Blankenberg, Stefan

Abstract Aims Cardiogenic shock (CS) is often treated with catecholamines titrated to an adequate target mean arterial pressure (MAP) while minimizing adverse effects. We aim to assess the optimal catecholamine dose/MAP balance in heart failure-associated CS (HF-CS). Methods Patients with HF-CS were retrospectively enrolled from 16 tertiary centres in 5 European countries (2016–2021; NCT03313687). Dosage was quantified by inotropic scores (epinephrine, norepinephrine, and dobutamine). Associations of baseline and seven-day summarized dosage with intensive care unit (ICU) discharge (mixed-effects logistic regression) and 30-day mortality (Cox regression) were analysed. Potential catecholamine/MAP target ratios for optimized outcomes were assessed in models adjusted for age, sex, pH, lactate and prior resuscitation, stratified by centre. Results N = 704 patients: median age 63 years, 74% male, 34% post-resuscitation, median lactate 5.2 mmol/l. Of these, 53% were discharged from ICU, 48% died within 30 days. Higher inotropic scores independently predicted a lower probability of ICU discharge (baseline score: OR 0.78 [95%-CI 0.69–0.88]; summarized score: OR 0.46 [0.38–0.56]; both P < .001) and higher risk of 30-day mortality (baseline score: HR 1.27 [1.15–1.40], summarized score HR 1.83 [1.60–2.09]; both P < .001). A score/MAP ratio <0.403 µg/kg/min/mmHg was associated with higher ICU discharge odds (ceiling effect); a < 0.426 µg/kg/min/mmHg with lower 30-day mortality hazards (no ceiling effect). Lowering catecholamine doses by accepting reduced MAP targets was linked to better outcomes. Conclusion In HF-CS, higher catecholamine support independently associates with worse outcomes. Accepting lower blood pressure targets to reduce catecholamine dosage may improve outcomes. Validation in randomized controlled trials is urgently needed.

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.

Aims Early risk stratification is essential to guide treatment in cardiogenic shock (CS). Existing CS risk scores were derived in selected cohorts, without accounting for the heterogeneity of CS. The aim of this study was to develop a universal risk score (the Cardiogenic Shock Score, CSS) for all CS patients, irrespective of the underlying cause. Methods and results Within a registry of 1308 CS unselected patients admitted to a tertiary care hospital between 2009 and 2019, a Cox regression model was fitted to derive the CSS, with 30‐day mortality as main outcome. The CSS's predictive ability was compared to the IABP‐SHOCK II score, the CardShock score and SCAI classification by C‐indices and validated in an external cohort of 934 CS patients. Based on the Cox regression, nine predictors were included in the CSS: age, sex, acute myocardial infarction (AMI‐CS), systolic blood pressure, heart rate, pH, lactate, glucose and cardiac arrest. The CSS had the highest C‐index in the overall cohort (0.740 vs. 0.677/0.683 for IABP‐SHOCK II score/CardShock score), in patients with AMI‐CS (0.738 vs. 0.675/0.689 for IABP‐SHOCK II score/CardShock score) and in patients with non‐AMI‐CS (0.734 vs. 0.677/0.669 for IABP‐SHOCK II score/CardShock score). In the external validation cohort, the CSS had a C‐index of 0.73, which was higher than all other tested scores. Conclusion The CSS provides improved information on the risk of death in unselected patients with CS compared to existing scores, irrespective of its cause. Because it is based on point‐of‐care variables which can be obtained even in critical situations, the CSS has the potential to guide treatment decisions in CS.

AbstractAimsCardiogenic shock (CS) is associated with poor outcomes in older patients, but it remains unclear if this is due to higher shock severity. We sought to determine the associations between age and shock severity on mortality among patients with CS.Methods and resultsPatients with a diagnosis of CS from Mayo Clinic (2007–15) and University Clinic Hamburg (2009–17) were subdivided by age. Shock severity was graded using the Society for Cardiovascular Angiography and Intervention (SCAI) shock stages. Predictors of 30-day survival were determined using Cox proportional-hazards analysis. We included 1749 patients (934 from Mayo Clinic and 815 from University Clinic Hamburg), with a mean age of 67.6 ± 14.6 years, including 33.6% females. Acute coronary syndrome was the cause of CS in 54.0%. The distribution of SCAI shock stages was 24.1%; C, 28.0%; D, 33.2%; and E, 14.8%. Older patients had similar overall shock severity, more co-morbidities, worse kidney function, and decreased use of mechanical circulatory support compared to younger patients. Overall 30-day survival was 53.3% and progressively decreased as age or SCAI shock stage increased, with a clear gradient towards lower 30-day survival as a function of increasing age and SCAI shock stage. Progressively older age groups had incrementally lower adjusted 30-day survival than patients aged &lt;50 years.ConclusionOlder patients with CS have lower short-term survival, despite similar shock severity, with a high risk of death in older patients with more severe shock. Further research is needed to determine the optimal treatment strategies for older CS patients.

