Background Identifying critically ill patients at risk of cardiac arrest is important because it offers the opportunity for early intervention and increased survival. The aim of this study was to develop a deep learning model to predict critical events, such as cardiopulmonary resuscitation or mortality. Methods: This retrospective observational study was conducted at a tertiary university hospital. All patients younger than 18 years who were admitted to the pediatric intensive care unit from January 2010 to May 2023 were included. The main outcome was prediction performance of the deep learning model at forecasting critical events. Long short-term memory was used as a deep learning algorithm. The five-fold cross validation method was employed for model learning and testing. Results: Among the vital sign measurements collected during the study period, 11,660 measurements were used to develop the model after preprocessing; 1,060 of these data points were measurements that corresponded to critical events. The prediction performance of the model was the area under the receiver operating characteristic curve (95% confidence interval) of 0.988 (0.9751.000), and the area under the precision-recall curve was 0.862 (0.700–1.000). Conclusions: The performance of the developed model at predicting critical events was excellent. However, follow-up research is needed for external validation.
Background Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS).
Methods This retrospective study was performed at a tertiary children’s hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as systolic blood pressure, heart rate, respiratory rate, oxygen saturation, and whether the ARS was activated were collected. We divided patients into two groups according to activation status and then compared the occurrence of critical events (cardiopulmonary resuscitation or unexpected intensive care unit admission). We evaluated the ability of ARS to predict critical events and calculated compliance. We also analyzed the correlation between each parameter that activates ARS and critical events.
Results The critical events prediction performance of ARS has a specificity of 98.5%, a sensitivity of 24.0%, a negative predictive value of 99.6%, and a positive predictive value of 8.1%. The compliance rate was 15.6%. Statistically significant increases in the risk of critical events were observed for all abnormal criteria except low heart rate. There was no significant difference in the incidence of critical events.
Conclusions ARS, a single parameter system, had good specificity and negative predictive value for predicting critical events; however, sensitivity and positive predictive value were not good, and medical staff compliance was poor.
Background There are conflicting results regarding the association between body mass index and the prognosis of cardiac arrest patients. We investigated the association of the composition and distribution of muscle and fat with neurologic outcomes at hospital discharge in successfully resuscitated out-of-hospital cardiac arrest (OHCA) patients. Methods: This prospective, single-centre, observational study involved adult OHCA patients, conducted between April 2019 and June 2021. The ratio of total skeletal muscle, upper limb muscle, lower limb muscle, and total fat to body weight was measured using InBody S10, a bioimpedance analyser, after achieving the return of spontaneous circulation. Restricted cubic spline curves with four knots were used to examine the relationship between total skeletal muscle, upper limb muscle, and lower limb muscle relative to total body weight and neurologic outcome at discharge. Multivariable logistic regression analysis was performed to assess an independent association. Results: A total of 66 patients were enrolled in the study. The proportion of total muscle and lower limb muscle positively correlated with the possibility of having a good neurologic outcome. The proportion of lower limb muscle showed an independent association in the multivariable analysis (adjusted odds ratio, 2.29; 95% confidence interval, 1.06–13.98), and its optimal cut-off value calculated through receiver operating characteristic curve analysis was 23.1%, which can predict a good neurological outcome. Conclusions: A higher proportion of lower limb muscle to body weight was independently associated with the probability of having a good neurologic outcome in OHCA patients.
Yunseob Shin, Kyung-Jae Cho, Yeha Lee, Yu Hyeon Choi, Jae Hwa Jung, Soo Yeon Kim, Yeo Hyang Kim, Young A Kim, Joongbum Cho, Seong Jong Park, Won Kyoung Jhang
Acute Crit Care. 2022;37(4):654-666. Published online October 26, 2022
Background Early recognition of deterioration events is crucial to improve clinical outcomes. For this purpose, we developed a deep-learning-based pediatric early-warning system (pDEWS) and aimed to validate its clinical performance. Methods: This is a retrospective multicenter cohort study including five tertiary-care academic children’s hospitals. All pediatric patients younger than 19 years admitted to the general ward from January 2019 to December 2019 were included. Using patient electronic medical records, we evaluated the clinical performance of the pDEWS for identifying deterioration events defined as in-hospital cardiac arrest (IHCA) and unexpected general ward-to-pediatric intensive care unit transfer (UIT) within 24 hours before event occurrence. We also compared pDEWS performance to those of the modified pediatric early-warning score (PEWS) and prediction models using logistic regression (LR) and random forest (RF). Results: The study population consisted of 28,758 patients with 34 cases of IHCA and 291 cases of UIT. pDEWS showed better performance for predicting deterioration events with a larger area under the receiver operating characteristic curve, fewer false alarms, a lower mean alarm count per day, and a smaller number of cases needed to examine than the modified PEWS, LR, or RF models regardless of site, event occurrence time, age group, or sex. Conclusions: The pDEWS outperformed modified PEWS, LR, and RF models for early and accurate prediction of deterioration events regardless of clinical situation. This study demonstrated the potential of pDEWS as an efficient screening tool for efferent operation of rapid response teams.
