Diagnostic Accuracy of Commercially Available Automated External Defibrillators.
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ABSTRACT:
SUBMITTER: Nishiyama T
PROVIDER: S-EPMC4845298 | biostudies-other | 2015 Dec
REPOSITORIES: biostudies-other
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Project description:Background and purposeSemiautomatic measurement of ICA stenosis potentially increases observer reproducibility. In this study, we assessed the diagnostic accuracy and interobserver reproducibility of a commercially available semiautomatic ICA stenosis measurement on CTA and estimated the agreement among different software packages.Materials and methodsWe analyzed 141 arteries from 90 patients with TIA or ischemic stroke. Manual stenosis measurements were performed by 2 neuroradiologists. Semiautomatic measurements by using 4 methods (3mensio and comparable software from Philips, TeraRecon, and Siemens) were performed by 2 observers. Diagnostic accuracy was estimated by comparing semiautomatic with manual measurements. Interobserver reproducibility and agreement between different packages was assessed by calculation of the intraclass correlation coefficient and Bland-Altman 95% limits of agreement. False-negative classifications were retrospectively inspected by a neuroradiologist.ResultsThere was no significant difference in the diagnostic performance of the 4 semiautomatic methods. The sensitivity for detecting ≥50% and ≥70% degree of stenosis was between 76% and 82% and 46% and 62%, respectively. Specificity and overall diagnostic accuracy were between 92% and 97% and 85% and 90%, respectively. The interobserver intraclass correlation coefficient was between 0.83 and 0.96 for semiautomatic measurements and 0.81 for manual measurement. The limits of agreement between each pair of semiautomatic packages ranged from -18%-24% to -33%-31%. False-negative classifications were caused by ulcerative plaques and observer variation in stenosis and reference measurements.ConclusionsSemiautomatic methods have a low-to-good sensitivity and a good specificity and overall diagnostic accuracy. The high interobserver reproducibility makes semiautomatic stenosis measurement valuable for clinical practice, but semiautomatic measurements should be checked by an experienced radiologist.
| S-EPMC7965040 | biostudies-literature
Project description:BACKGROUND:Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. METHODS:We applied our model to 53?702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. RESULTS:The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. CONCLUSIONS:An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event.
| S-EPMC5516537 | biostudies-literature
Project description:Automated external defibrillators (AEDs) improve survival from out-of-hospital cardiac arrests, but data on their effectiveness in hospitalized patients are limited.To evaluate the association between AED use and survival for in-hospital cardiac arrest.Cohort study of 11,695 hospitalized patients with cardiac arrests between January 1, 2000, and August 26, 2008, at 204 US hospitals following the introduction of AEDs on general hospital wards.Survival to hospital discharge by AED use, using multivariable hierarchical regression analyses to adjust for patient factors and hospital site.Of 11,695 patients, 9616 (82.2%) had nonshockable rhythms (asystole and pulseless electrical activity) and 2079 (17.8%) had shockable rhythms (ventricular fibrillation and pulseless ventricular tachycardia). AEDs were used in 4515 patients (38.6%). Overall, 2117 patients (18.1%) survived to hospital discharge. Within the entire study population, AED use was associated with a lower rate of survival after in-hospital cardiac arrest compared with no AED use (16.3% vs 19.3%; adjusted rate ratio [RR], 0.85; 95% confidence interval [CI], 0.78-0.92; P < .001). Among cardiac arrests due to nonshockable rhythms, AED use was associated with lower survival (10.4% vs 15.4%; adjusted RR, 0.74; 95% CI, 0.65-0.83; P < .001). In contrast, for cardiac arrests due to shockable rhythms, AED use was not associated with survival (38.4% vs 39.8%; adjusted RR, 1.00; 95% CI, 0.88-1.13; P = .99). These patterns were consistently observed in both monitored and nonmonitored hospital units where AEDs were used, after matching patients to the individual units in each hospital where the cardiac arrest occurred, and with a propensity score analysis.Among hospitalized patients with cardiac arrest, use of AEDs was not associated with improved survival.
| S-EPMC3587791 | biostudies-literature
Project description:BackgroundEarly defibrillation is an essential element of the chain of survival for out-of-hospital cardiac arrest (OHCA). Public access defibrillation (PAD) programmes aim to place automated external defibrillators (AED) in areas with high OHCA incidence, but there is sometimes a mismatch between AED density and OHCA incidence.ObjectivesThis study aimed to assess whether there were any disparities in the characteristics of areas that have an AED and those that do not in England.MethodsDetails of the location of AEDs registered with English Ambulance Services were obtained from individual services or internet sources. Neighbourhood characteristics of lower layer super output areas (LSOA) were obtained from the Office for National Statistics. Comparisons were made between LSOAs with and without a registered AED.ResultsAEDs were statistically more likely to be in LSOAs with a lower residential but higher workplace population density, with people predominantly from a white ethnic background and working in higher socio-economically classified occupations (p < 0.05). There was a significant correlation between AED coverage and the LSOA Index of Multiple Deprivation (IMD) (r = 0.79, p = 0.007), with only 27.4% in the lowest IMD decile compared to about 45% in highest. AED density varied significantly across the country from 0.82/km2 in the north east to 2.97/km2 in London.ConclusionsIn England, AEDs were disproportionately placed in more affluent areas, with a lower residential population density. This contrasts with locations where OHCAs have previously occurred. Future PAD programmes should give preference to areas of higher deprivation and be tailored to the local community.
