Critical Care Medicine最新文献

Delirium is a heterogeneous syndrome characterized by an acute change in level of consciousness that is associated with inattention and disorganized thinking. Delirium affects most critically ill patients and is associated with poor patient-oriented outcomes such as increased mortality, longer ICU and hospital length of stay, and worse long-term cognitive outcomes. The concept of delirium and its subtypes has existed since nearly the beginning of recorded medical literature, yet robust therapies have yet to be identified. Analogous to other critical illness syndromes, we suspect the lack of identified therapies stems from patient heterogeneity and prior subtyping efforts that do not capture the underlying etiology of delirium. The time has come to leverage machine learning approaches, such as supervised and unsupervised clustering, to identify clinical and pathophysiological distinct clusters of delirium that will likely respond differently to various interventions. We use sedation in the ICU as an example of how precision therapies can be applied to critically ill patients, highlighting the fact that while for some patients a sedative drug may cause delirium, in another cohort sedation is the specific treatment. Finally, we conclude with a proposition to move away from the term delirium, and rather focus on the treatable traits that may allow precision therapies to be tested.

Objectives: Hyperkalemia is a common life-threatening condition causing severe electrophysiologic derangements and arrhythmias. The beneficial effects of calcium (Ca2+) treatment for hyperkalemia have been attributed to "membrane stabilization," by restoration of resting membrane potential (RMP). However, the underlying mechanisms remain poorly understood. Our objective was to investigate the mechanisms underlying adverse electrophysiologic effects of hyperkalemia and the therapeutic effects of Ca2+ treatment.

Design: Controlled experimental trial.

Setting: Laboratory investigation.

Subjects: Canine myocytes and tissue preparations.

Interventions and measurements: Optical action potentials and volume averaged electrocardiograms were recorded from the transmural wall of ventricular wedge preparations (n = 7) at baseline (4 mM potassium), hyperkalemia (8-12 mM), and hyperkalemia + Ca2+ (3.6 mM). Isolated myocytes were studied during hyperkalemia (8 mM) and after Ca2+ treatment (6 mM) to determine cellular RMP.

Main results: Hyperkalemia markedly slowed conduction velocity (CV, by 67% ± 7%; p < 0.001) and homogeneously shortened action potential duration (APD, by 20% ± 10%; p < 0.002). In all preparations, this resulted in QRS widening and the "sine wave" pattern observed in severe hyperkalemia. Ca2+ treatment restored CV (increase by 44% ± 18%; p < 0.02), resulting in narrowing of the QRS and normalization of the electrocardiogram, but did not restore APD. RMP was significantly elevated by hyperkalemia; however, it was not restored with Ca2+ treatment suggesting a mechanism unrelated to "membrane stabilization." In addition, the effect of Ca2+ was attenuated during L-type Ca2+ channel blockade, suggesting a mechanism related to Ca2+-dependent (rather than normally sodium-dependent) conduction.

Conclusions: These data suggest that Ca2+ treatment for hyperkalemia restores conduction through Ca2+-dependent propagation, rather than restoration of membrane potential or "membrane stabilization." Our findings provide a mechanistic rationale for Ca2+ treatment when hyperkalemia produces abnormalities of conduction (i.e., QRS prolongation).

Objectives: To evaluate the transferability of deep learning (DL) models for the early detection of adverse events to previously unseen hospitals.

Design: Retrospective observational cohort study utilizing harmonized intensive care data from four public datasets.

Setting: ICUs across Europe and the United States.

Patients: Adult patients admitted to the ICU for at least 6 hours who had good data quality.

Interventions: None.

