Evidence Accrual Research Articles

Diagnostic Accuracy of Smartwatches for the Detection of Cardiac Arrhythmia: Systematic Review and Meta-analysis

BackgroundSignificant morbidity, mortality, and financial burden are associated with cardiac rhythm abnormalities. Conventional investigative tools are often unsuccessful in detecting cardiac arrhythmias because of their episodic nature. Smartwatches have gained popularity in recent years as a health tool for the detection of cardiac rhythms.ObjectiveThis study aims to systematically review and meta-analyze the diagnostic accuracy of smartwatches in the detection of cardiac arrhythmias.MethodsA systematic literature search of the Embase, MEDLINE, and Cochrane Library databases was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to identify studies reporting the use of a smartwatch for the detection of cardiac arrhythmia. Summary estimates of sensitivity, specificity, and area under the curve were attempted using a bivariate model for the diagnostic meta-analysis. Studies were examined for quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool.ResultsA total of 18 studies examining atrial fibrillation detection, bradyarrhythmias and tachyarrhythmias, and premature contractions were analyzed, measuring diagnostic accuracy in 424,371 subjects in total. The signals analyzed by smartwatches were based on photoplethysmography. The overall sensitivity, specificity, and accuracy of smartwatches for detecting cardiac arrhythmias were 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97), and 97% (95% CI 0.96-0.99), respectively. The pooled positive predictive value and negative predictive value for detecting cardiac arrhythmias were 85% (95% CI 0.79-0.90) and 100% (95% CI 1.0-1.0), respectively.ConclusionsThis review demonstrates the evolving field of digital disease detection. The current diagnostic accuracy of smartwatch technology for the detection of cardiac arrhythmias is high. Although the innovative drive of digital devices in health care will continue to gain momentum toward screening, the process of accurate evidence accrual and regulatory standards ready to accept their introduction is strongly needed.Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42020213237; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213237.

The evidence for interventions in early childhood allergy prevention - towards a living systematic review: protocol.

Background: Research in early childhood allergy prevention (ECAP) is flourishing and new intervention strategies have proven to be promising. Due to the dynamic nature of ECAP, gaps between what is known and how guidelines inform practice are likely. A living systematic review (LSR) can narrow this gap by incorporating new evidence as it becomes available. No efficacy comparisons across various ECAP interventions for similar outcomes have been carried out. Networks of randomised clinical trials can be evaluated in the context of a network meta-analysis (NMA). We aim to establish a LSR on the efficacy and safety of any intervention investigated in randomised controlled trials (RCT) to prevent the occurrence of allergic sensitisation (AS), symptoms or diagnoses of allergic diseases in infancy and early childhood (0-3 years). Methods: A baseline SR will synthesise the evidence from existing SRs of RCTs as well as RCTs not yet considered in these. After completion of the baseline SR we propose to conduct a LSR. Using this methodology, we aim to undertake constant evidence surveillance, three-monthly search updates, and review updates every three months, should new evidence emerge. Conclusions: The ECAP evidence landscape has undergone dramatic transformations and this process is likely to continue. As a response to this, a LSR offers the potential to allow more timely synthesis of new evidence as it emerges. Long gaps between updates of SRs makes it harder for guidelines and recommendations to be up to date. Users of information, such as parents, may be confused if they encounter new evidence that is not part of a trusted guideline. A LSR approach allows us to continuously search the literature and update the evidence-base of existing ECAP interventions resulting in a decreased timespan from evidence accrual to informing clinical practice.

The evidence for interventions in early childhood allergy prevention - towards a living systematic review: protocol.

Background: Research in early childhood allergy prevention (ECAP) is flourishing and new intervention strategies have proven to be promising. Due to the dynamic nature of ECAP, gaps between what is known and how guidelines inform practice are likely. A living systematic review (LSR) can narrow this gap by incorporating new evidence as it becomes available. No efficacy comparisons across various ECAP interventions for similar outcomes have been carried out. Networks of randomised clinical trials can be evaluated in the context of a network meta-analysis (NMA). We aim to establish a LSR on the efficacy and safety of any intervention investigated in randomised controlled trials (RCT) to prevent the occurrence of allergic sensitisation (AS), symptoms or diagnoses of allergic diseases in infancy and early childhood (0-3 years). Methods: A baseline SR will synthesise the evidence from existing SRs of RCTs as well as RCTs not yet considered in these. After completion of the baseline SR we propose to conduct a LSR. Using this methodology, we aim to undertake constant evidence surveillance, three-monthly search updates, and review updates every three months, should new evidence emerge. Conclusions: The ECAP evidence landscape has undergone dramatic transformations and this process is likely to continue. As a response to this, a LSR offers the potential to allow more timely synthesis of new evidence as it emerges. Long gaps between updates of SRs makes it harder for guidelines and recommendations to be up to date. Users of information, such as parents, may be confused if they encounter new evidence that is not part of a trusted guideline. A LSR approach allows us to continuously search the literature and update the evidence-base of existing ECAP interventions resulting in a decreased timespan from evidence accrual to informing clinical practice.

