The German Resuscitation Registry - Epidemiological data for out-of-hospital and in-hospital cardiac arrest.

Introduction: The German Resuscitation Registry was started in 2007 and collects data on out-of-hospital as well as in-hospital cardiac arrest and resuscitation. It has collected more than 400.000 datasets till today. Methods: The German Resuscitation Registry (GRR) is a voluntary quality improvement tool and research tool for out-of-hospital and in-hospital resuscitation as well as in-hospital emergency treatment. It collects data for initial treatment, in-hospital care as well as long-term outcome in an online database. For risk stratification two scores have been developed, published, and implemented. The participants are getting annual and monthly or quarterly reports in addition to the standardized online, 24/7 available analyzing options. An annual public report is published as well. We are reporting on the OHCA annual report of 2022. Results: In 2022 the incidence of CPR started or continued by EMS was 77.6/100.000 inhabitants/year. The mean age was 70.2 years and 66.7% were male bystanders who started CPR in 51.3%. The average response time for the first EMS vehicle to arrive on scene was 6:55 min.In 57.9% of the cases, they had a presumed cardiac cause. The primary outcome, return-of-spontaneous circulation (ROSC) was achieved in 42.1%. Discussion: With its more than 450.000 included datasets, the GRR is an established tool for quality improvement and research in Germany and internationally. The results for the incidence of OHCA and outcome from 2022 are compared to EuReCa TWO data ranging in the upper third of European countries. Furthermore, the GRR has contributed to increasing knowledge of OHCA by conducting and publishing research e.g. on epidemiology, airway management, and medication of OHCA.

[Impact of the 2020 lockdown on prehospital psychiatric emergencies in a large city]. / Auswirkungen des Lockdowns 2020 auf präklinische psychiatrische Notarzteinsätze in einer Großstadt.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic represented a serious challenge for healthcare systems worldwide. Special psychiatric patients represent a vulnerable group and are particularly affected by lockdown interventions. Knowledge on the possible effects for this group of patients in an emergency physician setting is low. OBJECTIVE: The aim of this paper is to investigate the impact of the first lockdown during the COVID-19 pandemic in 2020 on emergency ambulance services for psychiatric patients in a large German city. MATERIAL AND METHODS: A retrospective analysis was conducted on all prehospital psychiatric emergencies in a large German city during the first pandemic-related lockdown from 22 March 2020 to 4 May 2020, with the same period in 2019 serving as a reference. RESULTS: During the first lockdown there was a significant increase in the number of emergency missions with respect to psychiatric cases. A substantial rise in substance-associated deployments was observed. Moreover, there was an increase in the proportion of psychiatric patients who did not meet emergency criteria. Suicidal tendencies and agitation status played a minor role during the lockdown. CONCLUSION: The lockdown had a notable impact on the frequency and profile of emergency physician calls in the metropolitan area studied. The substantial increase in substance-associated callouts can be interpreted as both a deterioration in access to the healthcare system and an expression of the increased stress faced by the general population and vulnerable groups in particular.

Accelerometry-Based Classification of Circulatory States During Out-of-Hospital Cardiac Arrest.

OBJECTIVE: Exploit accelerometry data for an automatic, reliable, and prompt detection of spontaneous circulation during cardiac arrest, as this is both vital for patient survival and practically challenging. METHODS: We developed a machine learning algorithm to automatically predict the circulatory state during cardiopulmonary resuscitation from 4-second-long snippets of accelerometry and electrocardiogram (ECG) data from pauses of chest compressions of real-world defibrillator records. The algorithm was trained based on 422 cases from the German Resuscitation Registry, for which ground truth labels were created by a manual annotation of physicians. It uses a kernelized Support Vector Machine classifier based on 49 features, which partially reflect the correlation between accelerometry and electrocardiogram data. RESULTS: Evaluating 50 different test-training data splits, the proposed algorithm exhibits a balanced accuracy of 81.2%, a sensitivity of 80.6%, and a specificity of 81.8%, whereas using only ECG leads to a balanced accuracy of 76.5%, a sensitivity of 80.2%, and a specificity of 72.8%. CONCLUSION: The first method employing accelerometry for pulse/no-pulse decision yields a significant increase in performance compared to single ECG-signal usage. SIGNIFICANCE: This shows that accelerometry provides relevant information for pulse/no-pulse decisions. In application, such an algorithm may be used to simplify retrospective annotation for quality management and, moreover, to support clinicians to assess circulatory state during cardiac arrest treatment.

