Circadian variation pattern of sudden cardiac arrest occurred in Chinese community.

BACKGROUND: The circadian variation pattern of sudden cardiac arrest (SCA) occurred in Chinese community including both community healthcare centres and primary hospitals remains unknown. This study analysed the circadian variation of SCA in the Chinese community. METHODS: Data between 2018 and 2022 from the remote ECG diagnosis system of Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine were analysed to examine the circadian rhythm of SCA, stratified by initial shockable (ventricular tachycardia or ventricular fibrillation) versus non-shockable (asystole or pulseless electrical activity) rhythm. RESULTS: Among 10 210 cases of SCA, major cases (8736, 85.6%) were non-shockable and 1474 (14.4%) cases were shockable. The circadian rhythm of SCA was as follows: peak time was from 08:00 to 11:59 (30.1%), while deep valley was from 00:00 to 03:59 (7.5%). The proportions of events by non-shockable and shockable events were similar and both reached their peak from 08:00 to 11:59, with a percentage of 29.0% and 36.4%, respectively. Multivariable analysis showed that the relative risk of shockable compared with non-shockable arrests was lower between 00:00 and 03:59 (adjusted OR (aOR): 0.72, 95% CI: 0.54 to 0.97, p=0.028) and 04:00 to 07:59 (aOR: 0.60, 95% CI: 0.46 to 0.79, p<0.001), but higher between 08:00 and 11:59 (aOR: 1.34, 95% CI: 1.09 to 1.64, p=0.005). CONCLUSIONS: In Chinese community, there is a distinct circadian rhythm of SCA, regardless of initial rhythms. Our findings may be helpful in decision-making, in that more attention and manpower should be placed on the morning hours of first-aid and resuscitation management in Chinese community.

Installation of Public Access Defibrillators for Out-of-Hospital Cardiac Arrests: Identifying Suitable Locations by Using a Geographic Information System.

BACKGROUND: Survival following an out-of-hospital cardiac arrest depends on prompt defibrillation. Despite the efforts made to install automated external defibrillators (AEDs) in crowded areas, their usage rate remains suboptimal. This study evaluated the efficiency of installing AEDs at key landmarks in Taoyuan City to enhance accessibility and usage. METHODS AND RESULTS: This retrospective cohort study analyzed nontraumatic public out-of-hospital cardiac arrest cases in Taoyuan City from 2017 to 2021, using data from the Taoyuan Fire Department and a regional registry. AED data were collected for 1163 devices. A geographic information system mapped target locations within the city, and real-world walking routes were examined to assess coverage. The primary outcome was actual coverage and the coverage efficiency ratio, calculated as the actual coverage divided by the number of facilities at a location. The coverage efficiency ratio compared the coverage efficiency of target locations with existing public access defibrillators (PADs). Top locations for superior coverage in both downtown and outside downtown areas were bus stops and convenience stores (7-Eleven and FamilyMart), which outperformed existing PADs. Convenience stores had a higher coverage efficiency ratio than the public service sector. Bus stops showed high AED usage rates before ambulance arrival. CONCLUSIONS: The current PAD locations in Taoyuan City offer limited coverage, which highlights the need for strategically installed AEDs, particularly in convenience stores. Policymakers should consider using the cultural relevance and accessibility of convenience stores, particularly 7-Eleven branches, to enhance AED usage rates.

External Validation and Comparison of Statistical and Machine Learning-Based Models in Predicting Outcomes Following Out-of-Hospital Cardiac Arrest: A Multicenter Retrospective Analysis.