Estimation of Target Maneuvers from Tracked Behavior Using Fuzzy Evidence Accrual

Estimation of Target Maneuvers from Tracked Behavior Using Fuzzy Evidence Accrual

Feature Object Extraction: Evidence Accrual for the Level 1 Fusion Classification Problem

Classification of a target is a key element of the Level 1 Fusion problem. Estimation of the classification of a potential target could be used to determine whether it should be prosecuted. This increasingly important problem requires the development of a quality estimate based on fusing reports across time and from a variety of sensors. The most common automated techniques for the classification problem provide a probability measure of the possible classes. Another concept in classification is the use of evidence accrual. As opposed to the creation of scoring techniques that use a random variable representation of the classification, the evidence accrual technique builds scores based on the information that can be compared to other scores or thresholds of the decision process. Since evidence affects the various potential classes differently, the technique developed is based on decoupled fuzzy-logic-based Kalman filters, similar to the concept of first-order observers. The proposed technique addresses three key issues in the classification problem. First, it is designed to incorporate both numeric and nonnumeric sensor reports. Second, it incorporates measurement uncertainty. Finally, it provides a level of uncertainty for each class. The technique is implemented in two forms: one that emulates the Bayesian taxonomy and one that allows for evidence to be independently applied to each potential class.

Testing Evidence Accrual Models by Manipulating Stimulus Onset

Many models of response time assume that subjects accrue stimulus “evidence” samples in time (e.g., random walk models, counter models). In this paper, the concept of one stimulus dominating another is used to construct a test of the whole class of evidence accrual models. For an example of dominance, consider stimuli that are presented either virtually instantaneously (stepped) or in a gradually increasing manner (ramped). Ramped stimuli are presented such that the ramped portion precedes the stepped onset of stepped stimuli. In this case ramped stimuli dominate stepped stimuli. In this paper the class of evidence accrual models is formalized. It is shown that under appropriate assumptions evidence accrual models do predict more accurate responses to dominating stimuli. However, this result does not hold for response latencies. There are anomalous cases where an evidence accrual model (the accumulator model of Vickers (1970, Ergonomics13, 37–58)) predicts slower mean correct response latencies to dominating stimuli. It is shown through extensive computer simulation that these anomalous cases occur only when response criteria are so asymmetric that there are exceedingly extreme response biases. For experiments where response biases are not exceedingly extreme, random walk and accumulator models predict more accurate and quicker correct responses to dominating stimuli. In sum, manipulating the time course of stimuli in accordance with the concept of dominance can provide empirical tests of the class of evidence accrual models.

Metacognition in psychophysical judgment: an unfolding view of comparative judgments of mental workload.

An experiment is reported in which it was found that when subjects were required to indicate which of two visual extents was more difficult to categorize as "long" or "short," they executed these categorizations and then measured the distance of the representation of each stimulus from the long-short category boundary; the stimulus nearer the boundary was judged to be the more difficult. When they were requested to indicate which was easier to categorize, they selected the alternative that was farther. Coombs's theory of data (1952, 1964) and his unfolding theory of preferential choice (1950, 1964) provided the conceptualization of metacognition in this psychophysical task context. Strong support for the probabilistic version of unfolding theory was obtained from the observed selective effects of laterality on the levels of stochastic transitivity attained for various classes of triples and the reliably longer times for comparisons with bilateral pairs than with unilateral pairs. The semantic congruity effects obtained, together with the changes in the form of the relationship between probability and response time as a function of practice, can be best accounted for by an evidence accrual theory in which the distances from the active reference point are measured and compared with a criterion on each evidence accrual. No support is provided for the view that propositionally based semantic "ease"-"difficulty" codes serve as the basis for these metacognitive comparative judgments of ease and difficulty.

Semantic congruity effects and theories of the comparison process.

Two experiments requiring comparisons of point locations on the line demonstrate that the magnitude of the response-time-based congruity effect parallels the form of the macro and the micro speed-accuracy trade-off function. This is predicted from the evidence accrual class of theories but is contrary to either the propositionally based semantic coding theory or the expectancy view. Very large accuracy-based congruity effects with comparisons of point locations in the plane are evident. Congruity effects arise because the duration of each evidence accrual is increased and the quality of the information is reduced as the distance of the stimulus representations from the instruction-activated reference point increases. This evidence accrual view is extended to account for the properties of perceptual and symbolic comparisons.

Intensity and number of alternatives in hue identification: Piéron's law and choice reaction time.

Two experiments investigated the effects of intensity and the number of response alternatives in hue identification. Three questions were addressed. First, what is the relationship between these effects? If intensity and number of alternatives affect different processes in series, these factors would have additive effects on reaction time (RT). Other models predict a multiplicative interaction. These models assume that when a stimulus is presented, evidence accrues over time for each response alternative, and that when the evidence for a particular alternative exceeds its criterion, the response is made. A natural auxiliary assumption is that intensity affects the rate of evidence accrual, while the number of alternatives affects the criterion. The second question addressed is, how does choice RT change as a function of intensity? Piéron used a power function to describe the effect of intensity on simple RT. This paper considers three candidates for intensity’s effect on choice RT: the power, logistic, and Michaelis functions. Each candidate function was tested in an additive model and a multiplicative model. The best account was given by the power function in an additive model. The last question is, does each process produce an output that can be classified as correct or incorrect? Schweickert (1985) proposed that factors that selectively influenced such processes would have additive effects on log percent correct. Instead, an interaction was found. Perhaps the assumption that the process affected by intensity produces a single output is wrong.