Intensive Care Medicine Experimental最新文献

Background: Sepsis is a condition with high mortality and morbidity, characterized by deregulation of the immune response against the pathogen. Current treatment strategies rely mainly on antibiotics and supportive care. However, there is growing interest in exploring cell-based therapies as complementary approaches. Human liver stem cells (HLSCs) are pluripotent cells of mesenchymal origin, showing some advantages compared to mesenchymal stem cells in terms of immunomodulatory properties. HSLC-derived extracellular vesicles (EVs) exhibited a superior efficacy profile compared to cells due to their potential to get through biological barriers and possibly to avoid tumorigenicity and showed to be effective in vivo and ex vivo models of liver and kidney disease. The potential of HLSCs and their EVs in recovering damage to distal organs due to sepsis other than the kidney remains unknown. This study aimed to investigate the therapeutic potential of the intravenous administration of HSLCs or HSLCs-derived EVs in a murine model of sepsis.

Results: Sepsis was induced by caecal ligation and puncture (CLP) on C57/BL6 mice. After CLP, mice were assigned to receive either normal saline, HLSCs or their EVs and compared to a sham group which underwent only laparotomy. Survival, persistence of bacteraemia, lung function evaluation, histology and bone marrow analysis were performed. Administration of HLSCs or HLSC-EVs resulted in improved bacterial clearance and lung function in terms of lung elastance and oedema. Naïve murine hematopoietic progenitors in bone marrow were enhanced after treatment as well. Administration of HLSCs and HLSC-EVs after CLP to significantly improved survival.

Conclusions: Treatment with HLSCs or HLSC-derived EVs was effective in improving acute lung injury, dysmyelopoiesis and ultimately survival in this experimental murine model of lethal sepsis.

The mechanisms of oxygen diffusion in brain capillaries have not been fully clarified to date. According to the laws of physics, the well-documented phenomenon of hyperoxemia-induced excessive increases in brain tissue oxygen pressure (PbtO2) contradicts traditional models of cerebral capillary oxygen diffusion. Circulating models predict a significant drop in oxygen pressure (PO2), and some of them foresee the presence of hypoxic or anoxic corners near the capillary end, regardless of high PbtO2 levels. We propose that the cerebral intracapillary transformation of hemoglobin from the relaxed (R) to the tense (T) quaternary conformational state, driven by deoxygenation and an overload of negative allosteric effectors, and characterized by a lower, more hyperbolic dissociation curve, mitigates the oxygen pressure difference across cerebral capillaries, ensuring a homogeneous pericapillary distribution of oxygen. The hemoglobin R to T state transition is responsible for the high PbtO2 levels observed in viable cerebral tissue during hyperoxemia.

Open-lung ventilation during cardiopulmonary bypass (CPB) in patients undergoing heart transplantation (HTx) is a potential strategy to mitigate postoperative acute respiratory distress syndrome (ARDS). We utilized an ovine HTx model to investigate whether open-lung ventilation during CPB reduces postoperative lung damage and complications. Eighteen sheep from an ovine HTx model were included, with ventilatory interventions randomly assigned during CPB: the OPENVENT group received low tidal volume (V_T) of 3 mL/kg and positive end-expiratory pressure (PEEP) of 8 cm H₂0, while no ventilation was provided in the NOVENT group as per standard of care. The recipient sheep were monitored for 6 h post-surgery. The primary outcome was histological lung damage, scored at the end of the study. Secondary outcomes included pulmonary shunt, driving pressure, hemodynamics and inflammatory lung infiltration. All animals completed the study. The OPENVENT group showed significantly lower histological lung damage versus the NOVENT group (0.22 vs 0.27, p = 0.042) and lower pulmonary shunt (19.2 vs 32.1%, p = 0.001). In addition, the OPENVENT group exhibited a reduced driving pressure (9.6 cm H₂O vs. 12.8 cm H₂O, p = 0.039), lower neutrophil (5.25% vs 7.97%, p ≤ 0.001) and macrophage infiltrations (11.1% vs 19.6%, p < 0.001). No significant differences were observed in hemodynamic parameters. In an ovine model of HTx, open-lung ventilation during CPB significantly reduced lung histological injury and inflammatory infiltration. This highlights the value of an open-lung approach during CPB and emphasizes the need for further clinical evidence to decrease risks of lung injury in HTx patients.