BACKGROUND: The aim of this study was to validate and compare the performance of statistical (Utstein-Based Return of Spontaneous Circulation and Shockable Rhythm-Witness-Age-pH) and machine learning-based (Prehospital Return of Spontaneous Circulation and Swedish Cardiac Arrest Risk Score) models in predicting the outcomes following out-of-hospital cardiac arrest and to assess the impact of the COVID-19 pandemic on the models' performance. METHODS AND RESULTS: This retrospective analysis included adult patients with out-of-hospital cardiac arrest treated at 3 academic hospitals between 2015 and 2023. The primary outcome was neurological outcomes at hospital discharge. Patients were divided into pre- (2015-2019) and post-2020 (2020-2023) subgroups to examine the effect of the COVID-19 pandemic on out-of-hospital cardiac arrest outcome prediction. The models' performance was evaluated using the area under the receiver operating characteristic curve and compared by the DeLong test. The analysis included 2161 patients, 1241 (57.4%) of whom were resuscitated after 2020. The cohort had a median age of 69.2 years, and 1399 patients (64.7%) were men. Overall, 69 patients (3.2%) had neurologically intact survival. The area under the receiver operating characteristic curves for predicting neurological outcomes were 0.85 (95% CI, 0.83-0.87) for the Utstein-Based Return of Spontaneous Circulation score, 0.82 (95% CI, 0.81-0.84) for the Shockable Rhythm-Witness-Age-pH score, 0.79 (95% CI, 0.78-0.81) for the Prehospital Return of Spontaneous Circulation score, and 0.79 (95% CI, 0.77-0.81) for the Swedish Cardiac Arrest Risk Score model. The Utstein-Based Return of Spontaneous Circulation score significantly outperformed both the Prehospital Return of Spontaneous Circulation score (P<0.001) and the Swedish Cardiac Arrest Risk Score model (P=0.007). Subgroup analysis indicated no significant difference in predictive performance for patients resuscitated before versus after 2020. CONCLUSIONS: In this external validation, both statistical and machine learning-based models demonstrated excellent and fair performance, respectively, in predicting neurological outcomes despite different model architectures. The predictive performance of all evaluated clinical scoring systems was not significantly influenced by the COVID-19 pandemic.

Detecting cardiac states with wearable photoplethysmograms and implications for out-of-hospital cardiac arrest detection.

Out-of-hospital cardiac arrest (OHCA) is a global health problem affecting approximately 4.4 million individuals yearly. OHCA has a poor survival rate, specifically when unwitnessed (accounting for up to 75% of cases). Rapid recognition can significantly improve OHCA survival, and consumer wearables with continuous cardiopulmonary monitoring capabilities hold potential to "witness" cardiac arrest and activate emergency services. In this study, we used an arterial occlusion model to simulate cardiac arrest and investigated the ability of infrared photoplethysmogram (PPG) sensors, often utilized in consumer wearable devices, to differentiate normal cardiac pulsation, pulseless cardiac (i.e., resembling a cardiac arrest), and non-physiologic (i.e., off-body) states. Across the classification models trained and evaluated on three anatomical locations, higher classification performances were observed on the finger (macro average F1-score of 0.964 on the fingertip and 0.954 on the finger base) compared to the wrist (macro average F1-score of 0.837). The wrist-based classification model, which was trained and evaluated using all PPG measurements, including both high- and low-quality recordings, achieved a macro average precision and recall of 0.922 and 0.800, respectively. This wrist-based model, which represents the most common form factor in consumer wearables, could only capture about 43.8% of pulseless events. However, models trained and tested exclusively on high-quality recordings achieved higher classification outcomes (macro average F1-score of 0.975 on the fingertip, 0.973 on the finger base, and 0.934 on the wrist). The fingertip model had the highest performance to differentiate arterial occlusion pulselessness from normal cardiac pulsation and off-body measurements with macro average precision and recall of 0.978 and 0.972, respectively. This model was able to identify 93.7% of pulseless states (i.e., resembling a cardiac arrest event), with a 0.4% false positive rate. All classification models relied on a combination of time-, power spectral density (PSD)-, and frequency-domain features to differentiate normal cardiac pulsation, pulseless cardiac, and off-body PPG recordings. However, our best model represented an idealized detection condition, relying on ensuring high-quality PPG data for training and evaluation of machine learning algorithms. While 90.7% of our PPG recordings from the fingertip were considered of high quality, only 53.2% of the measurements from the wrist passed the quality criteria. Our findings have implications for adapting consumer wearables to provide OHCA detection, involving advancements in hardware and software to ensure high-quality measurements in real-world settings, as well as development of wearables with form factors that enable high-quality PPG data acquisition more consistently. Given these improvements, we demonstrate that OHCA detection can feasibly be made available to anyone using PPG-based consumer wearables.

Ethics of Wearable-Based Out-of-Hospital Cardiac Arrest Detection.

