Journal of critical care最新文献

{"title":"Letter to the editor: \"Risk factors associated with acute kidney injury in patients with traumatic brain injury: A systematic review and meta-analysis\".","authors":"Julien Moury, Nathan De Lissnyder, Soufiane Habryka, Sydney Blackman, Sarah Dahma, Ilann Oueslati, Patrick M Honore","doi":"10.1016/j.jcrc.2025.155218","DOIUrl":"https://doi.org/10.1016/j.jcrc.2025.155218","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"155218"},"PeriodicalIF":2.9,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144816802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor: \"Reversal of antithrombotics in the critically ill: An international online survey\".","authors":"Bülent Özlek, Veysel Ozan Tanık, Kürşat Akbuğa, Ali Sezgin","doi":"10.1016/j.jcrc.2025.155215","DOIUrl":"https://doi.org/10.1016/j.jcrc.2025.155215","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"155215"},"PeriodicalIF":2.9,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144812090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor: \"Risk factors associated with acute kidney injury in patients with traumatic brain injury: A systematic review and meta-analysis\".","authors":"Aishwarya Raparthi, Sharanya Kumar Bavurothu","doi":"10.1016/j.jcrc.2025.155217","DOIUrl":"https://doi.org/10.1016/j.jcrc.2025.155217","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"155217"},"PeriodicalIF":2.9,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144812091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach.","authors":"Renée A M Tuinte, Nicolaas Heyning, Annebel Ten Broeke, Hugo R W Touw, Jaap Ten Oever, Jacobien J Hoogerwerf","doi":"10.1016/j.jcrc.2025.155214","DOIUrl":"https://doi.org/10.1016/j.jcrc.2025.155214","url":null,"abstract":"<p><strong>Objectives: </strong>To identify relevant objective variables for retrospective identification of 'suspected infection' and sepsis, using behavioural artificial intelligence technology (BAIT), and to explore the accuracy of this approach for sepsis surveillance.</p><p><strong>Methods: </strong>BAIT uses choice behaviour analysis to make implicit expert knowledge explicit. Online choice experiments with 25-30 hypothetical retrospective patient scenarios were composed, each consisting of objective variables relevant to sepsis surveillance. Experts reviewed these scenarios and labelled them as 'sepsis' or 'no sepsis'. Two rounds were conducted: round 1 focused on a sepsis surveillance definition, round 2 only on 'suspected infection' in patients with a qSOFA≥2. Relative importance (RI) of variables was calculated using binary logistic regression. Model accuracy was assessed using an expert adjudicated sepsis database.</p><p><strong>Results: </strong>In round 1, 22 experts participated. Temperature (RI 24 %), CRP (RI 18 %) and systolic blood pressure (RI 16 %) contributed most to sepsis identification, respectively. Model accuracy was 74 % (sensitivity 87 %, specificity 66 %). Round 2 involved 21 experts. Focusing on 'suspected infection', CRP (RI 27 %), temperature (RI 18 %) and leukocyte count (RI 11 %) were most important, respectively. Model accuracy was 75 % (sensitivity 83 %, specificity 71 %).</p><p><strong>Conclusion: </strong>Inflammatory parameters contributed most to retrospective sepsis and 'suspected infection' identification by experts. BAIT-model accuracy for surveillance was 74-75 %.</p>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"155214"},"PeriodicalIF":2.9,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144812089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immediate \"sipping\" vs. delayed oral fluid intake after extubation: A randomized controlled trial.","authors":"Šárka Sedláčková, Věra Nigrovičová, Monika Pecková, Miroslav Durila","doi":"10.1016/j.jcrc.2025.155212","DOIUrl":"https://doi.org/10.1016/j.jcrc.2025.155212","url":null,"abstract":"<p><strong>Purpose: </strong>Despite advances in perioperative care, delayed oral fluid intake after extubation remains common and is often based on tradition rather than evidence. This study aimed to evaluate whether immediate oral fluid intake \"sipping\" after extubation reduces thirst and discomfort and is safe in an intensive care setting.