Background: Effective antimicrobial therapy is an essential part of intensive care medicine and renal replacement therapy is an important and common intervention which significantly affects the pharmacokinetics of many antimicrobials. This is especially critical for substances with a narrow therapeutic range, creating a dilemma of weighing the risk of toxicity from increased drug exposure against risk of ineffective treatment and promotion of antimicrobial resistance. To address this problem, we investigate a target-controlled dialysis by in vitro experiments - a novel technique in which drug is spiked into the dialysis solution to make use of the physicochemical properties of renal replacement therapy for solute transport, with the goal to reduce the risk of inadequate drug exposure.

Methods: Five antibiotics (ceftazidime, meropenem, piperacillin/tazobactam, vancomycin, flucloxacillin) were dialyzed in an in vitro model of continuous veno-venous hemodialysis using 1 L of bovine serum albumin solution as simulated patient plasma compartment. This was done with and without antibiotics in target concentrations added to the dialysis solution, mimicking three clinically relevant scenarios: (i) target-controlled dialysis in a subject with sub-therapeutic drug levels, (ii) target-controlled dialysis in a subject with supra-therapeutic drug levels, and (iii) traditional dialysis of drugs starting at the target concentration. Drug levels were quantified by high-performance liquid chromatography. Additionally, the stability over 24 h of all antibiotics in two typical dialysis solutions was assessed.

Results: Our data shows that with target-controlled dialysis, antibiotic concentrations will change in the desired direction towards the target concentration, depending on the patients' unbound drug levels in relation to the concentration in the dialysis solution. The desired target concentrations can be induced and maintained, regardless of the initial concentration. Furthermore, the stability tests revealed only a minor and clinically irrelevant loss in drug concentration (all < 10.2%) after 12 h.

Conclusions: We outlined the mechanistic plausibility and provided experimental evidence of the feasibility of the target-controlled dialysis concept, which could help to maintain therapeutic concentrations of many time-dependent antibiotics in critically ill patients under renal replacement therapy. The required stability in dialysis solutions was shown for a set of important antibiotics. The next step will be the prudent application of this concept to patients in clinical trials.

Sepsis is characterized by a dysregulated and excessive systemic inflammatory response to infection, associated with vascular and metabolic abnormalities that ultimately lead to organ dysfunction. In immune cells, both non-oxidative and oxidative metabolic rates are closely linked to inflammatory responses. Mitochondria play a central role in supporting these cellular processes by utilizing metabolic substrates and synthesizing ATP through oxygen consumption. To meet fluctuating cellular demands, mitochondria must exhibit adaptive plasticity underlying bioenergetic capacity, biogenesis, fusion, and fission. Given their role as a hub for various cellular functions, mitochondrial alterations induced by sepsis may hold significant pathophysiological implications and impact on clinical outcomes. In patients, mitochondrial DNA concentration, protein expression levels, and bioenergetic profiles can be accessed via tissue biopsies or isolated peripheral blood cells. Clinically, monocytes and lymphocytes serve as promising matrices for evaluating mitochondrial function. These mononuclear cells are highly oxidative, mitochondria-rich, routinely monitored in blood, easy to collect and process, and show a clinical association with immune status. Hence, mitochondrial assessments in immune cells could serve as biomarkers for clinical recovery, immunometabolic status, and responsiveness to oxygen and vasopressor therapies in sepsis. These characteristics underscore mitochondrial parameters in both tissues and immune cells as practical tools for exploring underlying mechanisms and monitoring septic patients in intensive care settings. In this article, we examine pathophysiological aspects, key methods for measuring mitochondrial function, and prominent studies in this field.

Background: This systematic review aims to identify predictors of intradialytic hypotension (IDH) in critically ill patients undergoing kidney replacement therapy (KRT) for acute kidney injury (AKI).

Methods: A comprehensive search of PubMed was conducted from 2002 to April 2024. Studies included critically ill adults undergoing KRT for AKI, excluding pediatric patients, non-critically ill individuals, those with chronic kidney disease, and those not undergoing KRT. The primary outcome was identifying predictive tools for hypotensive episodes during KRT sessions.

