Daily Sepsis Research Analysis

This study reveals that phospholipase A2 (PLA2), normally stable and nontoxic, can be activated specifically within the alveolar environment to induce rapid, "electric shock-like" lethality, akin to chemical toxins, while also exhibiting extreme toxicity comparable to that of biological toxins, and functioning as a potential "time bomb" in the body. When exacerbated inflammation impairs the pulmonary barrier, PLA2 from the circulation can penetrate into the lungs. Once activated in the alveolar space, it rapidly hydrolyzes pulmonary surfactant phospholipids, causing a drastic decline in surface tension (>30%). This leads to alveolar overdistension, instantaneous respiratory failure, and asphyxiation-an acute mortality effect strikingly similar to that observed in sepsis and severe pulmonary diseases. PLA2 penetration and lethality are more pronounced in aged animals. Based on these findings, a combination therapy comprising phospholipase (dioleoylphosphatidylserine) and an inhibitor (varespladib) was developed, which significantly improved survival rates from 0% to over 90% in mice with sepsis, acute lung injury, and PLA2 poisoning. This study provides critical theoretical foundations and intervention strategies for the clinical treatment of related diseases.

BACKGROUND: The prediction of the onset of sepsis, a life-threatening condition resulting from a dysregulated response to an infection, is one of the most common prediction tasks in intensive care-related machine learning research. To assess the performance of such models, different evaluation strategies, including fixed horizon (a single prediction at a set time before onset), peak score (a single prediction using the maximum predicted risk across time), and continuous evaluation (multiple predictions assessed continuously across time), are commonly implemented, but there is no clear consensus on which approach should be used in order to provide clinically meaningful performance evaluation. OBJECTIVE: This study aimed to assess different evaluation approaches of sepsis prediction models trained on a public intensive care dataset applied to German intensive care data. METHODS: In this retrospective, observational cohort study, we assessed the efficacy of machine learning models, pretrained on the Medical Information Mart for Intensive Care IV dataset, when applied to BerlinICU, a multisite German intensive care dataset. To understand the real-world impact of implementing these models, we examined the performance variability across various evaluation strategies. RESULTS: The BerlinICU dataset includes 40,132 intensive care admissions spanning 10 years (2012-2021). Using the latest Sepsis-3 definition, we identified 4134 septic admissions (10.3% prevalence). Application of a temporal convolutional network model to BerlinICU yielded an area under the receiver operating characteristic curve (AUROC) of 0.67 (95% CI 0.66-0.68) for continuous evaluation with a 6-hour prediction horizon, compared with 0.84 (95% CI 0.83-0.85) on the test set of Medical Information Mart for Intensive Care IV. On BerlinICU, peak score evaluation showed a similar AUROC compared with continuous evaluation, while fixed horizon evaluation showed a reduced AUROC of 0.61 (95% CI 0.60-0.62). Onset matching had minimal impact on performance estimates using continuous evaluation or fixed horizon evaluation, but increased estimates for peak score evaluation. Performance metrics improved with shorter prediction horizons across all strategies. CONCLUSIONS: Our results demonstrate that the choice of evaluation strategy has a significant impact on the performance metrics of intensive care prediction models. The same model applied to the same dataset yields markedly different performance metrics depending on the evaluation approach. Therefore, careful selection of the evaluation approach is essential to ensure that the interpretation of performance metrics aligns with clinical intentions and enables meaningful comparisons between studies. In our view, the continuous evaluation approach best reflects the continual monitoring of patients that is performed in real-world clinical practice. In contrast, fixed-horizon and peak score evaluation approaches may produce skewed results when not properly matching the length of stay distributions between sepsis cases and control cases. Especially for peak score evaluation, longer visits tend to produce higher maximum scores because sampling from more values increases the likelihood of capturing higher values purely by chance.

OBJECTIVE: A definition of refractory septic shock is necessary to guide diagnosis, management, prognostication, research, and future guidelines for this most severe form of the disease. We sought to achieve consensus on clinical criteria that would be used to define refractory septic shock. DESIGN: Review of literature, expert panel position statements, and Delphi rounds with an international expert group. SETTING: Consensus was defined as having at least 75% of panellists in agreement or disagreement on the three highest or lowest levels of a 7-point Likert scale or based on responses to single- or multiple-choice questions, respectively. SUBJECTS: A panel of multinational, multiprofessional, and multidisciplinary critical care experts assembled by the Society of Critical Care Medicine and the European Society of Intensive Care Medicine (57 invitations and 56 participants). MEASUREMENTS AND MAIN RESULTS: A five-round Delphi process was conducted for consensus and stability. The steering committee proposed 34 statements, and five of them were rejected by panel experts after round 2. Among 29 statements selected from eight domains, consensus was reached for 13. The panel agreed on the need for a comprehensive consensus set of clinical criteria for refractory septic shock. Markers of organ dysfunction (75%, 2 rounds), tissue perfusion (91.1%, 2 rounds) including lactate (94.6%, 2 rounds) and capillary refill time (76.8%, 2 rounds), assessment of fluid responsiveness after initial resuscitation (92.9%, 5 rounds), and use of vasoactive drugs at norepinephrine equivalents greater than 0.5 µg/kg/min (75.0%, 3 rounds) were selected as clinical criteria of refractory septic shock. The use of critical care ultrasound (CCUS) (92.9%, 3 rounds) was the single diagnostic modality that reached a consensus-based agreement. CONCLUSIONS: A consensus for 13 criteria to frame the definition of refractory septic shock was reached. Refractory septic shock is characterised by persistently elevated lactate concentrations and or prolonged capillary refill time in patients with septic shock who are fluid unresponsive, require a norepinephrine base equivalent dose greater than 0.5 µg per kilogram per minute, and undergo CCUS assessment when mixed shock is suspected.