Journal of critical care最新文献

{"title":"Authors reply: “Associations of positive end-expiratory pressure (PEEP) with extubation failure and clinical outcomes in invasively ventilated patients with acute brain injury: A secondary analysis of the ENIO study”","authors":"Denise Battaglini , Raphael Cinotti , Karim Asehnoune , Andrea Loggini , Luca Montagnani , Lorenzo Ball , Francesca Gualdi , Patricia R.M. Rocco , Marcus J. Schultz , Nicolò Antonino Patroniti , Chiara Robba","doi":"10.1016/j.jcrc.2026.155449","DOIUrl":"10.1016/j.jcrc.2026.155449","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155449"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022764","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":"Acute respiratory distress syndrome and acute kidney injury in critically ill patients: A scoping review on this lung-kidney crosstalk","authors":"Francisco Z. Mattedi ,&nbsp;Heitor S. Ribeiro ,&nbsp;Geraldo F. Busatto ,&nbsp;Carlos R.R. Carvalho ,&nbsp;Dirce Maria Trevisan Zanetta ,&nbsp;Emmanuel A. Burdmann ,&nbsp;on behalf of the HCFMUSP COVID-19 Study Group","doi":"10.1016/j.jcrc.2026.155445","DOIUrl":"10.1016/j.jcrc.2026.155445","url":null,"abstract":"<div><h3>Introduction</h3><div>The incidence of acute kidney injury (AKI) in patients with acute respiratory distress syndrome (ARDS) is high; nonetheless, the lung-kidney crosstalk remains unclear.</div></div><div><h3>Objective</h3><div>Describe the association between ARDS and AKI in critically ill patients.</div></div><div><h3>Methods</h3><div>This scoping review was conducted according to the JBI and PRISM-ScR and included studies that investigated critically ill patients with ARDS (Participants), described AKI-related outcomes (Concept), and were conducted in hospitals (Context). MEDLINE, Embase, and LILACS databases were searched for articles published up to January 2024. Only observational studies were considered. Data on the diagnosis of ARDS-AKI and other kidney-related outcomes were extracted.</div></div><div><h3>Results</h3><div>A total of 2943 studies were screened, of which 28 were included in this review. Most studies were prospective and the majority originated from Europe. AKI was diagnosed using the KDIGO criteria in most studies and the pooled overall rate of AKI development across the studies was 46.8% (95% CI: 40.8–52.8). Two reports identified ARDS as an independent risk factor for AKI. Kidney replacement therapy was described in 17 studies. AKI recovery was described in only three studies. Seventeen studies evaluated hospital mortality, specifically in patients with ARDS-AKI, and found a greater mortality risk as compared to only ARDS.</div></div><div><h3>Conclusions</h3><div>This scoping review emphasizes the variability of the evidence, which hinders definitive conclusions about the association between ARDS and AKI, despite their common occurrence in critically ill patients. Therefore, a significant gap remains in our understanding of this lung-kidney interaction.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155445"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074328","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: “Incidence and predictors of adverse events during intra-hospital transport of critically ill patients in a tertiary ICU in Ethiopia: A prospective observational study”","authors":"Mikiyas G. Teferi ,&nbsp;Addisu G. Ayalew ,&nbsp;Nanati J. Aliye ,&nbsp;Kassahun A. Dinku ,&nbsp;Getaw W. Hassen ,&nbsp;Fetiya Alferid","doi":"10.1016/j.jcrc.2026.155466","DOIUrl":"10.1016/j.jcrc.2026.155466","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155466"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046645","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: “Different microcirculatory patterns in patients with COVID-19 and non-COVID-19 ARDS: A multicenter cross-sectional study”","authors":"Fengyu Chen ,&nbsp;Chunming Zhang,&nbsp;Kan Kan,&nbsp;Zejun Xue,&nbsp;Jun Zhang","doi":"10.1016/j.jcrc.2026.155455","DOIUrl":"10.1016/j.jcrc.2026.155455","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155455"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146100197","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: “Can large language models approximate the results of meta-analyses in critical care? A meta-research