Out-of-hospital cardiac arrest is a major health problem, and immediate treatment is essential for improving the chances of survival. The development of technological solutions to detect out-of-hospital cardiac arrest and alert emergency responders is gaining momentum; multiple research consortia are currently developing wearable technology for this purpose. For the responsible design and implementation of this technology, it is necessary to attend to the ethical implications. This review identifies relevant ethical aspects of wearable-based out-of-hospital cardiac arrest detection according to four key principles of medical ethics. First, aspects related to beneficence concern the effectiveness of the technology. Second, nonmaleficence requires preventing psychological distress associated with wearing the device and raises questions about the desirability of screening. Third, grounded in autonomy are empowerment, the potential reidentification from continuously collected data, issues of data access, bystander privacy, and informed consent. Finally, justice concerns include the risks of algorithmic bias and unequal technology access. Based on this overview and relevant legislation, we formulate design recommendations. We suggest that key elements are device accuracy and reliability, dynamic consent, purpose limitation, and personalization. Further empirical research is needed into the perspectives of stakeholders, including people at risk of out-of-hospital cardiac arrest and their next-of-kin, to achieve a successful and ethically balanced integration of this technology in society.

Long-Term Socioeconomic and Mental Health Changes After Out-of-Hospital Cardiac Arrest in Women and Men.

BACKGROUND: Long-term effects of out-of-hospital cardiac arrest (OHCA) may affect the ability to work and mental health. Our aim was to analyze 5-year changes in socioeconomic and mental health outcomes after OHCA in women and men. METHODS: We included 259 women and 996 men from North Holland, the Netherlands, who survived 30 days after OHCA occurred between 2009 and 2015. We assessed changes in employment, income, primary earner status, and anxiety/depression (using medication proxies) from the year before the OHCA to 5 years after with generalized linear mixed models, stratified by sex. We tested differences in changes by sex with interaction terms. Additionally, we explored yearly changes. The 5-year changes after OHCA were compared with changes in a sex- and age-matched sample of people without OHCA. Differences were tested using an interaction term of time and OHCA status. RESULTS: In both women and men (median age [Q1, Q3]: 51 [45, 55] and 54 [48, 57] years, respectively), decreases from before OHCA to 5 years thereafter were observed in the proportion employed (from 72.8% to 53.4% [women] and 80.9% to 63.7% [men]) and the median income. No change in primary earner status was observed in either sex. Dispensing of anxiety/depression medication increased only in women, especially after 1 year (odds ratio, 5.68 [95% CI, 2.05-15.74]) and 5 years (odds ratio, 5.73 [95% CI, 1.88-17.53]). Notable differences between women and men were observed for changes in primary earner status and anxiety/depression medication (eg, at year 1, odds ratio for women, 6.71 [95% CI, 1.96-23.01]; and for men, 0.69 [95% CI, 0.33-1.45]). However, except for anxiety/depression medication in women, similar changes were also observed in the general population. CONCLUSIONS: OHCA survivors experience changes in employment, income, and primary earner status similar to the general population. However, women who survived OHCA more often received anxiety/depression medication in the years following OHCA.

Investigating Users' Attitudes Toward Automated Smartwatch Cardiac Arrest Detection: Cross-Sectional Survey Study.

Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality in the developed world. Timely detection of cardiac arrest and prompt activation of emergency medical services (EMS) are essential, yet challenging. Automated cardiac arrest detection using sensor signals from smartwatches has the potential to shorten the interval between cardiac arrest and activation of EMS, thereby increasing the likelihood of survival. Objective: This cross-sectional survey study aims to investigate users' perspectives on aspects of continuous monitoring such as privacy and data protection, as well as other implications, and to collect insights into their attitudes toward the technology. Methods: We conducted a cross-sectional web-based survey in the Netherlands among 2 groups of potential users of automated cardiac arrest technology: consumers who already own a smartwatch and patients at risk of cardiac arrest. Surveys primarily consisted of closed-ended questions with some additional open-ended questions to provide supplementary insight. The quantitative data were analyzed descriptively, and a content analysis of the open-ended questions was conducted. Results: In the consumer group (n=1005), 90.2% (n=906; 95% CI 88.1%-91.9%) of participants expressed an interest in the technology, and 89% (n=1196; 95% CI 87.3%-90.7%) of the patient group (n=1344) showed interest. More than 75% (consumer group: n= 756; patient group: n=1004) of the participants in both groups indicated they were willing to use the technology. The main concerns raised by participants regarding the technology included privacy, data protection, reliability, and accessibility. Conclusions: The vast majority of potential users expressed a strong interest in and positive attitude toward automated cardiac arrest detection using smartwatch technology. However, a number of concerns were identified, which should be addressed in the development and implementation process to optimize acceptance and effectiveness of the technology.

Validation of the NULL-EASE Score for Predicting Survival in a Multiethnic Asian Cohort of Out-of-Hospital Cardiac Arrest.

