Validity of administrative claims‐based algorithms for ventricular arrhythmia and cardiac arrest in the pediatric population

2020 ◽  
Vol 29 (11) ◽  
pp. 1499-1503 ◽  
Author(s):  
Angela S. Czaja ◽  
Kathryn Collins ◽  
Robert J. Valuck ◽  
Heather D. Anderson ◽  
Debashis Ghosh ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Ventricular Arrhythmia ◽  
Pediatric Population ◽  
Administrative Claims

Artificial Intelligence in Predicting Cardiac Arrest: A Scoping Review (Preprint)

2021 ◽  
Author(s):  
Asma Alamgir ◽  
Osama Mousa 2nd ◽  
Zubair Shah 3rd
Keyword(s):  
Artificial Intelligence ◽  
At Risk ◽  
Cardiac Arrest ◽  
Scoping Review ◽  
Pediatric Population ◽  
Data Extraction ◽  
Warning System ◽  
Reference List ◽  
Evaluation Tool ◽  
Patients At Risk

BACKGROUND Cardiac arrest is a life-threatening cessation of heart activity. Early prediction of cardiac arrest is important as it provides an opportunity to take the necessary measures to prevent or intervene during the onset. Artificial intelligence technologies and big data have been increasingly used to enhance the ability to predict and prepare for the patients at risk. OBJECTIVE This study aims to explore the use of AI technology in predicting cardiac arrest as reported in the literature. METHODS Scoping review was conducted in line with guidelines of PRISMA Extension for Scoping Review (PRISMA-ScR). Scopus, Science Direct, Embase, IEEE, and Google Scholar were searched to identify relevant studies. Backward reference list checking of included studies was also conducted. The study selection and data extraction were conducted independently by two reviewers. Data extracted from the included studies were synthesized narratively. RESULTS Out of 697 citations retrieved, 41 studies were included in the review, and 6 were added after backward citation checking. The included studies reported the use of AI in the prediction of cardiac arrest. We were able to classify the approach taken by the studies in three different categories - 26 studies predicted cardiac arrest by analyzing specific parameters or variables of the patients while 16 studies developed an AI-based warning system. The rest of the 5 studies focused on distinguishing high-risk cardiac arrest patients from patients, not at risk. 2 studies focused on the pediatric population, and the rest focused on adults (n=45). The majority of the studies used datasets with a size of less than 10,000 (n=32). Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (n=38) and the most used algorithm belonged to the neural network (n=23). K-Fold cross-validation was the most used algorithm evaluation tool reported in the studies (n=24). CONCLUSIONS : AI is extensively being used to predict cardiac arrest in different patient settings. Technology is expected to play an integral role in changing cardiac medicine for the better. There is a need for more reviews to learn the obstacles of implementing AI technologies in the clinical setting. Moreover, research focusing on how to best provide clinicians support to understand, adapt and implement the technology in their practice is also required.

Clinical and Electroencephalographic Correlates in Pediatric Cardiac Arrest: Experience at a Tertiary Care Center

2018 ◽  
Vol 49 (05) ◽  
pp. 324-329 ◽  
Author(s):  
Jun Park ◽  
Garrett Brooks
Keyword(s):  
Cardiac Arrest ◽  
Clinical Laboratory ◽  
Cardiopulmonary Arrest ◽  
Pediatric Population ◽  
Care Center ◽  
Tertiary Care ◽  
Cerebral Performance Category ◽  
Neurologic Outcome ◽  
Background Suppression ◽  
Poor Outcome

AbstractPediatric cardiac arrest is a significant cause of death and neurologic disability; however, there is a paucity of literature specifically evaluating the utility of prognostic factors in the pediatric population. This retrospective chart review examines clinical, laboratory, and electroencephalographic (EEG) data in children following cardiopulmonary arrest to better characterize findings that may inform prognosis. Pre-arrest clinical characteristics, resuscitation details, and post-arrest hospital course variables were analyzed and neurologic outcome was determined using the Pediatric Cerebral Performance Category scale. Forty-one patients were identified who had cardiac arrest from March, 2011 to January, 2015. Duration of cardiopulmonary resuscitation (p = 0.013), out-of-hospital arrest (p = 0.005), arterial pH (0.014), arterial lactate (0.004), lack of pupil reactivity to light (p < 0.001), absent motor response to noxious stimuli (p < 0.001), and absent brainstem reflexes (p < 0.001) were all predictors of poor neurologic outcome. EEG background suppression (p = 0.005) was associated with poor outcome. Nine patients had electrographically recorded seizures, which began up to 1 week following cardiac arrest. Two patients (4.9%) experienced post-anoxic myoclonic status epilepticus and both had a poor outcome.