Survival after traumatic cardiac arrest is possible-a comparison of German patient-registries.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) due to trauma is rare, and survival in this group is infrequent. Over the last decades, several new procedures have been implemented to increase survival, and a "Special circumstances chapter" was included in the European Resuscitation Council (ERC) guidelines in 2015. This article analysed outcomes after traumatic cardiac arrest in Germany using data from the German Resuscitation Registry (GRR) and the TraumaRegister DGU® (TR-DGU) of the German Trauma Society.  METHODS: In this study, data from patients with OHCA between 01.01.2014 and 31.12.2019 secondary to major trauma and where cardiopulmonary resuscitation (CPR) was started were eligible for inclusion. Endpoints were return of spontaneous circulation (ROSC), hospital admission with ROSC and survival to hospital discharge. RESULTS: 1.049 patients were eligible for inclusion. ROSC was achieved in 28.7% of the patients, 240 patients (22.9%) were admitted to hospital with ROSC and 147 (14.0%) with ongoing CPR. 643 (67.8%) patients were declared dead on scene. Of all patients resuscitated after traumatic OHCA, 27.3% (259) died in hospital. The overall mortality was 95.0% and 5.0% survived to hospital discharge (47). In a multivariate logistic regression analysis; age, sex, injury severity score (ISS), head injury, found in cardiac arrest, shock on admission, blood transfusion, CPR in emergency room (ER), emergency surgery and initial electrocardiogram (ECG), were independent predictors of mortality. CONCLUSION: Traumatic cardiac arrest was an infrequent event with low overall survival. The mortality has remained unchanged over the last decades in Germany. Additional efforts are necessary to identify reversible cardiac arrest causes and provide targeted trauma resuscitation on scene. TRIAL REGISTRATION: DRKS, DRKS-ID DRKS00027944. Retrospectively registered 03/02/2022.

Impact of COVID-19 on out-of-hospital cardiac arrest: A registry-based cohort-study from the German Resuscitation Registry.

INTRODUCTION: The global COVID-19 pandemic effects people and the health system. Some international studies reported an increasing number of out-of-hospital cardiac arrest (OHCA). Comparable studies regarding the impact of COVID-19 on incidence and outcome of OHCA are not yet available for Germany. MATERIALS AND METHODS: This epidemiological study from the German Resuscitation Registry (GRR) compared a non-pandemic period (01.03.2018-28.02.2019) and a pandemic period (01.03.2020-28.02.2021) regarding the pandemic-related impact on OHCA care. RESULTS: A total of 18,799 cases were included. The incidence of OHCA (non-pandemic 117.9 vs. pandemic period 128.0/100,000 inhabitants) and of OHCA with resuscitation attempted increased (66.0 vs. 69.1/100,000). OHCA occurred predominantly and more often at home (62.8% vs. 66.5%, p<0.001). The first ECG rhythm was less often shockable (22.2% vs. 20.3%, p = 0.03). Fewer cases of OHCA were observed (58.6% vs. 55.6% p = 0.02). Both the bystander resuscitation rate and the proportion of telephone guided CPR remained stable (38.6% vs. 39.8%, p = 0.23; and 22.3% vs. 22.5%, p = 0.77). EMS arrival times increased (08:39 min vs. 09:08 min, p<0.001). Fewer patients reached a return of spontaneous circulation (ROSC) (45.4% vs. 40.9%, p<0.001), were admitted to hospital (50.2% vs. 45.0%, p<0.001), and discharged alive (13.9% vs. 10.2%, p<0.001). DISCUSSION: Survival after OHCA significantly decreased while the bystander resuscitation rate remained stable. However, longer EMS arrival times and fewer cases of witnessed OHCA may have contributed to poorer survival. Any change to EMS systems in the care of OHCA should be critically evaluated as it may mean a real loss of life-regardless of the pandemic situation.

A sliding-window based algorithm to determine the presence of chest compressions from acceleration data.

