High-Sensitivity Troponin T Predicts Postoperative Cardiogenic Shock Requiring Mechanical Circulatory Support in Patients With Valve Disease

Cardiogenic Shock: Focus on Non-Cardiac Biomarkers

PURPOSE OF REVIEW

To examine the evolving multifaceted nature of cardiogenic shock (CS) in the context of non-cardiac biomarkers that may improve CS management and risk stratification.

RECENT FINDINGS

There are increasing data highlighting the role of lactate, glucose, and other markers of inflammation and end-organ dysfunction in CS. These biomarkers provide a more comprehensive understanding of the concurrent hemo-metabolic and cellular disturbances observed in CS and offer insights beyond standard structural and functional cardiac assessments. Non-cardiac biomarkers both refine the diagnostic accuracy and improve the prognostic assessments in CS. Further studies revolving around novel biomarkers are warranted to support more targeted and effective therapeutic and management interventions in these high-risk patients.

Risk Factors of Postoperative Hospital-Acquired Pneumonia in Patients Undergoing Cardiac Surgery

Background and Objectives. Hospital-acquired pneumonia is one of the complications that may occur in the postoperative period in patients undergoing heart valve surgery, which may result in prolonged hospitalization, development of respiratory failure requiring mechanical ventilation or even death. This study investigated the preoperative risk factors of postoperative pneumonia after heart valve surgery. Materials and Methods: This was a prospective study in a group of consecutive patients with hemodynamically significant valvular heart disease undergoing valve surgery. The primary endpoint at the in-hospital follow-up was hospital-acquired pneumonia after heart valve surgery. Logistic regression analysis was used to assess which variables were predictive of the primary endpoint, and odds ratios (ORdis) were calculated with a 95% confidence interval (CI). Multivariate analysis was based on the results of single-factor logistic regression, i.e., in further steps all statistically significant variables were taken into consideration. Results: The present study included 505 patients. Postoperative pneumonia occurred in 23 patients. The mean time to diagnosis of pneumonia was approximately 3 days after heart valve surgery (±2 days). In multivariate analysis, preoperative level of high-sensitivity Troponin T (hs-TnT) (OR 2.086; 95% CI 1.211-3.593; p = 0.008) and right ventricular systolic pressure (RVSP) (OR 1.043; 95% CI 1.018-1.067; p 0.004) remained independent predictors of the postoperative pneumonia. Of the patients with postoperative pneumonia, 3 patients died due to the development of multiple organ dysfunction syndrome (MODS). Conclusions: Preoperative determination of serum hs-TnT concentration and echocardiographic measurement of the RVSP parameter may be useful in predicting postoperative pneumonia in patients undergoing heart valve surgery.

Early Prediction of Cardiogenic Shock Using Machine Learning

Cardiogenic shock (CS) is a severe condition with in-hospital mortality of up to 50%. Patients who develop CS may have previous cardiac history, but that may not always be the case, adding to the challenges in optimally identifying and managing these patients. Patients may present to a medical facility with CS or develop CS while in the emergency department (ED), in a general inpatient ward (WARD) or in the critical care unit (CC). While different clinical pathways for management exist once CS is recognized, there are challenges in identifying the patients in a timely manner, in all settings, in a timeframe that will allow proper management. We therefore developed and evaluated retrospectively a machine learning model based on the XGBoost (XGB) algorithm which runs automatically on patient data from the electronic health record (EHR). The algorithm was trained on 8 years of de-identified data (from 2010 to 2017) collected from a large regional healthcare system. The input variables include demographics, vital signs, laboratory values, some orders, and specific pre-existing diagnoses. The model was designed to make predictions 2 h prior to the need of first CS intervention (inotrope, vasopressor, or mechanical circulatory support). The algorithm achieves an overall area under curve (AUC) of 0.87 (0.81 in CC, 0.84 in ED, 0.97 in WARD), which is considered useful for clinical use. The algorithm can be refined based on specific elements defining patient subpopulations, for example presence of acute myocardial infarction (AMI) or congestive heart failure (CHF), further increasing its precision when a patient has these conditions. The top-contributing risk factors learned by the model are consistent with existing clinical findings. Our conclusion is that a useful machine learning model can be used to predict the development of CS. This manuscript describes the main steps of the development process and our results.

