Predictive value of individual Sequential Organ Failure Assessment sub-scores for mortality in the cardiac intensive care unit

Arterial hyperoxia and mortality in the cardiac intensive care unit

BACKGROUND

Arterial hyperoxia (hyperoxemia), defined as a high arterial partial pressure of oxygen (PaO2), has been associated with adverse outcomes in critically ill populations, but has not been examined in the cardiac intensive care unit (CICU). We evaluated the association between exposure to hyperoxia on admission with in-hospital mortality in a mixed CICU cohort.

METHODS

We included unique Mayo Clinic CICU patients admitted from 2007 to 2018 with admission PaO2 data (defined as the PaO2 value closest to CICU admission) and no hypoxia (PaO2 < 60mmHg). The admission PaO2 was evaluated as a continuous variable and categorized (60-100 mmHg, 101-150 mmHg, 151-200 mmHg, 201-300 mmHg, >300 mmHg). Logistic regression was used to evaluate predictors of in-hospital mortality before and after multivariable adjustment.

RESULTS

We included 3,368 patients with a median age of 70.3 years; 70.3% received positive-pressure ventilation. The median PaO2 was 99 mmHg, with a distribution as follows: 60-100 mmHg, 51.9%; 101-150 mmHg, 28.6%; 151-200 mmHg, 10.6%; 201-300 mmHg, 6.4%; >300 mmHg, 2.5%. A J-shaped association between admission PaO2 and in-hospital mortality was observed, with a nadir around 100 mmHg. A higher PaO2 was associated with increased in-hospital mortality (adjusted OR 1.17 per 100 mmHg higher, 95% CI 1.01-1.34, p = 0.03). Patients with PaO2 >300 mmHg had higher in-hospital mortality versus PaO2 60-100 mmHg (adjusted OR 2.37, 95% CI 1.41-3.94, p < 0.001).

CONCLUSIONS

Hyperoxia at the time of CICU admission is associated with higher in-hospital mortality, primarily in those with severely elevated PaO2 >300 mmHg.

Validation of Adult Sepsis Event and Epidemiologic Analysis of Sepsis Prevalence and Mortality Using Adult Sepsis Event's Electronic Health Records-Based Sequential Organ Failure Assessment Criteria: A Single-Center Study in South Korea

OBJECTIVES

In 2018, the Centers for Disease Control and Prevention introduced the Adult Sepsis Event (ASE) definition, using electronic health records (EHRs) data for surveillance and sepsis quality improvement. However, data regarding ASE outside the United States remain limited. We therefore aimed to validate the diagnostic accuracy of the ASE and to assess the prevalence and mortality of sepsis using ASE.

DESIGN

Retrospective cohort study.

SETTING

A single center in South Korea, with 2732 beds including 221 ICU beds.

PATIENTS

During the validation phase, adult patients who were hospitalized or visiting the emergency department between November 5 and November 11, 2019, were included. In the subsequent phase of epidemiologic analysis, we included adult patients who were admitted from January to December 2020.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

ASE had a sensitivity of 91.6%, a specificity of 98.3%, a positive predictive value (PPV) of 57.4%, and a negative predictive value of 99.8% when compared with the Sepsis-3 definition. Of 126,998 adult patient hospitalizations in 2020, 6,872 cases were diagnosed with sepsis based on the ASE (5.4% per year), and 893 patients were identified as having sepsis according to the International Classification of Diseases , 10th Edition (ICD-10) (0.7% per year). Hospital mortality rates were 16.6% (ASE) and 23.5% (ICD-10-coded sepsis). Monthly sepsis prevalence and hospital mortality exhibited less variation when diagnosed using ASE compared with ICD-10 coding (coefficient of variation [CV] for sepsis prevalence: 0.051 vs. 0.163, Miller test p < 0.001; CV for hospital mortality: 0.087 vs. 0.261, p = 0.001).

CONCLUSIONS

ASE demonstrated high sensitivity and a moderate PPV compared with the Sepsis-3 criteria in a Korean population. The prevalence of sepsis, as defined by ASE, was 5.4% per year and was similar to U.S. estimates. The prevalence of sepsis by ASE was eight times higher and exhibited less monthly variability compared with that based on the ICD-10 code.

