Anaesthesia Critical Care & Pain Medicine最新文献

Background: The Hypotension Prediction Index (HPI) is a machine-learning algorithm designed to predict hypotension. by maintaining mean arterial pressure (MAP) above 65 mmHg. This meta-analysis evaluated whether HPI-guided management improves postoperative outcomes and included post hoc analyses of intraoperative hypotension (IOH) metrics in adults undergoing major abdominal surgery.

Methods: A comprehensive search of PubMed, EMBASE, and Cochrane databases identified randomized controlled trials comparing HPI-guided management with standard care. Primary outcomes were postoperative complications, acute kidney injury (AKI), perioperative mortality, and hospital length of stay (LOS). Post hoc analyses assessed IOH metrics, including time-weighted average (TWA) of MAP < 65 mmHg, area under the threshold (AUT), total time with MAP < 65 mmHg, and intraoperative fluid use. Meta-analyses were conducted using random-effects models to calculate pooled standardized mean differences (SMDs), odds ratios (ORs), and mean differences (MDs).

Results: Eight trials involving 1534 patients were included. No significant differences were observed for AKI (OR: 0.85; 95% CI: 0.64-1.13), postoperative complications (OR: 1.10; 95% CI: 0.83-1.46), mortality (OR: 0.96; 95% CI: 0.32-2.83), LOS (SMD: -0.15; 95% CI: -0.73 to 0.42), or fluid use (SMD: -0.06; 95% CI: -0.35 to 0.24). HPI reduced TWA MAP < 65 mmHg (SMD: -0.25; MD: -20.5 minutes), AUT (SMD: -0.83), and total time with MAP < 65 mmHg (SMD: -0.74).

Conclusions: HPI-guided management did not significantly improve patient-centered outcomes. Post hoc analyses indicated a reduction in IOH metrics, but the clinical relevance of these findings remains uncertain given the lack of blinding and high risk of bias.

Registration: PROSPERO: CRD42023490654.

Objective: Acute hypoxemic respiratory failure (AHRF) is a common complication after cardiac surgery, but its prognostic significance for hospital mortality remains inadequately defined. We aimed to determine the association between early AHRF and hospital mortality following cardiac surgery.

Methods: In this retrospective multicenter cohort study, we used data from the Australian and New Zealand Intensive Care Society Adult Patient Database. All adult patients (aged ≥16 years) admitted to an ICU following coronary artery bypass grafting (CABG), valvular surgery, or combined procedures between January 2018 and December 2022 were included. AHRF was defined as a PaO₂/FiO₂ ratio <300 mmHg during the ICU admission. The primary outcome was hospital mortality. Secondary outcomes included ICU mortality and ICU and hospital length of stay. A nested hierarchical multivariable logistic regression model was used to assess the association between PaO₂/FiO₂ ratio and hospital mortality.

Results: Among 86,214 included patients, 62.7% (n = 54,044) had AHRF. Overall hospital mortality was low (1.1%), but significantly higher in patients with AHRF (1.4%vs. 0.8%; p < 0.001). AHRF was independently associated with increased hospital mortality (adjusted odds ratio = 1.56; 95%CI, 1.33-1.82). A non-linear relationship was observed between PaO₂/FiO₂ ratio and hospital mortality, with a sharp rise in mortality below a threshold of approximately 200 mmHg.

Conclusions: In this large cohort of cardiac surgery patients, AHRF was common and significantly associated with increased hospital mortality. A non-linear inflection in risk below a PaO₂/FiO₂ ratio of 200 mmHg suggests the importance of early recognition and targeted respiratory support in the postoperative period.

Older patients represent a rapidly expanding and clinically vulnerable population within intensive care units (ICUs), often presenting with complex, multifactorial health challenges. The physiological changes associated with aging, when compounded by critical illness, result in significant dysfunction of both peripheral and respiratory musculature. These alterations are further aggravated by clinical frailty, a multidimensional syndrome now recognized as a key determinant of adverse outcomes in critically ill patients. Respiratory muscle dysfunction in this population contributes to prolonged weaning from mechanical ventilation, diminished physical resilience, and delayed functional recovery. Converging factors such as age-related sarcopenia, diaphragmatic atrophy, impaired neuromuscular transmission, and systemic inflammation impair respiratory mechanics and ventilatory efficiency. The interplay between frailty and respiratory muscle weakness highlights the urgent need for early identification and targeted interventions. This review synthesizes current evidence on the pathophysiological changes affecting respiratory and peripheral muscles in older ICU patients and explores their impact on clinical outcomes. It emphasizes the essential role of clinicians in developing and implementing early, individualized rehabilitation strategies tailored to the needs of this population. Multidisciplinary approaches aimed at improving respiratory muscle performance, accelerating functional recovery, and reducing the burden of ICU-acquired weakness and ventilator dependence are also discussed. Recognizing the unique physiological and functional needs of older critically ill patients is imperative for optimizing rehabilitation trajectories and improving both short- and long-term outcomes in this increasingly prevalent patient group.

