Autonomic Nervous System Activity for Risk Stratification of Emergency Patients With Pneumonia

Cardiac deceleration capacity is associated with severity of inflammation in COVID-19

PURPOSE

In this pilot study, we investigated the cardiac autonomic activity of coronavirus disease 2019 (COVID-19)-infected hospitalized patients. COVID-19 is characterized by cough, fever, and dyspnea, which in some severe cases can lead to hypoxia, respiratory failure, and shock. Since breathing disorders and pulmonary diseases are tightly linked to autonomic dysfunction, we analyzed the cardiac autonomic activity by measuring the deceleration capacity (DC) in COVID-19 patients.

METHODS

In 14 adults (4 men and 10 women) with a median age of 63.5 years and positive for SARS-CoV-2 by polymerase chain reaction (PCR) with severe symptoms requiring hospital treatment, a high-resolution digital 30 min electrocardiogram (ECG) in Frank leads configuration was performed in a resting supine position within the first 48 h after hospital admission. DC was assessed using validated software and associated with several markers of inflammation and clinical course.

RESULTS

The study revealed a significant association between reduced DC (≤ 2.5 ms) and older age (74 years) in COVID-19 patients, compared to those with a higher DC > 2.5 ms (56.5 years). However, the duration of hospitalization was similar for both groups. There was a nonsignificant trend towards a higher maximum viral load in patients with reduced DC. Further, patients with a DC ≤ 2.5 ms showed higher levels of inflammatory markers such as C-reactive protein (CRP) and procalcitonin (PCT), as well as leukocytosis, compared to patients with a DC > 2.5 ms. Also, the COVID-19-severity marker ferritin was significantly elevated in patients with lower DC. Other markers associated with COVID-19, such as lactate dehydrogenase (LDH) and creatine kinase (CK), exhibited comparable levels in both groups.

CONCLUSIONS

Reduced DC (≤ 2.5 ms) was significantly associated with older age, increased inflammatory markers, and elevated ferritin in patients with COVID-19. These findings suggest that DC might serve as a valuable indicator for predicting the risk of severe inflammation in COVID-19 and possibly complications associated with this disease, such as heart failure. Further studies are needed to confirm these observations and clarify the clinical significance of DC in COVID-19 and other infectious diseases.

Deceleration capacity of heart rate predicts 1-year mortality in patients undergoing transcatheter edge-to-edge mitral valve repair

BACKGROUND

Risk stratification for transcatheter procedures in patients with severe mitral regurgitation is challenging. Deceleration capacity (DC) has already proven to be a reliable risk predictor in patients undergoing transcatheter aortic valve implantation. We hypothesized, that DC provides prognostic value in patients undergoing transcatheter edge-to-edge mitral valve repair (TEER).

METHODS

We retrospectively analyzed electrocardiogram signals from 106 patients undergoing TEER at the University Hospital of Tübingen. All patients received continuous heart-rate monitoring to assess DC following the procedure. One-year all-cause mortality was defined as the primary end point.

RESULTS

Sixteen patients (15.1%) died within 1 year. The DC in nonsurvivors was significantly reduced compared to survivors (5.1 ± 3.0 vs. 3.0 ± 1.6 ms, p = 0.002). A higher EuroSCORE II and impaired left ventricular function were furthermore associated with poor outcome. In Cox regression analyses, a DC < 4.5 ms was found a strong predictor of 1-year mortality (hazard ratio: 0.10, 95% confidence interval: 0.13-0.79, p = 0.029). Finally, a significant negative correlation was found between DC and residual mitral regurgitation after TEER (r = -0.41, p < 0.001).

CONCLUSION

In patients with severe mitral regurgitation undergoing TEER, DC may serve as a new predictor of follow-up mortality.

Effect of antipsychotic use by patients with schizophrenia on deceleration capacity and its relation to the corrected QT interval

OBJECTIVE

Schizophrenia patients treated with antipsychotics are at higher risk of sudden cardiac death. Decreased deceleration capacity (DC) of the heart rate is an accurate predictor of cardiac mortality. We evaluated the risk of sudden cardiac death due to antipsychotic use by assessing DC and examining the association between DC and the corrected QT interval (QTc) in schizophrenia patients.

METHODS

We measured the DC and QTc of 138 schizophrenia patients. We then compared the DC of 86 age- and sex-matched healthy controls with that of 86 schizophrenia patients. We investigated the correlation of DC of approximately 138 schizophrenia patients with prescribed doses of antipsychotics using linear regression analysis. We compared the DC of schizophrenia patients with and without prolonged QT intervals.

RESULTS

We found DC significantly differed between schizophrenia patients on antipsychotic medication and healthy controls. Additionally, DC was negatively correlated with antipsychotic use, especially chlorpromazine, zotepine, olanzapine and clozapine, in a dose-dependent manner. There was no significant association between DC and the QTc.

CONCLUSION

Assessing DC could facilitate monitoring and identification of increased risk of cardiac mortality in patients with schizophrenia that take antipsychotics. Assessing both DC and the QTc may enhance the accuracy of predicting sudden cardiac death.