Results: The review analyzed data from 8 studies involving 2873 patients. Various machine learning models were assessed for their predictive accuracy. The Extreme Gradient Boosting Machine (XGB) model was the top performer with an area under the receiver operating characteristic curve (AUROC) of 0.828 (95% CI 0.796-0.861), closely followed by the deep neural network (DNN) with an AUROC of 0.822 (95% CI 0.789-0.856). All machine learning models outperformed other predictors. The SOCRATE score, which includes cardiovascular SOFA score, index capillary refill, and lactate level, had an AUROC of 0.79 (95% CI 0.69-0.89, p < 0.0001). Peripheral perfusion index (PPI) and heart rate variability (HRV) showed AUROCs of 0.721 (95% CI 0.547-0.857) and 0.761 (95% CI 0.59-0.887), respectively. Pulmonary vascular permeability index (PVPI) and mechanical ventilation also demonstrated significant diagnostic performance. A PVPI ≥ 1.6 at the onset of intermittent hemodialysis (IHD) sessions predicted IDH associated with preload dependence with a sensitivity of 91% (95% CI 59-100%) and specificity of 53% (95% CI 42-63%).

Conclusion: This systematic review shows how combining predictive models with clinical indicators can forecast IDH in critically ill AKI patients undergoing KRT, with validation in diverse settings needed to improve accuracy and patient care strategies.

Background: Acute Respiratory Distress Syndrome (ARDS) has a high morbidity and mortality. One therapy that can decrease mortality is ventilation in the prone position (PP). Patients undergoing PP are amongst the sickest, and there is a need for early identification of patients at particularly high risk of death. These patients may benefit from an in-depth review of treatment or consideration of rescue therapies. We report the development of a machine learning model trained to predict early mortality in patients undergoing prone positioning as part of the management of their ARDS.

Methods: Prospectively collected clinical data were analysed retrospectively from a single tertiary ICU. The records of patients who underwent an initial session of prone positioning whilst receiving invasive mechanical ventilation were identified (n = 131). The decision to perform prone positioning was based on the criteria in the PROSEVA study. A C5.0 classifier algorithm with adaptive boosting was trained on data gathered before, during, and after initial proning. Data was split between training (85% of data) and testing (15% of data). Hyperparameter tuning was achieved through a grid-search using a maximal entropy configuration. Predictions for 7-day mortality after initial proning session were made on the training and testing data.

Results: The model demonstrated good performance in predicting 7-day mortality (AUROC: 0.89 training, 0.78 testing). Seven variables were used for prediction. Sensitivity was 0.80 and specificity was 0.67 on the testing data set. Patients predicted to survive had 13.3% mortality, while those predicted to die had 66.67% mortality. Among patients in whom the model predicted patient would survive to day 7 based on their response, mortality at day 7 was 13.3%. Conversely, if the model predicted the patient would not survive to day 7, mortality was 66.67%.

Conclusions: This proof-of-concept study shows that with a limited data set, a C5.0 classifier can predict 7-day mortality from a number of variables, including the response to initial proning, and identify a cohort at significantly higher risk of death. This can help identify patients failing conventional therapies who may benefit from a thorough review of their management, including consideration of rescue treatments, such as extracorporeal membrane oxygenation. This study shows the potential of a machine learning model to identify ARDS patients at high risk of early mortality following PP. This information can guide clinicians in tailoring treatment strategies and considering rescue therapies. Further validation in larger cohorts is needed.

Background: Enhancing venous return during cardiopulmonary resuscitation (CPR) can lead to better hemodynamics and improved outcome after cardiac arrest (CA). Peripheral Intravenous Analysis (PIVA) provides feedback on venous flow changes and may indicate an increase in venous return and cardiac output during CPR. We hypothesize PIVA can serve as an early indicator of increased venous return, preceding end-tidal CO₂ (etCO₂) increase, before the return of spontaneous circulation (ROSC) in a rat model of CA and CPR.

Results: Eight male Wistar rats were intubated and ventilated, and etCO₂ was measured. Vessels were cannulated in the tail vein, femoral vein, femoral artery, and central venous and connected to pressure transducers. Ventilation was discontinued to achieve asphyxial CA. After 8 min, CPR began with ventilation, epinephrine, and automated chest compressions 200 times per minute until mean arterial pressure increased to 120 mmHg. Waveforms were recorded and analyzed. PIVA was calculated using a Fourier transformation of venous waveforms. Data are mean ± SE. Maximum PIVA values occurred in the tail vein 34.7 ± 2.9 s before ROSC, with subsequent PIVA peaks in femoral vein and centrally at 30.9 ± 5.4 and 25.1 ± 5.0 s, respectively. All PIVA peaks preceded etCO₂ increase (21.5 ± 3.2 s before ROSC).

Conclusion: PIVA consistently detected venous pressure changes prior to changes in etCO₂. This suggests that PIVA has the potential to serve as an important indicator of venous return and cardiac output during CPR, and also as a predictor of ROSC.