Guide to Lung-Protective Ventilation in Cardiac Patients

The incidence of acute respiratory insufficiency has continued to increase among patients admitted to modern-day cardiovascular intensive care units. Positive pressure ventilation (PPV) remains the mainstay of treatment for these patients. Alterations in intrathoracic pressure during PPV has distinct effects on both the right and left ventricles, affecting cardiovascular performance. Lung-protective ventilation (LPV) minimizes the risk of further lung injury through ventilator-induced lung injury and, hence, an understanding of LPV and its cardiopulmonary interactions is beneficial for cardiologists.

Association between the neutrophil-to-lymphocyte ratio and in-hospital mortality in patients with chronic kidney disease and coronary artery disease in the intensive care unit

BACKGROUND

The objective of this study was to investigate the correlation between neutrophil-to-lymphocyte ratios (NLR) and the risk of in-hospital death in patients admitted to the intensive care unit (ICU) with both chronic kidney disease (CKD) and coronary artery disease (CAD).

METHODS

Data from the MIMIC-IV database, which includes a vast collection of more than 50,000 ICU admissions occurring between 2008 and 2019, was utilized in the study and eICU-CRD was conducted for external verification. The Boruta algorithm was employed for feature selection. Univariable and multivariable logistic regression analyses and multivariate restricted cubic spline regression were employed to scrutinize the association between NLR and in-hospital mortality. The receiver operating characteristic (ROC) curves were conducted to estimate the predictive ability of NLR.

RESULTS

After carefully applying criteria to include and exclude participants, a total of 2254 patients with CKD and CAD were included in the research. The findings showed a median NLR of 7.3 (4.4, 12.1). The outcomes of multivariable logistic regression demonstrated that NLR significantly elevated the risk of in-hospital mortality (OR 2.122, 95% confidence interval [CI] 1.542-2.921, P < 0.001) after accounting for all relevant factors. Further insights from subgroup analyses unveiled that age and Sequential Organ Failure Assessment (SOFA) scores displayed an interactive effect in the correlation between NLR and in-hospital deaths. The NLR combined with traditional cardiovascular risk factors showed relatively great predictive value for in-hospital mortality (AUC 0.750).

CONCLUSION

The findings of this research indicate that the NLR can be used as an indicator for predicting the likelihood of death during a patient's stay in the intensive care unit, particularly for individuals with both CAD and CKD. The results indicate that NLR may serve as a valuable tool for assessing and managing risks in this group at high risk. Further investigation is required to authenticate these findings and investigate the mechanisms that underlie the correlation between NLR and mortality in individuals with CAD and CKD.

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.

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.

Ceftazidime/Avibactam, Polymyxin or Tigecycline as a Rescue Strategy for the Treatment of Carbapenem-Resistant Klebsiella pneumoniae in Bloodstream Infection: A Retrospective Cohort Study

Objective

To analyze the clinical characteristics, outcomes, and risk factors of patients treated with ceftazidime/avibactam, polymyxin, or tigecycline (CPT) compared with those receiving a conventional therapy (CT) (ie, imipenem, levofloxacin, or gentamicin).

Methods

A single-center retrospective cohort study included patients with carbapenem-resistant Klebsiella pneumoniae bloodstream infection (CRKP-BSI) treated at one Chinese tertiary hospital between March 2012 and November 2022 was performed. Clinical characteristics, outcomes, and risk factors of patients treated with CPT or CT were compared. Predictors of 30-day mortality of patients with CRKP-BSI were also analysed in our study.

Results

Among 184 recruited patients with CRKP-BSI, 39.7% (73/184) were treated with CPT, while 60.3% (111/184) were treated with CT. Compared to patients treated with CT, patients treated with CPT had worse conditions, as evidenced by a higher rate of underlying diseases and invasive procedures; however, they also had a better prognosis and lower rates of 14-day treatment failure (p = 0.024). In addition, univariate analysis and multivariate analysis showed that SOFA score [odds ratio (OR) = 1.310, 95% confidence interval (CI) 1.157-1.483; p < 0.001] and cold weather (OR = 3.658, 95% CI 1.474-9.081; p = 0.005) were independent risk factors for 30-day mortality.