Autonomic Dysfunction during Acute SARS-CoV-2 Infection: A Systematic Review

Although autonomic dysfunction (AD) after the recovery from Coronavirus disease 2019 (COVID-19) has been thoroughly described, few data are available regarding the involvement of the autonomic nervous system (ANS) during the acute phase of SARS-CoV-2 infection. The primary aim of this review was to summarize current knowledge regarding the AD occurring during acute COVID-19. Secondarily, we aimed to clarify the prognostic value of ANS involvement and the role of autonomic parameters in predicting SARS-CoV-2 infection. According to the PRISMA guidelines, we performed a systematic review across Scopus and PubMed databases, resulting in 1585 records. The records check and the analysis of included reports’ references allowed us to include 22 articles. The studies were widely heterogeneous for study population, dysautonomia assessment, and COVID-19 severity. Heart rate variability was the tool most frequently chosen to analyze autonomic parameters, followed by automated pupillometry. Most studies found ANS involvement during acute COVID-19, and AD was often related to a worse outcome. Further studies are needed to clarify the role of autonomic parameters in predicting SARS-CoV-2 infection. The evidence emerging from this review suggests that a complex autonomic nervous system imbalance is a prominent feature of acute COVID-19, often leading to a poor prognosis.

Deceleration capacity is associated with acute respiratory distress syndrome in COVID-19

BACKGROUND

Acute respiratory distress syndrome (ARDS) is considered the main cause of COVID-19 associated morbidity and mortality. Early and reliable risk stratification is of crucial clinical importance in order to identify persons at risk for developing a severe course of disease. Deceleration capacity (DC) of heart rate as a marker of cardiac autonomic function predicts outcome in persons with myocardial infarction and heart failure. We hypothesized that reduced modulation of heart rate may be helpful in identifying persons with COVID-19 at risk for developing ARDS.

METHODS

We prospectively enrolled 60 consecutive COVID-19 positive persons presenting at the University Hospital of Tuebingen. Arterial blood gas analysis and 24 h-Holter ECG recordings were performed and analyzed at admission. The primary end point was defined as development of ARDS with regards to the Berlin classification.

RESULTS

61.7% (37 of 60 persons) developed an ARDS. In persons with ARDS DC was significantly reduced when compared to persons with milder course of infection (3.2 ms vs. 6.6 ms, p < 0.001). DC achieved a good discrimination performance (AUC = 0.76) for ARDS in COVID-19 persons. In a multivariate analysis, decreased DC was associated with the development of ARDS.

CONCLUSION

Our data suggest a promising role of DC to risk stratification in COVID-19.

Deceleration capacity for rapid risk stratification in patients suffering from acute ischemic stroke: A prospective exploratory pilot study

Deceleration capacitiy for rapid risk stratification in stroke patientsCerebral ischemia is a major cause of neurologic deficit and patients suffering from ischemic stroke bear a relevant risk of mortality. Identifying stroke patients at high mortality risk is of crucial clinical relevance. Deceleration capacity of heart rate (DC) as a parameter of cardiac autonomic function is an excellent predictor of mortality in myocardial infarction and heart failure patients.The aim of our study was to evaluate whether DC provides prognostic information regarding mortality risk in patients with acute ischemic stroke.From September 2015 to March 2018 we prospectively enrolled consecutive patients presenting at the Stroke Unit of our university hospital with acute ischemic stroke who were in sinus rhythm. In these patients 24 hours-Holter-ECG recordings and evaluation of National Institute of Health Stroke Scale (NIHSS) were performed. DC was calculated according to a previously published algorithm. Primary endpoint was intrahospital mortality.Eight hundred seventy eight stroke patients were included in the study. Intrahospital mortality was 2.8% (25 patients). Both DC and NIHSS were significantly different between non-survivors and survivors (Mean ± SD: DC: 4.1 ± 2.8 ms vs 6.3 ± 3.3 ms, P < .001) (NIHSS: 7.6 ± 7.1 vs 4.3 ± 5.5, P = .02). DC achieved an area under the curve value (AUC) of 0.708 for predicting intrahospital mortality, while the AUC value of NIHSS was 0.641. In a binary logistic regression analysis, DC, NIHSS and age were independent predictors for intrahospital mortality (DC: HR CI 95%: 0.88 (0.79-0.97); P = .01; NIHSS: HR CI 95%: 1.08 (1.02-1.15); P = .01; Age: HR CI 95%: 1.07 (1.02-1.11); P = .004. The combination of NIHSS, age and DC in a prediction model led to a significant improvement of the AUC, which was 0.757 (P < .001, incremental development index [IDI] 95% CI: 0.037 (0.018-0.057)), compared to the individual risk parameters.Our study demonstrated that DC is suitable for both objective and independent risk stratification in patients suffering from ischemic stroke. The application of a prediction model combining NIHSS, age and DC is superior to the single markers in identifying patients at high mortality risk.