This publication presents in detail five exemplary cases and the algorithm used in the article (Orlob et al. 2022). Defibrillator records for the five exemplary cases were obtained from the German Resuscitation Registry. They consist of accelerometry, electrocardiogram and capnography time series as well as defibrillation times, energies and impedance when recorded. For these cases, experienced physicians annotated time points of cardiac arrest and return of spontaneous circulation or termination of resuscitation attempts, as well as the beginning and ending of every single chest compression period in consensus, as described in Orlob et al. (2022). Furthermore, an algorithm was developed which reliably detects chest compression periods automatically without the time-consuming process of manual annotation. This algorithm allows for an usage in automatic resuscitation quality assessment, machine learning approaches, and handling of big amounts of data (Orlob et al. 2022).

Chest compression fraction calculation: A new, automated, robust method to identify periods of chest compressions from defibrillator data - Tested in Zoll X Series.

AIM: To introduce and evaluate a new, open-source algorithm to detect chest compression periods automatically by the rhythmic, high amplitude signals from an accelerometer, without processing single chest compression events, and to consecutively calculate the chest compression fraction (CCF). METHODS: A consecutive sample of defibrillator records from the German Resuscitation Registry was obtained and manually annotated in consensus as ground truth. Chest compression periods were determined by different automatic approaches, including the new algorithm. The diagnostic performance of these approaches was assessed. Further, using the different approaches in conjunction with different granularities of manual annotation, several CCF versions were calculated and compared by intraclass correlation coefficient (ICC). RESULTS: 131 defibrillator recordings with a total duration of 5755 minutes were analysed. The new algorithm had a sensitivity of 99.39 (95% CI 99.38, 99.41)% and specificity of 99.17 (95% CI 99.15; 99.18)% to detect chest compressions at any given timepoint. The ICC compared to ground truth was 0.998 for the new algorithm and 0.999 for manual annotation, while the ICC of the proposed algorithm compared to the proprietary software was 0.978. The time required for manual annotation to calculate CCF was reduced by 70.48 (22.55, [94.35, 14.45])%. CONCLUSION: The proposed algorithm reliably detects chest compressions in defibrillator recordings. It can markedly reduce the workload for manual annotation, which may facilitate uniform reporting of measured quality of cardiopulmonary resuscitation. The algorithm is made freely available and may be used in big data analysis and machine learning approaches.

One out of three bystanders of out-of-hospital cardiac arrests shows signs of pathological psychological processing weeks after the incident - results from structured telephone interviews.

BACKGROUND: Witnessing an out-of-hospital cardiac arrest (OHCA) is a traumatic experience. This study analyses bystanders` psychological processing of OHCA. We examined the potential impact of bystanders performing resuscitation and the influence of the relationship between bystander and patient (stranger vs. family/friend of the patient) on the psychological processing. METHODS: A telephone interview survey with bystanders, who witnessed an OHCA of an adult patient was performed weeks after the event between December 2014 and April 2016. The semi-standardized questionnaire contained a question regarding the paramount emotion at the time of the interview. In a post-hoc analysis statements given in response were rated by independent researchers into the categories "signs of pathological psychological processing", "physiological psychological processing" and "no signs of psychological distress due to the OHCA". RESULTS: In this analysis 89 telephone interviews were included. In 27 cases (30.3%) signs of pathological psychological processing could be detected. Bystanders performing resuscitation had a higher rate of "no signs of psychological distress after witnessing OHCA" compared to those not resuscitating (54.7% vs. 26.7%, p < 0.05; relative risk 2.01; 95%CI 1.08, 3.89). No statistical significant differences in the psychological processing could be shown for gender, age, relationship to the patient, current employment in the health sector, location of cardiac arrest or number of additional bystanders. CONCLUSIONS: One out of three bystanders of OHCA suffers signs of pathological psychological processing. This was independent of bystander´s age, gender and relationship to the patient. Performing resuscitation seems to help coping with witnessing OHCA.

Medical Emergency Datasets Can Improve the Comprehensiveness of Handover Information: A Simulation Study.

