Critical Care最新文献

{"title":"Impact of age and mean intracranial pressure on the morphology of intracranial pressure waveform and its association with mortality in traumatic brain injury","authors":"Magdalena Kasprowicz, Cyprian Mataczyński, Agnieszka Uryga, Adam I. Pelah, Eric Schmidt, Marek Czosnyka, Agnieszka Kazimierska","doi":"10.1186/s13054-025-05295-w","DOIUrl":"https://doi.org/10.1186/s13054-025-05295-w","url":null,"abstract":"Morphological analysis of intracranial pressure (ICP) pulse waveforms provides indirect information on cerebrospinal compliance, which might be reduced by space-occupying lesions but also by intracranial hypertension and aging. This study investigates the impact of age and mean ICP on the shape and amplitude of ICP pulse waveform in traumatic brain injury (TBI). Additionally, it explores the association between morphological parameters and mortality after TBI. ICP recordings from 183 TBI patients (median age: 50 (30, 61) years) from the CENTER-TBI database were retrospectively analyzed. ICP morphology was assessed using the artificial intelligence-based pulse shape index (PSI) and peak-to-peak amplitude of ICP pulse waveform (AmpICP). The impact of mean ICP, age, and their interaction on PSI and AmpICP were estimated using factorial ANOVA. To account for influence of disturbance in the intracranial volume on AmpICP and PSI, a multiple regression analysis was performed using age, mean ICP, and the Rotterdam CT score as explanatory variables. The associations of AmpICP and PSI with six-month mortality were assessed using the area under the ROC curve (AUC). Age had a predominant influence on PSI (p < 0.01), accounting for 33.1% of its variance, while mean ICP explained 6.6% (p < 0.01). Conversely, mean ICP primarily affected AmpICP (p < 0.01), explaining 22.8% of its variance, with age contributing 8.0% (p < 0.01). A combined effect of age and mean ICP on AmpICP (p = 0.01) explained 11.7% of its variance but did not influence PSI. After accounting for Rotterdam CT score, the results remained consistent, indicating that advanced age has the strongest impact on PSI (β = 0.342, p < 0.01) while elevated mean ICP has dominant influence on AmpICP (β = 0.522, p < 0.01). Both AmpICP and PSI were moderately associated with mortality (AUC: 0.76 and 0.71, respectively). AmpICP and PSI capture distinct aspects of cerebrospinal compliance. PSI appears to reflect age-related stiffening of the cerebrovascular system, while AmpICP, influenced by mean ICP, indicates acute volume compensatory changes. Combined, they provide a more comprehensive assessment of cerebrospinal volume–pressure compensation. Both morphological metrics are associated with mortality after TBI. As cerebrospinal compliance declines with age, older TBI patients become more susceptible to uncontrolled rises in ICP, which can worsen their outcome.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"180 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143434987","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":"Urinary proteomics in sepsis-associated AKI","authors":"Jill Moser, Tamar J. van der Aart, Hjalmar R. Bouma","doi":"10.1186/s13054-025-05306-w","DOIUrl":"https://doi.org/10.1186/s13054-025-05306-w","url":null,"abstract":"&lt;p&gt;To the Editor,&lt;/p&gt;&lt;p&gt;We read with interest the recent article by Stanaway et al. titled &lt;i&gt;“Urinary proteomics identifies distinct immunological profiles of sepsis-associated AKI sub-phenotypes”&lt;/i&gt; [1]. The study represents a significant advancement in understanding acute kidney injury (AKI) in sepsis through urinary proteomics, offering promising insights to improve early recognition, predict responses to therapy, and implement or develop targeted treatment strategies. However, some aspects of the study warrant further discussion.&lt;/p&gt;&lt;p&gt;The observation that bacterial infections were more common in AKI-SP2, whereas COVID-19 predominated in AKI-SP1, supports the phenotype of endothelial dysfunction and inflammation. However, this raises the question of whether AKI-SP2 represents a distinct AKI sub-phenotype or reflects endothelial dysfunction typically associated with bacterial sepsis. Additionally, the observed overlap of proteins associated with AKI-SP2 and those linked to the risk of renal replacement therapy (RRT) raises the question of whether AKI-SP2 represents a distinct sub-phenotype or reflects a continuum of severe AKI. Clarification of this overlap could enhance our biological understanding of these processes. Moreover, the finding that urinary proteomic profiles of AKI-SP1 were largely similar to those of non-AKI patients suggests the need to refine diagnostic thresholds or explore alternative biomarker panels to improve classification accuracy. Addressing this issue may require the use of more specific biomarkers directly associated with the pathophysiological mechanisms of AKI to improve patient phenotyping. Given the study’s emphasis on urinary proteomics, defining sub-phenotypes directly from urinary proteomic data seems feasible, potentially yielding kidney-specific classifications that more accurately reflect local injury processes, which could enable tailored therapeutic strategies.