BACKGROUND: NULL-PLEASE is a simple and accurate clinical scoring system developed in a Western cohort of patients with out-of-hospital cardiac arrest (OHCA). The need for blood test results limits its use in early stages of care. We adapted and validated the NULL-EASE score (without laboratory tests) in an independent, multiethnic Asian cohort of patients with out-of-hospital cardiac arrest. METHODS AND RESULTS: Using the Singapore OHCA registry, we included consecutive adult patients with out-of-hospital cardiac arrest who survived to hospital admission between April 2010 to December 2020. In-hospital mortality was the primary outcome. Logistic regression analyses were performed with STATA MP v18. Of 3274 patients (median age 64, interquartile range 54-75; 67.9% male) included in the study, 2476 (75.6%) had in-hospital mortality. NULL-EASE score was significantly lower in survivors compared with nonsurvivors (median [inter quartile range] 3 [1-4] versus 6 [4-7]; P<0.001) and strongly predictive of mortality (area under receiver operating characteristic, 0.81 [95% CI, 0.79-0.83]). Patients with a score of ≥3 had higher odds of mortality (adjusted odds ratio, 8.11 [95% CI, 6.57-10.00]) when compared with those with lower scores, after adjusting for sex, residential arrest, diabetes, respiratory disease, and stroke. A cutoff value of ≥3 predicted mortality with 92.2% sensitivity, 84.1% positive predictive value, 46.1% specificity, and 65.5% negative predictive value. NULL-EASE score performed better in younger compared with older patients (area under receiver operating characteristic, 0.82 versus 0.77, P=0.008). CONCLUSIONS: The NULL-EASE score has good discriminative performance (sensitivity and accuracy) in our multiethnic Asian cohort, but the cutoff of ≥3 falls short of the desired level of specificity for therapeutic decision-making.

Door-to-Needle Time for Extracorporeal Cardiopulmonary Resuscitation and Neurological Outcomes in Out-of-Hospital Cardiac Arrest: A Nationwide Study.

BACKGROUND: Extracorporeal cardiopulmonary resuscitation (ECPR) is an option for refractory cardiac arrest, and immediate initiation after indication is recommended. However, the practical goals of ECPR preparation (such as the door-to-needle time) remain unclear. This study aimed to elucidate the association between the door-to-needle time and neurological outcomes of out-of-hospital cardiac arrest. METHODS AND RESULTS: This is a post hoc analysis of a nationwide multicenter study on out-of-hospital cardiac arrest treated with ECPR at 36 institutions between 2013 and 2018 (SAVE-J [Study of Advanced Cardiac Life Support for Ventricular Fibrillation with Extracorporeal Circulation in Japan] II study). Adult patients without hypothermia (≥32 °C) in whom circulation was not returned at ECPR initiation were included. The probability of favorable neurological function at 30 days (defined as Cerebral Performance Category ≤2) was estimated using a generalized estimating equations model, in which institutional, patient, and treatment characteristics were adjusted. Estimated probabilities were then calculated according to the door-to-needle time with 3-minute increments, and a clinical threshold was assumed. Among 1298 patients eligible for this study, 136 (10.6%) had favorable neurological function. The estimated probability of favorable outcomes was highest in patients with 1 to 3 minutes of door-to-needle time (12.9% [11.4%-14.3%]) and remained at 9% to 10% until 27 to 30 minutes. Then, the probability dropped gradually with each 3-minute delay. A 30-minute threshold was assumed, and shorter door-to-extracorporeal membrane oxygenation/low-flow time and fewer adverse events related to cannulation were observed in patients with door-to-needle time <30 minutes. CONCLUSIONS: The probability of favorable functions after out-of-hospital cardiac arrest decreased as the door-to-needle time for ECPR was prolonged, with a rapid decline after 27 to 30 minutes. REGISTRATION: URL: https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000041577; Unique identifier: UMIN000036490.

Predicting Out-of-Hospital Cardiac Arrest in the General Population Using Electronic Health Records.

