Critical Care Research and Practice最新文献

Purpose: Implicit bias in medicine is widespread, with minority populations historically underrepresented in research. Studies have shown racial and ethnic disparities in patient outcomes, including in acute respiratory distress syndrome (ARDS). This study examines the representation of minority patients in ARDS research in the USA. Methods: We examined the 1000 most cited ARDS studies from 2011 to 2021 in the top five critical care journals: AJRC, CHEST, Critical Care, CCM, and ICM. Results: 211 met the inclusion criteria, with 90 providing racial and ethnic demographic information for analysis. These included 17 in AJRC, 36 in CCM, 18 in CHEST, 11 in CC, and 8 in ICM. The average number of citations was 53 (±63). Publications peaked from 2015 to 2017 (15/year), while 2021 had the fewest. The mean patient count was 15,168, including 42 prospective, 29 randomized controlled, and 19 retrospective studies. Eighty-eight studies reported an average patient age of 53 years (±6), and 72% (±15%) of patients were White. Thirty-five studies reported only White patient demographics, while 53 included Black patients, 29 discussed Hispanic patients, 21 mentioned Asian patients. Most studies reported an average of 43% female participants, with no correlations found regarding White patient numbers, publication year, citations, or journals. Conclusion: A substantial number of highly cited studies about ARDS published in prominent critical care journals did not have detailed information regarding the racial composition of the patient population, and a large majority included overwhelmingly White patients and a preponderance of male gender patients.

Sepsis remains one of the leading causes of morbidity and mortality worldwide, particularly among critically ill patients in intensive care units (ICUs). Traditional diagnostic approaches, such as the Sequential Organ Failure Assessment (SOFA) and systemic inflammatory response syndrome (SIRS) criteria, often detect sepsis after significant organ dysfunction has occurred, limiting the potential for early intervention. In this study, we reviewed how artificial intelligence (AI)-driven methodologies, including machine learning (ML), deep learning (DL), and natural language processing (NLP), can aid physicians. AI, in this case, particularly ML, processes massive amounts of real-time clinical data, vital signs, lab results, and patient history and can detect subtle patterns and predict sepsis earlier than traditional methods like SOFA or SIRS, which often lag behind after the presentation of the sequela. Models like random forest, XGBoost, and neural networks achieve high accuracy and area under the receiver operating characteristic curve (AUROC) scores (0.8-0.99) in ICU and emergency settings, enabling timely intervention by distinguishing sepsis from similar conditions despite the lack of perfect biomarkers. In practice, however, there are several potential pitfalls. Algorithmic bias due to nonrepresentative data, data fragmentation, lack of validation, and explainability issues are current barriers in developed models. Future research should address these limitations and develop more sophisticated models.

Purpose: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is a life-saving intervention for refractory cardiopulmonary failure. Identifying factors associated with survival is essential for optimizing patient selection and management. In this study, we aimed to identify VA-ECMO survival predictors and evaluate the associated complications, costs, and outcomes. Methods: A retrospective analysis was conducted on data from 123 adult patients who underwent VA-ECMO at the Songklanagarind Hospital between 2017 and 2023. Clinical characteristics, ECMO-related complications, hospital expenses, and survival outcomes were analyzed. Univariate and multivariate logistic regression analyses were used to determine independent predictors of survival. Results: Fifty (40.7%) patients survived until hospital discharge. Compared to central VA-ECMO, peripheral VA-ECMO was significantly associated with improved survival (adjusted OR: 26.44, 95% CI: 1.95-358.7, p = 0.014). Preexisting liver dysfunction (adjusted OR: 0.27, 95% CI: 0.09-0.79, p = 0.016) and renal dysfunction (adjusted OR: 0.29, 95% CI: 0.1-0.85, p = 0.023) were independent mortality predictors. Survival odds were significantly lower in patients with American Society of Anesthesiologists (ASA) Class 5 (adjusted OR: 0.07, 95% CI: 0.01-0.67, p = 0.022). Neurological complications were more common in nonsurvivors than in survivors (41.1% vs. 18%, p = 0.012). Survivors had significantly higher total hospital costs (997,563.5 vs. 696,191 THB, p = 0.004) and longer hospital stays (28.5 vs. 3 days, p < 0.001). The multivariate model demonstrated strong predictive performance, with an area under the curve of 0.85. Conclusions: ECMO cannulation strategy, preexisting liver and renal dysfunction, and ASA classification were key factors associated with survival. Peripheral VA-ECMO was associated with better outcomes, and organ dysfunction significantly increased the mortality risk.