&lt;/p&gt;&lt;p&gt;The timing of sample collection from patients with sepsis remains a significant challenge as the onset and progression of critical symptoms can vary widely between individuals. This variability is influenced by patient-related factors, type of pathogen involved, and specific organs affected. Given the dynamic progression of sepsis, aligning sample collection more precisely with the timing of sepsis onset could reduce variability and improve data consistency; however, this remains an extremely challenging, if not impossible, task. Alternatively, patients could be aligned based on the onset of AKI as defined by the KDIGO guidelines [2] or using predictive or functional AKI biomarkers such as Cystatin C rather than ICU admission, which may provide a more clinically relevant timeline for analysis, reduce inter-patient variability, and provide a clearer picture of AKI-related changes in urinary proteomic profiles as AKI evolves. Longitudinal analysis with repeated sampling could enable the identification of temporal proteomic changes associated ","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"67 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417251","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":"Early high-sensitivity troponin elevation and short-term mortality in sepsis: a systematic review with meta-analysis","authors":"Abraham I. J. Gajardo, Santiago Ferrière-Steinert, Joaquín Valenzuela Jiménez, Sebastián Heskia Araya, Thomas Kouyoumdjian Carvajal, José Ramos-Rojas, Juan Nicolás Medel","doi":"10.1186/s13054-025-05249-2","DOIUrl":"https://doi.org/10.1186/s13054-025-05249-2","url":null,"abstract":"Serum cardiac troponin (cTn) elevation is a well-established phenomenon in sepsis. However, the clinical significance of this phenomenon with high-sensitivity (hs) assays and the current sepsis definition needs to be settled. What is the association between early serum cTn levels measured by hs-assays and the risk of short-term mortality in septic patients? We conducted a systematic review using a comprehensive PubMed, Scopus, and Embase search. Studies were eligible if they reported association data on early hs-cTn and mortality in an adult sample with sepsis that met the Sepsis-3 definition. For the synthesis of the effect of hs-cTn on mortality, we applied random effect models on the pooled unadjusted and adjusted odds ratio (OR and aOR, respectively) of elevated vs. normal hs-cTn serum values, and on the crude standardized mean difference (SMD) of hs-cTn between survivors and non-survivors. In total, 6242 patients from 17 studies were included, with short-term mortality rates ranging from 16.9% to 53.8%. Using a crude analysis, non-survivor patients showed higher hs-cTn than survivors (SMD of 0.87, 95%CI: 0.41–1.33). Elevated hs-cTn was associated with increased mortality (OR = 1.78, 95% CI: 1.41–2.25). However, this prognostic effect was absent in studies that adjusted for different confounders (aOR = 1.06, 95% CI: 0.99–1.14). Non-survivors of sepsis exhibited significantly elevated hs-cTn levels. While elevated hs-cTn levels are associated with an increased risk of mortality, they are not independently associated with this outcome in sepsis.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"64 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143418360","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 to: Retrospective ANalysis of multi-drug resistant Gram-nEgative bacteRia on veno-venous extracorporeal membrane oxygenation. The multicenter RANGER STUDY","authors":"Annalisa Boscolo, Andrea Bruni, Marco Giani, Eugenio Garofalo, Nicolò Sella, Tommaso Pettenuzzo, Michela Bombino, Matteo Palcani, Emanuele Rezoagli, Matteo Pozzi, Elena Falcioni, Elisa Pistollato, Eugenio Biamonte, Francesco Murgolo, Graziella D’Arrigo, Mercedes Gori, Giovanni Luigi Tripepi, Leonardo Gottin, Federico Longhini, Salvatore Grasso, Paolo Navalesi, Giuseppe Foti","doi":"10.1186/s13054-024-05231-4","DOIUrl":"https://doi.org/10.1186/s13054-024-05231-4","url":null,"abstract":"&lt;p&gt;&lt;b&gt;Correction: Critical Care (2024) 28:279 &lt;/b&gt; &lt;b&gt;https://doi.org/10.1186/s13054-024-05068-x&lt;/b&gt;&lt;/p&gt;&lt;p&gt;Following publication of the original article [1], the authors identified an error in Tables 1–4. There were values missing in Table 3 and alignment/indention errors in Tables 1–4. Both the incorrect and correct tables are given hereafter.