| S-EPMC8786665 | biostudies-literature
Project description:Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for VF-detection are customarily assessed using Holter recordings from public electrocardiogram (ECG) databases, which may be different from the ECG seen during OHCA events. This study evaluates VF-detection using data from both OHCA patients and public Holter recordings. ECG-segments of 4-s and 8-s duration were analyzed. For each segment 30 features were computed and fed to state of the art machine learning (ML) algorithms. ML-algorithms with built-in feature selection capabilities were used to determine the optimal feature subsets for both databases. Patient-wise bootstrap techniques were used to evaluate algorithm performance in terms of sensitivity (Se), specificity (Sp) and balanced error rate (BER). Performance was significantly better for public data with a mean Se of 96.6%, Sp of 98.8% and BER 2.2% compared to a mean Se of 94.7%, Sp of 96.5% and BER 4.4% for OHCA data. OHCA data required two times more features than the data from public databases for an accurate detection (6 vs 3). No significant differences in performance were found for different segment lengths, the BER differences were below 0.5-points in all cases. Our results show that VF-detection is more challenging for OHCA data than for data from public databases, and that accurate VF-detection is possible with segments as short as 4-s.
| S-EPMC4956226 | biostudies-literature
Project description:ObjectiveEarly defibrillation is crucial for the survival of patients with out-of-hospital cardiac arrest. This study aimed to examine the trends and associated factors regarding public awareness and willingness to use automated external defibrillators (AEDs) through citywide surveys.MethodsThree-round surveys were conducted in February 2012 (n=1,000), December 2016 (n=1,141), and December 2018 (n=1,001) among citizens in Daegu, South Korea, who were aged ≥19 years. The subjects were selected through a three-stage quota sampling. Awareness and willingness to use an AED were assessed in the three groups. The primary outcome was willingness to use AEDs.ResultsOf 3,142 respondents, 3,069 were eligible for analysis. The proportion of respondents who knew how to use AEDs increased from 4.7% in 2012 to 20.8% in 2018. Of the respondents in 2012, 2016, and 2018, 39.7%, 50.0%, and 43.2%, respectively, were willing to use an AED. Factors associated with willingness to use AEDs were male sex (adjusted odds ratio [AOR], 1.39; 95% confidence interval [CI], 1.10-1.75), cardiopulmonary resuscitation training experience in the previous 2 years (AOR, 1.80; 95% CI, 1.43-2.28), recognition of the Good Samaritan law (AOR, 1.45; 95% CI, 1.13-1.86), and awareness of how to use an AED (AOR, 4.40; 95% CI, 3.26-5.93).ConclusionTo increase willingness to use AEDs, education in AED use and the Good Samaritan law, along with re-education to maintain knowledge of AED use, should be considered.
| S-EPMC8041576 | biostudies-literature
Project description:Endurance athletes, particularly competitive runners, are using wrist worn devices with the heart rate (HR) feature to guide their training. However, few studies have assessed the effectiveness of these at high levels of exertion. The purpose of this study was to measure the accuracy of the HR monitor feature in four watches at six different treadmill speeds. This prospective study recruited 50 healthy, athletic adults (68% male, mean age of 29, and mean BMI of 23 kg/m2). All subjects wore a three lead ECG and Polar H7 chest strap monitor and two different randomly assigned wrist worn HR monitors. These included the Apple Watch III, Fitbit Iconic, Garmin Vivosmart HR, and Tom Tom Spark 3. Once all devices were on, they were asked to run at the following speeds on a treadmill (in mph): 4, 5, 6, 7, 8, and 9 for two min. HR was assessed on all devices and agreement among measurements determined with Lin's concordance correlation coefficient (CCC) (rc). The Polar H7 chest strap had the greatest agreement with the ECG (rc=98). This was followed by the Apple Watch III (rc=96). The Fitbit Iconic, Garmin Vivosmart HR, and Tom Tom Spark 3 all had the same level of agreement (rc=89). The Polar H7 chest strap was the most accurate, and the Apple Watch was superior among watches. For endurance athletes and their coaches, a chest strap device or Apple Watch may be the best choice for guiding workouts and performance.