Background: This manuscript examines the use of respiratory therapists (RTs) to perform central venous and arterial line placements to address the lack of available staff to perform these procedures. To address these concerns, researchers implemented a program to provide further education to RTs to advance their skills to perform these procedures. Our facility sought to create a train-the-trainer formatted vascular access program utilizing RTs to relieve procedure burdens for critical care providers and maintain safe patient care with CLABSI rates better than the National Database of Nursing Quality Indicators (NDNQI) 95th percentile. Methods: A quality improvement project using the IOWA model was performed at the mixed ICU/CCU at a West Texas tertiary care hospital. All patients admitted from May 2017 through December 2023 to the mixed ICU/CCU for arterial catheters (ACs) and all inpatient units for central venous catheters (CVCs) were included. A training program using formal evidence-based protocols was created by the critical care medical director, who implemented the program and provided the original training with the goal of educating facility RTs on proper insertion of venous and ACs. Simple descriptive statistics were used to analyze the results of the program. Results: Over the 5-year retrospective review of RTs placing vascular access lines, only two negative events occurred. Our RTs performed 3878 ACs with zero complications. They also performed 6471 CVCs with only two complications (both pneumothoraces). Overall, the RT team had a success rate of 94.45% There was a minimal complication rate of 0.03%. Conclusions: We found the integration of RTs to the vascular access role to be highly successful in meeting both facility and patient needs.

Importance: Mechanical ventilation is indispensable for the management of acute respiratory distress syndrome (ARDS), yet suboptimal ventilator settings can exacerbate lung injury. There is growing evidence that lung-protective ventilation strategies reduce ventilator-induced lung injury (VILI) and improve outcomes. Understanding the role of key parameters, such as driving pressure and tidal volume, is essential for optimizing patient care. Observations: This narrative review synthesizes the evidence underpinning the evolution of lung-protective ventilation strategies in ARDS, focusing on the importance of low tidal volume ventilation and the monitoring of driving pressure. A targeted literature search was performed in PubMed, Embase, The Cochrane Library, Google Scholar, and Web of Science up to April 2025, focusing on adult ARDS. Original research studies (randomized controlled trials, retrospective and prospective cohort studies) and meta-analyses published in English were included. Conclusions and Relevance: Evidence supports adopting lung-protective strategies, including low tidal volume ventilation and careful driving pressure monitoring, to reduce VILI and improve survival in ARDS patients. By integrating these evidence-based principles into mechanical ventilation management, clinicians can enhance patient outcomes, reduce iatrogenic harm, and advance the overall quality of ARDS care.

Objectives: To investigate the incidence and determinants of do-not-resuscitate (DNR) orders, as well as mortality-associated risk factors, in the pediatric intensive care unit (PICU) of a tertiary care center in Saudi Arabia. Design: Retrospective cohort study. Setting: The PICU at the King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia. Patients: Patients aged 1 week to 14 years who were admitted to the PICU between January 2021 and December 2023. Interventions: None. Measurements and Main Results: Of the 3344 patients admitted to the PICU, 53.1% were male; the median age was 3 years (interquartile range: 0-8). The most common underlying conditions were neurological in 723 patients (21.6%), hematological/oncological in 463 (13.9%), and cardiovascular in 417 (12.5%). DNR orders were issued for 6.4% of admissions; among the 213 patients with DNR orders, 24 (11.3%) had a history of resuscitation before the DNR order. The mortality rate was significantly higher among patients with DNR orders (42.3%) compared to those without (1.3%; p < 0.001). Of all 3344 patients, 130 (3.9%) died; of these, 90 (69.2%) had DNR orders. Predictors of DNR status included male gender, hematological/oncological and cardiovascular diseases, bone marrow transplantation, respiratory distress, sepsis, seizures, bleeding, and need for mechanical ventilation (p < 0.05). Conclusions: This study revealed a DNR order rate of 6.4% among all PICU admissions, with 69.2% of PICU deaths occurring in patients with DNR status. Further analysis is warranted to understand the factors influencing DNR decisions and their impact on patient outcomes.