BACKGROUND: The majority of out-of-hospital cardiac arrests (OHCAs) occur among individuals in the general population, for whom there is no established strategy to identify risk. In this study, we assess the use of electronic health record (EHR) data to identify OHCA in the general population and define salient factors contributing to OHCA risk. METHODS: The analytical cohort included 2366 individuals with OHCA and 23 660 age- and sex-matched controls receiving health care at the University of Washington. Comorbidities, electrocardiographic measures, vital signs, and medication prescription were abstracted from the EHR. The primary outcome was OHCA. Secondary outcomes included shockable and nonshockable OHCA. Model performance including area under the receiver operating characteristic curve and positive predictive value were assessed and adjusted for observed rate of OHCA across the health system. RESULTS: There were significant differences in demographic characteristics, vital signs, electrocardiographic measures, comorbidities, and medication distribution between individuals with OHCA and controls. In external validation, discrimination in machine learning models (area under the receiver operating characteristic curve 0.80-0.85) was superior to a baseline model with conventional cardiovascular risk factors (area under the receiver operating characteristic curve 0.66). At a specificity threshold of 99%, correcting for baseline OHCA incidence across the health system, positive predictive value was 2.5% to 3.1% in machine learning models compared with 0.8% for the baseline model. Longer corrected QT interval, substance abuse disorder, fluid and electrolyte disorder, alcohol abuse, and higher heart rate were identified as salient predictors of OHCA risk across all machine learning models. Established cardiovascular risk factors retained predictive importance for shockable OHCA, but demographic characteristics (minority race, single marital status) and noncardiovascular comorbidities (substance abuse disorder) also contributed to risk prediction. For nonshockable OHCA, a range of salient predictors, including comorbidities, habits, vital signs, demographic characteristics, and electrocardiographic measures, were identified. CONCLUSIONS: In a population-based case-control study, machine learning models incorporating readily available EHR data showed reasonable discrimination and risk enrichment for OHCA in the general population. Salient factors associated with OCHA risk were myriad across the cardiovascular and noncardiovascular spectrum. Public health and tailored strategies for OHCA prediction and prevention will require incorporation of this complexity.

Association between sub-phenotypes identified using latent class analysis and neurological outcomes in patients with out-of-hospital cardiac arrest in Japan.

BACKGROUND: In patients who experience out-of-hospital cardiac arrest (OHCA), it is important to assess the association of sub-phenotypes identified by latent class analysis (LCA) using pre-hospital prognostic factors and factors measurable immediately after hospital arrival with neurological outcomes at 30 days, which would aid in making treatment decisions. METHODS: This study retrospectively analyzed data obtained from the Japanese OHCA registry between June 2014 and December 2019. The registry included a complete set of data on adult patients with OHCA, which was used in the LCA. The association between the sub-phenotypes and 30-day survival with favorable neurological outcomes was investigated. Furthermore, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by multivariate logistic regression analysis using in-hospital data as covariates. RESULTS: A total of, 22,261 adult patients who experienced OHCA were classified into three sub-phenotypes. The factor with the highest discriminative power upon patient's arrival was Glasgow Coma Scale followed by partial pressure of oxygen. Thirty-day survival with favorable neurological outcome as the primary outcome was evident in 66.0% participants in Group 1, 5.2% in Group 2, and 0.5% in Group 3. The 30-day survival rates were 80.6%, 11.8%, and 1.3% in groups 1, 2, and 3, respectively. Logistic regression analysis revealed that the ORs (95% CI) for 30-day survival with favorable neurological outcomes were 137.1 (99.4-192.2) for Group 1 and 4.59 (3.46-6.23) for Group 2 in comparison to Group 3. For 30-day survival, the ORs (95%CI) were 161.7 (124.2-212.1) for Group 1 and 5.78 (4.78-7.04) for Group 2, compared to Group 3. CONCLUSIONS: This study identified three sub-phenotypes based on the prognostic factors available immediately after hospital arrival that could predict neurological outcomes and be useful in determining the treatment strategy of patients experiencing OHCA upon their arrival at the hospital.

Vitamin D deficiency as a risk factor for sudden cardiac arrest: A multicenter case-control study.