Conclusion

Compared to CRKP-BSI patients treated with CT, patients treated with CPT had worse conditions but better prognoses. CRKP-BSI occurred more frequently in hot weather; however, higher 30-day mortality was associated with cold weather. A randomized trial is needed to confirm these observational results.

Usefulness of the Quick-Sepsis Organ Failure Assessment Score in Cardiovascular Intensive Care Unit to Predict Prognosis in Acute Coronary Syndrome

Triage of patients with acute coronary syndrome (ACS) at high risk of in-hospital complications is essential. In this study, we evaluated the quick sepsis organ failure assessment (qSOFA) score as a tool for predicting the prognosis of 964 patients admitted to the cardiovascular intensive care unit (CICU) with ACS over a 4-year period. In total, out of 964 patients included, with a percentage of 4.6% for 30-day mortality. The risk of 30-day mortality was independently associated with qSOFA ≥ 2 at admission (hazard ratio = 2.76, 95% CI 1.32-5.74, p = 0.007). For MACEs, qSOFA ≥ 2 at admission was a predictive factor with (odds ratio = 2.42, 95% CI 1.37-4.36, p = .002). A qSOFA ≥ 2 on admission had an AUC of 0.729 (95% CI [0.694, 0.762]), with a good specificity of 91.6%. For 30-day mortality, an AUC of 0.759 (95%CI [0.726, 0.792]) for cardiogenic shock with specificity of 92.5%. For MACEs, an AUC of 0.702 (95% CI [0.64, 0.700] with a specificity of 95%. Concerning the different scores tested, we found no significant difference between the Zwolle score and the qSOFA score for predicting prognosis, whereas the CADILLAC score was better than qSOFA for predicting 30-day mortality (AUC = 0.829 and De long test = 0.03). However, there was no difference between qSOFA and CADILLAC scores for predicting cardiogenic shock (De Long test at 0.08). This is the first study to evaluate qSOFA as a predictive score for 30-day mortality and MACEs, and the results are very encouraging, particularly for cardiogenic shock.

Predictive ability of the sequential organ failure assessment score for in-hospital mortality in patients with cardiac critical illnesses: a nationwide observational study

AIMS

Several studies have reported a high predictive ability of the Sequential Organ Failure Assessment (SOFA) score for in-hospital mortality specifically for patients with cardiac critical illnesses, however, differences according to the admission classification (surgical or non-surgical) are unknown. The present study aimed to evaluate the predictive ability of the SOFA score in surgical and non-surgical patients with cardiac critical illnesses.

METHODS AND RESULTS

Using the Japanese nationwide Diagnosis Procedure Combination database, we identified patients with cardiac critical illnesses, defined as patients admitted to the intensive care unit (ICU) and treated by cardiologists or cardiovascular surgeons as their physicians in charge from April 2018 to March 2020. The discriminatory ability of the SOFA score for in-hospital mortality was assessed by calculating the area under the receiver operating characteristic curve (AUROC). Among 52 819 eligible patients with available data on their SOFA scores, 33 526 (64%) were postoperative cardiac surgeries. The median SOFA score on ICU admission was 5.0 (interquartile range, 2.0-8.0) and overall in-hospital mortality 6.8%. The AUROC of the SOFA score was 0.75 [95% confidence interval (CI), 0.75-0.76]. In the subgroup analyses, the AUROCs were 0.76 (95% CI, 0.74-0.77) in the surgical patients, 0.83 (95% CI, 0.83-0.84) in the non-surgical patients, and 0.88 (95% CI, 0.87-0.89) in the non-surgical acute coronary syndrome patients.

CONCLUSIONS

The predictive ability of the SOFA score on the day of ICU admission for in-hospital mortality was confirmed to be acceptable in the patients with cardiac critical illnesses and varied according to the admission classification and primary diagnoses.

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.

