Epidemiology and outcomes of acute kidney injury in cardiac intensive care unit patients

Shock Severity Classification and Mortality in Adults With Cardiac, Medical, Surgical, and Neurological Critical Illness

OBJECTIVE

To evaluate whether the Society for Cardiovascular Angiography and Interventions (SCAI) Shock Classification could perform risk stratification in a mixed cohort of intensive care unit (ICU) patients, similar to its validation in patients with acute cardiac disease.

METHODS

We included 21,461 adult Mayo Clinic ICU patient admissions from December 1, 2014, to February 28, 2018, including cardiac ICU (16.7%), medical ICU (37.4%), neurosciences ICU (27.7%), and surgical ICU (18.2%). The SCAI Shock Classification (a 5-stage classification from no shock [A] to refractory shock [E]) was assigned in each 4-hour period during the first 24 hours of ICU admission.

RESULTS

The median age was 65 years, and 43.2% were female. In-hospital mortality occurred in 1611 (7.5%) patients, with a stepwise increase in in-hospital mortality in each higher maximum SCAI Shock stage overall: A, 4.0%; B, 4.6%; C, 7.0%; D, 13.9%; and E, 40.2%. The SCAI Shock Classification provided incremental mortality risk stratification in each ICU, with the best performance in the cardiac ICU and the worse performance in the neurosciences ICU. The SCAI Shock Classification was associated with higher adjusted in-hospital mortality (adjusted odds ratio, 1.32 per each stage; 95% CI, 1.24 to 1.41; P<.001); this association was not observed in the neurosciences ICU when considered separately.

CONCLUSION

The SCAI Shock Classification provided incremental mortality risk stratification beyond established prognostic markers across the spectrum of medical and surgical critical illness, proving utility outside its original intent.

Association between the shock index on admission and in-hospital mortality in the cardiac intensive care unit

BACKGROUND

An elevated shock index (SI) predicts worse outcomes in multiple clinical arenas. We aimed to determine whether the SI can aid in mortality risk stratification in unselected cardiac intensive care unit patients.

METHODS

We included admissions to the Mayo Clinic from 2007 to 2015 and stratified them based on admission SI. The primary outcome was in-hospital mortality, and predictors of in-hospital mortality were analyzed using multivariable logistic regression.

RESULTS

We included 9,939 unique cardiac intensive care unit patients with available data for SI. Patients were grouped by SI as follows: < 0.6, 3,973 (40%); 0.6-0.99, 4,810 (48%); and ≥ 1.0, 1,156 (12%). After multivariable adjustment, both heart rate (adjusted OR 1.06 per 10 beats per minute higher; CI 1.02-1.10; p-value 0.005) and systolic blood pressure (adjusted OR 0.94 per 10 mmHg higher; CI 0.90-0.97; p-value < 0.001) remained associated with higher in-hospital mortality. As SI increased there was an incremental increase in in-hospital mortality (adjusted OR 1.07 per 0.1 beats per minute/mmHg higher, CI 1.04-1.10, p-Value < 0.001). A higher SI was associated with increased mortality across all examined admission diagnoses.

CONCLUSION

The SI is a simple and universally available bedside marker that can be used at the time of admission to predict in-hospital mortality in cardiac intensive care unit patients.

Prevalence, risk factors, and outcomes of acute kidney injury in a pediatric cardiac intensive care unit: A cross-sectional study

Background and Aims

Acute kidney injury (AKI) is a common complication in pediatric cardiac intensive care unit (CICU). This study aims to identify the prevalence, risk factors, and outcomes of AKI in pediatrics admitted to a CICU unit of a tertiary hospital.

Methods

We retrospectively gathered the data of 253 randomly selected patients admitted to the CICU unit from March 2018 to March 2022. Data were collected from EHRs. We used the Kidney Disease Improving Global Outcomes (KDIGO) criteria for identifying AKI in patients.

Results

Overall, AKI prevalence was 22.9% in our population. In the multivariable analysis, vancomycin intake (odds ratio [OR]: 2.109, 95% confidence interval [CI]: 1.15-3.84), angiography (OR: 4.38, 95% CI: 1.28-14.93), and mechanical ventilation (OR: 2.08, 95% CI: 1.02-4.23) were independent risk factors of AKI development and patients with AKI had a higher in-hospital mortality rate (OR: 5.81, 95% CI: 2.55-13.19), higher need for cardiopulmonary resuscitation (OR: 3.08, 95% CI: 1.17-8.09), and longer ICU length of stay (OR: 6.49, 95% CI: 3.31-9.67). Furthermore, furosemide administration was associated with lower risk of developing AKI (OR: 0.52, 95% CI: 0.27-0.97).