BACKGROUND AND AIMS: Vitamin D is known to influence the risk of cardiovascular disease, which is a recognized risk factor for sudden cardiac arrest (SCA). However, the relationship between vitamin D and SCA is not well understood. Therefore, this study aims to investigate the association between vitamin D and SCA in out-of-hospital cardiac arrest (OHCA) patients compared to healthy controls. METHODS AND RESULTS: Using the Phase II Cardiac Arrest Pursuit Trial with Unique Registration and Epidemiologic Surveillance (CAPTURES II) registry, a 1:1 propensity score-matched case-control study was conducted between 2017 and 2020. Serum 25-hydroxyvitamin D (vitamin D) levels in patients with OHCA (454 cases) and healthy controls (454 cases) were compared after matching for age, sex, cardiovascular risk factors, and lifestyle behaviors. The mean vitamin D levels were 14.5 ± 7.6 and 21.3 ± 8.3 ng/mL among SCA cases and controls, respectively. Logistic regression analysis was used adjusting for cardiovascular risk factors, lifestyle behaviors, corrected serum calcium levels, and estimated glomerular filtration rate (eGRF). The adjusted odds ratio (aOR) for vitamin D was 0.89 (95% confidence interval [CI] 0.87-0.91). The dose-response relationship demonstrated that vitamin D deficiency was associated with SCA incidence (severe deficiency, aOR 10.87, 95% CI 4.82-24.54; moderate deficiency, aOR 2.24, 95% CI 1.20-4.20). CONCLUSION: Vitamin D deficiency was independently and strongly associated with an increased risk of SCA, irrespective of cardiovascular and lifestyle factors, corrected calcium levels, and eGFR.

Incidence and Survival of Out-of-Hospital Cardiac Arrest in Public Housing Areas in 3 European Capitals.

BACKGROUND: Strategies to reach out-of-hospital cardiac arrests (called cardiac arrest) in residential areas and reduce disparities in care and outcomes are warranted. This study investigated incidences of cardiac arrests in public housing areas. METHODS: This register-based cohort study included cardiac arrest patients from Amsterdam (the Netherlands) from 2016 to 2021, Copenhagen (Denmark) from 2016 to 2021, and Vienna (Austria) from 2018 to 2021. Using Poisson regression adjusted for spatial correlation and city, we compared cardiac arrest incidence rates (number per square kilometer per year and number per 100 000 inhabitants per year) in public housing and other residential areas and examined the proportion of cardiac arrests within public housing and adjacent areas (100-m radius). RESULTS: Overall, 9152 patients were included of which 3038 (33.2%) cardiac arrests occurred in public housing areas and 2685 (29.3%) in adjacent areas. In Amsterdam, 635/1801 (35.3%) cardiac arrests occurred in public housing areas; in Copenhagen, 1036/3077 (33.7%); and in Vienna, 1367/4274 (32.0%). Public housing areas covered 42.4 (12.6%) of 336.7 km2 and 1 024 470 (24.6%) of 4 164 700 inhabitants. Across the capitals, we observed a lower probability of 30-day survival in public housing versus other residential areas (244/2803 [8.7%] versus 783/5532 [14.2%]). The incidence rates and rate ratio of cardiac arrest in public housing versus other residential areas were incidence rate, 16.5 versus 4.1 n/km2 per year; rate ratio, 3.46 (95% CI, 3.31-3.62) and incidence rate, 56.1 versus 36.8 n/100 000 inhabitants per year; rate ratio, 1.48 (95% CI, 1.42-1.55). The incidence rates and rate ratios in public housing versus other residential areas were consistent across the 3 capitals. CONCLUSIONS: Across 3 European capitals, one-third of cardiac arrests occurred in public housing areas, with an additional third in adjacent areas. Public housing areas exhibited consistently higher cardiac arrest incidences per square kilometer and 100 000 inhabitants and lower survival than other residential areas. Public housing areas could be a key target to improve cardiac arrest survival in countries with a public housing sector.

Prognostic Impact of Heart Rhythm Shockability Trajectory in Out-of-Hospital Cardiac Arrest: A Multicenter Retrospective Study.

BACKGROUND: This study aimed to investigate the association between the temporal transitions in heart rhythms during cardiopulmonary resuscitation (CPR) and outcomes after out-of-hospital cardiac arrest. METHODS: This was an analysis of the prospectively collected databases in 3 academic hospitals in northern and central Taiwan. Adult patients with out-of-hospital cardiac arrest transported by emergency medical service between 2015 and 2022 were included. Favorable neurological recovery and survival to hospital discharge were the primary and secondary outcomes, respectively. Time-specific heart rhythm shockability was defined as the probability of shockable rhythms at a particular time point during CPR. The temporal changes in the time-specific heart rhythm shockability were calculated by group-based trajectory modeling. Multivariable logistic regression analyses were performed to examine the association between the trajectory group and outcomes. Subgroup analyses examined the effects of extracorporeal CPR in different trajectories. RESULTS: The study comprised 2118 patients. The median patient age was 69.1 years, and 1376 (65.0%) patients were male. Three distinct trajectories were identified: high-shockability (52 patients; 2.5%), intermediate-shockability (262 patients; 12.4%), and low-shockability (1804 patients; 85.2%) trajectories. The median proportion of shockable rhythms over the course of CPR for the 3 trajectories was 81.7% (interquartile range, 73.2%-100.0%), 26.7% (interquartile range, 16.7%-37.5%), and 0% (interquartile range, 0%-0%), respectively. The multivariable analysis indicated both intermediate- and high-shockability trajectories were associated with favorable neurological recovery (intermediate-shockability: adjusted odds ratio [aOR], 4.98 [95% CI, 2.34-10.59]; high-shockability: aOR, 5.40 [95% CI, 2.03-14.32]) and survival (intermediate-shockability: aOR, 2.46 [95% CI, 1.44-4.18]; high-shockability: aOR, 2.76 [95% CI, 1.20-6.38]). The subgroup analysis further indicated extracorporeal CPR was significantly associated with favorable neurological outcomes (aOR, 4.06 [95% CI, 1.11-14.81]) only in the intermediate-shockability trajectory. CONCLUSIONS: Heart rhythm shockability trajectories were associated with out-of-hospital cardiac arrest outcomes, which may be a supplementary factor in guiding the allocation of medical resources, such as extracorporeal CPR.