Background: Bedside ultrasonography is capable of evaluating gastric residual volume (GRV) and facilitating the identification of feeding intolerance (FI) among critically ill pediatric patients; however, a specialized predictive model tailored to this demographic has yet to be established. This study aims to develop a predictive model for the estimation of GRV using ultrasonography in this specific patient group. Methods: This prospective observational study included critically ill pediatric patients receiving enteral nutrition (EN). Clinical data, including gender, age, weight, height, gastric antrum cross-sectional area (CSA) in supine and right lateral positions, and qualitative grading system scores (Grade 0-2), were collected. GRV was measured by suctioning gastric contents under real-time ultrasound guidance, which was considered the actual GRV. The predictive models for GRV were developed using linear regression analysis. The agreement between predicted and actual GRV values was assessed using Bland-Altman analysis. Results: A total of 108 children were included in the analysis. Significant differences (p < 0.05) were observed in GRV, GRV per kilogram, supine and right lateral decubitus (RLD) CSA among grades. Spearman correlation analysis revealed strong correlations between RLD CSA (r = 0.88, p < 0.001) and qualitative grading system scores (r = 0.86, p < 0.001) with suctioned GRV. A predictive model was developed using RLD CSA and qualitative grading system scores as predictors: GRV (mL) = -12.9 + 10.3 (RLD CSA [cm²]) + 3.3 × Grade 1 + 10.1 × Grade 2. This model demonstrated an adjusted coefficient of determination (R ²) of 0.878, Akaike's information criterion (AIC) of 873.43, and Bayesian information criterion (BIC) of 884.06. Bland-Altman analysis showed a mean difference of 0.1 mL/kg between predicted and suctioned GRV, with 95% limits of agreement (LoA) ranging from -1.65 to 1.87 mL/kg. Conclusion: The results suggest that ultrasound-based monitoring can predict GRV in critically ill children. In addition, the qualitative grading system can differentiate between high and low GRV, potentially serving as a rapid screening tool for identifying patients with high GRV.

Hospital-acquired anaemia (HAA) is characterised by initially normal haemoglobin levels upon admission that are lowered during the hospital stay. The decreased haemoglobin levels related to the days of intensive care unit (ICU) hospitalisation may explain the effect of other interventions on haemoglobin levels. This study aimed to investigate the association between decreased haemoglobin levels and days of hospitalisation in critically ill patients in the Qassim region by analysing haemoglobin levels within the first 7, 14, and 21 days after ICU admission. A total of 180 patients were admitted during the study period. Patients with gastrointestinal bleeding, transfusion-dependent anaemia, a history of anaemia or bleeding, those with chronic kidney disease or on dialysis, and those who had hematologic or other malignancies were excluded (n = 97). Finally, those who were at least 18 years old, was within the normal range of haemoglobin upon admission to the ICU and had been hospitalized for at least 21 days in the ICU were included (n = 83). The initial average haemoglobin concentration was higher in men (15.24 g/dL) than in women (13.45 g/dL). Both experienced a significant and relatively parallel decline in haemoglobin levels (8.95 g/dL) and (8.66 g/dL), respectively, throughout the 21 day hospitalization period. The p value (< 0.001) suggests that the fixed effects are statistically significant, indicating that time (days) has a significant effect on haemoglobin levels. This study found a consistent decrease in haemoglobin levels over the ICU hospitalisation period, suggesting a progressive condition or treatment effect leading to reduced haemoglobin levels. However, further studies are required to analyse the causes of HAA in ICU.

