Citations

Introduction: Acute kidney injury (AKI) is a highly prevalent risk factor for mortality among patients with cardiogenic shock (CS). We sought to assess the incidence and prognostic relevance of AKI as a function of shock severity in unselected Cardiac Intensive Care Unit (CICU) patients, as measured by the Society for the Cardiovascular Angiography and Interventions (SCAI) shock stage. Methods: We retrospectively reviewed admissions to the Mayo Clinic from 2007 to 2015 and stratified patients by the SCAI shock stage. AKI was defined and staged based on changes in serum creatinine during hospitalization as per KDIGO guidelines. Predictors of in-hospital mortality were analyzed using Kaplan-Meier survival analysis, and one-year mortality was analyzed using Cox proportional-hazards analysis. Results: The final study population included 10,004 unique patients with a mean age of 67 years and 37% females. The percentage of patients with SCAI shock stages A, B, C, D, and E were 47%, 30%, 15%, 7%, and 1%, respectively. AKI of any severity occurred in 51% of patients during hospitalization, including severe (stage 2/3) AKI in 16%. The incidence of AKI and severe AKI increased with the SCAI shock stage. Hospital mortality occurred in 8% of patients and increased as a function of the AKI stage and SCAI shock stage. AKI was associated with increased hospital mortality after multivariable adjustment (adjusted OR per AKI stage 1.17, 95% CI 1.05-1.30, p=0.005). Twenty-one percent of patients died within one year of CICU admission, and worse AKI was associated with increased one-year mortality (adjusted HR per AKI stage 1.11, 95% CI 1.05-1.18, p=<0.001). Hospital survivors with AKI of any severity had higher mortality compared with patients who did not have AKI (p<0.001). Conclusions: AKI was increasingly common in CICU patients with higher shock severity. In-hospital and one-year mortality risk increased as a function of the severity of AKI and the SCAI shock stage. This analysis emphasizes the importance of AKI as a complication of shock and as a predictor of adverse outcomes in CICU patients.

Abstract Aims This study aims to evaluate the impact of the combination of cardiogenic shock (CS) and cardiac arrest (CA) complicating non-ST-segment elevation myocardial infarction (NSTEMI). Methods and results Adult (&gt;18 years) NSTEMI admissions using the National Inpatient Sample database (2000 to 2017) were stratified by the presence of CA and/or CS. Outcomes of interest included in-hospital mortality, early coronary angiography, hospitalization costs, and length of stay. Of the 7 302 447 hospitalizations due to NSTEMI, 147 795 (2.0%) had CS only, 155 522 (2.1%) had CA only, and 41 360 (0.6%) had both CS and CA. Compared with 2000, the adjusted odds ratios (ORs) and 95% confidence interval (CIs) for CS, CA, and both CS and CA in 2017 were 3.75 (3.58–3.92), 1.46 (1.42–1.50), and 4.52 (4.16–4.87), respectively (all P &lt; 0.001). The CS + CA (61.2%) cohort had higher multiorgan failure than CS (42.3%) and CA only (32.0%) cohorts, P &lt; 0.001. The CA only cohort had lower rates of overall (52% vs. 59–60%) and early (17% vs. 18–27%) angiography compared with the other groups (all P &lt; 0.001). CS + CA admissions had higher in-hospital mortality compared with those with CS alone (aOR 4.12 [95% CI 4.00–4.24]), CA alone (aOR 1.69 [95% CI 1.65–1.74]), or without CS/CA (aOR 22.66 [95% CI 22.06–23.27]). The presence of CS, either alone or with CA, was associated with higher hospitalization costs and longer hospital length of stay. Conclusions The combination of CS and CA is associated with higher rates of acute non-cardiac organ failure and in-hospital mortality in NSTEMI admissions as compared with those with either CS or CA alone.