Advances in knowledge have significantly enhanced our understanding of the structure and function of microcirculation. The tools used to study microcirculation have been refined and diversified. This review presents existing tools for anaesthesiologists and highlights two key areas where microcirculatory knowledge can be applied in anaesthesia: perioperative hemodynamic management and preoperative patient assessment. Preoperative microcirculatory assessment can identify dysfunction associated with chronic conditions and predict perioperative outcomes. This information allows for personalised patient management, improved counselling, and anticipation of postoperative complications. Intraoperatively, microcirculation monitoring provides valuable insights into tissue perfusion, guiding hemodynamic targets and fluid management. Despite its promising potential, integrating microcirculation monitoring into anaesthesia clinical practice presents challenges. Further research is needed to determine its prognostic value, refine monitoring tools, and validate the impact of microcirculation-focused interventions on patient outcomes.

Introduction: Post-induction hypotension is a common complication in general anesthesia, particularly in patients with chronic hypertension. This study aims to analyze the practices of Certified Registered Nurse Anesthetist (CRNA) in collaboration with anesthesiologists of hemodynamic management in these patients.

Methodology: A multicenter quantitative descriptive survey was conducted among CRNAs working in 11 public and private hospitals. A questionnaire was developed to compare the management of two clinical cases: the first involved a hypertensive patient undergoing low-risk surgery, while the second described an older patient with multiple comorbidities undergoing high-risk surgery. The hemodynamic monitoring methods used by CRNAs were evaluated.

Results: Of the 158 CRNAs who responded (48.2% of 352 surveyed), 85% reported using mean arterial pressure (MAP) as their monitoring target. MAP targets ranged from 75 ± 9 mmHg for the first case to 80 ± 11 mmHg for the second. The study shows that 88% of CRNAs titrate anesthetics (over 70% using depth monitoring), and 70% start norepinephrine before the first induction. These rates rise to 94% and 99% for the second case. Norepinephrine is the first-line treatment for hypotension, while fluid loading comes fourth after Trendelenburg and anesthetic reduction. In the second, pulse wave analysis is most used (53%), followed by oesophageal Doppler (25%). Despite the availability of non-invasive stroke volume monitoring, 35% of CRNAs express interest in its implementation.

Conclusion: These findings highlight a predominant shift among CRNAs toward proactive, vasoactive-centered hemodynamic management.

Introduction: This study describes cefazolin pharmacokinetics in paediatric patients undergoing cardiac surgery using cardiopulmonary bypass to optimise antimicrobial prophylaxis.

Methods: A prospective, single-centre, observational study was conducted to describe cefazolin pharmacokinetics in paediatric patients undergoing cardiac surgery. Cefazolin was administered intravenously before skin incision, every three hours intraoperatively, and every eight hours postoperatively. Blood samples were collected on 6-8 occasions intraoperatively and six postoperatively, depending on re-dosing. Unbound cefazolin concentrations were measured using a chromatographic assay and analysed using a population pharmacokinetic approach in Monolix®. Dosing simulations were performed to determine the optimal regimen to maintain unbound cefazolin concentrations above the minimum inhibitory concentration for 100% of the dosing interval (fT_>MIC) in both intraoperative and postoperative phases.

Results: Sixty-eight patients were recruited and included in the pharmacokinetic model. Conventional cefazolin dosing regimens (preoperative 50 mg/kg, intraoperative 25 mg/kg 3 -hly and postoperative 25 mg/kg 8 -hly) resulted in subtherapeutic concentrations in up to 16.8% of paediatric patients postoperatively in cardiac surgery requiring cardiopulmonary bypass. Target attainment decreased with increasing eGFR. Dosing simulations indicated that increasing the postoperative dose to 25 mg/kg 3 -hly or using extended and continuous infusions achieves target attainment for all groups.

Discussion: Postoperative cefazolin concentrations in paediatric patients undergoing cardiopulmonary bypass are often inadequate to maintain optimal antimicrobial prophylaxis. More frequent postoperative dosing or the use of extended and continuous infusion strategies can ensure effective target attainment, potentially reducing the risk of surgical site infections in this vulnerable population.

