Interpretation of the 12‑lead Electrocardiogram (ECG) is normally assisted with an automated diagnosis (AD), which can facilitate an ‘automation bias’ where interpreters can be anchored. In this ...paper, we studied, 1) the effect of an incorrect AD on interpretation accuracy and interpreter confidence (a proxy for uncertainty), and 2) whether confidence and other interpreter features can predict interpretation accuracy using machine learning.
This study analysed 9000 ECG interpretations from cardiology and non-cardiology fellows (CFs and non-CFs). One third of the ECGs involved no ADs, one third with ADs (half as incorrect) and one third had multiple ADs. Interpretations were scored and interpreter confidence was recorded for each interpretation and subsequently standardised using sigma scaling. Spearman coefficients were used for correlation analysis and C5.0 decision trees were used for predicting interpretation accuracy using basic interpreter features such as confidence, age, experience and designation.
Interpretation accuracies achieved by CFs and non-CFs dropped by 43.20% and 58.95% respectively when an incorrect AD was presented (p < 0.001). Overall correlation between scaled confidence and interpretation accuracy was higher amongst CFs. However, correlation between confidence and interpretation accuracy decreased for both groups when an incorrect AD was presented. We found that an incorrect AD disturbs the reliability of interpreter confidence in predicting accuracy. An incorrect AD has a greater effect on the confidence of non-CFs (although this is not statistically significant it is close to the threshold, p = 0.065). The best C5.0 decision tree achieved an accuracy rate of 64.67% (p < 0.001), however this is only 6.56% greater than the no-information-rate.
Incorrect ADs reduce the interpreter's diagnostic accuracy indicating an automation bias. Non-CFs tend to agree more with the ADs in comparison to CFs, hence less expert physicians are more effected by automation bias. Incorrect ADs reduce the interpreter's confidence and also reduces the predictive power of confidence for predicting accuracy (even more so for non-CFs). Whilst a statistically significant model was developed, it is difficult to predict interpretation accuracy using machine learning on basic features such as interpreter confidence, age, reader experience and designation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Atrial fibrillation is the most common heart‐rhythm disorder, affecting about 1.5% to 2% of the population with an increased risk of mortality and morbidity due to stroke, thromboembolism, and heart ...failure. If the conversion back to sinus rhythm does not happen spontaneously, pharmacological or electrical cardioversion (ECV) is the next available treatment options for some patients. However, the long‐term success following ECV is variable. This review describes the factors that are associated with maintenance of sinus rhythm following ECV and proposes a clinical strategy based on the available evidence.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
Background and Aims
The epidemiology of peripartum cardiomyopathy (PPCM) in Europe is poorly understood and data on long-term outcomes are lacking. A retrospective, observational, ...population-level study of validated cases of PPCM in Scotland from 1998 to 2017 was conducted.
Methods
Women hospitalized with presumed de novo left ventricular systolic dysfunction around the time of pregnancy and no clear alternative cause were included. Each case was matched to 10 controls. Incidence and risk factors were identified. Morbidity and mortality were examined in mothers and children.
Results
The incidence of PPCM was 1 in 4950 deliveries. Among 225 women with PPCM, obesity, gestational hypertensive disorders, and multi-gestation were found to be associated with having the condition. Over a median of 8.3 years (9.7 years for echocardiographic outcomes), 8% of women with PPCM died and 75% were rehospitalized for any cause at least once. Mortality and rehospitalization rates in women with PPCM were ∼12- and ∼3-times that of controls, respectively. The composite of all-cause death, mechanical circulatory support, or cardiac transplantation occurred in 14%. LV recovery occurred in 76% and, of those who recovered, 13% went on to have a decline in LV systolic function despite initial recovery. The mortality rate for children born to women with PPCM was ∼5-times that of children born to controls and they had an ∼3-times greater incidence of cardiovascular disease over a median of 8.8 years.
Conclusions
PPCM affected 1 in 4950 women around the time of pregnancy. The condition is associated with considerable morbidity and mortality for the mother and child. There should be a low threshold for investigating at-risk women. Long term follow-up, despite apparent recovery, should be considered.
Structured Graphical Abstract
Graphical abstract
Graphical summary of the main study findings. CV, cardiovascular; LV, left ventricular; LVEF, left ventricular ejection fraction; PPCM, peripartum cardiomyopathy.
Endothelial dysfunction has been implicated as a key factor in the development of a wide range of cardiovascular diseases, but its definition and mechanisms vary greatly between different disease ...processes. This review combines evidence from cell-culture experiments, in vitro and in vivo animal models, and clinical studies to identify the variety of mechanisms involved in endothelial dysfunction in its broadest sense. Several prominent disease states, including hypertension, heart failure, and atherosclerosis, are used to illustrate the different manifestations of endothelial dysfunction and to establish its clinical implications in the context of the range of mechanisms involved in its development. The size of the literature relating to this subject precludes a comprehensive survey; this review aims to cover the key elements of endothelial dysfunction in cardiovascular disease and to highlight the importance of the process across many different conditions.