Conclusion

AKI is common and is associated with worse outcomes in patients with congenital heart disease. Our results emphasize the importance of early identification and monitoring of AKI in the pediatric CICU setting.

The Changing Epidemiology of the Cardiac Intensive Care Unit

Coronary care units (CCUs) were originally designed to monitor and treat peri-infarction ventricular arrhythmias but have evolved into highly specialized cardiac intensive care units (CICUs) that provide care to a patient population that is increasingly heterogeneous and complex. Paralleling broader epidemiologic trends, patients admitted to contemporary CICUs are older and have a greater burden of cardiovascular and non-cardiovascular comorbidities. Moreover, contemporary CICU patients have high illness severity and often present with acute noncardiac organ dysfunction. In addition to these shifting demographic patterns, there have been important epidemiologic changes in CICU technologies, multidisciplinary systems of care, and physician staffing and training.

Serial Assessment of Shock Severity in Cardiac Intensive Care Unit Patients

BACKGROUND

One-time assessment of the Society for Cardiovascular Angiography and Interventions (SCAI) shock classification robustly predicts mortality in the cardiac intensive care unit (CICU). We sought to determine whether serial SCAI shock classification could improve risk stratification.

METHODS AND RESULTS

Unique admissions to a single academic level 1 CICU from 2015 to 2018 were included in this retrospective cohort study. Electronic health record data were used to assign the SCAI shock stage during 4-hour blocks of the first 24 hours of CICU admission. Shock was defined as hypoperfusion (SCAI shock stage C, D, or E). In-hospital death was evaluated using logistic regression. Among 2918 unique CICU patients, 1537 (52.7%) met criteria for shock during ≥1 block, and 266 (9.1%) died in the hospital. The SCAI shock stage on admission was: A, 37.6%; B, 31.5%; C, 25.9%; D, 1.8%; and E, 3.3%. Patients who met SCAI criteria for shock on admission (first 4 hours) and those with worsening SCAI shock stage after admission were at higher risk for in-hospital death. Each higher admission (adjusted odds ratio, 1.36 [95% CI, 1.18-1.56]; area under the receiver operating characteristic curve, 0.70), maximum (adjusted odds ratio, 1.59 [95% CI, 1.37-1.85]; area under the receiver operating characteristic curve, 0.73) and mean (adjusted odds ratio, 2.42 [95% CI, 1.99-2.95]; area under the receiver operating characteristic curve, 0.78) SCAI shock stage was incrementally associated with a higher in-hospital mortality rate. Discrimination was highest for the mean SCAI shock stage (P<0.05). Each additional 4-hour block meeting SCAI criteria for shock predicted a higher mortality rate (adjusted odds ratio, 1.15 [95% CI, 1.07-1.24]).

CONCLUSIONS

Dynamic assessment of shock using serial SCAI shock classification assignment can improve mortality risk stratification in CICU patients by quantifying the magnitude and duration of shock.

Digital health utilities in acute kidney injury management

PURPOSE OF REVIEW

Acute kidney injury (AKI) is a highly prevalent clinical syndrome that substantially impacts patient outcomes. It is accepted by the clinical communities that the management of AKI is time-sensitive. Unfortunately, despite growing proof of its preventability, AKI management remains suboptimal in community, acute care, and postacute care settings. Digital health solutions comprise various tools and models to improve care processes and patient outcomes in multiple medical fields. AKI development, progression, recovery, or lack thereof, offers tremendous opportunities for developing, validating, and implementing digital health solutions in multiple settings. This article will review the definitions and components of digital health, the characteristics of AKI that allow digital health solutions to be considered, and the opportunities and threats in implementing these solutions.

RECENT FINDINGS

Over the past two decades, the academic output related to the use of digital health solutions in AKI has exponentially grown. While this indicates the growing interest in the topic, most topics are primarily related to clinical decision support by detecting AKI within hospitals or using artificial intelligence or machine learning technologies to predict AKI within acute care settings. However, recently, projects to assess the impact of digital health solutions in more complex scenarios, for example, managing nephrotoxins among adults of pediatric patients who already have AKI, is increasing. Depending on the type of patients, chosen digital health solution intervention, comparator groups, and selected outcomes, some of these studies showed benefits, while some did not indicate additional gain in care processes or clinical outcomes.