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Post-cardiac arrest syndrome is a complex and critical issue in resuscitated patients undergone cardiac arrest. Ischemic-reperfusion injury occurs in multiple organs due to the return of spontaneous circulation. Bundle of management practicies are required for post-cardiac arrest care. Early invasive coronary angiography should be considered to identify and treat coronary artery obstructive disease. Vasopressors such as norepinephrine and dobutamine are the first-line treatment for shock. Maintainance of oxyhemoglobin saturation greater than 94% but less than 100% is recommended to avoid fatality. Target temperature therapeutic hypothermia helps to resuscitated patients. Strict temperature control is required and is maintained with the help of cooling devices and monitoring the core temperature. Montorings include electrocardiogram, oxymetry, capnography, and electroencephalography (EEG) along with blood pressue, temprature, and vital signs. Seizure should be treated if EEG shows evidence of seizure or epileptiform activity. Clinical neurologic examination and magnetic resonance imaging are considered to predict neurological outcome. Glycemic control and metabolic management are favorable for a good neurological outcome. Recovery from acute kidney injury is essential for survival and a good neurological outcome.
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Background This study assessed the association between the initial Acute Physiology and Chronic Health Evaluation (APACHE) II score and good neurological outcome in comatose survivors of out-of-hospital cardiac arrest who received targeted temperature management (TTM).
Methods Data from survivors of cardiac arrest who received TTM between January 2011 and June 2016 were retrospectively analyzed. The initial APACHE II score was determined using the data immediately collected after return of spontaneous circulation rather than within 24 hours after being admitted to the intensive care unit. Good neurological outcome, defined as Cerebral Performance Category 1 or 2 on day 28, was the primary outcome of this study.
Results Among 143 survivors of cardiac arrest who received TTM, 62 (43.4%) survived, and 34 (23.8%) exhibited good neurological outcome on day 28. The initial APACHE II score was significantly lower in the patients with good neurological outcome than in those with poor neurological outcome (23.71 ± 4.39 vs. 27.62 ± 6.16, P = 0.001). The predictive ability of the initial APACHE II score for good neurological outcome, assessed using the area under the receiver operating characteristic curve, was 0.697 (95% confidence interval [CI], 0.599 to 0.795; P = 0.001). The initial APACHE II score was associated with good neurological outcome after adjusting for confounders (odds ratio, 0.878; 95% CI, 0.792 to 0.974; P = 0.014).
Conclusions In the present study, the APACHE II score calculated in the immediate post-cardiac arrest period was associated with good neurological outcome. The initial APACHE II score might be useful for early identification of good neurological outcome.
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Background The aim of this study was to investigate the relationships between left ventricular ejection fraction (LVEF) and mortality and neurologic outcomes with post-cardiac arrest syndrome (PCAS) after out-of-hospital cardiac arrest (OHCA).
Methods Patients with PCAS after OHCA admitted to the intensive care unit between January 2014 and December 2015 were analyzed retrospectively.
Results A total of 104 patients were enrolled in this study. The mean age was 54.4 ± 15.3 years, and 75 of the patients were male (72.1%). Arrest with a cardiac origin was found in 55 (52.9%). LVEF < 45%, 45-55%, and > 55% was measured in 39 (37.5%), 18 (17.3%), and 47 (45.2%) of patients, respectively. In multivariate analysis, severe LV dysfunction (LVEF < 45%) was significantly related to 7-day mortality (odds ratio 3.02, 95% Confidence Interval 1.01-9.0, p-value 0.047).
Conclusions In this study, moderate to severe LVEF within 48 hours after return of spontaneous circulation was significantly related to 7-day short-term mortality in patients with PCAS after OHCA. Clinicians should actively treat myocardial dysfunction, and further studies are needed.