The application of artificial intelligence to interpret the electrocardiogram (ECG) has predominantly included the use of knowledge engineered rule-based algorithms which have become widely used ...today in clinical practice. However, over recent decades, there has been a steady increase in the number of research studies that are using machine learning (ML) to read or interrogate ECG data.
The aim of this study is to review the use of ML with ECG data using a time series approach.
Papers that address the subject of ML and the ECG were identified by systematically searching databases that archive papers from January 1995 to October 2019. Time series analysis was used to study the changing popularity of the different types of ML algorithms that have been used with ECG data over the past two decades. Finally, a meta-analysis of how various ML techniques performed for various diagnostic classifications was also undertaken.
A total of 757 papers was identified. Based on results, the use of ML with ECG data started to increase sharply (p < 0.001) from 2012. Healthcare applications, especially in heart abnormality classification, were the most common application of ML when using ECG data (p < 0.001). However, many new emerging applications include using ML and the ECG for biometrics and driver drowsiness. The support vector machine was the technique of choice for a decade. However, since 2018, deep learning has been trending upwards and is likely to be the leading technique in the coming few years. Despite the accuracy paradox, accuracy was the most frequently used metric in the studies reviewed, followed by sensitivity, specificity, F1 score and then AUC.
Applying ML using ECG data has shown promise. Data scientists and physicians should collaborate to ensure that clinical knowledge is being applied appropriately and is informing the design of ML algorithms. Data scientists also need to consider knowledge guided feature engineering and the explicability of the ML algorithm as well as being transparent in the algorithm's performance to appropriately calibrate human-AI trust. Future work is required to enhance ML performance in ECG classification.
•From 2018, DL has appeared and used for ECG classification with promising results.•ML outperformed physicians in detecting some arrhythmias such as AF.•SVM has since been the trend and the most frequently used ML algorithm•Accuracy has been trending upwards significantly for evaluating ML algorithms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Oxidative stress is a key feature of the atherothrombotic process involved in the etiology of heart attacks, ischemic strokes, and peripheral arterial disease. It stands to reason that antioxidants ...represent a credible therapeutic option to prevent disease progression and thereby improve outcome, but despite positive findings from in vitro studies, clinical trials have failed to consistently show benefit. The aim of this review is to re-appraise the concept of antioxidants in the prevention and management of cardiovascular disease. In particular, the review will explore the reasons behind failed antioxidant strategies with vitamin supplements and will evaluate how flavonoids might improve cardiovascular function despite bioavailability that is not sufficiently high to directly influence antioxidant capacity. As well as reaching conclusions relating to those antioxidant strategies that might hold merit, the major myths, limitations, and pitfalls associated with this research field are explored.
Aims
A recent systematic review highlighted the lack of robust studies on prescribers' perspectives of direct‐acting oral anticoagulants (DOACs) for nonvalvular atrial fibrillation. The aim was to ...determine prescribers' views and experiences of prescribing DOACs.
Methods
A cross‐sectional survey of prescribers in a remote and rural area of Scotland. Survey items were: demographics; prescribing of DOACs; views of potential influences on DOAC prescribing; knowledge of prescribing guidelines; and experiences. Items on potential influences were based on the Theoretical Domains Framework. Data were analysed using descriptive and inferential statistics, and content analysis of responses to open questions. Principal component analysis was performed on the items of potential influences.
Results
In total, 154 responses were received, 120 (77.9%) from doctors, 18 (11.7%) from nurse prescribers and 10 (6.4%) from pharmacist prescribers (6 missing). Principal component analysis of the Theoretical Domains Framework items of potential influences gave 4 components. Component scores for (i) role of professionals, their knowledge and skills and (ii) influences on prescribing were positive. Those for (iii) consequences of prescribing and (iv) monitoring for safety and effectiveness were more neutral. There were low levels of agreement for statements relating to DOACs being more effective, safer and cost‐effective than warfarin. There were similar responses around the complexity of bleeding management and detection of over and under‐anticoagulation.
