Critical care science最新文献

Artificial intelligence technologies are rapidly advancing and significantly impacting healthcare, particularly in critical care environments where rapid, precise decision-making is crucial. They promise reductions in clinical errors, enhanced diagnostic accuracy, optimized treatment plans, and better resource allocation. Artificial intelligence applications are widespread across medical fields, with numerous artificial intelligence/machine learning-enabled medical devices approved by regulatory bodies, like the US Food and Drug Administration, aiding in diagnosis, monitoring, and personalized patient care. However, integrating artificial intelligence into healthcare presents challenges, notably the potential to exacerbate existing biases and disparities, especially when systems are trained on homogeneous datasets lacking diversity. Biased artificial intelligence can negatively affect patient outcomes for underrepresented groups, perpetuating health disparities. Additional concerns include data privacy and security, lack of transparency, algorithmic bias, and regulatory hurdles. Addressing these risks requires ensuring diverse and representative datasets, implementing robust auditing and monitoring practices, enhancing transparency, involving diverse perspectives in artificial intelligence development, and promoting critical thinking among healthcare professionals. Furthermore, the environmental impact of artificial intelligence, huge models reliant on energy-intensive data centers, poses challenges due to increased greenhouse gas emissions and resource consumption, disproportionately affecting low-income countries and exacerbating global inequalities. Systemic changes driven by corporate responsibility, government policy, and adopting sustainable artificial intelligence practices within healthcare are necessary. This narrative review explores the current landscape of artificial intelligence in healthcare, highlighting its potential benefits and delineating associated risks and challenges, underscoring the importance of mitigating biases and environmental impacts to ensure equitable and sustainable integration of artificial intelligence technologies in healthcare settings.

Objective: To revisit the VENTIlatory Strategies for Patients with Severe Traumatic Brain Injury (VENTILO) survey, focusing on ventilatory management practices among healthcare professionals in low- and middle-income countries.

Methodology: A cross-sectional on-line survey, VENTIlatory strategies for patients with severe traumatic brain injury in the LOw- and Middle-Income CountrieS (VENTILOMICS), was conducted using the original VENTILO survey questionnaire, developed following a review of literature on respiratory management in traumatic brain injury patients, captured demographics of participants, type of hospital/specialty and available neuromonitoring tools; protocols for mechanical ventilation and weaning, and respiratory management strategies. Descriptive statistics were computed for all study variables. We analyzed data based on the economic status of the low- and middle-income countries.

Results: There were 204 respondents from 28 low- and middle-income countries. Our results indicate that 55 - 70% of respondents recommend tidal volumes of 6 - 8mL/kg for patients with high or medium partial pressure of arterial oxygen/inspired fraction of oxygen, while tidal volumes of 4 - 6mL/kg is preferred for those with low partial pressure of arterial oxygen/inspired fraction of oxygen ratios. For patients with intracranial hypertension, lower positive end-expiratory pressure levels were utilized.

Conclusion: The findings suggest a consistent approach to lung-protective ventilation across low-and middle-income countries, with notable variations influenced by local resources and economic status. This study highlights the necessity for tailored research and guidelines to address the specific challenges faced in traumatic brain injury management within low-and middle-income countries.

Purpose: Pain may pose significant challenges in the intensive care unit, especially in mechanically ventilated patients. Methadone has recently emerged as an alternative option for eliciting acute analgesia. In this systematic review, we evaluated the use of methadone in mechanically ventilated patients in the intensive care unit.

Source: We searched MEDLINE, EMBASE, Wiley's Cochrane Library, CINAHL, PubMed (non-MEDLINE), Scopus, and LILACS databases from inception to January 24th, 2025. Eligible studies included randomized controlled trials and observational studies that compared the use of methadone to the standard of care or to other analgosedation strategies in mechanically ventilated patients in the intensive care unit. The primary outcome was the duration of mechanical ventilation. The secondary outcomes included opioid-associated adverse effects and scores regarding pain, agitation, and delirium.

Principal: findings: The search strategy yielded 3,523 studies. A total of 773 patients were included across the 12 studies (including 7 abstracts and 5 manuscripts). Patient populations included patients with trauma, those with burns, those at high risk for fentanyl abstinence syndrome, those with opioid use disorder, those with opioid withdrawal symptoms, and those who had received fentanyl for 72 hours prior to weaning. Overall, compared with the group that did not receive methadone, the methadone group was associated with more ventilator-free days, shorter weaning times, and a greater probability of successful weaning on day 5. Most of the studies exhibited high risks of bias; moreover, the overall quality of the evidence was low.

Conclusion: Few studies have evaluated the use of methadone in mechanically ventilated patients. Based on the low-quality evidence, methadone may be associated with improved patient-centered outcomes. Further research is warranted with respect to this topic.

Restoring immune homeostasis after an acute insult is essential for achieving a full recovery from an acute respiratory distress syndrome episode. Immune monitoring tools that are not exclusive to the blood compartment are in great demand to help guide treatment decisions. In this longitudinal study, we report a case of severe malaria-associated acute respiratory distress syndrome supported by venovenous extracorporeal membrane oxygenation. Although there was persistent lymphopenia, we observed dynamic shifts in T cells and rare innate lymphoid cell populations. The type 2 immune profile was preponderant at the acute phase, and decreased exhausted T-cell populations indicated recovery. There were significantly different blood and bronchoalveolar lavage fluid profiles. Multiple-compartment immune monitoring is possible and valuable for precise immune modulation.

Background: There are notable gaps in the understanding of the underlying pathophysiology of persistent critical illness (PerCI) and its extensive implications for patient outcomes. In this context, whether different PerCI definitions could yield distinct long-term outcomes for intensive care unit survivors is currently unknown.

Methods: This prospective cohort study spanned 10 Brazilian hospitals from March 2015 to December 2017. We enrolled emergency medical and surgical patients with intensive care unit stays exceeding 72 hours and tracked them for more than 12 months after intensive care unit discharge. Chronic patients were classified using four widely recognized persistent critical illness definitions from the literature: 1) mechanical ventilation > 21 days or tracheostomy for mechanical ventilation weaning; 2) mechanical ventilation duration > 14 days; 3) intensive care unit stay > 10 days; and 4) intensive care unit stay > 8 days accompanied by specific clinical conditions warranting extended intensive care unit care. Additionally, the data were compared to those of survivors who did not meet any of the four persistent critical illness criteria.

Results: The study enrolled 1,616 patients, with 609 (37.7%) fulfilling one or more persistent critical illness definitions. The twelve-month survival rates among persistent critical illness patients varied by definition. At 12 months, patients with PerCI definitions centered on mechanical ventilation duration had markedly lower survival rates than non-persistent critical illness patients did (definition 1: HR: 1.49, 95%CI: 1.10 - 2.02; definition 2: HR: 1.66, 95%CI: 1.20 - 2.30). In contrast, definitions based on intensive care unit length of stay produced survival rates more aligned with non-persistent critical illness patients (definition 3: HR: 1.01, 95%CI: 0.82 - 1.25; definition 4: HR: 1.10, 95%CI: 0.88 - 1.30).

Conclusion: Compared with other critically ill patients, patients with persistent critical illness definitions that are based on the duration of mechanical ventilation are associated with reduced 12-month survival, highlighting the impact of prolonged respiratory support on patient outcomes.