</p><p><strong>Methods: </strong>In this single-center, prospective, randomized controlled trial, 160 ICU patients who met extubation criteria were randomized 1:1 to either delayed fluid intake (2 h post-extubation) or immediate sipping (up to 3 ml/kg over 2 h). Thirst, discomfort, and adverse effects (nausea, vomiting, aspiration) were assessed at 0, 5, 30, 60, 90, and 120 min. Thirst relief was also evaluated in the experimental group. Statistical significance was set at p < 0.05.</p><p><strong>Results: </strong>At 120 min, 64 of 80 patients in each group (80 %; 95 % CI: 70-88 %) reported thirst. The difference between groups was 0.0 % (95 % CI: -12 % to 12 %; p = 1.000). However, thirst relief between baseline and 120 min was observed in 11.3 % of patients in the sipping group (95 % CI: 5-20 %) vs. 1.3 % in the standard group (95 % CI: 0-7 %), with a difference of 10 % (95 % CI: 1-19 %; p = 0.0338). At 90 min, throat discomfort was present in 23.8 % of the sipping group (95 % CI: 15-35 %) vs. 42.5 % in the standard group (95 % CI: 32-54 %), with a difference of -18.7 % (95 % CI: -34 % to -3 %; p = 0.0118). Adverse effects (nausea, vomiting) were rare and comparable; no aspiration events were observed.</p><p><strong>Conclusion: </strong>Immediate oral fluid intake \"sipping\"after extubation appears to be safe, improves thirst relief, and reduces discomfort in ICU patients without increasing adverse effects. These findings challenge traditional fasting practices and support early rehydration in post-extubation care.</p><p><strong>Trial registration: </strong>The trial was registered at ClinicalTrials.gov on January 6, 2023 (Identifier: NCT05819645).</p>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"155212"},"PeriodicalIF":2.9,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144804206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mixed methods evaluation of a digital tool to support the transfer of medication information from ICU to ward.","authors":"Melissa T Baysari, Kristian Stanceski, Bethany A Van Dort, Jacques Raubenheimer, Lily Pham, Danielle Deidun, Adeola Bamgboje-Ayodele, Duncan Mackay, Jonathan Penm, Kevin Sam, Selvana Awad, Gordon Flynn, Atul Gaur, Stuart Lane","doi":"10.1016/j.jcrc.2025.155219","DOIUrl":"https://doi.org/10.1016/j.jcrc.2025.155219","url":null,"abstract":"<p><strong>Background: </strong>Transfer of medication information from intensive care units (ICUs) to general wards is error prone. Additional challenges emerge in hospitals where a different electronic medical record (eMR) is used in ICU and wards. Digital transfer systems, that support information transfer between different eMRs, could minimise errors, but limited research has evaluated these. We aimed to 1) determine the impact of eTOC, a medication transfer system, on medication errors and potential patient harms that occur during ICU-to-ward transfers, 2) to determine frequency of eTOC use post-implementation, and 3) explore how eTOC is used and viewed by clinicians.</p><p><strong>Methods: </strong>A mixed methods approach was used at one metropolitan and one regional hospital in NSW, Australia. Part 1 comprised a pragmatic pre-post chart-review study (n = 200 patient transfers) and Part 2 used a qualitative approach, including usability testing (n = 4) and semi-structured interviews with clinicians (n = 11).</p><p><strong>Results: </strong>Implementation of the eTOC system did not significantly reduce the number of transfers containing an error (51 % vs 46 %, pre-post). Although the use of eTOC more than halved the odds of a medication error occurring (OR: 0.44, 95 %CI: 0.27-0.71), the system was inconsistently used. Interviews and usability testing revealed that barriers related both to system design/configuration and to the context of use and organisation (e.g., time pressure) impacted uptake of eTOC.