Background: Access to patients' medical histories can be of vital importance to ensure proper treatment in an emergency. Germany is planning to introduce a medical emergency dataset (MED), accessible through an electronic health card, and comprising important patient information, such as diagnoses, medications, and allergies. Introduction: This article evaluates the effect of MEDs on the comprehensiveness of a physician's documentation and handover process to the emergency department of a hospital. Materials and Methods: In 2 randomized, crossover simulation studies, 72 emergency physicians participated in 2 emergency scenarios, either with or without access to an MED. Subsequently, they had to document the key information (pre-existing conditions, medications, and allergies) and hand it over to a fictional hospital. The influence of the MED on the documentation of key information was analyzed using the two-sided Prescott's exact test. Sensitivity analyses adjusting for scenario were conducted. Results: The results show that in scenarios with an MED, documentation of key information in the handover process was more complete. In the first trial, 2 of 3 key items (pre-existing conditions/information and allergies) presented a statistically noticeable difference in scenarios with the MED. The second trial confirmed these results for all key items. Discussion: The findings indicate that the use of MEDs in emergency care could be beneficial since documentation and handover in scenarios with an MED were superior to current real-world practices. Conclusions: Access to more complete patient information through an MED could help to improve the patient's treatment.

Correction: Real-time feedback improves chest compression quality in out-of-hospital cardiac arrest: A prospective cohort study.

[This corrects the article DOI: 10.1371/journal.pone.0229431.].

Real-time feedback improves chest compression quality in out-of-hospital cardiac arrest: A prospective cohort study.

BACKGROUND: Current guidelines underline the importance of high-quality chest compression during cardiopulmonary resuscitation (CPR), to improve outcomes. Contrary to this many studies show that chest compression is often carried out poorly in clinical practice, and long interruptions in compression are observed. This prospective cohort study aimed to analyse whether chest compression quality changes when a real-time feedback system is used to provide simultaneous audiovisual feedback on chest compression quality. For this purpose, pauses in compression, compression frequency and compression depth were compared. METHODS: The study included 292 out-of-hospital cardiac arrests in three consecutive study groups: first group, conventional resuscitation (no-sensor CPR); second group, using a feedback sensor to collect compression depth data without real-time feedback (sensor-only CPR); and third group, with real-time feedback on compression quality (sensor-feedback CPR). Pauses and frequency were analysed using compression artefacts on electrocardiography, and compression depth was measured using the feedback sensor. With this data, various parameters were determined in order to be able to compare the chest compression quality between the three consecutive groups. RESULTS: The compression fraction increased with sensor-only CPR (group 2) in comparison with no-sensor CPR (group 1) (80.1% vs. 87.49%; P < 0.001), but there were no further differences belonging compression fraction after activation of sensor-feedback CPR (group 3) (P = 1.00). Compression frequency declined over the three study groups, reaching the guideline recommendations (127.81 comp/min vs. 122.96 comp/min, P = 0.02 vs. 119.15 comp/min, P = 0.008) after activation of sensor-feedback CPR (group 3). Mean compression depth only changed minimally with sensor-feedback (52.49 mm vs. 54.66 mm; P = 0.16), but the fraction of compressions with sufficient depth (at least 5 cm) and compressions within the recommended 5-6 cm increased significantly with sensor-feedback CPR (56.90% vs. 71.03%; P = 0.003 and 28.74% vs. 43.97%; P < 0.001). CONCLUSIONS: The real-time feedback system improved chest compression quality regarding pauses in compression and compression frequency and facilitated compliance with the guideline recommendations. Compression depth did not change significantly after activation of the real-time feedback. Even the sole use of a CPR-feedback-sensor ("sensor-only CPR") improved performance regarding pauses in compression and compression frequency, a phenomenon known as the 'Hawthorne effect'. Based on this data real-time feedback systems can be expected to raise the quality level in some parts of chest compression quality. TRIAL REGISTRATION: International Clinical Trials Registry Platform of the World Health Organisation and German Register of Clinical Trials (DRKS00009903), Registered 09 February 2016 (retrospectively registered).

Application of mechanical cardiopulmonary resuscitation devices and their value in out-of-hospital cardiac arrest: A retrospective analysis of the German Resuscitation Registry.