Usefulness of Glucose to Lymphocyte Ratio to Predict in-Hospital Mortality in Patients with AECOPD Admitted to the Intensive Care Unit

The purpose of this study was to investigate the relationship between glucose to lymphocyte ratio (GLR) and the outcome of acute exacerbation chronic obstructive pulmonary disease (AECOPD) patients admitted to the intensive care unit (ICU). This study included 3573 patients from the eICU Collaborative Research Database (eICU-CRD) and 926 AECOPD patients admitted to ICU from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. The optimal cutoff value for GLR was 5.6. Kaplan-Meier analysis demonstrated that patients in lower GLR (< 5.6) group showed a better overall survival than patients in higher GLR (≥ 5.6) group in all sets. Multivariate Cox regression analysis demonstrated that age, Sequential Organ Failure Assessment (SOFA) score, SpO2, albumin and GLR are independent predictors of poor overall survival in the training cohort and were incorporated into the nomogram for in-hospital mortality as independent factors. The nomogram exhibited excellent discrimination with C-indexes in training cohort, internal validation and external validation cohort were (0.801, 95%CI: 0.769-0.863), (0.805, 95%CI: 0.759-0.851) and (0.811, 95%CI: 0.772-0.850), respectively. The calibration plot indicated an adequate fit of the nomogram for predicting the risk of in-hospital mortality in all sets. Moreover, the ROC analyses demonstrated that the discrimination abilities of GLR were better than other blood-based inflammatory biomarkers. As an easily available biomarker, GLR can independently predict the in-hospital mortality in AECOPD patients admitted to ICU. The nomogram combining GLR with other significant indicators exhibited excellence predictive performance for in-hospital mortality.

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.

Association of Sequential Organ Failure Assessment (SOFA) components with mortality

BACKGROUND

Sequential Organ Failure Assessment (SOFA) is a practical method to describe and quantify the presence and severity of organ system dysfunctions and failures. Some proposals suggest that SOFA could be employed as an endpoint in trials. To justify this, all SOFA component scores should reflect organ dysfunctions of comparable severity. We aimed to investigate whether the associations of different SOFA components with in-hospital mortality are comparable.

METHODS

We performed a study based on nationwide register data on adult patients admitted to 26 Finnish intensive care units (ICUs) during 2012-2015. We determined the SOFA score as the maximum score in the first 24 hours after ICU admission. We defined organ failure (OF) as an organ-specific SOFA score of three or higher. We evaluated the association of different SOFA component scores with mortality.

RESULTS

Our study population comprised 63,756 ICU patients. Overall hospital mortality was 10.7%. In-hospital mortality was 22.5% for patients with respiratory failure, 34.8% for those with coagulation failure, 40.1% for those with hepatic failure, 14.9% for those with cardiovascular failure, 26.9% for those with neurologic failure and 34.6% for the patients with renal failure. Among patients with comparable total SOFA scores, the risk of death was lower in patients with cardiovascular OF compared with patients with other OFs.

CONCLUSIONS

All SOFA components are associated with mortality, but their weights are not comparable. High scores of other organ systems mean a higher risk of death than high cardiovascular scores. The scoring of cardiovascular dysfunction needs to be updated.

Contemporary Review of Risk Scores in Prediction of Coronary and Cardiovascular Deaths

PURPOSE OF REVIEW

Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths.

RECENT FINDINGS

Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk. It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.

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.

Influence of intra-aortic balloon pump on mortality as a function of cardiogenic shock severity

BACKGROUND

Randomized studies of intra-aortic balloon pump (IABP) in cardiogenic shock (CS) have focused exclusively on patients with acute coronary syndromes (ACS) without stratification according to shock severity. We examined the association between IABP and mortality in CS patients across the Society for Cardiovascular Angiography and Intervention (SCAI) shock stages.

METHODS

We included cardiac intensive care unit patients admitted from 2007 to 2015 with CS from any etiology. In-hospital mortality associated with IABP was examined in each SCAI shock stage. Multivariable logistic regression was performed using inverse probability of treatment weighting (IPTW) to determine the association between IABP and in-hospital mortality.

RESULTS

We included 934 patients, with a mean age of 68 ± 14 years; 60% had ACS. The distribution of SCAI shock stages was: B, 41%; C, 13%; D, 38%; E, 8%. In-hospital mortality was lower in the 39% of patients who received IABP (27% vs. 43%, adjusted OR with IABP after IPTW 0.53, 95% CI 0.40-0.72, p < .0001). IABP use was associated with lower crude in-hospital mortality in each SCAI shock stage (all p < .05, except p = .08 in SCAI shock stage E). We did not observe any significant heterogeneity in the association between IABP use and in-hospital mortality as a function of SCAI shock stage.