External Validation of Updated Prediction Models for Neurological Outcomes at 90 Days in Patients With Out-of-Hospital Cardiac Arrest.

BACKGROUND: Few prediction models for individuals with early-stage out-of-hospital cardiac arrest (OHCA) have undergone external validation. This study aimed to externally validate updated prediction models for OHCA outcomes using a large nationwide dataset. METHODS AND RESULTS: We performed a secondary analysis of the JAAM-OHCA (Comprehensive Registry of In-Hospital Intensive Care for Out-of-Hospital Cardiac Arrest Survival and the Japanese Association for Acute Medicine Out-of-Hospital Cardiac Arrest) registry. Previously developed prediction models for patients with cardiac arrest who achieved the return of spontaneous circulation were updated. External validation was conducted using data from 56 institutions from the JAAM-OHCA registry. The primary outcome was a dichotomized 90-day cerebral performance category score. Two models were updated using the derivation set (n=3337). Model 1 included patient demographics, prehospital information, and the initial rhythm upon hospital admission; Model 2 included information obtained in the hospital immediately after the return of spontaneous circulation. In the validation set (n=4250), Models 1 and 2 exhibited a C-statistic of 0.945 (95% CI, 0.935-0.955) and 0.958 (95% CI, 0.951-0.960), respectively. Both models were well-calibrated to the observed outcomes. The decision curve analysis showed that Model 2 demonstrated higher net benefits at all risk thresholds than Model 1. A web-based calculator was developed to estimate the probability of poor outcomes (https://pcas-prediction.shinyapps.io/90d_lasso/). CONCLUSIONS: The updated models offer valuable information to medical professionals in the prediction of long-term neurological outcomes for patients with OHCA, potentially playing a vital role in clinical decision-making processes.

Mortality, morbidity & clinical outcome with different types of vasopressors in out of hospital cardiac arrest patients- a systematic review and meta-analysis.

BACKGROUND & OBJECTIVE: Despite their continued use, the effectiveness and safety of vasopressors in post-cardiac arrest patients remain controversial. This study examined the efficacy of various vasopressors in cardiac arrest patients in terms of clinical, morbidity, and mortality outcomes. METHODS: A comprehensive literature search was performed using online databases (MeSH terms: MEDLINE (Ovid), CENTRAL (Cochrane Library), Embase (Ovid), CINAHL, Scopus, and Google Scholar) from 1997 to 2023 for relevant English language studies. The primary outcomes of interest for this study included short-term survival leading to death, return of spontaneous circulation (ROSC), survival to hospital discharge, neurological outcomes, survival to hospital admission, myocardial infarction, and incidence of arrhythmias. RESULTS: In this meta-analysis, 26 studies, including 16 RCTs and ten non-RCTs, were evaluated. The focus was on the efficacy of epinephrine, vasopressin, methylprednisolone, dopamine, and their combinations in medical emergencies. Epinephrine treatment was associated with better odds of survival to hospital discharge (OR = 1.52, 95%CI [1.20, 1.94]; p < 0.001) and achieving ROSC (OR = 3.60, 95% CI [3.45, 3.76], P < 0.00001)) over placebo but not in other outcomes of interest such as short-term survival/ death at 28-30 days, survival to hospital admission, or neurological function. In addition, our analysis indicates non-superiority of vasopressin or epinephrine vasopressin-plus-epinephrine therapy over epinephrine monotherapy except for survival to hospital admission where the combinatorial therapy was associated with better outcome (0.76, 95%CI [0.64, 0.92]; p = 0.004). Similarly, we noted the non-superiority of vasopressin-plus-methylprednisolone versus placebo. Finally, while higher odds of survival to hospital discharge (OR = 3.35, 95%CI [1.81, 6.2]; p < 0.001) and ROSC (OR = 2.87, 95%CI [1.97, 4.19]; p < 0.001) favoring placebo over VSE therapy were observed, the risk of lethal arrhythmia was not statistically significant. There was insufficient literature to assess the effects of dopamine versus other treatment modalities meta-analytically. CONCLUSION: This meta-analysis indicated that only epinephrine yielded superior outcomes among vasopressors than placebo, albeit limited to survival to hospital discharge and ROSC. Additionally, we demonstrate the non-superiority of vasopressin over epinephrine, although vasopressin could not be compared to placebo due to the paucity of data. The addition of vasopressin to epinephrine treatment only improved survival to hospital admission.