SUMMARY

Careful needs assessment, selection of the correct digital health solution, and appropriate clinical validation of the benefits while avoiding additional health disparities are moral, professional, and ethical obligations for all individuals using these healthcare tools, including clinicians, data scientists, and administrators.

CHANGES IN VASOACTIVE DRUG REQUIREMENTS AND MORTALITY IN CARDIAC INTENSIVE CARE UNIT PATIENTS

ABSTRACT

Background: The Society for Cardiovascular Angiography and Intervention (SCAI) Shock Classification can define shock severity. We evaluated the vasoactive-inotropic score (VIS) combined with the SCAI Shock Classification for mortality risk stratification. Methods: This was a single-center retrospective cohort analysis including Mayo Clinic cardiac intensive care unit patients from 2007 to 2015. The peak VIS was calculated at 1 and 24 h after cardiac intensive care unit admission. In-hospital mortality was evaluated using multivariable logistic regression. Results: Of 9,916 included patients, vasoactive drugs were used in 875 (8.8%) within 1 h and 2,196 (22.1%) within 24 h. A total of 888 patients (9.0%) died during hospitalization. Patients who required vasoactive drugs within 1 h had higher in-hospital mortality (adjusted odds ratio [OR], 1.30; 95% confidence interval [CI], 1.03-1.65; P = 0.03) and in-hospital mortality rose with the VIS during the first 1 h (adjusted OR per 10 units, 1.22; 95% CI, 1.12-1.33; P < 0.001). The increase in VIS from 1 to 24 h was associated with higher in-hospital mortality (adjusted OR per 10 units, 1.16; 95% CI, 1.10-1.21; P < 0.001). These results were consistent in the 1,067 patients (10.9%) with cardiogenic shock. A gradient of in-hospital mortality was observed according to the VIS at 1 h and the increase in VIS from 1 to 24 h. Conclusions: Higher vasoactive drug requirements portend a higher risk of mortality, particularly a high VIS early after admission. The VIS provides incremental prognostic information beyond the SCAI Shock Classification, emphasizing the continuum of risk that exists across the spectrum of shock severity.

Urine Output and Mortality in Patients Resuscitated from out of Hospital Cardiac Arrest

BACKGROUND

Limited data exist regarding urine output (UO) as a prognostic marker in out-of-hospital-cardiac-arrest (OHCA) survivors undergoing targeted temperature management (TTM).

METHODS

We included 247 comatose adult patients who underwent TTM after OHCA between 2007 and 2017, excluding patients with end-stage renal disease. Three groups were defined based on mean hourly UO during the first 24 h: Group 1 (<0.5 mL/kg/h, n = 73), Group 2 (0.5-1 mL/kg/h, n = 81) and Group 3 (>1 mL/kg/h, n = 93). Serum creatinine was used to classify acute kidney injury (AKI). The primary and secondary outcomes respectively were in-hospital mortality and favorable neurological outcome at hospital discharge (modified Rankin Scale [mRS]<3).

RESULTS

In-hospital mortality decreased incrementally as UO increased (adjusted OR 0.9 per 0.1 mL/kg/h higher; p = 0.002). UO < 0.5 mL/kg/h was strongly associated with higher in-hospital mortality (adjusted OR 4.2 [1.6-10.8], p = 0.003) and less favorable neurological outcomes (adjusted OR 0.4 [0.2-0.8], p = 0.007). Even among patients without AKI, lower UO portended higher mortality (40% vs 15% vs 9% for UO groups 1, 2, and 3 respectively, p < 0.001).

CONCLUSION

Higher UO is incrementally associated with lower in-hospital mortality and better neurological outcomes. Oliguria may be a more sensitive early prognostic marker than creatinine-based AKI after OHCA.

A LASSO-derived clinical score to predict severe acute kidney injury in the cardiac surgery recovery unit: a large retrospective cohort study using the MIMIC database

OBJECTIVES

We aimed to develop an effective tool for predicting severe acute kidney injury (AKI) in patients admitted to the cardiac surgery recovery unit (CSRU).

DESIGN

A retrospective cohort study.

SETTING

Data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database, consisting of critically ill participants between 2001 and 2012 in the USA.

PARTICIPANTS

A total of 6271 patients admitted to the CSRU were enrolled from the MIMIC-III database.

PRIMARY AND SECONDARY OUTCOME

Stages 2-3 AKI.