</p><p><strong>Conclusions: </strong>There is significant potential for technology to support transfer of medication information from ICU to the ward and improve safety if technology is designed well and aligns with how work is done in practice.</p>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"155219"},"PeriodicalIF":2.9,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144804207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Authors reply: “Reversal of antithrombotics in the critically ill: An international online survey”","authors":"Stefan F. van Wonderen,&nbsp;Maite M.T. van Haeren,&nbsp;Alexander P.J. Vlaar,&nbsp;Marcella C.A. Müller","doi":"10.1016/j.jcrc.2025.155216","DOIUrl":"10.1016/j.jcrc.2025.155216","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"91 ","pages":"Article 155216"},"PeriodicalIF":2.9,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sharing is caring: A systematic review of publicly available intensive care data sets","authors":"A.R. Jagesar ,&nbsp;T.A. Dam ,&nbsp;T. Struja ,&nbsp;C.M. Sauer ,&nbsp;M. Otten ,&nbsp;L.A. Biesheuvel ,&nbsp;A.R.J. Girbes ,&nbsp;L. Adhikari ,&nbsp;Z. Zhang ,&nbsp;M. Faltys ,&nbsp;N. Rodemund ,&nbsp;P.J. Thoral ,&nbsp;L.A. Celi ,&nbsp;P.W.G. Elbers","doi":"10.1016/j.jcrc.2025.155205","DOIUrl":"10.1016/j.jcrc.2025.155205","url":null,"abstract":"<div><h3>Introduction</h3><div>Multiple Intensive Care Unit (ICU) databases have been publicly released to advance data driven intensive care medicine. However, these public ICU data sets are prone to changes, updates and new releases. Therefore, the goal of this review is to provide clinicians and data scientists with a state-of-the-art overview and guide for choosing the relevant ICU data sets for their respective research questions.</div></div><div><h3>Methods</h3><div>A systematic search was carried out in PubMed, PhysioNet, Arxiv, MedRxiv and BioRxiv to identify all publicly available intensive care data sets of adult patients. After data extraction of database characteristics, a qualitative synthesis of results was carried out.</div></div><div><h3>Results</h3><div>882 publications were identified. After screening, 7 publicly available ICU databases were included for analysis: AmsterdamUMCdb, eICU Collaborative Research Database (eICU-CRD), High Time Resolution ICU Dataset (HiRID), Medical Information Mart for Intensive Care (MIMIC)-IV, Northwestern ICU (NWICU), Salzburg Intensive Care database (SICdb) and Zigong Fourth People's Hospital (ZFPH) database of patients with infections. A qualitative synthesis showed notable differences in number of patients, usage of organ support, admission types and frequency of measurements.</div></div><div><h3>Conclusion</h3><div>Each public ICU data set differs due to differences in medical practice, information technologies and approach to legal restrictions. This systematic review provides clinicians and data scientists with an overview of available public ICU data sets and their characteristics.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"90 ","pages":"Article 155205"},"PeriodicalIF":2.9,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New prognostic score for mortality in critically ill patients. Development and validation","authors":"M.P. Gracia Arnillas ,&nbsp;F. Alvarez Lerma ,&nbsp;X. Nuvials Casals ,&nbsp;R. Gimeno Costa ,&nbsp;N. Mas Bilbao ,&nbsp;J. Lobo Palanco ,&nbsp;A. Escribá Bárcena ,&nbsp;M. Catalán González ,&nbsp;M. Martinez Alonso","doi":"10.1016/j.jcrc.2025.155191","DOIUrl":"10.1016/j.jcrc.2025.155191","url":null,"abstract":"<div><div>Objective: To develop and validate a novel prognostic model to predict mortality in critically ill patients admitted to the ICU. <strong>Unlike APACHE II the new model incorporates risk factors assessed throughout the entire ICU stay, allowing for a more comprehensive evaluation and</strong> a better understanding of how the probability of mortality changes. Design: Post-hoc analysis of multicenter, prospective data from 167 Spanish