CONCLUSIONS

IABP use was associated with substantially lower in-hospital mortality in patients with CS, without differences in this effect across the SCAI shock stages. Future studies should account for the severity and etiology of shock when evaluating the efficacy of IABP for CS.

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.

Trends in Therapy and Outcomes Associated With Respiratory Failure in Patients Admitted to the Cardiac Intensive Care Unit

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.

SOFA score and short-term mortality in acute decompensated heart failure

Acute decompensated heart failure (ADHF) is one of the leading causes for hospitalization and mortality. Identifying high risk patients is essential to ensure proper management. Sequential Organ Function Assessment Score (SOFA) is considered an excellent score to predict short-term mortality in sepsis and other life-threatening conditions. To assess the capability of SOFA score in predicting short-term mortality in ADHF. We retrospectively identified patients with first hospitalization with primary diagnosis of ADHF between the years (2008–2018). The SOFA score was calculated for all patients. A total 3232 patients were included in the study. The SOFA score was significantly associated with in-hospital mortality and 30-day mortality. The odds ratios for 1-point increase in the SOFA score were 1.86 (95% CI 1.68–1.96) and 1.627 (95% CI 1.523–1.737) respectively. The SOFA Score demonstrated a good predictive accuracy. The areas under the curve of receiver operating characteristic curves for in-hospital mortality and 30-day mortality were 0.765 (95% CI 0.733–0.798) and 0.706 (95% CI 0.676–0.736) respectively. SOFA score is associated with increased risk of short-term mortality in ADHF. SOFA can be used as a complementary risk score to screen high risk patients who need strict monitoring.

Use of SOFA score in cardiac arrest research: A scoping review

Background

The Sequential Organ Failure Assessment (SOFA) score is a commonly used severity-of-illness score in cardiac arrest research. Due to its nature, the SOFA score often has missing data. How much data is missing and how that missing data is handled is unknown.

Objectives

We conducted a scoping review on cardiac arrest studies using SOFA, focusing on missing data.

Data sources

PubMed, Embase, and Web of Science.

Study selection

All English-language peer-reviewed studies of cardiac arrest with SOFA as an outcome or exposure were included.

Data extraction

For each study, quantity of missing SOFA data, analytic strategy to handle missing SOFA variables, whether/to what degree mortality influenced the amount of missing SOFA scores), SOFA score modifications, and number of SOFA measurements was extracted.

Data synthesis

We included 66 studies published between 2006–2019. Five studies were randomized controlled trials, 26 were prospective cohort studies, and 25 were retrospective cohort studies. SOFA was used as an outcome in 36 (55%) and a primary outcome in 10 (15%). Nine studies (14%) mentioned the quantity of missing SOFA data, which ranged from 0 to 76% (median: 10% [IQR: 6%, 42%]). Twenty-seven (41%) studies reported a method to handle missing SOFA. The most common method used excluded subjects with missing data (81%). In the 50 studies using serial SOFA scores, 11 (22%) documented mortality prior to SOFA measurement; which ranged from 3% to 76% (median: 12% [IQR: 6%–35%]).

Conclusions

Missing data is common in cardiac arrest research using SOFA scores. Variability exists in reporting and handling missing SOFA variables.

Mortality risk stratification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients

AIMS

An artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm can identify left ventricular systolic dysfunction (LVSD). We sought to determine whether this AI-ECG algorithm could stratify mortality risk in cardiac intensive care unit (CICU) patients, independent of the presence of LVSD by transthoracic echocardiography (TTE).