BACKGROUND: Cardiac arrest is an event with a limited prognosis which has not substantially changed since the first description of cardiopulmonary resuscitation (CPR) in 1960. A promising new treatment approach may be mechanical CPR devices (mechanical CPR). METHODS: In a retrospective analysis of the German Resuscitation Registry between 2007-2014, we examined the outcome after using mechanical CPR on return of spontaneous circulation (ROSC) in adults with out-of-hospital cardiac arrest (OHCA). We compared mechanical CPR to manual CPR. According to preclinical risk factors, we calculated the predicted ROSC-after-cardiac-arrest (RACA) score for each group and compared it to the rate of ROSC observed. Using multivariate analysis, we adjusted the influence of the devices' application on ROSC for epidemiological factors and therapeutic measures. RESULTS: We included 19,609 patients in the study. ROSC was achieved in 51.5% of the mechanical CPR group (95%-CI 48.2-54.8%, ROSC expected 42.5%) and in 41.2% in the manual CPR group (95%-CI 40.4-41.9%, ROSC expected 39.2%). After multivariate adjustment, mechanical CPR was found to be an independent predictor of ROSC (OR 1.77; 95%-CI 1.48-2.12). Duration of CPR is a key determinant for achieving ROSC. CONCLUSIONS: Mechanical CPR was associated with an increased rate of ROSC and when adjusted for risk factors appeared advantageous over manual CPR. Mechanical CPR devices may increase survival and should be considered in particular circumstances according to a physicians' decision, especially during prolonged resuscitation.

The Effect of Ambulance Response Time on Survival Following Out-of-Hospital Cardiac Arrest.

BACKGROUND: Out of hospital cardiac arrest (OHCA) is one of the more common causes of death in Germany. Ambulance response time is an important planning parameter for emergency medical services (EMS) systems. We studied the effect of ambulance response time on survival after resuscitation from OHCA. METHODS: We analyzed data from the German Resuscitation Registry for the years 2010-2016. First, we used a multivariate logistic regression analysis to determine the effect of ambulance response time (defined as the interval from the alarm to the arrival of the first rescue vehicle) on the hospital-discharge rate (in percent), depending on various factors, including resuscitation by bystanders. Second, we compared faster and slower EMS systems (defined as those arriving on the scene within 8 minutes in more than 75% of cases or in ≤ 75% of cases) with respect to the frequency of resuscitation and the number of surviving patients. RESULTS: Our analysis of data from a total of 10 853 patients in the logistical regression model revealed that the rate of hospital discharge was significantly affected by the ambulance response time, bystander resuscitation, past medical history, age, witnessed vs. unwitnessed collapse, the initial heart rhythm, and the site of the collapse. The success of resuscitation was inversely related to the ambulance response time; thus, among patients who did not receive bystander resuscitation, the discharge rate declined from 12.9% at a mean response time of 1 minute and 10 seconds to 6.4% at a mean response time of 9 minutes and 47 seconds. Twelve faster EMS systems and 13 slower ones were identified, with a total of 9669 and 7865 resuscitated patients, respectively. The faster EMS systems initiated resuscitation more frequently and also had a higher discharge rate with good neurological outcome in proportion to the population of the catchment area (7.7 versus 5.6 persons per 100 000 population per year, odds ratio [OR] 0.72, 95% confidence interval [0.66; 0.79], p<0.001). CONCLUSION: Rapid ambulance response is associated with a higher rate of survival from OHCA with good neurological outcome. The response time, independently of whether bystander resuscitation measures are provided, ha^ a significant independent effect on the survival rate. In drawing conclusions from these findings, one should bear in mind that this was a retrospective registry study, with the corresponding limitations.

A better understanding of ambulance personnel's attitude towards real-time resuscitation feedback.

OBJECTIVE: High-quality chest compressions during cardiopulmonary resuscitation (CPR) play a significant role in surviving cardiac arrest. Chest-compression quality can be measured and corrected by real-time CPR feedback devices, which are not yet commonly used. This article looks at the acceptance of such systems in comparison of equipped and unequipped personnel. DESIGN: Two groups of emergency medical services' (EMS) personnel were interviewed using standardized questionnaires. SETTING: The survey was conducted in the German cities Dortmund and Münster. PARTICIPANTS: Overall, 205 persons participated in the survey: 103 paramedics and emergency physicians from the Dortmund fire service and 102 personnel from the Münster service. INTERVENTION: The staff of the Dortmund service were not equipped with real-time feedback systems. The test group of equipped personnel of the ambulance service of Münster Fire brigade uses real-time feedback systems since 2007. MAIN OUTCOME MEASURE: What is the acceptance level of real-time feedback systems? Are there differences between equipped and unequipped personnel? RESULTS: The total sample is receptive towards real-time feedback systems. More than 80% deem the system useful. However, this study revealed concerns and prejudices by unequipped personnel. Negative ratings are significantly lower at the Münster site that is experienced with the use of the real-time feedback system in contrast to the Dortmund site where no such experience exists-the system's use in daily routine results in better evaluation than the expectations of unequipped personnel. CONCLUSIONS: Real-time feedback systems receive overall positive ratings. Prejudices and concerns seem to decrease with continued use of the system.