hospitals (193 ICUs) collected over 7 years. Patients: Adults (&gt;18 years). Interventions: Demographic and clinical variables were analyzed. The model was developed using multivariable logistic regression in an estimation group and validated using a separate cohort. Variables of Interest: The <strong>primary outcome was ICU mortality</strong>, which was clearly defined and analyzed in both the model development and validation phases. The model incorporated APACHE II and eight additional factors <strong>evaluated across the entire ICU stay</strong>: prior antibiotic use (48 h pre-ICU), hospitalization days before ICU, hematologic diagnoses, invasive mechanical ventilation, parenteral nutrition, shunt ventricular, renal clearance techniques, and infections associated with invasive devices leading to sepsis. Results: Of the 137,666 patients, 91,777 were assigned to the estimation group and 45,889 to validation. Mortality was 10.8 %, strongly associated with APACHE II severity. The new model demonstrated superior discriminatory ability (AUROC = 0.872) compared to APACHE II alone (AUROC = 0.826) and it improved reclassification by 52 % over APACHE II: 19.4 % of survivors and 32.75 % of non-survivors. <strong>This improvement, though numerically modest, has clinical relevance by enhancing risk stratification and guiding interventions.</strong> Conclusions: A validated NMP model was developed using nine additional risk factors alongside APACHE II.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"90 ","pages":"Article 155191"},"PeriodicalIF":2.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A risk-adjusted length of stay to evaluate severe Community-Acquired Pneumonia (sCAP) outcomes: A machine learning analysis of 16,985 ICU admissions","authors":"Amanda Quintairos ,&nbsp;Vicente Souza Dantas ,&nbsp;Guilherme Ferrari ,&nbsp;Leonardo Bastos ,&nbsp;Igor Tona Peres ,&nbsp;Jorge Ibrain Figueira Salluh","doi":"10.1016/j.jcrc.2025.155208","DOIUrl":"10.1016/j.jcrc.2025.155208","url":null,"abstract":"<div><h3>Background</h3><div>Severe community-acquired pneumonia (sCAP) strains ICU resources, demands efficient allocation and robust performance metrics for value-based care. Current ICU assessment methods often lack the necessary detail and risk adjustment for effective resource management, especially for complex patient populations such as those with sCAP.</div></div><div><h3>Research question</h3><div>This study investigated whether the machine learning-based Standardized Length of Stay Ratio (SLOSR) could reliably measure risk-adjusted LOS for sCAP patients, enabling benchmarking. SLOSR is calculated as the sum of observed length of stay (LOS) divided by the sum of predicted LOS, enabling ICU benchmarking for resource use.</div></div><div><h3>Study design and methods</h3><div>We conducted a multicenter retrospective cohort study of 16,985 adult sCAP admissions across 220 ICUs in 57 Brazilian hospitals (January–December 2023). Data included demographics, comorbidities, SAPS 3, and ventilatory support. The machine learning model predicted LOS and calculated SLOSR. Rigorous validation included cross-validation, calibration plots, funnel plot analysis, RMSE, MAE, and R².</div></div><div><h3>Results</h3><div>Hospital mortality was 9.3 %, ICU mortality 6.4 %, median ICU LOS 4 days, mean SAPS 3 score 50; 28.1 % received ventilatory support. The SLOSR demonstrated a robust grouped R² of 0.89. The model achieved RMSE = 4.57 and MAE = 3.10, with excellent calibration. Funnel plot analysis revealed a median SLOSR of 1.13 (Q1 = 0.9; Q3 = 1.34), underscoring its potential for benchmarking.</div></div><div><h3>Conclusion</h3><div>SLOSR shows promise as tool for assessing adjusted LOS as a surrogate of resource use in sCAP patients in the context of Brazilian ICUs. Further research is needed to validate its performance in other settings.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"90 ","pages":"Article 155208"},"PeriodicalIF":2.9,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}