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The purpose of the study is to understand what clinicians believe defines fluid bolus therapy (FBT) and the expected response to such intervention. We asked intensive care specialists in 30 countries to participate in an electronic questionnaire of their practice, definition, and expectations of FBT. We obtained 3138 responses. Despite much variation, more than 80% of respondents felt that more than 250 mL of either colloid or crystalloid fluid given over less than 30 minutes defined FBT, with crystalloids most acceptable. The most acceptable crystalloid and colloid for use as FBT were 0.9% saline and 4% albumin solution, respectively. Most respondents believed that one or more of the following physiological changes indicates a response to FBT: a mean arterial pressure increase greater than 10 mm Hg, a heart rate decrease greater than 10 beats per minute, an increase in urinary output by more than 10 mL/h, an increase in central venous oxygen saturation greater than 4%, or a lactate decrease greater than 1 mmol/L. Despite wide variability between individuals and countries, clear majority views emerged to describe practice, define FBT, and identify a response to it. Further investigation is now required to describe actual FBT practice and to identify the magnitude and duration of the physiological response to FBT and its relationship to patient-centered outcomes.

Under-triage is a major threat when admitting patients at the Intermediate Care Unit (IMCU). This study aims to identify risk factors and predict early deterioration of IMCU admissions, to reduce the risk of under-triage. This retrospective cohort study included all admissions to the mixed-surgical stand-alone IMCU of a tertiary referral hospital (2001–2015). Variables included were age, sex, admission indication, admitting specialty, re-admission, and nursing interventions. Early clinical deterioration was defined as ICU transfer or death ≤24 h of admission. Multinomial and logistic regression analyses were performed to identify risk factors and obtain predictions, for several frequently encountered subgroups. A total of 9103 admissions were included, of which 350 (3.8%) early deteriorated. Patients admitted for hemodynamic and respiratory instability had a high risk of early deterioration (OR 16.3 (CI 4.5-59.1)), probability 47.1%. Patients admitted with respiratory insufficiency and active diuresis or complicated sepsis had a high probability of early deterioration (≥29% and ≥26% respectively). The model had an optimism-corrected c-statistic of 0.79 (IQR 0.78-0.80). Patients with combined hemodynamic and respiratory instability should not be admitted to the IMCU. Patients with respiratory insufficiency and active diuresis, or complicated sepsis require close monitoring. •The presented nomogram can be used to assess the probability of early clinical deterioration•Patients with hemodynamic and respiratory instability should be admitted at the ICU•IMCU Patients with respiratory insufficiency and active diuresis, or complicated sepsis require close monitoring

Software-Defined Wireless Body Area Network (WBAN)s have gained significance in emergency healthcare applications for remote patients. Prioritization of healthcare data traffic has a high influence on the congestion and delay in the WBAN routing process. Currently, the energy constraints, packet loss, retransmission delay and increased sensor heat are pivotal research challenges in WBAN. These challenges also degrade the network lifetime and create serious issues for critical health data transmission. In this context, a Priority-based Energy-efficient, Delay and Temperature Aware Routing Algorithm (PEDTARA) is presented in this paper using a hybrid optimization algorithm of Multi-objective Genetic Chaotic Spider Monkey Optimization (MGCSMO). This proposed optimized routing algorithm is designed by incorporating the benefits of chaotic and genetic operators to the position updating function of enhanced Spider Monkey Optimization. For the prioritized routing process, initially, the patient data transmission in the WBAN is categorized into normal, on-demand and emergency data transmissions. Each category is ensured with efficient routing using the three different strategies of the suggested PEDTARA. PEDTARA performs optimal shortest path routing for normal data, energy-efficient emergency routing for high priority critical data and faster but priority verified routing for on-demand data. Thus, the proposed PEDTARA ensures energy-efficient, congestion-controlled and delay and temperature aware routing at any given period of health monitoring. Experiments were performed over a high-performance simulation scenario and the evaluation results showed that the proposed PEDTARA performs efficient routing better than the traditional approaches in terms of energy, temperature, delay, congestion and network lifetime.

The goal of hemodynamic resuscitation is to optimize the microcirculation of organs to meet their oxygen and metabolic needs. Clinicians are currently blind to what is happening in the microcirculation of organs, which prevents them from achieving an additional degree of individualization of the hemodynamic resuscitation at tissue level. Indeed, clinicians never know whether optimization of the microcirculation and tissue oxygenation is actually achieved after macrovascular hemodynamic optimization. The challenge for the future is to have noninvasive, easy-to-use equipment that allows reliable assessment and immediate quantitative analysis of the microcirculation at the bedside. There are different methods for assessing the microcirculation at the bedside; all have strengths and challenges. The use of automated analysis and the future possibility of introducing artificial intelligence into analysis software could eliminate observer bias and provide guidance on microvascular-targeted treatment options. In addition, to gain caregiver confidence and support for the need to monitor the microcirculation, it is necessary to demonstrate that incorporating microcirculation analysis into the reasoning guiding hemodynamic resuscitation prevents organ dysfunction and improves the outcome of critically ill patients.