Predicting ROSC in out-of-hospital cardiac arrest using expiratory carbon dioxide concentration: Is trend-detection instead of absolute threshold values the key?

AIM: Guidelines recommend detecting return of spontaneous circulation (ROSC) by a rising concentration of carbon dioxide in the exhalation air. As CO2 is influenced by numerous factors, no absolute cut-off values of CO2 to detect ROSC are agreed on so far. As trends in CO2 might be less affected by influencing factors, we investigated an approach which is based on detecting CO2-trends in real-time. METHODS: We conducted a retrospective case-control study on 169 CO2 time series from out of hospital cardiac arrests resuscitated by Muenster City Ambulance-Service, Germany. A recently developed statistical method for real-time trend-detection (SCARM) was applied to each time series. For each series, the percentage of time points with detected positive and negative trends was determined. RESULTS: ROSC time series had larger percentages of positive trends than No-ROSC time series (p=0.003). The median percentage of positive trends was 15% in the ROSC time series (IQR: 5% to 23%) and 7% in the No-ROSC time series (IQR: 3% to 14%). A receiver operating characteristic (ROC) analysis yielded an optimal threshold of 13% to differentiate between ROSC and No-ROSC cases with a specificity of 58.4% and sensitivity of 73.9%; the area under the curve was 63.5%. CONCLUSION: Patients with ROSC differed from patients without ROSC as to the percentage of detected CO2 trends, indicating the potential of our real-time trend-detection approach. Since the study was designed as a proof of principle and its calculated specificity and sensitivity are low, more research is required to implement CO2-trend-detection into clinical use.

miRPursuit-a pipeline for automated analyses of small RNAs in model and nonmodel plants.

miRPursuit is a pipeline developed for running end-to-end analyses of high-throughput small RNA (sRNA) sequence data in model and nonmodel plants, from raw data to identified and annotated conserved and novel sequences. It consists of a series of UNIX shell scripts, which connect open-source sRNA analysis software. The involved parameters can be combined with convenient workflow management by users without advanced computational skills. miRPursuit presents several advantages when compared to other tools, including the possibility of processing several sRNA libraries in parallel, thus easily allowing a comparison of the differences in sRNA read accumulation among sRNA libraries. We validate miRPursuit by using datasets from a model plant and discuss its performance with the analysis of sRNAs from non-model species.

Senior citizens as rescuers: Is reduced knowledge the reason for omitted lay-resuscitation-attempts? Results from a representative survey with 2004 interviews.

OBJECTIVE: Resuscitation (CPR) provided by a bystander prior to the arrival of the emergency services is a beneficial factor for surviving a cardiac arrest (CA). Our registry-based data show, that older patients receive bystander-CPR less frequently. Little is known on possible reasons for this finding. We sought to investigate the hypothesis that awareness of CPR measures is lower in older laypersons being a possible reason for less CPR-attempts in senior citizens. METHODS: 1206 datasets on bystander resuscitations actually carried out were analyzed for age-dependent differences. Subsequently, we investigated whether the knowledge required carrying out bystander-CPR and the self-confidence to do so differ between younger and older citizens using computer-assisted telephone interviewing. 2004 interviews were performed and statistically analyzed. RESULTS: A lower level of knowledge to carry out bystander-CPR was seen in older individuals. For example, 82.4% of interviewees under 65 years of age, knew the correct emergency number. In this group, 66.6% named CPR as the relevant procedure in CA. Among older individuals these responses were only given by 75.1% and 49.5% (V = 0.082; P < 0.001 and V = 0.0157; P < 0.001). Additionally, a difference concerning participants' confidence in their own abilities was detectable. 58.0% of the persons younger than 65 years were confident that they would detect a CA in comparison to 44.6% of the participants older than 65 years (V = 0.120; P < 0.001). Similarly, 62.7% of the interviewees younger than 65 were certain to know what to do during CPR compared to 51.3% of the other group (V = 0.103; P < 0.001). CONCLUSIONS: Lower levels of older bystanders' knowledge and self-confidence might provide an explanation for why older patients receive bystander-CPR less frequently. Further investigation is necessary to identify causal connections and optimum ways to empower bystander resuscitation.