Impact of Cardiac Injury on the Clinical Outcome of Children with Convulsive Status Epilepticus

Objectives: the aim of this study was to determine the impact of cardiac injury on clinical profile, cardiac evaluation and outcome in patients hospitalized with convulsive status epilepticus (CSE). Materials and methods: this prospective observational study included 74 children with CSE. Cardiac injury was evaluated and defined using combination of cardiac troponin, electrocardiography (ECG) and echocardiography. Clinical outcome and mortality rates were compared in patients with and without cardiac injury. Results: A total of 74 patients with CSE were included in the study. Thirty-six (48.6%) patients demonstrated markers of cardiac injury. ECG changes occurred in 45.9% and echocardiographic signs of left ventricular systolic and diastolic dysfunction reported in 5.4% and 8.1%, respectively. The mean length of hospital stays and need for ICU admission were significantly higher in patients with cardiac injury compared to others. One third of patients with cardiac injury needed mechanical ventilation and this was significantly higher than patients without (p = 0.042). hypotension and/or shock developed in 25% of cardiac injury patients and most of them required inotropic support; this was significantly higher than others without markers of cardiac injury. The overall mortality in cardiac injury group was higher (13.9% vs. 2.6%); however, this difference was not statistically significant. Conclusion: Markers of cardiac injury were common and associated with poor clinical outcome and higher risk of mortality in patients with CSE, so extensive routine cardiovascular evaluation is essential in these patients.

A Machine Learning Approach for Chronic Heart Failure Diagnosis

The aim of this study was to address chronic heart failure (HF) diagnosis with the application of machine learning (ML) approaches. In the present study, we simulated the procedure that is followed in clinical practice, as the models we built are based on various combinations of feature categories, e.g., clinical features, echocardiogram, and laboratory findings. We also investigated the incremental value of each feature type. The total number of subjects utilized was 422. An ML approach is proposed, comprising of feature selection, handling class imbalance, and classification steps. The results for HF diagnosis were quite satisfactory with a high accuracy (91.23%), sensitivity (93.83%), and specificity (89.62%) when features from all categories were utilized. The results remained quite high, even in cases where single feature types were employed.

Validation of a Visual-Based Analytics Tool for Outcome Prediction in Polytrauma Patients (WATSON Trauma Pathway Explorer) and Comparison with the Predictive Values of TRISS

Introduction: Big data-based artificial intelligence (AI) has become increasingly important in medicine and may be helpful in the future to predict diseases and outcomes. For severely injured patients, a new analytics tool has recently been developed (WATSON Trauma Pathway Explorer) to assess individual risk profiles early after trauma. We performed a validation of this tool and a comparison with the Trauma and Injury Severity Score (TRISS), an established trauma survival estimation score. Methods: Prospective data collection, level I trauma centre, 1 January 2018–31 December 2019. Inclusion criteria: Primary admission for trauma, injury severity score (ISS) ≥ 16, age ≥ 16. Parameters: Age, ISS, temperature, presence of head injury by the Glasgow Coma Scale (GCS). Outcomes: SIRS and sepsis within 21 days and early death within 72 h after hospitalisation. Statistics: Area under the receiver operating characteristic (ROC) curve for predictive quality, calibration plots for graphical goodness of fit, Brier score for overall performance of WATSON and TRISS. Results: Between 2018 and 2019, 107 patients were included (33 female, 74 male; mean age 48.3 ± 19.7; mean temperature 35.9 ± 1.3; median ISS 30, IQR 23–36). The area under the curve (AUC) is 0.77 (95% CI 0.68–0.85) for SIRS and 0.71 (95% CI 0.58–0.83) for sepsis. WATSON and TRISS showed similar AUCs to predict early death (AUC 0.90, 95% CI 0.79–0.99 vs. AUC 0.88, 95% CI 0.77–0.97; p = 0.75). The goodness of fit of WATSON (X² = 8.19, Hosmer–Lemeshow p = 0.42) was superior to that of TRISS (X² = 31.93, Hosmer–Lemeshow p < 0.05), as was the overall performance based on Brier score (0.06 vs. 0.11 points). Discussion: The validation supports previous reports in terms of feasibility of the WATSON Trauma Pathway Explorer and emphasises its relevance to predict SIRS, sepsis, and early death when compared with the TRISS method.

Association Between High-Sensitivity Troponin T on Admission and Organ Dysfunction During Hospitalization in Patients Aged 80 Years and Older with Hip Fracture: A Single-Centered Prospective Cohort Study

Background

Prognostic evaluation of elderly patients with hip fracture is an issue that has been highly concerned by clinicians. Only a few studies have focused on organ dysfunction after hip fracture in the elderly. This study aimed to investigate the association between high-sensitivity troponin T (hs-TnT) at admission and organ dysfunction during hospitalization in elderly patients with hip fracture.

Methods

We enrolled 168 patients with hip fracture who were aged 80 years and older at Geriatric Orthopaedic Center of Sichuan Provincial Orthopedic Hospital between January 2020 and August 2020. Baseline characteristics, perioperative information, and short-term clinical outcomes were analyzed.