study”","authors":"Jiayi Chen","doi":"10.1016/j.jcrc.2026.155459","DOIUrl":"10.1016/j.jcrc.2026.155459","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155459"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024267","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: “Incidence and predictors of adverse events during intra-hospital transport of critically ill patients in a tertiary ICU in Ethiopia: a prospective observational study”","authors":"Ya-nan Yu,&nbsp;Bo Zhang","doi":"10.1016/j.jcrc.2026.155464","DOIUrl":"10.1016/j.jcrc.2026.155464","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155464"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024271","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":"Evaluating the efficacy of large language models in predicting intensive care unit admission needs","authors":"Engin İhsan Turan ,&nbsp;Abdurrahman Engin Baydemir ,&nbsp;Zehra Polat Turan ,&nbsp;Ayça Sultan Şahin","doi":"10.1016/j.jcrc.2026.155446","DOIUrl":"10.1016/j.jcrc.2026.155446","url":null,"abstract":"<div><h3>Background</h3><div>Timely identification and transfer of critically ill patients to intensive care units (ICUs) are crucial to reducing morbidity and mortality. Delayed ICU admission is linked to higher mortality, emphasizing the need for efficient prediction systems. Artificial intelligence (AI) has shown promise in enhancing clinical decision-making. This study evaluates the efficacy of ChatGPT and Gemini AI models in predicting ICU admission needs.</div></div><div><h3>Methods</h3><div>This retrospective observational study analyzed data from 8043 ICU consultation cases in a tertiary hospital between January 2020 and June 2024. Clinical parameters included medication use, consultation details, ECG findings, imaging results, comorbidities, and laboratory values. Preprocessed and anonymized data were analyzed using ChatGPT and Gemini, with performance assessed through accuracy, Kappa statistic, Pearson Chi-square, and logistic regression.</div></div><div><h3>Results</h3><div>ChatGPT demonstrated strong predictive performance, achieving an accuracy of 93.8% and a Kappa statistic of 0.802, indicating substantial agreement with anesthesiologists' ICU decisions. Its predictions showed a highly significant association with actual clinical outcomes (Pearson Chi-Square = 5293.310, <em>p</em> &lt; 0.001). Sensitivity and specificity analyses further confirmed ChatGPT's balanced performance in identifying both ICU and non-ICU patients. In contrast, Gemini showed more modest agreement with clinical decisions, with a Kappa value of 0.396, reflecting lower consistency despite producing correct classifications in a portion of cases.</div></div><div><h3>Conclusion</h3><div>ChatGPT demonstrated superior accuracy and reliability in predicting ICU needs compared to Gemini. Early identification of critically ill patients enables timely interventions, potentially reducing morbidity and mortality. Future studies should explore real-time AI integration into clinical workflows and validate findings through prospective research.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155446"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024321","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":"Eye on AKI - Are shifting trends the cue for a platform clinical trial?","authors":"N.A. Shah ,&nbsp;S. Kotwal ,&nbsp;M. Ostermann ,&nbsp;N. Hammond ,&nbsp;M. Gallagher","doi":"10.1016/j.jcrc.2026.155438","DOIUrl":"10.1016/j.jcrc.2026.155438","url":null,"abstract":"<div><h3>Purpose</h3><div>Acute kidney injury (AKI) affects ∼10–15% of hospital admissions in high-income countries and is associated with morbidity, mortality, and costs. Despite this burden, targeted therapies remain lacking, and randomised controlled trials have been slow to accommodate precision medicine. We evaluated temporal changes in the composition of kidney-related basic science research and the implications for AKI treatment development.</div></div><div><h3>Materials and methods</h3><div>We conducted a mapping review of kidney research publications indexed in EMBASE from 1 January 2013 to 31 December 2024. Publications were classified as basic science and further categorised as AKI-related, mechanistic, or therapeutic. Annual publication counts and proportions were summarised descriptively, and simple regression models were used to assess temporal trends.