Examining the Impact of Layperson Rescuer Gender on the Receipt of Bystander CPR for Women in Cardiac Arrest.

BACKGROUND: Women who suffer a witnessed out-of-hospital cardiac arrest receive bystander cardiopulmonary resuscitation (CPR) less often than men. To understand this phenomenon, we queried whether there are differences in deterrents to providing CPR based on the rescuer's gender. METHODS: Participants were surveyed using a national crowdsourcing platform. Participants ranked the following 5 previously identified themes as reasons: rescuers are afraid to injure or hurt women; rescuers might have a misconception that women do not suffer cardiac arrest; rescuers are afraid to be accused of sexual assault or sexual harassment; rescuers have a fear of touching women or that their touch might be inappropriate; and rescuers think that women are faking it or being overdramatic. Participants were adult US residents able to correctly define CPR. Participants ranked the themes if the rescuer was gender unidentified, a man, and a woman, in variable order. RESULTS: In November 2018, 520 surveys were completed. The respondents identified as 42.3% women, 74.2% White, 10.4% Black, and 6.7% Hispanic. Approximately half (48.1%) of the cohort knew how to perform CPR, but only 7.9% had ever performed CPR. When the rescuer was identified as a man, survey participants ranked fear of sexual assault or sexual harassment and fear of touching women or that the touch might be inappropriate as the top reasons (36.2% and 34.0% of responses, respectively). Conversely, when the rescuer was identified as a woman, survey respondents reported fear of hurting or injuring as the top reason (41.2%). CONCLUSIONS: Public perceptions as to why women receive less bystander CPR than men were different based on the gender of the rescuer. Participants reported that men rescuers would potentially be hindered by fears of accusations of sexual assault/harassment or inappropriate touch, while women rescuers would be deterred due to fears of causing physical injury.

The real incidence of sudden death: Fair estimations or futile speculations?

BACKGROUND: The true incidence of sudden death remains undetermined, with controversial results from various publications over time and countries. AIM: To investigate if different estimations would reach the values usually reported for France. METHODS: Three different kinds of estimations were used. First, the number of resuscitated sudden deaths and necropsies for sudden death in the Haute-Garonne French administrative department (i.e. county) over the last 10years was expanded to the national level. Second, sudden death coding of death certificates was collected at the national level. Third, the total number of out-of-hospital cardiac arrests leading to any emergency call (with/without intervention) in Haute-Garonne over the last 10years was expanded to the national level. RESULTS: There was a mean of 26 resuscitated sudden deaths and 145 necropsies for sudden death each year in Haute-Garonne, i.e. 12 to 14 sudden deaths for 100,000 inhabitants, and 7700 to 9400 sudden deaths yearly when related to the whole French population, according to the year of inclusion. Based on death certificates, a mean of 6584 sudden deaths was registered each year in France. Finally, there were about 600 yearly calls/interventions for out-of-hospital cardiac arrests in Haute-Garonne, i.e. 40 to 50 sudden deaths for 100,000 inhabitants, and 16,000 to 27,000 sudden deaths yearly for the whole French territory, according to the year of inclusion. CONCLUSIONS: The incidence of sudden death ranges from 6500 to 27,000 in France according to the calculation methods. This huge difference raises the question of the true current incidence of sudden death, which may have been overestimated previously or may be underestimated in France. More straight prospective surveys are needed to solve this question, because of relevant implications for priorities that should be given to sudden death.