AbstractBackgroundAcute kidney injury (AKI) is common among patients with cardiogenic shock (CS) and it is independently associated with mortality. We sought to assess the prevalence, severity, and prognosis of AKI as a function of cardiogenic shock severity in unselected Cardiac Intensive Care Unit (CICU) patients.MethodsWe retrospectively reviewed admissions to the Mayo Clinic between 2007 to 2015 and stratified patients by the AKI stage (based on modified Kidney Disease: Improving Global Outcomes criteria) and Society for cardiovascular angiography and interventions (SCAI) shock stage. The association with in‐hospital mortality was analyzed using multivariable logistic regression.ResultsWe included 9,311 unique patients with a mean age of 67 years and 37% females. SCAI shock stages A, B, C, D, and E were present in 47%, 30%, 15%, 7%, and 1% of patients. The incidence of AKI of any severity was 39% in the CICU and 51% during the hospitalization. Hospital mortality occurred in 8% of all patients, and the risk increased as a function of the rising AKI and SCAI shock stage. Worsening AKI stage was associated with increased adjusted hospital mortality (adjusted OR per AKI stage 1.22, 95% CI 1.10–1.36, p < .001). Higher AKI stages were associated with increased adjusted hospital mortality in SCAI stage A/B (p < .001), but not in SCAI stage C, D, or E (all p > .05).ConclusionsHigher AKI stages were independently associated with mortality in CICU patients after accounting for shock severity and may add incremental prognostic utility in patients with lower SCAI stages.

AbstractContinuous renal replacement therapy (CRRT) is the preferred extracorporeal kidney support therapy employed to support critically ill patients with acute or chronic kidney dysfunction in intensive care units. Significant heterogeneity in CRRT practice exists in part due to variable logistics, resources, and scarcity of evidence‐based CRRT practices. Importantly, homogenization of practice patterns by developing substantial evidence and effective dissemination among providers is essential for optimizing CRRT practices. The emphasis on quality of CRRT delivery has prompted identification of potential quality indicators, development of multifaceted quality improvement initiatives, effective computer science utilization, and a surge of multidisciplinary quality assurance teams that advocate for “best” CRRT practices. This manuscript provides an overview of quality improvement methodologies and reviews candidate quality indicators of CRRT and the impact of quality improvement on enhancing CRRT delivery practices.

Purpose: To describe the epidemiology, outcomes, and temporal trends of respiratory failure in the cardiac intensive care unit (CICU). Materials and Methods: Retrospective cohort analysis of 2,986 unique Mayo Clinic CICU patients from 2007 to 2018 with respiratory failure. Temporal trends were analyzed, along with hospital and 1-year mortality. Multivariable logistic regression was used to determine adjusted hospital mortality trends. Results: The prevalence of respiratory failure in the CICU increased from 15% to 38% during the study period ( P < 0.001 for trend). Among patients with respiratory failure, the utilization of invasive ventilation decreased and noninvasive ventilation modalities increased over time. Hospital mortality and 1-year mortality were 24% and 54%, respectively, with variation according to the type of respiratory support (highest among patients receiving invasive ventilation alone: 35% and 46%, respectively). Hospital mortality was highest among patients with concomitant cardiac arrest and/or shock (52% for patients with both). Hospital mortality decreased in the overall population from 35% to 25% ( P < 0.001 for trend), but was unchanged among patients receiving positive-pressure ventilation. Conclusions: The prevalence of respiratory failure in CICU more than doubled during the last decade. The use of noninvasive respiratory support increased, while overall mortality declined over time. Cardiac arrest and shock accounted for the majority of deaths. Further research is needed to optimize the outcomes of high-risk CICU patients with respiratory failure.

ABSTRACT Background: Recent data suggests improved outcomes among cardiac intensive care unit (CICU) patients treated with norepinephrine, especially patients with severe shock. We aimed to describe the association between norepinephrine and mortality in CICU patients with severe shock, defined as those requiring high-dose vasopressors (HDV). Materials and Results: We retrospectively evaluated Mayo Clinic CICU patients treated with vasopressors from 2007 to 2015. HDV was defined as a peak Cumulative Vasopressor Index of four for any vasopressor. Peak norepinephrine equivalent (NEE) dose was used to compare vasopressor doses. Multivariable logistic regression was used to determine predictors of hospital mortality. Results: We included 2,090 patients with a median age of 69 years (IQR 59–78), including 35% females; 44% of patients received HDV. Hospital mortality was higher among patients receiving HDV (42% vs. 16%, unadjusted OR 3.87, 95% CI 3.16–4.75, P < 0.01). On multivariable analysis in HDV patients, hospital mortality increased with rising peak NEE (adjusted OR 1.02 per 0.01 mcg/kg/min, 95% CI 1.01–1.02, P < 0.01) and the use of NE was associated with lower hospital mortality (adjusted OR 0.46, 95% CI 0.31–0.72, P < 0.01). After adjustment for illness severity, peak NEE and norepinephrine use were not associated with mortality among patients who did not require HDV. Conclusions: Mortality is high among CICU patients requiring HDV, and rises with increasing vasopressor requirements. Use of NE was associated with lower mortality among patients requiring HDV, but not among those without HDV, implying that patients with more severe shock may benefit from preferential use of NE.