Intensive Care Units (ICUs) present a high-stakes environment where timely decision-making is critical for managing patients with life-threatening conditions. The continuous influx of complex data often challenges clinicians, increasing the risk of errors. Artificial Intelligence (AI) offers transformative potential to enhance ICU care by supporting data analysis, decision-making, and workflow efficiency. This review aims to explore current applications of AI in ICUs, assess their impact on clinical outcomes, workflow optimization, and ethical considerations, and propose an Integrated AI Framework for enhanced critical care delivery. A literature search was conducted across PubMed, Scopus, and Web of Science, focusing on studies published between 2014 and 2024. The data were synthesized using an inductive thematic analysis approach to evaluate AI’s impact on clinical outcomes and to identify key barriers to its integration. AI has demonstrated significant advancements in ICU care, including early detection of sepsis, prediction of cardiac arrest, and workflow optimization through decision support systems. Predictive models reduced sepsis-related mortality by up to 20%, while workflow enhancements improved medication accuracy by 30% and reduced adverse events by 25%. Advanced techniques such as natural language processing (NLP), large language models (LLMs), and multimodal data integration have further streamlined ICU operations. However, challenges remain, including algorithmic bias, data privacy concerns, and integration barriers. The Ideal Human Care in Green ICU model integrates advanced AI technologies with multidisciplinary collaboration to provide personalized, evidence-based, and patient-centered care. This model emphasizes ethical AI practices, transparency, and family engagement to ensure responsible implementation. AI can transform ICU care by improving outcomes and workflows, but ethical, practical, and explainable challenges must be addressed through diverse, validated research. AI integration in ICUs improves patient outcomes and workflows by enabling early detection and precise treatment, but ethical issues and real-world validation are crucial.

PurposeIn the critically ill, hospital-acquired bloodstream infections (HA-BSI) are associated with significant mortality. Granular data are required for optimizing management, and developing guidelines and clinical trials.MethodsWe carried out a prospective international cohort study of adult patients (≥ 18 years of age) with HA-BSI treated in intensive care units (ICUs) between June 2019 and February 2021.Results2600 patients from 333 ICUs in 52 countries were included. 78% HA-BSI were ICU-acquired. Median Sequential Organ Failure Assessment (SOFA) score was 8 [IQR 5; 11] at HA-BSI diagnosis. Most frequent sources of infection included pneumonia (26.7%) and intravascular catheters (26.4%). Most frequent pathogens were Gram-negative bacteria (59.0%), predominantly Klebsiella spp. (27.9%), Acinetobacter spp. (20.3%), Escherichia coli (15.8%), and Pseudomonas spp. (14.3%). Carbapenem resistance was present in 37.8%, 84.6%, 7.4%, and 33.2%, respectively. Difficult-to-treat resistance (DTR) was present in 23.5% and pan-drug resistance in 1.5%. Antimicrobial therapy was deemed adequate within 24 h for 51.5%. Antimicrobial resistance was associated with longer delays to adequate antimicrobial therapy. Source control was needed in 52.5% but not achieved in 18.2%. Mortality was 37.1%, and only 16.1% had been discharged alive from hospital by day-28.ConclusionsHA-BSI was frequently caused by Gram-negative, carbapenem-resistant and DTR pathogens. Antimicrobial resistance led to delays in adequate antimicrobial therapy. Mortality was high, and at day-28 only a minority of the patients were discharged alive from the hospital. Prevention of antimicrobial resistance and focusing on adequate antimicrobial therapy and source control are important to optimize patient management and outcomes.

Objective This European Society of Intensive Care Medicine (ESICM) guideline provides evidence-based recommendations on the volume of early resuscitation fluid for adult critically ill patients. Methods An international panel of experts developed the guideline, focusing on fluid resuscitation volume in adult critically ill patients with circulatory failure. Using the PICO format, questions were formulated, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was applied to assess evidence and formulate recommendations. Results In adults with sepsis or septic shock, the guideline suggests administering up to 30 ml/kg of intravenous crystalloids in the initial phase, with adjustments based on clinical context and frequent reassessments (very low certainty of evidence). We suggest using an individualized approach in the optimization phase (very low certainty of evidence). No recommendation could be made for or against restrictive or liberal fluid strategies in the optimization phase (moderate certainty of no effect). For hemorrhagic shock, a restrictive fluid strategy is suggested after blunt trauma (moderate certainty) and penetrating trauma (low certainty), with fluid administration for non-traumatic hemorrhagic shock guided by hemodynamic and biochemical parameters (ungraded best practice). For circulatory failure due to left-sided cardiogenic shock, fluid resuscitation as the primary treatment is not recommended. Fluids should be administered cautiously for cardiac tamponade until definitive treatment and guided by surrogate markers of right heart congestion in acute pulmonary embolism (ungraded best practice). No recommendation could be made for circulatory failure associated with acute respiratory distress syndrome. Conclusions The panel made four conditional recommendations and four ungraded best practice statements. No recommendations were made for two questions. Knowledge gaps were identified, and suggestions for future research were provided.