Background: Congenital heart diseases (CHDs) are structural abnormalities of the heart or great vessels. Prostaglandin E1 (PGE1) is used to maintain the ductus arteriosus open in neonates with ductal-dependent heart lesions but is associated with apnea. We aimed to investigate the effects of caffeine therapy on the occurrence of apnea in neonates with CHD. Methods: This single-blinded randomized clinical trial was performed on 51 CHD neonates who were treated with PGE1 or PGE1 + caffeine. PGE1 dose ranged from 0.01 to 0.1 mcg/kg/min, and caffeine was administered initially at 20 mg/kg, followed by a daily bolus dose of 10 mg/kg. Demographic and clinical data, prevalence of apnea, and PGE1 side effects were recorded and analyzed. Results: A total of 51 CHD neonates receiving PGE1 + caffeine (n = 25) and PGE1 (n = 26) were included. The median age of total neonates was 2 (1-7) days, and 57% were female. There was no statistically significant difference between the baseline characteristics of participants, but neonates in the caffeine group received a higher mean dose of PGE1 (0.03 ± 0.17 vs. 0.02 ± 0.02, p=0.049) over the course of the treatment. The prevalence of apnea was 20% in the PGE1 + caffeine group and 42% in the PGE1 group (p=0.086). In the Cox regression model, the age of neonates had a significant effect on time to apnea in patients receiving caffeine (HR = 0.87, p=0.04). Conclusion: Our findings fail to demonstrate that caffeine therapy reduces PGE1-induced apnea. A larger randomized controlled trial is required to confirm or refute the efficacy of caffeine in reducing the incidence of apnea associated with PGE1 infusion. Trial Registration: Iranian Registry of Clinical Trials: IRCT20220503054729N1.

Background: Many studies have attempted to determine the incidence, predictors, and outcomes of cerebrovascular stroke after cardiac surgery, with different, sometimes contradictory, results because of differences in population risk profiles, study design, and surgical details. Methods: We retrospectively reviewed the records of all adult patients who underwent cardiac surgery between January 2018 and January 2023. Univariate, multivariable, and survival analyses were performed to identify the outcomes and predictors of ischemic and hemorrhagic strokes. Results: Of the 1334 patients studied, 70 (5.2%) patients had ischemic stroke, 23 (1.7%) had intracranial hemorrhage (ICH), and 9 (0.7%) had combined ischemic and hemorrhagic strokes. The patients who developed strokes had longer cardiopulmonary bypass (CPB) time (165.5 [126, 234] versus 136 [104, 171] min, p < 0.001) and aortic cross-clamping time (112 [79, 163] versus 89 [75, 121.5] min, p < 0.001), with higher rates of intra-aortic balloon pump (IABP) use (13.3% vs. 4.4%, p < 0.001), veno-arterial extracorporeal membrane oxygenation use (24.8% vs. 12.37%, p < 0.001), and mediastinal exploration for bleeding (22.9% vs. 8.9%, p < 0.0011). The patients who developed strokes showed increased hospital mortality (37.1% vs. 5.6%, p < 0.001), new need for dialysis (29.5% vs. 10.7%, p < 0.001), higher rate of tracheostomy (13.3% vs. 1.2%, p < 0.001), and longer intensive care unit (ICU) stay (12 [7, 28] versus 3 [2, 8] days, p < 0.001) and post-ICU stay (16 [7, 39] versus 5 [3, 10] days, p < 0.001). Follow-up for 36.4 (21.67, 50.7) months revealed an insignificant mortality difference, but there was an increased risk of recurrent cerebrovascular strokes. Cox-proportional hazards regression showed an increased risk of hospital mortality after cardiac surgery in patients who developed acute ischemic stroke (HR: 5.075, 95% CI: 3.28-7.851, p < 0.001) and ICH (HR: 12.288, 95% CI: 7.576-19.93, p < 0.001). Logistic multivariable regression showed that increased age, hyperlactatemia, redo cardiotomy, history of old stroke, CPB time, and perioperative IABP use were the predictors of ischemic stroke. Young age, old ICH, hyperlactatemia, and hypoalbuminemia were the predictors of postoperative ICH. Postoperative ICH, ischemic stroke, atrial fibrillation, chronic kidney disease, blood lactate level 24 h after surgery, and increased age were the independent predictors of mortality. Conclusions: Ischemic and hemorrhagic cerebrovascular strokes are serious complications that increase postoperative mortality and prolong hospitalization after cardiac surgery. Atrial fibrillation was not a significant predictor of postoperative stroke but was a predictor of hospital mortality. Careful attention should be given to maintaining hemodynamic stability and minimizing CPB time, especially in patients with a hist