Citations

Background Lactic acidosis is associated with mortality in patients with cardiogenic shock (CS). Elevated lactate levels and systemic acidemia (low blood pH) have both been proposed as drivers of death. We, therefore, analyzed the association of both high lactate concentrations and low blood pH with 30‐day mortality in patients with CS. Methods and Results This was a 2‐center historical cohort study of unselected patients with CS with available data for admission lactate level or blood pH. CS severity was graded using the Society for Cardiovascular Angiography and Intervention (SCAI) shock classification. All‐cause survival at 30 days was analyzed using Kaplan‐Meier curves and Cox proportional‐hazards analysis. There were 1814 patients with CS (mean age, 67.3 years; 68.5% men); 51.8% had myocardial infarction and 53.0% had cardiac arrest. The distribution of SCAI shock stages was B, 10.8%; C, 30.7%; D, 38.1%; and E, 18.7%. In both cohorts, higher lactate or lower pH predicted a higher risk of adjusted 30‐day mortality. Patients with a lactate ≥5 mmol/L or pH <7.2 were at increased risk of adjusted 30‐day mortality; patients with both lactate ≥5 mmol/L and pH <7.2 had the highest risk of adjusted 30‐day mortality. Patients in SCAI shock stages C, D, and E had higher 30‐day mortality in each SCAI shock stage if they had lactate ≥5 mmol/L or pH <7.2, particularly if they met both criteria. Conclusions Higher lactate and lower pH predict mortality in patients with cardiogenic shock beyond standard measures of shock severity. Severe lactic acidosis may serve as a risk modifier for the SCAI shock classification. Definitions of refractory or hemometabolic shock should include high lactate levels and low blood pH.

One of the primary reasons for intensive care admission is shock. Identifying the underlying cause of shock (hypovolemic, distributive, cardiogenic, and obstructive) may lead to entirely different clinical pathways for management. Among patients with hypovolemic and distributive shock, fluid therapy is one of the leading management strategies. Although an appropriate amount of fluid administration might save a patient's life, inadequate (or excessive) fluid use could lead to more complications, including organ failure and mortality due to either hypovolemia or volume overload. Currently, intensivists have access to a wide variety of information sources and tools to monitor the underlying hemodynamic status, including medical history, physical examination, and specific hemodynamic monitoring devices. Although appropriate and timely assessment and interpretation of this information can promote adequate fluid resuscitation, misinterpretation of these data can also lead to additional mortality and morbidity. This article provides a narrative review of the most commonly used hemodynamic monitoring approaches to assessing fluid responsiveness and fluid tolerance. In addition, we describe the benefits and disadvantages of these tools.

Abstract Background Serum chloride derangement is common in critically ill patients requiring continuous renal replacement therapy (CRRT). We aimed to assess the association between serum chloride levels before and during CRRT with mortality. Methods This is a retrospective cohort study of critically ill patients receiving CRRT for acute kidney injury from December 2006 through November 2015 in a tertiary referral hospital in the United States. We used logistic regression to assess serum chloride before and mean serum chloride during CRRT as predictors for 90 days mortality after CRRT initiation. The normal reference range for serum chloride was 99–108 mmol/L. Results Of 1282 eligible patients, 25%, 50%, and 25% had hypochloremia, normochloremia, and hyperchloremia, respectively. The adjusted odds ratio for 90 days mortality in patients with hypochloremia before CRRT was 1.82 (95% CI 1.29–2.55). During CRRT, 4%, 70%, 26% of patients had mean serum chloride in the hypochloremia, normochloremia, and hyperchloremia range, respectively. The adjusted odds ratio for 90 days mortality in patients with mean serum chloride during CRRT in the hypochloremia range was 2.96 (95% CI 1.43–6.12). Hyperchloremia before and during CRRT was not associated with mortality. The greater serum chloride range during CRRT was associated with increased mortality (OR 1.29; 95% CI 1.13–1.47 per 5 mmol/L increase). Conclusion Hypochloremia before and during CRRT is associated with higher mortality.

Background: Acute kidney injury (AKI) survivors are at heightened risk for poor short- and long-term health outcomes. Even among those who recover after an AKI episode, the risk for chronic kidney disease is 4- to 6-fold higher than in patients without AKI, underscoring the importance of identifying methods to improve AKI survivorship. Objective: The purpose of this report was to describe the development and feasibility of a novel multidisciplinary approach to caring for AKI survivors at care transitions (ACT). Design: Observational process improvement initiative. Setting: Single academic medical center in the United States. Patients: The studied population was adults with stage 3 AKI not discharging on dialysis who were established with a primary care provider (PCP) at our institution. Methods: An electronic health record tool was developed prior to implementation to identify AKI survivors. The ACT program encompassed engaging patients in the hospital, delivering education by nephrology-trained nurses before discharge, completing recommended laboratory testing after discharge, and conducting structured kidney-focused follow-up with a pharmacist and a PCP within 7 to 14 days after discharge. Patients could be referred for nephrology evaluation at the discretion of the PCP. Results: Preliminary data demonstrated that most AKI survivors of interest could be identified, educated, and followed up with this model. This strategy appeared feasible, scalable, and maximized the unique expertise of each member of the multidisciplinary team. Limitations: Small sample size, future assessment of process, clinical, and patient-reported outcomes needed. Conclusions: The multidisciplinary ACT workflow supported by clinical decision support was feasible and addressed gaps in existing care transition models. Team-based care delivery in primary care appears to be a mechanism to extend the capacity for kidney health monitoring for AKI survivors.

AbstractBackgroundProposed phenotypes have recently been identified in cardiogenic shock (CS) populations using unsupervised machine learning clustering methods. We sought to validate these phenotypes in a mixed cardiac intensive care unit (CICU) population of patients with CS.MethodsWe included Mayo Clinic CICU patients admitted from 2007 to 2018 with CS. Agnostic K means clustering was used to assign patients to three clusters based on admission values of estimated glomerular filtration rate, bicarbonate, alanine aminotransferase, lactate, platelets, and white blood cell count. In‐hospital mortality and 1‐year mortality were analyzed using logistic regression and Cox proportional‐hazards models, respectively.ResultsWe included 1498 CS patients with a mean age of 67.8 ± 13.9 years, and 37.1% were females. The acute coronary syndrome was present in 57.3%, and cardiac arrest was present in 34.0%. Patients were assigned to clusters as follows: Cluster 1 (noncongested), 603 (40.2%); Cluster 2 (cardiorenal), 452 (30.2%); and Cluster 3 (hemometabolic), 443 (29.6%). Clinical, laboratory, and echocardiographic characteristics differed across clusters, with the greatest illness severity in Cluster 3. Cluster assignment was associated with in‐hospital mortality across subgroups. In‐hospital mortality was higher in Cluster 3 (adjusted odds ratio [OR]: 2.6 vs. Cluster 1 and adjusted OR: 2.0 vs. Cluster 2, both p < 0.001). Adjusted 1‐year mortality was incrementally higher in Cluster 3 versus Cluster 2 versus Cluster 1 (all p < 0.01).ConclusionsWe observed similar phenotypes in CICU patients with CS as previously reported, identifying a gradient in both in‐hospital and 1‐year mortality by cluster. Identifying these clinical phenotypes can improve mortality risk stratification for CS patients beyond standard measures.