| S-EPMC6732081 | biostudies-literature
Project description:Timely and accurate laboratory testing is essential for managing the global COVID-19 pandemic. Reverse transcription polymerase chain reaction remains the gold-standard for SARS-CoV-2 diagnosis, but several practical issues limit the test's use. Immunoassays have been indicated as an alternative for individual and mass testing.ObjectivesTo access the performance of 12 serological tests for COVID-19 diagnosis.MethodsWe conducted a blind evaluation of six lateral-flow immunoassays (LFIAs) and six enzyme-linked immunosorbent assays (ELISAs) commercially available in Brazil for detecting anti-SARS-CoV-2 antibodies.ResultsConsidering patients with seven or more days of symptoms, the sensitivity ranged from 59.5% to 83.1% for LFIAs and from 50.7% to 92.6% for ELISAs. For both methods, the sensitivity increased with clinical severity and days of symptoms. The agreement among LFIAs performed with digital blood and serum was moderate. Specificity was, in general, higher for LFIAs than for ELISAs. Infectious diseases prevalent in the tropics, such as HIV, leishmaniasis, arboviruses, and malaria, represent conditions with the potential to cause false-positive results with these tests, which significantly compromises their specificity.ConclusionThe performance of immunoassays was only moderate, affected by the duration and clinical severity of the disease. Absence of discriminatory power between IgM/IgA and IgG has also been demonstrated, which prevents the use of acute-phase antibodies for decisions on social isolation.
| S-EPMC7544564 | biostudies-literature
Project description:BackgroundCOVID-19 is an ongoing public health pandemic regardless of the countless efforts made by various actors. Quality diagnostic tests are important for early detection and control. Notably, several commercially available one step RT-PCR based assays have been recommended by the WHO. Yet, their analytic and diagnostic performances have not been well documented in resource-limited settings. Hence, this study aimed to evaluate the diagnostic sensitivities and specificities of three commercially available one step reverse transcriptase-polymerase chain reaction (RT-PCR) assays in Ethiopia in clinical setting.MethodsA cross-sectional study was conducted from April to June, 2021 on 279 respiratory swabs originating from community surveillance, contact cases and suspect cases. RNA was extracted using manual extraction method. Master-mix preparation, amplification and result interpretation was done as per the respective manufacturer. Agreements between RT-PCRs were analyzed using kappa values. Bayesian latent class models (BLCM) were fitted to obtain reliable estimates of diagnostic sensitivities, specificities of the three assays and prevalence in the absence of a true gold standard.ResultsAmong the 279 respiratory samples, 50(18%), 59(21.2%), and 69(24.7%) were tested positive by TIB, Da An, and BGI assays, respectively. Moderate to substantial level of agreement was reported among the three assays with kappa value between 0 .55 and 0.72. Based on the BLCM relatively high specificities (95% CI) of 0.991(0.973-1.000), 0.961(0.930-0.991) and 0.916(0.875-0.952) and considerably lower sensitivities with 0.813(0.658-0.938), 0.836(0.712-0.940) and 0.810(0.687-0.920) for TIB MOLBIOL, Da An and BGI respectively were found.ConclusionsWhile all the three RT-PCR assays displayed comparable sensitivities, the specificities of TIB MOLBIOL and Da An were considerably higher than BGI. These results help adjust the apparent prevalence determined by the three RT-PCRs and thus support public health decisions in resource limited settings and consider alternatives as per their prioritization matrix.
| S-EPMC8775315 | biostudies-literature
Project description:AimHigh-quality chest compressions is challenging for bystanders and first responders to out-of-hospital cardiac arrest (OHCA). Long compression pauses and compression rates higher than recommended are common and detrimental to survival. Our aim was to design a simple and low computational cost algorithm for feedback on compression rate using the transthoracic impedance (TI) acquired by automated external defibrillators (AEDs).MethodsECG and TI signals from AED recordings of 242 OHCA patients treated by basic life support (BLS) ambulances were retrospectively analyzed. Beginning and end of chest compression series and each individual compression were annotated. The algorithm computed a biased estimate of the autocorrelation of the TI signal in consecutive non-overlapping 2-s analysis windows to detect the presence of chest compressions and estimate compression rate.ResultsA total of 237 episodes were included in the study, with a median (IQR) duration of 10 (6-16) min. The algorithm performed with a global sensitivity in the detection of chest compressions of 98.7%, positive predictive value of 98.7%, specificity of 97.1%, and negative predictive value of 97.1% (validation subset including 207 episodes). The unsigned error in the estimation of compression rate was 1.7 (1.3-2.9) compressions per minute.ConclusionOur algorithm is accurate and robust for real-time guidance on chest compression rate using AEDs. The algorithm is simple and easy to implement with minimal software modifications. Deployment of AEDs with this capability could potentially contribute to enhancing the quality of chest compressions in the first minutes from collapse.
| S-EPMC7526915 | biostudies-literature