\u0000&lt;/p&gt;&lt;p&gt;The incorrect Table 1:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 1 Patients’ characteristics at V–V ECMO connection&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The correct Table 1:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 1 Patients’ characteristics at V-V ECMO connection.&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The incorrect Table 2:\u0000&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 2 Outcomes&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The correct Table 2:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 2 Outcomes.&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The incorrect Table 3:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 3 Microbiological characteristics of MDR GN bacteria&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The correct Table 3:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 3 Microbiological characteristics of MDR GN bacteria.&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The incorrect Table 4:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 4 Concomitant pathogens and antibiotics.&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size table&lt;/span&gt;&lt;svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"&gt;&lt;use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"&gt;&lt;/use&gt;&lt;/svg&gt;&lt;/figure&gt;&lt;p&gt;The correct Table 4:&lt;/p&gt;&lt;figure&gt;&lt;figcaption&gt;&lt;b data-test=\"table-caption\"&gt;Table 4 Concomitant pathogens and antibiotics.&lt;/b&gt;&lt;/figcaption&gt;&lt;span&gt;Full size","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"128 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143401651","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":"The acute microbiota injury","authors":"Sylvain Diop, Maxime Aparicio, Roman Mounier","doi":"10.1186/s13054-025-05312-y","DOIUrl":"https://doi.org/10.1186/s13054-025-05312-y","url":null,"abstract":"&lt;p&gt;Dear editor,&lt;/p&gt;&lt;p&gt;Hospital acquired infection (HAI) in intensive care unit (ICU) is a major public health issue associated with increased morbi-mortality and costs. Over the years our perception and our understanding of the pathophysiology of HAI as evolved but the treatment remains basically limited to antimicrobial therapy [1]. In critically ill patients, there is evidence that the alteration of the interaction between the immune system and the microbiota could promotes the occurrence of HAI [1]. Accordingly, limiting microbiota injuries during the ICU stays could be a major mean to prevent HAI.&lt;/p&gt;&lt;p&gt;Nowadays, it is well established that all the epithelia are colonized by a diverse and dynamic living ecosystem composed of microorganisms, viruses and fungi. The microbiota, referring to the different communities of bacteria living symbiotically with our epithelia, participate to the proper development and functioning of our metabolic pathways (i.e. cognitive and immunity development) through a constant crosstalk between host and bacteria [2]. These microbiotas are constitutive of the human being [3,4,5]. We are not only a multicellular eukaryotes organism but a holobiont, an assemblage of different species of organisms, a &lt;i&gt;Homo microbicus.&lt;/i&gt; [2, 6]&lt;/p&gt;&lt;p&gt;Healthy microbiota promotes host defense effectors, plays the role of a physical and functional barriers and inhibits the growth of pathogenic bacteria [7]. Conversely, altered microbiota (i.e. dysbiosis) plays an important role on the pathophysiology of immune and inflammatory disease: skin microbiotal dysbiosis is associated with the onset of atopic dermatitis, alteration of lung microbiota may be associated with asthma development and/or hospital-acquired pneumonia and gut microbiota dysbiosis plays a predominant role in Crohn’s disease [1, 8] Immunity and microbiota are interdependent, thus the alteration of one could lead to the alteration of the other [9].&lt;/p&gt;&lt;p&gt;Critically ill patients are exposed to conditions that impaired one or more physiologic functions commonly referred as acute injury (i.e. acute lung injury, acute kidneys injury). These injuries could result of either the direct hit of the organ or the consequences of an acute systemic response leading to potential complications and worsened outcomes.&lt;/p&gt;&lt;p&gt;As for other organs, the function of microbiota could be impaired in case of acute injury and strained its resilience. In critically ills patients, several factors, some intrinsic, some related to the underlying disease or iatrogenic, may promote dysbiosis (decrease in bacterial diversity, loss of commensal bacteria and increase of pathogenic bacterial inoculum) [1]. Accordingly, the alteration of lung microbiota is associated with the development of hospital-acquired pneumonia and acute respiratory syndrome [1]. Likewise, gut microbiota dysbiosis promotes colitis and play a role in acute kidneys injury [10].