The Association of Early Electrocardiographic Abnormalities With Brain Injury Severity and Outcome in Severe Traumatic Brain Injury

Early Cardiac Evaluation, Abnormal Test Results, and Associations with Outcomes in Patients with Acute Brain Injury Admitted to a Neurocritical Care Unit

Background: to examine factors associated with cardiac evaluation and associations between cardiac test abnormalities and clinical outcomes in patients with acute brain injury (ABI) due to acute ischemic stroke (AIS), spontaneous subarachnoid hemorrhage (SAH), spontaneous intracerebral hemorrhage (sICH), and traumatic brain injury (TBI) requiring neurocritical care. Methods: In a cohort of patients ≥18 years, we examined the utilization of electrocardiography (ECG), beta-natriuretic peptide (BNP), cardiac troponin (cTnI), and transthoracic echocardiography (TTE). We investigated the association between cTnI, BNP, sex-adjusted prolonged QTc interval, low ejection fraction (EF < 40%), all-cause mortality, death by neurologic criteria (DNC), transition to comfort measures only (CMO), and hospital discharge to home using univariable and multivariable analysis (adjusted for age, sex, race/ethnicity, insurance carrier, pre-admission cardiac disorder, ABI type, admission Glasgow Coma Scale Score, mechanical ventilation, and intracranial pressure [ICP] monitoring). Results: The final sample comprised 11,822 patients: AIS (46.7%), sICH (18.5%), SAH (14.8%), and TBI (20.0%). A total of 63% (n = 7472) received cardiac workup, which increased over nine years (p < 0.001). A cardiac investigation was associated with increased age, male sex (aOR 1.16 [1.07, 1.27]), non-white ethnicity (aOR), non-commercial insurance (aOR 1.21 [1.09, 1.33]), pre-admission cardiac disorder (aOR 1.21 [1.09, 1.34]), mechanical ventilation (aOR1.78 [1.57, 2.02]) and ICP monitoring (aOR1.68 [1.49, 1.89]). Compared to AIS, sICH (aOR 0.25 [0.22, 0.29]), SAH (aOR 0.36 [0.30, 0.43]), and TBI (aOR 0.19 [0.17, 0.24]) patients were less likely to receive cardiac investigation. Patients with troponin 25th-50th quartile (aOR 1.65 [1.10-2.47]), troponin 50th-75th quartile (aOR 1.79 [1.22-2.63]), troponin >75th quartile (aOR 2.18 [1.49-3.17]), BNP 50th-75th quartile (aOR 2.86 [1.28-6.40]), BNP >75th quartile (aOR 4.54 [2.09-9.85]), prolonged QTc (aOR 3.41 [2.28; 5.30]), and EF < 40% (aOR 2.47 [1.07; 5.14]) were more likely to be DNC. Patients with troponin 50th-75th quartile (aOR 1.77 [1.14-2.73]), troponin >75th quartile (aOR 1.81 [1.18-2.78]), and prolonged QTc (aOR 1.71 [1.39; 2.12]) were more likely to be associated with a transition to CMO. Patients with prolonged QTc (aOR 0.66 [0.58; 0.76]) were less likely to be discharged home. Conclusions: This large, single-center study demonstrates low rates of cardiac evaluations in TBI, SAH, and sICH compared to AIS. However, there are strong associations between electrocardiography, biomarkers of cardiac injury and heart failure, and echocardiography findings on clinical outcomes in patients with ABI. Findings need validation in a multicenter cohort.

Cardiac Injury After Traumatic Brain Injury: Clinical Consequences and Management

Traumatic brain injury (TBI) is a significant public health issue because of its increasing incidence and the substantial short-term and long-term burden it imposes. This burden includes high mortality rates, morbidity, and a significant impact on productivity and quality of life for survivors. During the management of TBI, extracranial complications commonly arise during the patient's stay in the intensive care unit. These complications can have an impact on both mortality and the neurological outcome of patients with TBI. Among these extracranial complications, cardiac injury is a relatively frequent occurrence, affecting approximately 25-35% of patients with TBI. The pathophysiology underlying cardiac injury in TBI involves the intricate interplay between the brain and the heart. Acute brain injury triggers a systemic inflammatory response and a surge of catecholamines, leading to the release of neurotransmitters and cytokines. These substances have detrimental effects on the brain and peripheral organs, creating a vicious cycle that exacerbates brain damage and cellular dysfunction. The most common manifestation of cardiac injury in TBI is corrected QT (QTc) prolongation and supraventricular arrhythmias, with a prevalence up to 5 to 10 times higher than in the general adult population. Other forms of cardiac injury, such as regional wall motion alteration, troponin elevation, myocardial stunning, or Takotsubo cardiomyopathy, have also been described. In this context, the use of β-blockers has shown potential benefits by intervening in this maladaptive process. β-blockers can limit the pathological effects on cardiac rhythm, blood circulation, and cerebral metabolism. They may also mitigate metabolic acidosis and potentially contribute to improved cerebral perfusion. However, further clinical studies are needed to elucidate the role of new therapeutic strategies in limiting cardiac dysfunction in patients with severe TBI.