RESULT

As identified by least absolute shrinkage and selection operator (LASSO) and logistic regression, risk factors for AKI included age, sex, weight, respiratory rate, systolic blood pressure, diastolic blood pressure, central venous pressure, urine output, partial pressure of oxygen, sedative use, furosemide use, atrial fibrillation, congestive heart failure and left heart catheterisation, all of which were used to establish a clinical score. The areas under the receiver operating characteristic curve of the model were 0.779 (95% CI: 0.766 to 0.793) for the primary cohort and 0.778 (95% CI: 0.757 to 0.799) for the validation cohort. The calibration curves showed good agreement between the predictions and observations. Decision curve analysis demonstrated that the model could achieve a net benefit.

CONCLUSION

A clinical score built by using LASSO regression and logistic regression to screen multiple clinical risk factors was established to estimate the probability of severe AKI in CSRU patients. This may be an intuitive and practical tool for severe AKI prediction in the CSRU.

Epidemiology and Outcomes of Patients Readmitted to the Intensive Care Unit After Cardiac Intensive Care Unit Admission

Readmission to the intensive care unit (ICU) during the index hospitalization is associated with poor outcomes in medical or surgical ICU survivors. Little is known about critically ill patients with acute cardiovascular conditions cared for in a cardiac intensive care unit (CICU). We sought to describe the incidence, risk factors, and outcomes of all ICU readmissions in patients who survived to CICU discharge. We retrospectively reviewed Mayo Clinic patients from 2007 to 2015 who survived the index CICU admission and identified patients with a second ICU stay during their index hospitalization; these patients were categorized as ICU transfers (patients who went directly from the CICU to another ICU) or ICU readmissions (patients initially transferred from the CICU to the ward, and then back to an ICU). Among 9,434 CICU survivors (mean age 67 years), 138 patients (1.5%) had a second ICU stay during the index hospitalization: 60 ICU transfers (0.6%) and 78 ICU readmissions (0.8%). The most common indications for ICU readmission were respiratory failure and procedure/surgery. On multivariable modeling, respiratory failure, severe acute kidney injury, and Charlson Comorbidity Index at the time of discharge from the index ICU stay were associated with ICU readmission. Death during the first ICU readmission (n = 78) occurred in 7.7% of patients. In-hospital mortality was higher for patients with a second ICU stay. In conclusion, few CICU survivors have a second ICU stay during their index hospitalization; these patients are at a higher risk of in-hospital and 1-year mortality. Respiratory failure, severe acute kidney injury, and higher co-morbidity burden identify CICU survivors at elevated risk of ICU readmission.

Association of latent class analysis-derived subphenotypes of acute kidney injury with mortality in critically ill patients with cardiovascular disease: a retrospective cohort study

Background

To explore the potential heterogeneity of acute kidney injury (AKI) and evaluate the prognostic differences among AKI subphenotypes in critically ill patients with cardiovascular diseases.

Methods

Data were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database. Latent class analysis (LCA) was used to explore the potential subphenotypes of AKI in critically ill patients with cardiovascular diseases. The number of classes was identified by the Bayesian information criterion and entropy. The differences in prognostic ability among the AKI subphenotypes were evaluated by logistic regression analysis.

Result

A total of 7738 AKI patients were enrolled in this study. Using LCA, AKI patients were divided into 4 heterogeneous subphenotypes, which were obviously different from the Kidney Disease: Improving Global Outcomes (KDIGO) stages. Interestingly, class 3 classified by LCA was dominated by stage 2, while the mortality rate in class 3 was significantly different from that in class 1 (15.2% vs. 1.6%, p < 0.05). After further adjustment, the mortality rate in class 3 remained higher than that in class 1, with an odds ratio of 12.31 (95% confidence interval, 8.96–16.89).

Conclusions

LCA was feasible for AKI classification in critically ill patients with cardiovascular disease, and 4 distinct subphenotypes of AKI patients with different prognoses were identified. Our results highlighted the potential heterogeneity of AKI patients, which is worthy of further investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02587-9.

Peripheral blood neutrophil-to-lymphocyte ratio is associated with mortality across the spectrum of cardiogenic shock severity

PURPOSE

To evaluate the association between the neutrophil-to-lymphocyte ratio (NLR) and mortality across the cardiogenic shock (CS) severity spectrum, defined using the Society of Cardiovascular Interventions and Angiography (SCAI) shock stages.

MATERIALS AND METHODS

We retrospectively analyzed cardiac intensive care unit (CICU) patients between 2007 and 2015. Predictors of in-hospital mortality were analyzed using logistic regression.