Out-of-Hospital Cardiac Arrest in the Pediatric Population in Hong Kong

2018 ◽  
Vol 34 (3) ◽  
pp. 179-184 ◽  
Author(s):  
Alex Kwok-Keung Law ◽  
Man-Ho Ng ◽  
Kam-Lun Hon ◽  
Colin A. Graham
Keyword(s):  
Cardiac Arrest ◽  
Hong Kong ◽  
Pediatric Population ◽  
Hospital Cardiac Arrest

Survival and neurological status after out-of-hospital cardiac arrest in the pediatric population in Andalusia

2016 ◽  
Vol 40 (3) ◽  
pp. 163-168
Author(s):  
F. Rosell-Ortiz ◽  
F.J. Mellado-Vergel ◽  
J.B. López-Messa ◽  
P. Fernández-Valle ◽  
M.M. Ruiz-Montero ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Pediatric Population ◽  
Neurological Status ◽  
Hospital Cardiac Arrest

scholarly journals Description of Ventricular Arrhythmia after Taking Herbal Medicines in Middle-Aged Couples

2020 ◽  
Vol 2020 ◽  
pp. 1-4
Author(s):  
Mohammad Ali Zakeri ◽  
Vahid Mohammadi ◽  
Gholamreza Bazmandegan ◽  
Maryam Zakeri
Keyword(s):  
Cardiac Arrest ◽  
Heart Disease ◽  
Ventricular Tachycardia ◽  
Sudden Cardiac Death ◽  
Ventricular Arrhythmia ◽  
Cardiac Death ◽  
Ventricular Arrhythmias ◽  
Herbal Medicines ◽  
Medicinal Herbs ◽  
History Of

Medicinal herbs and some derivatives have been used in the treatment of heart disease which is rarely responsible for ventricular arrhythmias and cardiac arrest. Ventricular tachycardia (VT) increases the risk of sudden cardiac death (SCD). However, only a few reports are available about the cardiac ventricular arrhythmia followed by taking herbal medicines. We present two patients (a couple) without a history of heart disease who referred to the hospital with ventricular arrhythmia.

scholarly journals Effect of Prophylactic Amiodarone Infusion on the Recurrence of Ventricular Arrhythmias in Out-of-Hospital Cardiac Arrest Survivors: A Propensity-Matched Analysis

2019 ◽  
Vol 8 (2) ◽  
pp. 244 ◽  
Author(s):  
Byung Lee ◽  
Chun Youn ◽  
Youn-Jung Kim ◽  
Seung Ryoo ◽  
Kyung Lim ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Propensity Score ◽  
Ventricular Arrhythmia ◽  
Odds Ratio ◽  
Propensity Scores ◽  
Tertiary Care ◽  
Temperature Management ◽  
Amiodarone Therapy ◽  
Shockable Rhythm ◽  
Hospital Cardiac Arrest

Amiodarone is recommended for shock-refractory ventricular arrhythmia during resuscitation; however, it is unknown whether amiodarone is effective for preventing ventricular arrhythmia recurrence in out-of-hospital cardiac arrest (OHCA) survivors treated with targeted temperature management (TTM). We investigated the effectiveness of prophylactic amiodarone in preventing ventricular arrhythmia recurrence in OHCA survivors. Data of consecutive adult non-traumatic OHCA survivors treated with TTM between 2010 and 2016 were extracted from prospective cardiac arrest registries of four tertiary care hospitals. The prophylactic amiodarone group was matched in a 1:1 ratio by using propensity scores. The primary outcome was ventricular arrhythmia recurrence requiring defibrillation during TTM. Among 295 patients with an initially shockable rhythm and 149 patients with initially non-shockable-turned-shockable rhythm, 124 patients (27.9%) received prophylactic amiodarone infusion. The incidence of ventricular arrhythmia recurrence was 11.26% (50/444). Multivariate analysis showed prophylactic amiodarone therapy to be the independent factor associated with ventricular arrhythmia recurrence (odds ratio 1.95, 95% CI 1.04–3.65, p = 0.04), however, no such association was observed (odds ratio 1.32, 95% CI 0.57–3.04, p = 0.51) after propensity score matching. In this propensity-score-matched study, prophylactic amiodarone infusion had no effect on preventing ventricular arrhythmia recurrence in OHCA survivors with shockable cardiac arrest. Prophylactic amiodarone administration must be considered carefully.

Sign in / Sign up

Export Citation Format

Share Document