PurposeFrailty is common in critically ill patients but the timing and optimal method of frailty ascertainment, trajectory and relationship with care processes remain uncertain. We sought to elucidate the trajectory and care processes of frailty in critically ill patients as measured by the Clinical Frailty Scale (CFS) and Frailty Index (FI).MethodsThis is a multi-centre prospective cohort study enrolling patients ≥ 50 years old receiving life support > 24 h. Frailty severity was assessed with a CFS, and a FI based on the elements of a comprehensive geriatric assessment (CGA) at intensive care unit (ICU) admission, hospital discharge and 6 months. For the primary outcome of frailty prevalence, it was a priori dichotomously defined as a CFS ≥ 5 or FI ≥ 0.2. Processes of care, adverse events were collected during ICU and ward stays while outcomes were determined for ICU, hospital, and 6 months.ResultsIn 687 patients, whose age (mean ± standard deviation) was 68.8 ± 9.2 years, frailty prevalence was higher when measured with the FI (CFS, FI %): ICU admission (29.8, 44.8), hospital discharge (54.6, 67.9), 6 months (34.1, 42.6). Compared to ICU admission, aggregate frailty severity increased to hospital discharge but improved by 6 months; individually, CFS and FI were higher in 45.3% and 50.6% patients, respectively at 6 months. Compared to hospital discharge, 18.7% (CFS) and 20% (FI) were higher at 6 months. Mortality was higher in frail patients. Processes of care and adverse events were similar except for worse ICU/ward mobility and more frequent delirium in frail patients.ConclusionsFrailty severity was dynamic, can be measured during recovery from critical illness using the CFS and FI which were both associated with worse outcomes. Although the CFS is a global measure, a CGA FI based may have advantages of being able to measure frailty levels, identify deficits, and potential targets for intervention.

PurposeIndividualising drug dosing using model-informed precision dosing (MIPD) of beta-lactam antibiotics and ciprofloxacin has been proposed as an alternative to standard dosing to optimise antibiotic efficacy in critically ill patients. However, randomised clinical trials (RCT) on clinical outcomes have been lacking.MethodsThis multicentre RCT, including patients admitted to the intensive care unit (ICU) who were treated with antibiotics, was conducted in eight hospitals in the Netherlands. Patients were randomised to MIPD with dose and interval adjustments based on monitoring serum drug levels (therapeutic drug monitoring) combined with pharmacometric modelling of beta-lactam antibiotics and ciprofloxacin. The primary outcome was ICU length of stay (LOS). Secondary outcomes were ICU mortality, hospital mortality, 28-day mortality, 6-month mortality, delta sequential organ failure assessment (SOFA) score, adverse events and target attainment.ResultsIn total, 388 (MIPD n = 189; standard dosing n = 199) patients were analysed (median age 64 [IQR 55–71]). We found no significant differences in ICU LOS between MIPD compared to standard dosing (10 MIPD vs 8 standard dosing; IRR = 1.16; 95% CI 0.96–1.41; p = 0.13). There was no significant difference in target attainment before intervention at day 1 (T1) (55.6% MIPD vs 60.9% standard dosing; p = 0.24) or at day 3 (T3) (59.5% vs 60.4%; p = 0.84). There were no significant differences in other secondary outcomes.ConclusionsWe could not show a beneficial effect of MIPD of beta-lactam antibiotics and ciprofloxacin on ICU LOS in critically ill patients. Our data highlight the need to identify other approaches to dose optimisation.

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. In this context, biomarkers could be considered as indicators of either infection or dysregulated host response or response to treatment and/or aid clinicians to prognosticate patient risk. More than 250 biomarkers have been identified and evaluated over the last few decades, but no biomarker accurately differentiates between sepsis and sepsis-like syndrome. Published data support the use of biomarkers for pathogen identification, clinical diagnosis, and optimization of antibiotic treatment. In this narrative review, we highlight how clinicians could improve the use of pathogen-specific and of the most used host-response biomarkers, procalcitonin and C-reactive protein, to improve the clinical care of patients with sepsis. Biomarker kinetics are more useful than single values in predicting sepsis, when making the diagnosis and assessing the response to antibiotic therapy. Finally, integrated biomarker-guided algorithms may hold promise to improve both the diagnosis and prognosis of sepsis. Herein, we provide current data on the clinical utility of pathogen-specific and host-response biomarkers, offer guidance on how to optimize their use, and propose the needs for future research.