AbstractAimsLong‐term lithium therapy (LTLT) has been associated with kidney insufficiency in bipolar disorder (BD). We aimed to investigate the risk factors of chronic kidney disease (CKD) development and progression among BD patients receiving LTLT.MethodsWe included adult patients with BD on LTLT (≥1 year) who were enrolled in the Mayo Clinic Bipolar Biobank, Rochester, Minnesota. We reviewed electronic medical records to extract information related to lithium therapy and kidney‐related data to assess changes in the estimated glomerular filtration rate (eGFR). CKD severity was assessed based on eGFR.ResultsAmong 154 patients who received LTLT, 41 patients (27%) developed CKD, of whom 20 (49%) patients continued lithium (continuers) and 19 (46%) discontinued it (discontinuers). The median time to stage 3 CKD development was 21.7 years from the start of Li treatment. Type‐2 diabetes mellitus and benzodiazepine use were independent predictors for CKD development in the survival analysis, after controlling for age. The subsequent CKD progression rate did not differ between continuers and discontinuers (mean GFR 48.6 vs. 44.1, p = 0.13) at the end of follow‐up duration (mean duration: 3.5 ± 4.4 years for continuers and 4.9 ± 5.3 years for discontinuers).ConclusionCKD was observed in one fourth of patients with BD receiving LTLT. There was no significant difference in the progression of CKD among Li continuers versus discontinuers, at the mean follow‐up duration of 4.2 years, after the CKD diagnosis. Progression of CKD could be influenced by existing comorbidities and may not necessarily be due to lithium alone.

Purpose of review Acute kidney injury (AKI) frequently complicates hospital admission, especially in the ICU or after major surgery, and is associated with high morbidity and mortality. The risk of developing AKI depends on the presence of preexisting comorbidities and the cause of the current disease. Besides, many other parameters affect the kidney function, such as the state of other vital organs, the host response, and the initiated treatment. Advancements in the field of informatics have led to the opportunity to store and utilize the patient-related data to train and validate models to detect specific patterns and, as such, predict disease states or outcomes. Recent findings Machine-learning techniques have also been applied to predict AKI, as well as the patients’ outcomes related to their AKI, such as mortality or the need for kidney replacement therapy. Several models have recently been developed, but only a few of them have been validated in external cohorts. Summary In this article, we provide an overview of the machine-learning prediction models for AKI and its outcomes in critically ill patients and individuals undergoing major surgery. We also discuss the pitfalls and the opportunities related to the implementation of these models in clinical practices.

Objectives: Thrombocytopenia is common in critically ill patients treated with continuous renal replacement therapy and decreases in platelets following continuous renal replacement therapy initiation have been associated with increased mortality. Platelets play a role in innate and adaptive immunity, making it plausible that decreases in platelets following continuous renal replacement therapy initiation predispose patients to development of infection. Our objective was to determine if greater decreases in platelets following continuous renal replacement therapy correlate with increased rates of secondary infection. Design: Retrospective cohort analysis. Setting: This study uses a continuous renal replacement therapy database from Mayo Clinic (Rochester, MN), a tertiary academic center. Participants: Adult patients who survived until ICU discharge and were on continuous renal replacement therapy for less than 30 days were included. A subgroup analysis was also performed in patients with thrombocytopenia (platelets < 100 × 103/µL) at continuous renal replacement therapy initiation. Measurements and Main Results: The primary predictor variable was a decrease in platelets from precontinuous renal replacement therapy levels of greater than 40% or less than or equal to 40%, although multiple cut points were analyzed. The primary outcome was infection after ICU discharge, and secondary endpoints included post-ICU septic shock and post-ICU mortality. Univariable, multivariable, and propensity-adjusted analyses were used to determine associations between the predictor variable and the outcomes. Results: Among 797 eligible patients, 253 had thrombocytopenia at continuous renal replacement therapy initiation. A greater than 40% decrease in platelets after continuous renal replacement therapy initiation was associated in the multivariable-adjusted models with increased odds of post-ICU infection in the full cohort (odds ratio, 1.49; CI, 1.02–2.16) and in the thrombocytopenia cohort (odds ratio, 2.63; CI, 1.35–5.15) cohorts. Conclusions: Platelet count drop by greater than 40% following continuous renal replacement therapy initiation is associated with an increased risk of secondary infection, particularly in patients with thrombocytopenia at the time of continuous renal replacement therapy initiation. Further research is needed to evaluate the impact of both continuous renal replacement therapy and platelet loss on subsequent infection risk.