Electrocardiographic changes in patients with raised intracranial pressure from supratentorial brain tumors

Objectives

A wide variety of electrocardiographic (ECG) changes has been described in the context of neurological catastrophe. There has been diverse and plentiful literature emphasizing the cardiac changes in acute cerebrovascular events and traumatic brain injury. In stark contrast, there is scarce literature on the incidence of cardiac dysfunction caused by raised intracranial pressure (ICP) resulting from brain tumors. The study aimed to observe the ECG changes concurrent with intracranial hypertension resulting from supratentorial brain tumors.

Materials and Methods

This is a pre-specified subgroup analysis of a prospective and observational study on cardiac function in patients presenting for neurosurgery. Data of 100 consecutive patients of either sex between 18 and 60 years who presented with primary supratentorial brain tumors were analyzed. The patients were divided into two groups: Group 1 consisted of patients without clinical and radiological features of raised ICP and Group 2 consisted of patients with clinical and radiological features of raised ICP. A 12-lead ECG was obtained for every patient on the day before the neurosurgical procedure as part of the pre-anesthetic assessment. The cardiologist and the neuroanesthetist independently examined the ECG, and it was then classified and coded as per the standardized Minnesota code. Statistical analysis was performed with IBM SPSS (release 22.0; IBM Corp., Armonk, NY, USA). The normality of the distribution of continuous variables was tested using the Shapiro-Wilk test. Normally distributed variables were expressed as Mean ± SD. All nominal or categorical variables are described as frequencies and percentages. Categorical variables were compared using the Chi-square test or the Fisher's exact test. The normally distributed continuous variables were compared using Student's t-test. "P < 0.05" was considered statistically significant.

Results

About 6% in Group 1 and 32% in Group 2 had abnormal ECG. This was significantly different in Group 2 compared to Group 1 (P < 0.05). No patients in Group 1 had sinus bradycardia, whereas it was observed in 12% of the patients in Group 2 (P = 0.02). ST-segment depression was found in 12% of patients in Group 2, whereas none had it in Group 1 (P = 0.02). ST-segment elevation was noticed in 16 % in Group 2 and 2% in Group 1 (P = 0.01). T-wave abnormalities were found in 16% compared to 4% in Group 1 (P = 0.03).

Conclusion

In patients with supratentorial tumors, we observed that those with raised ICP had a higher incidence of ECG changes than those with normal ICP. In addition, repolarization abnormalities and arrhythmias were significantly higher in patients with raised ICP.

Role of electrocardiogram findings in predicting 48-h mortality in patients with traumatic brain injury

OBJECTIVE

Electrocardiogram (ECG) patterns can change, especially in patients with central nervous system disorders such as spontaneous subarachnoid hemorrhage. However, the association between the prognosis of traumatic brain injury (TBI) and ECG findings is unknown. Therefore, this study aimed to compare and to analyze ECG findings to predict early mortality in patients with TBI.

METHODS

This retrospective observational study included patients with severe trauma and TBI who were admitted to the emergency department (ED) between January 2018 and December 2020. TBI was defined as an abbreviated injury scale score of the head of ≥3. We examined ECG findings, including PR prolongation (≥ 200 ms), QRS complex widening (≥ 120 ms), corrected QT interval prolongation (QTP, ≥ 480 ms), ST-segment elevation, and ST-segment depression (STD) at ED arrival. The primary outcome was 48-h mortality.