Background: Variations in cardiac troponin concentrations by age, sex, and time between samples in patients with suspected myocardial infarction are not currently accounted for in diagnostic approaches. We aimed to combine these variables through machine learning to improve the assessment of risk for individual patients. Methods: A machine learning algorithm (myocardial-ischemic-injury-index [MI 3 ]) incorporating age, sex, and paired high-sensitivity cardiac troponin I concentrations, was trained on 3013 patients and tested on 7998 patients with suspected myocardial infarction. MI 3 uses gradient boosting to compute a value (0–100) reflecting an individual’s likelihood of a diagnosis of type 1 myocardial infarction and estimates the sensitivity, negative predictive value, specificity and positive predictive value for that individual. Assessment was by calibration and area under the receiver operating characteristic curve. Secondary analysis evaluated example MI 3 thresholds from the training set that identified patients as low risk (99% sensitivity) and high risk (75% positive predictive value), and performance at these thresholds was compared in the test set to the 99th percentile and European Society of Cardiology rule-out pathways. Results: Myocardial infarction occurred in 404 (13.4%) patients in the training set and 849 (10.6%) patients in the test set. MI 3 was well calibrated with a very high area under the receiver operating characteristic curve of 0.963 [0.956–0.971] in the test set and similar performance in early and late presenters. Example MI 3 thresholds identifying low- and high-risk patients in the training set were 1.6 and 49.7, respectively. In the test set, MI 3 values were <1.6 in 69.5% with a negative predictive value of 99.7% (99.5–99.8%) and sensitivity of 97.8% (96.7–98.7%), and were ≥49.7 in 10.6% with a positive predictive value of 71.8% (68.9–75.0%) and specificity of 96.7% (96.3–97.1%). Using these thresholds, MI 3 performed better than the European Society of Cardiology 0/3-hour pathway (sensitivity, 82.5% [74.5–88.8%]; specificity, 92.2% [90.7–93.5%]) and the 99th percentile at any time point (sensitivity, 89.6% [87.4–91.6%]); specificity, 89.3% [88.6–90.0%]). Conclusions: Using machine learning, MI 3 provides an individualized and objective assessment of the likelihood of myocardial infarction, which can be used to identify low- and high-risk patients who may benefit from earlier clinical decisions. Clinical Trial Registration: URL: https://www.anzctr.org.au . Unique identifier: ACTRN12616001441404.

Background Platelet polyphosphate is an inorganic procoagulant polymer of orthophosphate units that is stored in dense granules and is released upon platelet activation. Here, we describe an assay to measure polyphosphate on the surface of procoagulant human platelets. Methods and Results Recombinant Escherichia coli ‐expressed exopolyphosphatase deletion mutant PPX_Δ12 labeled with fluorescent Alexa488 dye was used as a polyphosphate probe in flow cytometry. PPX_Δ12‐Alexa488‐signal dose‐dependently increased with long‐chain polyphosphate binding to platelets. In contrast, short‐chain polyphosphate that is found in the supernatant of activated platelets, did not bind to the platelet surface. Both exopolyphosphatase treatment and polyphosphate pre‐incubation abolished PPX_Δ12‐Alexa488 binding to polyphosphate on platelets. Stimulation of platelets with thrombin receptor agonist Trap6, and P2Y 12 receptor activator ADP increased polyphosphate accumulation on platelet surfaces and PPX_Δ12‐Alexa488 signal in a dose‐dependent manner. Conclusion This study indicates that long‐chain polyphosphate binds to platelet plasma membranes and presents a promising diagnostic assay to measure this interaction on human platelets in platelet‐rich plasma. Future investigations will aim to determine if polyphosphate can be used as a novel biomarker of thrombosis. © 2016 International Clinical Cytometry Society