RESULTS

We included 8280 patients aged 67.3 ± 15.2 years (37.2% females). Elevated NLR (≥7) was present in 45% of patients. NLR increased with worsening SCAI stage and was associated with higher in-hospital mortality in shock stages A to C (all p < 0.001). After multivariable adjustment, NLR remained associated with higher in-hospital mortality (adjusted odds ratio 1.05 per 3.5 NLR units, 95% CI 1.03-1.08, p < 0.001), with an optimal cut-off of ≥7 (in-hospital mortality 13.1% vs. 4.1%, adjusted odds ratio 1.44, 95% CI 1.14-1.81, p = 0.002). Patients in SCAI stage A or B with NLR ≥7 had higher in-hospital mortality than patients in SCAI stage B or C with NLR <7, respectively.

CONCLUSIONS

Elevated NLR is associated with higher in-hospital mortality in CICU patients with or at risk for CS, emphasizing the importance of systemic inflammation as a determinant of outcomes in CS patients.

PROGNOSTIC UTILITY OF NEUTROPHIL GELATINASE ASSOCIATED LIPOCALIN IN CARDIAC ICU: A PROSPECTIVE STUDY

Our study aims to evaluate the role of neutrophil gelatinase associated lipocalin (NGAL) as an early surrogate marker in predicting acute kidney injury (AKI) and mortality in cardiac ICU patients. The study was conducted at SRN Hospital, excluding those with known renal diseases. Out of 152 patients, 56 developed AKI (cases) and 96 were our controls. Higher NGAL was associated with increased mortality rates (P = 0.0201 and 0.0255 for serum and urinary NGAL respectively). Our study concluded that NGAL measurement at admission may be a boon in improving the outcome of cardiac ICU patients.

Laboratory Markers of Acidosis and Mortality in Cardiogenic Shock: Developing a Definition of Hemometabolic Shock

BACKGROUND

Acidosis and higher lactate predict worse outcomes in cardiogenic shock (CS) patients. We sought to determine whether overall acidosis severity on admission predicted in-hospital mortality in CS patients.

METHODS

This retrospective descriptive analysis included CS patients admitted to a single academic tertiary cardiac intensive care unit from 2007 to 2015. Admission arterial pH, base excess, and anion gap values were used to generate a Composite Acidosis Score (range 0-5, with a score ≥2 defining Severe Acidosis). Adjusted in-hospital mortality was analyzed using multivariable logistic regression.

RESULTS

We included 1,065 patients with median age of 68.9 (59.0, 77.2) years (36.4% females). Concomitant diagnoses included cardiac arrest in 38.1% and acute coronary syndrome in 59.1%. Severe Acidosis was present in 35.2%, and these patients had worse shock and more organ failure. In-hospital mortality occurred in 34.1% and was higher among patients with Severe Acidosis (54.9% vs. 22.4%, adjusted odds ratio [OR] 2.01, 95% CI 1.43-2.83, P < 0.001). Increasing Composite Acidosis Score was associated with higher in-hospital mortality (adjusted OR 1.25 per point, 95% CI 1.11-1.40, P < 0.001). Severe Acidosis was associated with higher hospital mortality at every level of shock severity and organ failure (all P < 0.05). Admission lactate level had equivalent discrimination for in-hospital mortality as the Composite Acidosis Score (0.69 vs. 0.66; P = 0.32 by De Long test).

CONCLUSION

Given its incremental association with higher in-hospital mortality among CS patients beyond shock severity and organ failure, we propose Severe Acidosis as a marker of hemometabolic shock. Lactate levels performed as well as a composite measure of acidosis for predicting mortality.

Prognostic Implications of a Cumulative Renal Score Based on Both Serum Creatinine and Urine Output Criteria for Staging of Acute Kidney Injury: A Cohort Study

Purpose

Traditionally, the Kidney Disease: Improving Global Outcomes (KDIGO) stages acute kidney injury (AKI) into three stages based on the highest severity of increase in serum creatinine (SC) or urine output (UO) criteria. Clinically, however, the two criteria do not provide equivalent information. Thus, we aimed to develop a cumulative renal score (the sum of the highest KDIGO SC and UO severity stages) for staging of AKI, expanding the original three KDIGO stages to six stages. We hypothesized that the cumulative renal score would more accurately describe AKI severity and outcomes.

Patients and Methods

Critically ill adult patients were identified from the Multi-parameter Intelligent Monitoring in Intensive Care III Database. The primary outcome was hospital mortality. Logistic regression was used to explore the association between cumulative renal score and hospital mortality.