RESULTS

Of the total patients with TBI, 1024 patients were included in this study and 48-h mortality occurred in 89 patients (8.7%). In multivariate analysis, QTP (odds ratio [OR], 2.017; confidence interval [CI], 1.203-3.382) and STD (OR, 8.428; 95% CI, 5.019-14.152) were independently associated with 48-h mortality in patients with TBI. The areas under the curve (AUCs) of the revised trauma score (RTS), injury severity score (ISS), QTP, STD, and the combination of QTP and STD were 0.790 (95% CI, 0.764-0.815), 0.632 (95% CI, 0.602-0.662), 0.605 (95% CI, 0.574-0.635), 0.723 (95% CI, 0.695-0.750), and 0.786 (95% CI, 0.759-0.811), respectively. The AUC of the combination of QTP and STD significantly differed from that of ISS, QTP, and STD, but not RTS.

CONCLUSION

Based on the ECG findings, QTP and STD were associated with 48-h mortality in patients with TBI.

Non-Invasive Hemodynamics Monitoring System Based on Electrocardiography via Deep Convolutional Autoencoder

This study evaluates cardiovascular and cerebral hemodynamics systems by only using non-invasive electrocardiography (ECG) signals. The Massachusetts General Hospital/Marquette Foundation (MGH/MF) and Cerebral Hemodynamic Autoregulatory Information System Database (CHARIS DB) from the PhysioNet database are used for cardiovascular and cerebral hemodynamics, respectively. For cardiovascular hemodynamics, the ECG is used for generating the arterial blood pressure (ABP), central venous pressure (CVP), and pulmonary arterial pressure (PAP). Meanwhile, for cerebral hemodynamics, the ECG is utilized for the intracranial pressure (ICP) generator. A deep convolutional autoencoder system is applied for this study. The cross-validation method with Pearson’s linear correlation (R), root mean squared error (RMSE), and mean absolute error (MAE) are measured for the evaluations. Initially, the ECG is used to generate the cardiovascular waveform. For the ABP system—the systolic blood pressure (SBP) and diastolic blood pressures (DBP)—the R evaluations are 0.894 ± 0.004 and 0.881 ± 0.005, respectively. The MAE evaluations for SBP and DBP are, respectively, 6.645 ± 0.353 mmHg and 3.210 ± 0.104 mmHg. Furthermore, for the PAP system—the systolic and diastolic pressures—the R evaluations are 0.864 ± 0.003 mmHg and 0.817 ± 0.006 mmHg, respectively. The MAE evaluations for systolic and diastolic pressures are, respectively, 3.847 ± 0.136 mmHg and 2.964 ± 0.181 mmHg. Meanwhile, the mean CVP evaluations are 0.916 ± 0.001, 2.220 ± 0.039 mmHg, and 1.329 ± 0.036 mmHg, respectively, for R, RMSE, and MAE. For the mean ICP evaluation in cerebral hemodynamics, the R and MAE evaluations are 0.914 ± 0.003 and 2.404 ± 0.043 mmHg, respectively. This study, as a proof of concept, concludes that the non-invasive cardiovascular and cerebral hemodynamics systems can be potentially investigated by only using the ECG signal.

Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries

Mild traumatic brain injuries (mTBIs) are the most common type of brain injury. Timely diagnosis of mTBI is crucial in making 'go/no-go' decision in order to prevent repeated injury, avoid strenuous activities which may prolong recovery, and assure capabilities of high-level performance of the subject. If undiagnosed, mTBI may lead to various short- and long-term abnormalities, which include, but are not limited to impaired cognitive function, fatigue, depression, irritability, and headaches. Existing screening and diagnostic tools to detect acute andearly-stagemTBIs have insufficient sensitivity and specificity. This results in uncertainty in clinical decision-making regarding diagnosis and returning to activity or requiring further medical treatment. Therefore, it is important to identify relevant physiological biomarkers that can be integrated into a mutually complementary set and provide a combination of data modalities for improved on-site diagnostic sensitivity of mTBI. In recent years, the processing power, signal fidelity, and the number of recording channels and modalities of wearable healthcare devices have improved tremendously and generated an enormous amount of data. During the same period, there have been incredible advances in machine learning tools and data processing methodologies. These achievements are enabling clinicians and engineers to develop and implement multiparametric high-precision diagnostic tools for mTBI. In this review, we first assess clinical challenges in the diagnosis of acute mTBI, and then consider recording modalities and hardware implementation of various sensing technologies used to assess physiological biomarkers that may be related to mTBI. Finally, we discuss the state of the art in machine learning-based detection of mTBI and consider how a more diverse list of quantitative physiological biomarker features may improve current data-driven approaches in providing mTBI patients timely diagnosis and treatment.