The concept of integrating hemodynamic variables to define specific profiles or phenotypes has been established for decades. Describing hemodynamic phenotypes plays a key role in educating healthcare professionals about cardiovascular physiology, enhancing the understanding of shock mechanisms, and informing treatment strategies. Recently, two notable technical innovations have emerged to support bedside identification of hemodynamic phenotypes: machine learning (ML) algorithms and visual decision support tools. When it comes to "small data," such as a limited set of hemodynamic variables, ML algorithms may not be essential for data integration or interpretation. In addition, the hemodynamic phenotypes identified by ML techniques often mirror traditional textbook profiles, though occasionally with inconsistencies that may impact patient safety. This raises valid questions about the need to integrate complex and proprietary ML algorithms for bedside hemodynamic assessment. By contrast, visual tools leverage clinicians' innate ability to process graphical information rapidly, improving the understanding of cardiovascular physiology and enabling recognition of hemodynamic profiles at a glance. As such, they may offer a practical, accessible, and cost-effective alternative to ML-based solutions. Future studies comparing the clinical impact of visual versus ML-driven phenotyping are now needed to guide further development and implementation.

Anaemia is a common and constant challenge in oncology. Many patients treated for cancer suffer from undiagnosed and untreated anaemia and may receive unnecessary blood transfusions, despite existing guidelines. Transfusion can lead to increased morbidity and mortality, longer hospital stays, and higher costs, all in a dose-dependent manner. Patient Blood Management (PBM) is founded on three key pillars: managing anaemia, reducing blood loss, and improving tolerance to anaemia. These strategies should be implemented before, during, and after surgery. PBM programmes have proven to be effective in lowering transfusion rates and should be applied to every patient undergoing cancer-related surgery. As a standard of care, PBM could significantly enhance patient safety and long-term outcomes in a multidisciplinary surgical and medical oncology context. However, adherence to these recommendations remains insufficient. Key considerations during cancer surgery include: 1. Preoperative detection of anaemia and iron deficiency (ferritin<100 µg/L and/or < transferrin saturation < 20%), along with potential intravenous iron supplementation (depending on the product available). 2. Adherence to established transfusion guidelines (for oncology hospitalised adult patients who are hemodynamically stable and have no heart conditions, transfuse only when the haemoglobin concentration is less than 70 g/L). 3. Prevention of iatrogenic and unnecessary blood loss. 4. Utilisation of erythropoiesis-stimulating agents (to be discontinued once haemoglobin levels reach 120 g/L). 5. Administration of antifibrinolytic agents. 6. Use of cell-salvage techniques (with leukodepletion filter). A successful PBM programme requires time to reach optimal efficiency, and the involvement of multidisciplinary teams is essential to improve the quality of treatment.

Background: The aim of this study was to assess in-hospital mortality and identify its predictors in adult patients with hematological malignancies admitted to intensive care units (ICUs) in Japan.

Methods: We conducted a retrospective cohort study of adult patients with hematological malignancies admitted to ICUs participating in the Japanese Intensive care PAtient Database from 2015 to 2020. The primary outcome was in-hospital mortality. We compared survivors and non-survivors based on their characteristics at ICU admission and ICU treatments. We also assessed the relationship between institutional characteristics and in-hospital mortality.

Results: A total of 1,700 patients from 69 institutions were included. In-hospital mortality was 46.2%. The most common reason for ICU admission was respiratory failure (28.2%). Mechanical ventilation and continuous renal replacement therapy were used in 49.0% and 24.6% of patients, respectively. In multivariable logistic regression analysis, a higher in-hospital mortality was independently associated with type of neoplasm, Acute Physiological Assessment and Chronic Health Evaluation III score, invasive mechanical ventilation (OR 1.64, 95% CI 1.30-2.08), noninvasive ventilation (OR 1.71, 95% CI 1.22-2.41), and continuous renal replacement therapy (OR 1.98, 95% CI 1.51-2.61), whereas other patient characteristics (e.g., age, comorbidities, ICU admission source, reason for ICU admission) were not associated. There was also no association between institutional characteristics and in-hospital mortality.

Conclusions: In-hospital mortality of adult patients with hematological malignancies admitted to ICUs remains high. Factors associated with in-hospital mortality in these patients differed from those in the general ICU population. Institutional characteristics were not significantly associated with in-hospital mortality.