&lt;/p&gt;&lt;p&gt;These considerations lead us to propose the term of acut","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"15 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143401652","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":"Death by p-value: the overreliance on p-values in critical care research","authors":"Sharad Patel, Adam Green","doi":"10.1186/s13054-025-05307-9","DOIUrl":"https://doi.org/10.1186/s13054-025-05307-9","url":null,"abstract":"The p-value has changed from a versatile tool for scientific reasoning to a strict judge of medical information, with the usual 0.05 cutoff frequently deciding a study’s significance and subsequent clinical use. Through an examination of five critical care interventions that demonstrated meaningful treatment effects yet narrowly missed conventional statistical significance, this paper illustrates how rigid adherence to p-value thresholds may obscure therapeutically beneficial findings. By providing a clear, step-by-step illustration of a basic Bayesian calculation, we demonstrate that clinical importance can remain undetected when relying solely on p-values. These observations challenge current statistical paradigms and advocate for hybrid approaches—including both frequentist and Bayesian methodologies—to provide a more comprehensive understanding of clinical data, ultimately leading to better-informed medical decisions.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"58 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143393391","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":"Comparative evaluation and performance of large language models on expert level critical care questions: a benchmark study","authors":"Jessica D. Workum, Bas W. S. Volkers, Davy van de Sande, Sumesh Arora, Marco Goeijenbier, Diederik Gommers, Michel E. van Genderen","doi":"10.1186/s13054-025-05302-0","DOIUrl":"https://doi.org/10.1186/s13054-025-05302-0","url":null,"abstract":"Large language models (LLMs) show increasing potential for their use in healthcare for administrative support and clinical decision making. However, reports on their performance in critical care medicine is lacking. This study evaluated five LLMs (GPT-4o, GPT-4o-mini, GPT-3.5-turbo, Mistral Large 2407 and Llama 3.1 70B) on 1181 multiple choice questions (MCQs) from the gotheextramile.com database, a comprehensive database of critical care questions at European Diploma in Intensive Care examination level. Their performance was compared to random guessing and 350 human physicians on a 77-MCQ practice test. Metrics included accuracy, consistency, and domain-specific performance. Costs, as a proxy for energy consumption, were also analyzed. GPT-4o achieved the highest accuracy at 93.3%, followed by Llama 3.1 70B (87.5%), Mistral Large 2407 (87.9%), GPT-4o-mini (83.0%), and GPT-3.5-turbo (72.7%). Random guessing yielded 41.5% (p < 0.001). On the practice test, all models surpassed human physicians, scoring 89.0%, 80.9%, 84.4%, 80.3%, and 66.5%, respectively, compared to 42.7% for random guessing (p < 0.001) and 61.9% for the human physicians. However, in contrast to the other evaluated LLMs (p < 0.001), GPT-3.5-turbo’s performance did not significantly outperform physicians (p = 0.196). Despite high overall consistency, all models gave consistently incorrect answers. The most expensive model was GPT-4o, costing over 25 times more than the least expensive model, GPT-4o-mini. LLMs exhibit exceptional accuracy and consistency, with four outperforming human physicians on a European-level practice exam. GPT-4o led in performance but raised concerns about energy consumption. Despite their potential in critical care, all models produced consistently incorrect answers, highlighting the need for more thorough and ongoing evaluations to guide responsible implementation in clinical settings.