Measurements and main results: Using carefully harmonized data from a total of 334,812 ICU stays, we systematically assessed the transferability of DL models for three common adverse events: death, acute kidney injury (AKI), and sepsis. We tested whether using more than one data source and/or algorithmically optimizing for generalizability during training improves model performance at new hospitals. We found that models achieved high area under the receiver operating characteristic (AUROC) for mortality (0.838-0.869), AKI (0.823-0.866), and sepsis (0.749-0.824) at the training hospital. As expected, AUROC dropped when models were applied at other hospitals, sometimes by as much as -0.200. Using more than one dataset for training mitigated the performance drop, with multicenter models performing roughly on par with the best single-center model. Dedicated methods promoting generalizability did not noticeably improve performance in our experiments.

Conclusions: Our results emphasize the importance of diverse training data for DL-based risk prediction. They suggest that as data from more hospitals become available for training, models may become increasingly generalizable. Even so, good performance at a new hospital still depended on the inclusion of compatible hospitals during training.

Objectives: To assess if transfusion with low-titer group O whole blood (LTOWB) is associated with improved early and/or late survival compared with component blood product therapy (CT) in bleeding trauma patients.

Data sources: A systematic search of PubMed, CINAHL, and Web of Science was performed from their inception through December 1, 2023. Key terms included injury, hemorrhage, bleeding, blood transfusion, and whole blood.

Study selection: All studies comparing outcomes in injured civilian adults and children who received LTOWB versus CT were included.

Data extraction: Data including author, publication year, sample size, total blood volumes, and clinical outcomes were extracted from each article and reported following the Meta-analysis Of Observational Studies in Epidemiology guidelines. Main outcomes were 24-hour (early) and combined 28-day, 30-day, and in-hospital (late) mortality rates between recipients of LTOWB versus CT, which were pooled using random-effects models.

Data synthesis: Of 1297 studies reviewed, 24 were appropriate for analysis. Total subjects numbered 58,717 of whom 5,164 received LTOWB. Eleven studies included adults-only, seven included both adults and adolescents, and six only included children. The median (interquartile range) age for patients who received LTOWB and CT was 35 years (24-39) and 35.5 years (23-39), respectively. Overall, 14 studies reported early mortality and 22 studies reported late mortality. LTOWB was associated with improved 24-hour survival (risk ratios [RRs] [95% CI] = 1.07 [1.03-1.12]) and late (RR [95% CI] = 1.05 [1.01-1.09]) survival compared with component therapy. There was no evidence of small study bias and all studies were graded as a moderate level of bias.

Conclusions: These data suggest hemostatic resuscitation with LTOWB compared with CT improves early and late survival outcomes in bleeding civilian trauma patients. The majority of subjects were injured adults; multicenter randomized controlled studies in injured adults and children are underway to confirm these findings.

Objectives: To conduct a systematic review and meta-analysis assessing whether the use of antipsychotic medications in critically ill adult patients with delirium impacts patient-important outcomes.

Data sources: A medical librarian searched Ovid MEDLINE, EMBASE, APA PsycInfo, and Wiley's Cochrane Library as well as clinicaltrials.gov and the World Health Organization International Clinical Trials Registry Platform up to November 2023.

Study selection: Independently and in duplicate, reviewers screened abstracts and titles for eligibility, then full text of qualifying studies. We included parallel-group randomized controlled trials (RCTs) that included critically ill adult patients with delirium. The intervention group was required to receive antipsychotic medications at any dose, whereas the control group received usual care or placebo.

Data extraction: Reviewers extracted data independently and in duplicate using a piloted abstraction form. Statistical analyses were conducted using RevMan software (version 5.4).

Data synthesis: Five RCTs ( n = 1750) met eligibility criteria. The use of antipsychotic medications compared with placebo did not increase the number of delirium- or coma-free days (mean difference 0.90 d; 95% CI, -0.32 to 2.12; moderate certainty), nor did it result in a difference in mortality, duration of mechanical ventilation, ICU, or hospital length of stay. The use of antipsychotics did not result in an increased risk of adverse events (risk ratio 1.27; 95% CI, 0.71-2.30; high certainty). Subgroup analysis of typical versus atypical antipsychotics did not identify any subgroup effect for any outcome.