Results

Of the 208 patients admitted during the study period, 168 met the inclusion criteria; of these, 91 (54.2%) had higher hs-TnT than the 99th percentile in the normal population. After adjustment for confounders, elevated hs-TnT was independently associated with multiple organ dysfunction syndrome in the elderly (MODSE) (adjusted OR, 5.76; 95% CI, 1.74–19.10; P = 0.004), heart dysfunction (adjusted OR, 7.48; 95% CI, 2.17–25.82; P = 0.001), MODS severity score > 3 (adjusted OR, 5.22; 95% CI, 1.32–20.60; P = 0.018), and length of hospital stay > 14 days (adjusted OR, 2.38; 95% CI, 1.05–5.36; P = 0.037).

Conclusion

Increased hs-TnT on admission is an independent risk factor for MODSE after hip fracture in patients aged 80 years and older. Effective measures should be applied to avoid progression of MODSE from pre-failure stage to failure stage.

Clinical characteristics and long-term outcomes of peripartum takotsubo cardiomyopathy and peripartum cardiomyopathy

Aims

Although some peripartum‐associated cardiomyopathy patients present with features that are clinically and echocardiographically similar to those of takotsubo cardiomyopathy (TCM), little is known about the diagnosis and clinical course of peripartum TCM.

Methods and results

In a tertiary hospital in Seoul, Korea, we searched the hospital database to find cardiomyopathy cases that were associated with pregnancy from January 1995 to May 2019. Applying the published diagnostic criteria, we sought peripartum cardiomyopathy (PPCM) and peripartum TCM patients for comparison. Of 31 pregnancy‐associated cardiomyopathy patients, 10 cases of peripartum TCM and 21 cases of PPCM were found. Maternal near‐miss death was significantly more common in the peripartum TCM group than in the PPCM group (100.0% vs. 57.1%, P = 0.030). Complete recovery was observed with all peripartum TCM cases, while 23.8% of the PPCM cases had residual left ventricular dysfunction. One death and one heart transplantation occurred in the PPCM group, while neither occurred in the peripartum TCM group. There was no difference between the two groups in terms of the rate of major adverse clinical events at 3 years of follow‐up [PPCM group: 26.3% (5/19) vs. TCM group: 33.3% (3/9), P = 0.750].

Conclusions

One‐third of pregnancy‐associated cardiomyopathy patients had peripartum TCM. With contemporary supportive care, both PPCM and peripartum TCM patients had a low mortality rate and excellent long‐term outcomes.

Cardiac resynchronization therapy in New York Heart Association class-IV patients dependent on intravenous drugs or invasive supportive treatments

Aims

We sought to evaluate the effectiveness of cardiac resynchronization therapy (CRT) in far‐advanced heart failure (FA‐HF) patients with New York Heart Association (NYHA) class‐IV status and dependency on intravenous drugs (IVDs) and/or invasive supportive treatments (ISTs).

Methods and results

Among 305 patients who underwent CRT implantation between October 2005 to December 2019, we identified 17 FA‐HF patients with NYHA class‐IV status and dependency on IVDs (inotropes, diuretics, vasopressors, or vasodilators) and/or ISTs (extracorporeal membranous oxygenator or continuous renal replacement therapy). All patients (median age = 68.7 years, non‐ischaemic cardiomyopathy = 15) remained dependent on several IVDs (2.2 ± 1.3 per patient) and/or ISTs for 11.3 ± 7.8 days due to multiple tapering failure (4.3 ± 3.2 per patient) before CRT implantation. However, 14 (82%) patients were successfully weaned from IVDs/ISTs within 5.2 ± 5.3 days following CRT, and 12 (71%) stayed alive for more than 1 year free of ventricular assist device or heart transplantation with symptom improvement (≥1 NYHA class) and a reduced annual HF hospitalization rate (P = 0.002). Considerable improvements in ventricular systolic function (P = 0.004) and volumetric reverse remodelling (P = 0.007) were noticed during the long‐term follow‐up period (35 ± 15 months post‐CRT). The ventricular assist device/heart transplantation/death‐free survival rate post‐CRT was 71% and 65% at 1 and 3 years, respectively.

Conclusions

Cardiac resynchronization therapy implantation may be a feasible treatment that can offer short‐term and long‐term clinical benefits for NYHA class‐IV FA‐HF patients who are dependent on IVDs/ISTs. When considering treatment options, CRT should not be prematurely excluded solely based on a patient's dependency on IVDs/ISTs without first attempting to identify favourable CRT response factors.

Hemodynamic monitoring in patients with venoarterial extracorporeal membrane oxygenation

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is an effective mechanical circulatory support modality that rapidly restores systemic perfusion for circulatory failure in patients. Given the huge increase in VA-ECMO use, its optimal management depends on continuous and discrete hemodynamic monitoring. This article provides an overview of VA-ECMO pathophysiology, and the current state of the art in hemodynamic monitoring in patients with VA-ECMO.