Critical Care最新文献

Background: Monitoring respiratory effort and drive during mechanical ventilation is needed to deliver lung and diaphragm protection. Esophageal pressure (∆P_ES) is the gold standard measure of respiratory effort but is not routinely available. Airway occlusion pressure in the first 100 ms of the breath (P0.1) is a readily available surrogate for both respiratory effort and drive but is only modestly correlated with ∆P_ES in children. We sought to identify risk factors for P0.1 over or underestimating ∆P_ES in ventilated children.

Methods: Secondary analysis of physiological data from children and young adults enrolled in a randomized controlled trial testing lung and diaphragm protective ventilation in pediatric acute respiratory distress syndrome (PARDS) (NCT03266016). ∆P_ES (∆P_ES-REAL), P0.1 and predicted ∆P_ES (∆P_ES-PRED = 5.91*P0.1) were measured daily to identify phenotypes based upon the level of respiratory effort and drive: one passive (no spontaneous breathing), three where ∆P_ES-REAL and ∆P_ES-PRED were aligned (low, normal, and high effort and drive), two where ∆P_ES-REAL and ∆P_ES-PRED were mismatched (high underestimated effort, and overestimated effort). Logistic regression models were used to identify factors associated with each mismatch phenotype (High underestimated effort, or overestimated effort) as compared to all other spontaneous breathing phenotypes.

Results: We analyzed 953 patient days (222 patients). ∆P_ES-REAL and ∆P_ES-PRED were aligned in 536 (77%) of the active patient days. High underestimated effort (n = 119 (12%)) was associated with higher airway resistance (adjusted OR 5.62 (95%CI 2.58, 12.26) per log unit increase, p < 0.001), higher tidal volume (adjusted OR 1.53 (95%CI 1.04, 2.24) per cubic unit increase, p = 0.03), higher opioid use (adjusted OR 2.4 (95%CI 1.12, 5.13, p = 0.024), and lower set ventilator rate (adjusted OR 0.96 (95%CI 0.93, 0.99), p = 0.005). Overestimated effort was rare (n = 37 (4%)) and associated with higher alveolar dead space (adjusted OR 1.05 (95%CI 1.01, 1.09), p = 0.007) and lower respiratory resistance (adjusted OR 0.32 (95%CI 0.13, 0.81), p = 0.017).

Conclusions: In patients with PARDS, P0.1 commonly underestimated high respiratory effort particularly with high airway resistance, high tidal volume, and high doses of opioids. Future studies are needed to investigate the impact of measures of respiratory effort, drive, and the presence of a mismatch phenotype on clinical outcome.

Trial registration: NCT03266016; August 23, 2017.

The optimal dosing strategy of antimicrobial agents in critically ill patients receiving extracorporeal membrane oxygenation (ECMO) is unknown. We conducted comprehensive review of existing literature on effect of ECMO on pharmacokinetics and pharmacodynamics of antimicrobials, including antibacterials, antifungals, and antivirals that are commonly used in critically ill patients. We aim to provide practical guidance to clinicians on empiric dosing strategy for these patients. Finally, we discuss importance of therapeutic drug monitoring, limitations of current literature, and future research directions.

Background: The inadequacy of intensive care medicine in low-resource settings (LRS) has become significantly more visible after the COVID-19 pandemic. Recommendations for establishing medical critical care are scarce and rarely include expert clinicians from LRS.

Methods: In December 2023, the National Association of Intensivists from Bosnia and Herzegovina organized a hybrid international conference on the topic of organizational structure of medical critical care in LRS. The conference proceedings and literature review informed expert statements across several domains. Following the conference, the statements were distributed via an online survey to conference participants and their wider professional network using a modified Delphi methodology. An agreement of ≥ 80% was required to reach a consensus on a statement.

Results: Out of the 48 invited clinicians, 43 agreed to participate. The study participants came from 20 countries and included clinician representatives from different base specialties and health authorities. After the two rounds, consensus was reached for 13 out of 16 statements across 3 domains: organizational structure, staffing, and education. The participants favored multispecialty medical intensive care units run by a medical team with formal intensive care training. Recognition and support by health care authorities was deemed critical and the panel underscored the important roles of professional organizations, clinician educators trained in high-income countries, and novel technologies such as tele-medicine and tele-education.

Conclusion: Delphi process identified a set of consensus-based statements on how to create a sustainable patient-centered medical intensive care in LRS.

Background: Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis, considering multi-organ dynamics. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate the generalizability of the derived phenotypes.

Methods: We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥ 24 h. Data from two different high-volume academic hospital centers were used, where all phenotypes were derived in MICU of Hospital-I (N = 3225). The derived phenotypes were validated in MICU of Hospital-II (N = 848), SICU of Hospital-I (N = 1112), and SICU of Hospital-II (N = 465). Clinical data from 24 h preceding intubation was used to derive distinct phenotypes using an explainable machine learning-based clustering model interpreted by clinical experts.

Results: Four distinct ARF phenotypes were identified: A (severe multi-organ dysfunction (MOD) with a high likelihood of kidney injury and heart failure), B (severe hypoxemic respiratory failure [median P/F = 123]), C (mild hypoxia [median P/F = 240]), and D (severe MOD with a high likelihood of hepatic injury, coagulopathy, and lactic acidosis). Patients in each phenotype showed differences in clinical course and mortality rates despite similarities in demographics and admission co-morbidities. The phenotypes were reproduced in external validation utilizing the MICU of Hospital-II and SICUs from Hospital-I and -II. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p < 0.01) and consistent across MICU and SICU of both Hospital-I and -II. The phenotypes demonstrated differences in treatment effects associated with high positive end-expiratory pressure (PEEP) strategy.

Conclusion: The phenotypes demonstrated unique patterns of organ injury and differences in clinical outcomes, which may help inform future research and clinical trial design for tailored management strategies.