]. However, the clinical applicability of APP in non-COVID-19 ARDS populations remains controversial, with patient tolerance and heterogeneous lung recruitment responses posing significant challenges [3]. To address these limitations, electromagnetic impedance tomography (EIT)—a non-invasive, radiation-free imaging modality—provides dynamic regional ventilation monitoring through real-time bedside visualization of pulmonary impedance changes [4]. We illustrate the integration of EIT-derived ventilation mapping to guide personalized positioning strategies in a non-intubated patient with moderate ARDS, demonstrating its potential to optimize alveolar recruitment while mitigating positional intolerance.&lt;/p&gt;&lt;p&gt;A 61-year-old female with stage IIIC lung cancer, previously treated with chemotherapy and immune checkpoint inhibitors (ICIs), developed fatal ICI-related myocarditis. Two months post-treatment, she presented with dyspnea and acute hypoxic respiratory failure (P/F ratio: 143 mmHg, ROX index: 5.6, on high-flow nasal cannula (HFNC)) due to Pneumocystis jirovecii pneumonia (PCP). However, standard awake prone positioning was contraindicated due to worsening chest tightness and dyspnea. Over three days, we continuously monitored S/F ratio, respiratory rate, and ROX index using EIT while testing various positional adjustments (Fig. 1 A–F). The “Thinker’s position” demonstrated optimal oxygenation and was maintained for approximately 6 h daily, which was her tolerance limit [5]. The patient was successfully weaned from HFNC after 12 days. Follow-up CT at day 17 showed significant inflammatory resolution, and she was discharged on day 18.&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"figure-caption-text\"&gt;Fig. 1&lt;/b&gt;&lt;/figcaption&gt;&lt;picture&gt;&lt;source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05332-8/MediaObjects/13054_2025_5332_Fig1_HTML.png?as=webp\" type=\"image/webp\"/&gt;&lt;img alt=\"figure 1\" aria-describedby=\"Fig1\" height=\"760\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13054-025-05332-8/MediaObjects/13054_2025_5332_Fig1_HTML.png\" width=\"685\"/&gt;&lt;/picture&gt;&lt;p&gt;Changes in lung ventilation status and S/F, RR, and ROX of the patient in different positions under EIT monitoring. &lt;b&gt;A&lt;/b&gt; shows the EIT images from the first day to the third day. The images in each panel from top to bottom are: global impedance waveforms, tidal impedance variation distribution (RVD: region ventilation delay, in yellow), difference image (CW: compliance win, in turquoise; CL: compliance loss, in orange), and data trend chart. (I), (II), (III), and (IV) in Figure A represent the supine position, semi-recumbent position, “Thinker’s position”, and prone position respectively, and ea","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"36 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143532702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}