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"41 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375402","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":"Pertussis infection in critically ill infants: meta-analysis and validation of a mortality score","authors":"Vladimir L. Cousin, Caroline Caula, Jason Vignot, Raphael Joye, Matthieu Blanc, Clémence Marais, Pierre Tissières","doi":"10.1186/s13054-025-05300-2","DOIUrl":"https://doi.org/10.1186/s13054-025-05300-2","url":null,"abstract":"Despite widespread vaccination programs, pertussis continues circulating within populations and remains a life-threatening infection in infants. While several mortality risk factors have been described, a comprehensive synthesis is lacking. We conducted a meta-analysis of studies investigating mortality risk factors in Pertussis infections and validated those factors in a large cohort. Observational studies published in English were systematically searched in PubMed, EMBASE, and LiSSa databases from 01/2000 to 06/2024. The search yielded 816 unique citations. The primary outcome was mortality before discharge from the Pediatric Intensive Care Unit (PICU). Two independent reviewers assessed the risk of bias and extracted data. A REML-random effect model was used to calculate pooled prevalence and conduct the analysis. The identified risk factors were subsequently evaluated in a monocentric cohort of patients admitted to a tertiary hospital’s PICU for severe pertussis between January 1996 and December 2020. Data analysis was conducted between June and August 2024. Seventeen studies, including 2,725 patients, met the inclusion criteria. The pooled prevalence of mechanical ventilation, continuous renal replacement therapy, and Extracorporeal Membrane Oxygenation support were 55% (95% CI: 40–70; I2 = 98), 15% (95% CI: 3–27; I2 = 95), and 8% (95% CI: 3–12; I2 = 93), respectively. The pooled mortality incidence was 19% (95% CI:12–26; I2 = 96). Identified mortality risk factors included elevated heart rate, presence of pulmonary hypertension, presence of seizures, and elevated white blood cell (WBC) count. Validation in an 83-patient cohort (median age: 45 days, IQR: 30–55) revealed a mortality rate of 12%. Risk factors identified in the meta-analysis were significantly associated with non-survival in the cohort. A mortality prediction score was developed incorporating age < 30 days, heart rate > 200/min, and WBC > 30 G/l, achieving an area under the curve of 0.92 (95% CI: 0.86–0.99). This meta-analysis identified a simple yet effective score to assess the severity of pertussis infection in infants admitted to PICU. Accurate risk stratification may enable timely treatment of critically ill patients, potentially improving outcomes. Trial registration: The study protocol was registered on PROSPERO: CRD42024582057. ","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"9 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375403","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":"Authors’ response to: Relationship between leukopenia and mortality among patients with haematological malignancies","authors":"Aleece MacPhail, Michael Bailey, David Pilcher, Zoe McQuilten","doi":"10.1186/s13054-025-05272-3","DOIUrl":"https://doi.org/10.1186/s13054-025-05272-3","url":null,"abstract":"&lt;p&gt;To the editor,&lt;/p&gt;&lt;p&gt;We thank Caibao et al. [1] for taking the time to comment on our study “Sepsis mortality among patients with haematological malignancy admitted to Intensive Care 2000–2022: a binational cohort study\" [2], recently published in &lt;i&gt;Critical Care&lt;/i&gt;.&lt;/p&gt;&lt;p&gt;We agree that the relationship between leukopenia (a surrogate for neutropenia) and sepsis mortality in patients with haematological malignancies is complex. In our retrospective cohort study of patients with sepsis and haematological malignancies, we fitted a single mixed effects multivariable logistic regression model to identify risk factors for mortality. In this model we included an interaction term between leukopenia and haematological malignancy (leukopenia x HM status), each coded as a binary variable, with leukopenia defined as total white cell count &lt; 1.0 × 10&lt;sup&gt;9&lt;/sup&gt; cells/L. In our model output we report the marginal effect of neutropenia in the presence or absence of haematological malignancy. This choice was made for interpretability and clinical relevance. For clinicians, the impact of neutropenia on mortality risk for septic patients with haematological malignancy is important to guide prognostication, escalation of treatment, and recognition of non-neutropenic patients in local guidelines for management of sepsis.&lt;/p&gt;&lt;p&gt;As noted by Caibao and colleagues, we further observed that leukopenia was associated with mortality in a univariable model, both in the presence and absence of haematological malignancy, but not in a multivariable model. Formal assessment of collinearity was performed using variance inflation factor (VIF) and all included variables had VIF &lt; 10. This indicates that while crude mortality was higher in the neutropenic group, after adjustment for confounders including age, illness severity and year of admission, this was non-significant. Our findings are in keeping with previous studies reporting that neutropenia alone is not necessarily predictive of mortality after confounders including illness severity are accounted for [3, 4].