METHODS AND RESULTS

We included 11 266 unique Mayo Clinic CICU patients admitted from 2007 to 2018 who underwent AI-ECG after CICU admission. Left ventricular ejection fraction (LVEF) data were extracted for patients with a TTE during hospitalization. Hospital mortality was analysed using multivariable logistic regression. Mean age was 68 ± 15 years, including 37% females. Higher AI-ECG probability of LVSD remained associated with higher hospital mortality [adjusted odds ratio (OR) 1.05 per 0.1 higher, 95% confidence interval (CI) 1.02-1.08, P = 0.003] after adjustment for LVEF, which itself was inversely related with the risk of hospital mortality (adjusted OR 0.96 per 5% higher, 95% CI 0.93-0.99, P = 0.02). Patients with available LVEF data (n = 8242) were divided based on the presence of predicted (by AI-ECG) vs. observed (by TTE) LVSD (defined as LVEF ≤ 35%), using TTE as the gold standard. A stepwise increase in hospital mortality was observed for patients with a true negative, false positive, false negative, and true positive AI-ECG.

CONCLUSION

The AI-ECG prediction of LVSD is associated with hospital mortality in CICU patients, affording risk stratification in addition to that provided by echocardiographic LVEF. Our results emphasize the prognostic value of electrocardiographic patterns reflecting underlying myocardial disease that are recognized by the AI-ECG.

A simplified critical illness severity scoring system (CISSS): Development and internal validation

PURPOSE

To create a simplified critical illness severity scoring system with high prediction accuracy for 30-day mortality using only commonly available variables.

MATERIALS AND METHODS

This is a retrospective cohort study of ICU admissions 2010-2015 in 306 ICUs in 117 Veterans Affairs (VA) hospitals. We randomly divided our cohort into a training dataset (75%) and a validation dataset (25%). We created a critical illness severity scoring system (CISSS) using age, comorbidities, heart rate, mean arterial blood pressure, temperature, respiratory rate, hematocrit, white blood cell count, creatinine, sodium, glucose, albumin, bilirubin, bicarbonate, use of invasive mechanical ventilation, and whether the admission was surgical or not. We validated the performance of CISSS to predict 30-day mortality internally.

RESULTS

After excluding 31,743 re-admissions, we divided our sample (n = 534,001) into a training (n = 400,613) and a validation dataset (n = 133,388). In the training dataset, the area under the curve (AUC) of CISSS was 0.847(95%CI = 0.845-0.850). In the validation dataset, the AUC was 0.848 (95%CI = 0.844-0.852), the standardized mortality ratio (SMR) was 1.00 (95%CI = 0.98-1.02), and Brier's score for 30-day mortality was 0.058 (95%CI = 0.057-0.059). CISSS calibration was acceptable.

CONCLUSIONS

CISSS has very good performance and requires only commonly used variables that can be easily extracted by electronic health records.

Advanced Respiratory Support in the Contemporary Cardiac ICU

Supplemental Digital Content is available in the text.

The medical complexity and critical care needs of patients admitted to cardiac ICUs are increasing, and prospective studies examining the underlying cardiac and noncardiac diagnoses, the management strategies, and the prognosis of cardiac ICU patients with respiratory failure are needed.

Age and shock severity predict mortality in cardiac intensive care unit patients with and without heart failure

AIMS

Age is an important risk factor for mortality among patients with cardiogenic shock and heart failure (HF). We sought to assess the extent to which age modified the performance of the Society for Cardiovascular Angiography and Interventions (SCAI) shock stage for in-hospital and 1 year mortality in cardiac intensive care unit (CICU) patients with and without HF.

METHODS AND RESULTS

We retrospectively reviewed unique admissions to the Mayo Clinic CICU during 2007-2015 and stratified patients by age and SCAI shock stage. The association between age and in-hospital mortality was analysed using multivariable logistic regression, and 1 year mortality was analysed using Cox proportional hazards analysis, both in the entire cohort and among patients with an admission diagnosis of HF or acute coronary syndrome (ACS). The final study population included 10 004 unique patients with a mean age of 67 ± 15 years, including 46.1% with HF and 43.1% with ACS. Older patients more frequently had HF and had more extensive co-morbidities, higher illness severity, more organ failure, and differential use of critical care therapies. The percentage of patients with SCAI shock stages A, B, C, D, and E were 46%, 30%, 16%, 7%, and 1%, respectively. Patients with HF were older, had greater severity of illness and higher SCAI shock stage, and had higher rates of death at all time points. In-hospital mortality occurred in 908 (9%) patients, including 549 (12%) patients with HF (61% of all hospital deaths). Age was independently associated with hospital mortality (adjusted odds ratio per 10 years 1.3, 95% confidence interval 1.2-1.4, P < 0.001) and 1 year mortality (adjusted hazard ratio per 10 years 1.2, 95% confidence interval 1.2-1.3, P < 0.001) in the overall cohort. The associations of age with both hospital mortality (adjusted odds ratio 1.6 vs. 1.3 per 10 years older) and 1 year mortality (adjusted hazard ratio 1.5 vs. 1.3 per 10 years older) were higher for patients with ACS compared with patients with HF. Older age was associated with higher adjusted hospital mortality and 1 year mortality in each SCAI shock stage (all P < 0.05). Additive increases in both hospital mortality and 1 year mortality were observed with increasing age and SCAI shock stage.