Results

A total of 17,404 critically ill adult patients were enrolled. Patients with higher cumulative renal scores had greater hospital mortality than patients with lower cumulative renal scores (score 0, 7.6%; score 1, 9.3%; score 2, 12.5%; score 3, 18.9%; score 4, 27.1%; score 5, 34.7%; score 6, 46.8%, p < 0.001). After adjustment for significant covariates, relative to cumulative renal score 0, cumulative renal scores 2–6 were associated with increased hospital mortality. Within the traditional KDIGO stage 2 AKI, when compared with cumulative renal score 2, cumulative renal score 4 had increased hospital mortality. Within the traditional KDIGO stage 3 AKI, when compared with cumulative renal score 3, cumulative renal score 6 had increased hospital mortality.

Conclusion

Our study demonstrates that the KDIGO SC and UO criteria have a cumulative effect on AKI severity staging. The cumulative renal score improves the traditional KDIGO AKI staging by applying the two sets of criteria sequentially and provides more insight into the relationship between AKI and outcomes.

Biventricular Function and Shock Severity Predict Mortality in Cardiac ICU Patients

BACKGROUND

Ventricular function, including left ventricular systolic dysfunction (LVSD), right ventricular systolic dysfunction (RVSD), and biventricular dysfunction (BVD), contribute to shock in cardiac ICU (CICU) patients, but the prognostic usefulness remains unclear.

RESEARCH QUESTION

Do patients with ventricular dysfunction have higher mortality at each Society for Cardiovascular Angiography and Intervention (SCAI) shock stage?

STUDY DESIGN AND METHODS

We identified patients in the CICU admitted with available echocardiography data. LVSD was defined as left ventricular ejection fraction < 40%, RVSD as moderate or greater systolic dysfunction by semiquantitative measurement, and BVD as the presence of both. Multivariate logistic regression determined the relationship between ventricular dysfunction and adjusted in-hospital mortality as a function of SCAI stage.

RESULTS

The study population included 3,158 patients with a mean ± SD age of 68.2 ± 14.6 years, of which 51.8% had acute coronary syndromes. LVSD was present in 22.3%, RVSD in 11.8%, and BVD in 16.4%. After adjustment for SCAI shock stage, no difference in in-hospital mortality was found between patients with LVSD or RVSD and those without ventricular dysfunction (P > .05), but BVD was associated independently with higher in-hospital mortality (adjusted hazard ratio, 1.815; 95% CI, 1.237-2.663; P = .0023). The addition of ventricular dysfunction to the SCAI staging criteria increased discrimination for hospital mortality (area under the receiver operating characteristic curve, 0.784 vs 0.766; P < .001).

INTERPRETATION

Among patients admitted to the CICU, only BVD was associated independently with higher hospital mortality. The addition of echocardiography assessment to the SCAI shock criteria may facilitate improved clinical risk stratification.

Abnormal serum chloride is associated with increased mortality among unselected cardiac intensive care unit patients

Purpose

We sought to describe the association between serum chloride levels and mortality among unselected cardiac intensive care unit (CICU) patients.

Materials and methods

We retrospectively reviewed adult patients admitted to our CICU from 2007 to 2015. The association of dyschloremia and hospital mortality was assessed in a multiple variable model including additional confounders, and the association of dyschloremia and post-discharge mortality were assessed using Cox proportional-hazards analysis.

Results

9,426 patients with a mean age of 67±15 years (37% females) were included. Admission hypochloremia was present in 1,384 (15%) patients, and hyperchloremia was present in 1,606 (17%) patients. There was a U-shaped relationship between admission chloride and unadjusted hospital mortality, with increased hospital mortality among patients with hypochloremia (unadjusted OR 3.0, 95% CI 2.5–3.6, p<0.001) or hyperchloremia (unadjusted OR 1.9, 95% CI 1.6–2.3, p<0.001). After multivariate adjustment, hypochloremia remained associated with higher hospital mortality (adjusted OR 2.1, 95% CI 1.6–2.9, p <0.001). Post-discharge mortality among hospital survivors was higher among patients with admission hypochloremia (adjusted HR 1.3, 95% CI 1.1–1.6; p<0.001).

Conclusion

Abnormal serum chloride on admission to the CICU is associated with increased short- and long-term mortality, with hypochloremia being a strong independent predictor.

Incidence and outcomes of acute kidney injury stratified by cardiogenic shock severity

BACKGROUND

Acute 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.

METHODS

We 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.

RESULTS

We 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).

CONCLUSIONS

Higher 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.