Conclusion
This study has identified several key issues of DOAC prescribing (e.g. bleeding management) hence further emphasis is required in continuing professional development and during guideline implementation and evaluation.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Middle–Late Ordovician sequences from the Appalachian Basin and Arbuckle Mountain regions of North America were analyzed for carbonate-associated sulfate (δ34SCAS) and pyrite (δ34Spyr) paired with ...carbonate (δ13Ccarb) and organic matter (δ13Corg) chemostratigraphy. Two major negative drops in δ34SCAS (12‰ excursions) are recognized: the older decline in δ34SCAS occurs within the Histiodella holodentata–Phragmodus polonicus Conodont Zones and the younger drop is within the Cahabagnathus sweeti–Amorphognathus tvaerensis (Baltoniodus gerdae subzone) Zones. These overall these negative shifts in δ34SCAS have an antithetical relationship with positive shifts in δ34Spyr (~+10‰) and δ13Ccarb (~+2‰) recorded in the same successions. The older negative δ34SCAS shift is coincident with the widely documented mid-Darriwilian δ13C excursion (MDICE), and the younger negative δ34SCAS shift is coincident with another positive δ13Ccarb shift in the early Sandbian. Geochemical modeling of these sulfur isotope shifts suggests that a decrease in the global rate of pyrite burial or isotope fractionation between seawater sulfate and sedimentary pyrite could account for these negative δ34SCAS trends. Additionally, a substantial increase in the weathering flux of pyrite to the global oceans could also explain these secular sulfur isotope trends. While increased crustal weathering is broadly consistent with a sea-level lowstand, and the seawater 87Sr/86Sr isotope record of change in continental weathering in the late Darriwilian Stage of the Ordovician, geologic and geochemical proxy evidence do not support distinct pulses of continental weathering required to generate two separate negative shifts in δ34SCAS. These antithetical isotope trends may be best explained by changes in the marine redox state that significantly reduced microbially mediated pyrite burial and organic matter remineralization rates. Pulses of oceanic ventilation would have expanded habitable environments for marine organisms, and thus is broadly consistent with major increases in biodiversification during this period of the Ordovician.
•Newly paired sulfur and carbon isotope data of Ordovician carbonates from Laurentia•Two large drops in δ34SCAS correspond to positive shifts in δ13Ccarb values.•First isotopic evidence for Ordovician decoupling of carbon and sulfur cycles•These data support intervals of oceanic ventilation in the Middle–Late Ordovician.•Oceanic oxygenation provides bolstering conditions for coincident GOBE pulses.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Abstract
Objectives
To investigate relationships between factors influencing medication taking and behavioural determinants in patients who have undergone percutaneous coronary intervention (PCI).
...Methods
A cross-sectional survey using a postal questionnaire distributed to PCI patients. The questionnaire was iteratively developed by the research team with reference to the theoretical domains framework (TDF) of behavioural determinants, reviewed for face and content validity and piloted. Data were analysed using descriptive and principal component analysis (PCA). Inferential analysis explored relationships between PCA component scores and factors influencing medicating taking behaviour.
Key findings
Adjusted response rate was 62.4% (325/521). PCA gave three components: (C1) Self-perceptions of knowledge and abilities in relation to medication taking; (C2) Aspects relating to activities and support in medication taking; (C3) Emotional aspects in taking medication. Generally, respondents held very positive views. Statistically significant relationships between all three components and self-reported chest pain/discomfort indicated patients with ongoing chest pain/discomfort post-PCI are more likely to have behavioural determinants and beliefs which make medication taking challenging. Respondents who were on 10 or more medications had lower levels of agreement with the C2 and C3 statements indicating challenges associated with their activities/support and anxieties in medication taking.
Conclusions
PCI patients show links between TDF behavioural determinants and factors influencing medication taking for those reporting chest pain or polypharmacy. Further research needs to explore the effective design and implementation of behavioural change interventions to reduce the challenge of medication taking.
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BFBNIB, FZAB, GIS, IJS, KILJ, NUK, OILJ, SBCE, SBMB, UL, UPUK, VSZLJ
Patients' negative illness perceptions and beliefs about cardiac rehabilitation (CR) can influence uptake and adherence to CR. Little is known about the interpartner influence of these antecedent ...variables on quality of life of patients with coronary artery disease (CAD) and their family caregivers. The aims of the study were: 1) to assess differences in illness perceptions, beliefs about CR and quality of life between patients with CAD and their family caregivers upon entry to a CR programme and at 6 months follow-up; and 2) to examine whether patients' and caregivers' perceptions of the patient's illness and beliefs about CR at baseline predict their own and their partner's quality of life at 6 months.
In this longitudinal study of 40 patient-caregiver dyads from one CR service, patients completed the Brief Illness Perception Questionnaire and Beliefs about Cardiac Rehabilitation Questionnaire at baseline and 6 months; and caregivers completed these questionnaires based on their views about the patient's illness and CR. The Short-Form 12 Health Survey was used to assess patients' and caregivers' perceived health status. Dyadic data were analysed using the Actor-Partner Interdependence Model.
Most patients (70%) were men, mean age 62.45 years; and most caregivers (70%) were women, mean age 59.55 years. Caregivers were more concerned about the patient's illness than the patients themselves; although they had similar scores for beliefs about CR. Patients had poorer physical health than caregivers, but their level of mental health was similar. Caregivers' poorer mental health at 6 months was predicted by the patient's perceptions of timeline and illness concern (i.e. partner effects). Patient's and caregiver's illness perceptions and beliefs about CR were associated with their own physical and mental health at 6 months (i.e. actor effects).
Overall, the patients and caregivers had similar scores for illness perceptions and beliefs about CR. The actor and partner effect results indicate a need to focus on specific illness perceptions and beliefs about CR, targeting both the individual and the dyad, early in the rehabilitation process to help improve patients and caregivers physical and mental health (outcomes).
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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