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Postpartum hemorrhage is a common cause of maternal mortality; its main cause is placenta accreta. Therapeutic hypothermia is a generally accepted means of improving clinical signs in postcardiopulmonary resuscitation patients. A 41-year-old pregnant woman underwent a cesarean section under general anesthesia at 37 weeks of gestation. After the cesarean section, the patient experienced massive postpartum bleeding, which led to cardiac arrest. Once spontaneous circulation returned, the patient underwent an emergency hysterectomy and was placed under therapeutic hypothermia management. The patient recovered without neurological complications.
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Background The aim of this study was to retrospectively evaluate and analyze the brain magnetic resonance imaging (B-MRI) findings of patients with a favorable neurological outcome following cerebral performance category (CPC) after out-of-hospital cardiac arrest (OHCA) at single university hospital emergency center.
Methods Patients with return of spontaneous circulation (> 24 h) after OHCA who were older than 16 years of age and who had been admitted to the emergency intensive care unit (EICU) for over a 57-month period between July 2007 and March 2012 and survived with a favorable neurological outcome were enrolled. B-MRI was taken after recovery of their mental status.
Results Fifty-two patients among the 305 admitted patients had a good CPC, and 33 patients’ B-MRI were analyzed (CPC 1: 26 patients, CPC 2: 7 patients). Among these, 18 (54.5%) patients had a normal finding on B-MRI. On the other hand, ischemia/infarction/microangiopathy compatible with hypoxic-ischemic encephalopathy (HIE) were found on various brain areas including subcortical white matter (7/13), cerebral cortex, central semiovlae, basal ganglia, putamen, periventricular white matter, and cerebellum.
Conclusions Survivors with a favorable neurological outcome from OHCA showed HIE on B-MRI, especially all of the patients with a CPC 2. More detail neurologic category including brain imaging would be needed to categorize patients with favorable outcome after OHCA.
A 51-year-old male patient was referred for a sudden out-of-hospital cardiac arrest. Upon arrival, he was conscious and had no chest pain complaints. There was no abnormality in initial electrocardiographic and echocardiographic examinations. However, episodes of recurrent ventricular fibrillation (VF) were documented on rhythm monitoring. Each VF episode was triggered by an isolated monomorphic ventricular premature complex (VPC).
Suspecting idiopathic VF, emergency radiofrequency catheter ablation was planned for the VPCs. However, when coronary angiography was performed to exclude silent ischemia, the results showed a total occlusion of the right coronary artery posterolateral branch, which is thought to supply the left ventricular inferior and septal wall. After successful reperfusion, VF episodes and the triggering VPCs disappeared. We are documenting this case to emphasize the potential for silent myocardial infarction to cause out-of-hospital sudden cardiac arrest even in a patient without any symptom or sign of acute coronary syndrome.
BACKGROUND The prognostic significance of change in red cell distribution width (RDW) during hospital stays in patients treated with therapeutic hypothermia (TH) after out-of-hospital cardiac arrest (OHCA) was investigated. METHODS Patients treated with TH after OHCA between January 2009 and August 2013 were reviewed. Patients with return of spontaneous circulation (ROSC) were assessed according to Utstein Style. Hematologic variables including RDW, hematocrit, white blood cell count, and platelets were also obtained. RDW changes during the 72 hours after ROSC were categorized into five groups as follows: Group 1 (-0.8-0.1%), Group 2 (0.2-0.3%), Group 3 (0.4-0.5%), Group 4 (0.6-0.8%), and Group 5 (>0.8%). RESULTS A total of 218 patients were enrolled in the study.
RDW changes during the 72 hours after ROSC in Group 4 (HR 3.56, 95% CI 1.25-10.20) and Group 5 (HR 5.07, 95% CI 1.73-14.89) were associated with a statistically significant difference in one-month mortality. RDW changes were associated with statistically significant differences in neurologic outcome at 6 months after ROSC (Group 3 [HR 2.45, 95% CI 1.17-5.14], Group 4 [HR 2.79, 95% CI 1.33-5.84], Group 5 [HR 3.50, 95% CI 1.35-7.41]). Other significant variables were location of arrest, cause of arrest, serum albumin, and advanced cardiac life support time. CONCLUSIONS RDW change during the 72 hours after ROSC is a predictor of mortality and neurologic outcome in patients treated with TH after OHCA.