Conclusions: In conclusion, our systematic review and meta-analysis demonstrated with moderate certainty that there is no difference in delirium- or coma-free days when delirious critically ill adults are treated with antipsychotic medications. Further studies in the subset of patients with hyperactive delirium may be of benefit.

Objectives: Serial evaluations of lactate concentration may be more useful in predicting outcomes in patients with out-of-hospital cardiac arrest (OHCA) than a single measurement. This study aimed to evaluate the impact of lactate clearance (LC) on clinical and neurologic outcomes in patients with OHCA who underwent extracorporeal cardiopulmonary resuscitation (ECPR).

Design: Retrospective multicenter observational study.

Setting: Patients with OHCA receiving ECPR at 36 hospitals in Japan between January 1, 2013, and December 31, 2018.

Patients: This study evaluated 1227 patients, with lactate initial assessed upon emergency department admission and lactate second measured subsequently. To adjust for the disparity in the time between lactate measurements, the modified 6-hour LC was defined as follows: ([lactate initial -lactate second ]/lactate initial ) × 100 × (6/the duration between the initial and second measurements [hr]). The patients were divided into four groups according to the modified 6-hour LC with an equivalent number of patients among LC quartiles: Q1 (LC < 18.8), Q2 (18.8 < LC < 59.9), Q3 (60.0 < LC < 101.2), and Q4 (101.2 < LC).

Interventions: None.

Measurements and main results: The 30-day survival rates increased as the 6-hour LC increased (Q1, 21.2%; Q2, 36.8%; Q3, 41.4%; Q4, 53.6%; p for trend < 0.001). In the multivariate analysis, the modified 6-hour LC was significantly associated with a 30-day survival rate (adjusted odds ratio [AOR], 1.003; 95% CI, 1.001-1.005; p < 0.001) and favorable neurologic outcome (AOR, 1.002; 95% CI, 1.000-1.004; p = 0.027).

Conclusions: In patients with OHCA who underwent ECPR, an increase in the modified 6-hour LC was associated with favorable clinical and neurologic outcome. Thus, LC can be a criterion to assess whether ECPR should be continued.

Objectives: Extracorporeal cardiopulmonary resuscitation (ECPR) has been shown to improve neurologically favorable survival in patients with refractory out-of-hospital cardiac arrest (OHCA) caused by shockable rhythms. Further refinement of patient selection is needed to focus this resource-intensive therapy on those patients likely to benefit. This study sought to create a selection model using machine learning (ML) tools for refractory cardiac arrest patients undergoing ECPR.

Design: Retrospective cohort study.

Setting: Cardiac ICU in a Quaternary Care Center.

Patients: Adults 18-75 years old with refractory OHCA caused by a shockable rhythm.

Methods: Three hundred seventy-six consecutive patients with refractory OHCA and a shockable presenting rhythm were analyzed, of which 301 underwent ECPR and cannulation for venoarterial extracorporeal membrane oxygenation. Clinical variables that were widely available at the time of cannulation were analyzed and ranked on their ability to predict neurologically favorable survival.

Interventions: ML was used to train supervised models and predict favorable neurologic outcomes of ECPR. The best-performing models were internally validated using a holdout test set.

Measurements and main results: Neurologically favorable survival occurred in 119 of 301 patients (40%) receiving ECPR. Rhythm at the time of cannulation, intermittent or sustained return of spontaneous circulation, arrest to extracorporeal membrane oxygenation perfusion time, and lactic acid levels were the most predictive of the 11 variables analyzed. All variables were integrated into a training model that yielded an in-sample area under the receiver-operating characteristic curve (AUC) of 0.89 and a misclassification rate of 0.19. Out-of-sample validation of the model yielded an AUC of 0.80 and a misclassification rate of 0.23, demonstrating acceptable prediction ability.

Conclusions: ML can develop a tiered risk model to guide ECPR patient selection with tailored arrest profiles.