CONCLUSIONS

Age is an independent risk factor for mortality that modifies the relationship between the SCAI shock stage and mortality risk in CICU patients, providing robust risk stratification for in-hospital and 1 year mortality. Although patients with HF had a higher risk of dying, age was more strongly associated with mortality among patients with ACS.

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

PURPOSE

To describe the epidemiology and outcomes of acute kidney injury (AKI) among contemporary non-surgical cardiac intensive care unit (CICU) patients.

MATERIALS AND METHODS

We reviewed adult non-surgical CICU patients admitted from 2007 to 2015. The highest AKI stage during hospitalization was defined using modified Kidney Disease: Improving Global Outcomes (KDIGO) criteria, based on changes in serum creatinine. Hospital and 5-year mortality were examined using logistic regression and Cox proportional-hazards models, respectively.

RESULTS

We included 9311 patients with a mean age of 67.5 years, including 37% females. AKI was present in 51%: stage 1 AKI in 34%, stage 2 AKI in 9%, and stage 3 AKI in 8%. Hospital mortality was associated with AKI stage (adjusted OR for each AKI stage 1.17, 95% CI 1.04-1.31, p = 0.007). Five-year mortality was incrementally associated with AKI stage (adjusted HR per AKI stage 1.13, 95% CI 1.08-1.18; p < 0.001), particularly post-discharge mortality among hospital survivors (adjusted HR per AKI stage 1.20, 95% CI 1.15-1.25, p < 0.001). Patients with stage 3 AKI (especially requiring dialysis) had the highest adjusted hospital and five-year mortality.

CONCLUSION

AKI severity is incrementally associated with higher short-term and long-term mortality in CICU patients, especially severe AKI requiring dialysis.

Early noncardiovascular organ failure and mortality in the cardiac intensive care unit

Background

Noncardiac organ failure has been associated with worse outcomes among a cardiac intensive care unit (CICU) population.

Hypothesis

We hypothesized that early organ failure based on the sequential organ failure assessment (SOFA) score would be associated with mortality in CICU patients.

Methods

Adult CICU patients from 2007 to 2015 were reviewed. Organ failure was defined as any SOFA organ subscore ≥3 on the first CICU day. Organ failure was evaluated as a predictor of hospital mortality and postdischarge survival after adjustment for illness severity and comorbidities.

Results

We included 10 004 patients with a mean age of 67 ± 15 years (37% female). Admission diagnoses included acute coronary syndrome in 43%, heart failure in 46%, cardiac arrest in 12%, and cardiogenic shock in 11%. Organ failure was present in 31%, including multiorgan failure in 12%. Hospital mortality was higher in patients with organ failure (22% vs 3%, adjusted OR 3.0, 95% CI 2.5‐3.7, P < .001). After adjustment, each failing organ system predicted twofold higher odds of hospital mortality (adjusted OR 1.9, 95% CI 1.1‐2.1, P < .001). Mortality risk was highest with cardiovascular, coagulation and liver failure. Among hospital survivors, organ failure was associated with higher adjusted postdischarge mortality risk (P < .001); multiorgan failure did not confer added long‐term mortality risk.

Conclusions

Early noncardiovascular organ failure, especially multiorgan failure, is associated with increased hospital mortality in CICU patients, and this risk continues after hospital discharge, emphasizing the need to promote early recognition of organ failure in CICU patients.