&lt;/p&gt;&lt;p&gt;The complex relationship between leukopenia and mortality in septic patients with haematological malignancies warrants further study. Based on existing data, neutropenic patients should not be assumed to have a poorer prognosis, and sepsis in non-neutropenic patients should not be under-estimated.&lt;/p&gt;&lt;p&gt;No datasets were generated or analysed during the current study.&lt;/p&gt;&lt;ol data-track-component=\"outbound reference\" data-track-context=\"references section\"&gt;&lt;li data-counter=\"1.\"&gt;&lt;p&gt;Hu C, Li Q, Ding X. Relationship between leukopenia and mortality among patients with hematological malignancies. Crit Care. 2025;28:402.&lt;/p&gt;&lt;p&gt;Article Google Scholar &lt;/p&gt;&lt;/li&gt;&lt;li data-counter=\"2.\"&gt;&lt;p&gt;MacPhail A, Dendle C, Slavin M, Weinkove R, Bailey M, Pilcher D, et al. Sepsis mortality among patients with haematological malignancy admitted to intensive care 2000–2022: a binational cohort study. Crit Care. 2024;28(1):148.&lt;/","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"47 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143375404","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":"Noninvasive multimodal neuromonitoring in patients with post-cardiac arrest brain injury: a survey from China’s intensive care units","authors":"Yankang Ren, Xiaoxue Nie, Haiyan Liu, Tao Jiang, Yuan Bian, Feng Xu, Yuguo Chen, Xianfei Ji","doi":"10.1186/s13054-025-05293-y","DOIUrl":"https://doi.org/10.1186/s13054-025-05293-y","url":null,"abstract":"&lt;p&gt;Post-cardiac arrest brain injury (PCABI) exerts a profound impact on mortality and long-term disability of patients who undergo cardiac arrest (CA) and subsequently achieve the return of spontaneous circulation following cardiopulmonary resuscitation [1]. The primary aim of post-resuscitation therapy is to mitigate neurological damage to the greatest extent possible, necessitating comprehensive neurological monitoring and preventive strategies. The 2021 International Guidelines recommend several predictors for assessing the neurological prognosis of CA survivors [2]. Recently, a novel approach known as multimodal monitoring (MMM) has come to the fore [3], employing advanced technologies to monitor real-time brain pathophysiological changes and evaluate brain function. Nevertheless, the function of MMM in appraising neurological function and prognosticating outcomes among CA patients remains in the exploratory stage within intensive care units (ICUs). The objective of our survey was to provide a holistic understanding of the current practical applications of noninvasive MMM for patients with PCABI across various regions within Chinese ICUs.&lt;/p&gt;&lt;p&gt;The questionnaire was devised by our research team and comprised 13 questions, categorized into four primary themes: 1) information related to the healthcare organizations, 2) current practices concerning MMM items, 3) the existing provision of monitoring instruments and 4) assessment and expectations regarding MMM.&lt;/p&gt;&lt;p&gt;A cohort of 109 ICU professionals were identified across 7 Chinese regions. During the period from September to October 2024, participants were invited to complete the questionnaire via the WPS form. The collected responses were analyzed underwent descriptive analysis of quantitative and qualitative data.&lt;/p&gt;&lt;p&gt;Among the respondents predominantly working in Emergency Intensive Care Units, 73.4% were affiliated with Class IIIA medical units (Additional file 1: Table S1), and the majority located in Eastern China (67.9%). Regarding the bed capacity of the participants’ departments, those with 11–20 beds constituted the largest cohort at 31.2%. Furthermore, departments that admit CA patients and perform extracorporeal cardiopulmonary resuscitation (ECPR) annually reported rates of up to 46.8% and 54.1%, respectively.&lt;/p&gt;&lt;p&gt;The survey disclosed that merely 36.7% of participants employed MMM, falling short of 50%. A preponderant majority of respondents strongly concurred on the significance of MMM for early diagnosis, severity assessment, treatment planning, and prognostic evaluation. Furthermore, a majority of participants expressed a moderate level of trust in the results derived from MMM (68.8%) in clinical practice. Looking ahead, 89.0% of participants expressed their intention to actively introduce or augment the application of MMM in clinical settings (Additional file 1: Tables S2).&lt;/p&gt;&lt;p&gt;Among the assorted monitoring methods associated with MMM (Fig. 1), brain imaging examination (9","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"44 1","pages":""},"PeriodicalIF":15.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143258634","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}