</div></div><div><h3>Results</h3><div>Total kidney research output increased over time (<em>r</em> = 0.86, r² = 0.75, β1 = 1439.6, <em>p</em> &lt; 0.001), while the proportion classified as basic science declined (<em>r</em> = −0.85, r² = 0.72, β1 = −0.21, <em>p</em> &lt; 0.001). In contrast, the share of AKI-focused basic science rose markedly (<em>r</em> = 0.99, r² = 0.98, β1 = 0.54, <em>p</em> &lt; 0.001), with substantial growth in mechanistic (<em>r</em> = 0.94, r² = 0.89, β1 = 0.88, p &lt; 0.001) and therapeutic studies (<em>r</em> = 0.96, r² = 0.93, β1 = 0.96, p &lt; 0.001).</div></div><div><h3>Conclusions</h3><div>Overall kidney research is expanding, with increasing emphasis on AKI discovery science and a growing mechanistic and therapeutic pipeline. These trends support investment in trial infrastructure—such as adaptive platform trials capable of testing multiple, biomarker-enriched therapies—to accelerate translation into clinical practice.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155438"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024693","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: “Associations of positive end-expiratory pressure (PEEP) with extubationfailure and clinical outcomes in invasively ventilated patients with acute brain injury: A secondary analysis of the ENIO study”","authors":"Zhenhao Liu ,&nbsp;Yanqing Gong","doi":"10.1016/j.jcrc.2025.155415","DOIUrl":"10.1016/j.jcrc.2025.155415","url":null,"abstract":"","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155415"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980597","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":"Urine albumin-to-creatinine ratio for early diagnosis and risk stratification of acute kidney injury in high-risk critically ill ICU patients: A prospective cohort study","authors":"Nuanprae Kitisin ,&nbsp;Nattaya Raykateeraroj ,&nbsp;Yukiko Hikasa ,&nbsp;Alessandro Caroli ,&nbsp;Jonathan Nübel ,&nbsp;Glenn Eastwood ,&nbsp;Ary Serpa Neto","doi":"10.1016/j.jcrc.2026.155476","DOIUrl":"10.1016/j.jcrc.2026.155476","url":null,"abstract":"<div><h3>Background</h3><div>Acute kidney injury (AKI) is common in the intensive care unit (ICU) but is often detected only after creatinine rises or oliguria develops. Although novel biomarkers allow earlier detection, their cost limits use. The urine albumin-to-creatinine ratio (uACR) is inexpensive, yet its role in AKI risk stratification remains uncertain.</div></div><div><h3>Methods</h3><div>In a prospective single-centre cohort of mixed ICU patients, adults with existing AKI or at high risk (modified AKI Risk Based on Creatinine [ARBOC] score ≥ 3) were enrolled. uACR was measured at enrollment (uACR at Time 0) and 24 h (uACR at Time 1). Outcomes included the prevalence and prognostic value of elevated uACR (≥ 3.4 mg/mmol) for incident, progressive, or persistent AKI (&gt; 48 h), and for ≥30% decline in estimated glomerular filtration rate (eGFR) at discharge. Predictive performance was assessed using the area under the receiver operating characteristic curve (AUC), change in AUC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision-curve analysis.</div></div><div><h3>Results</h3><div>Of 1010 patients screened, 203 were analysed (89 with and 114 without AKI at enrollm). Elevated uACR was frequent (72% with AKI; 52% without). In AKI patients, high uACR correlated with longer and more persistent AKI. Discrimination for incident AKI was modest (AUC 0.61 and 0.66 for uACR at Time 0 and uACR at Time 1) but higher for persistent AKI (both AUC 0.68). Adding uACR at Time 0 to ARBOC improved reclassification (NRI 0.48; IDI 0.04) and clinical net benefit.</div></div><div><h3>Conclusions</h3><div>uACR modestly identified incident AKI and more strongly predicted persistent AKI. As a simple biomarker, uACR may serve as a low-cost adjunct to existing ICU risk stratification tools, but requires further validation before consideration for routine clinical use.</div></div>","PeriodicalId":15451,"journal":{"name":"Journal of critical care","volume":"93 ","pages":"Article 155476"},"PeriodicalIF":2.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146131919","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}