bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of wavelet continuous transform and signal averaged ECG for high frequency content and late potential detection in healthy individuals
Authors: Garcia Iglesias D , Rubin Lopez J.M , Perez Diez D , Moris De La Tassa C , De Cos Juez F.J , Calvo Cuervo D 
Published: November 2020

Abstract

Introduction
The Signal Averaged ECG (SAECG) is a classical method forSudden Cardiac Death (SCD) risk assessment, by means of Late Potentials (LP) in the filtered QRS (fQRS)[1]. But it is highly dependent on noise and require long time records, which make it tedious to use. Wavelet Continuous Transform (WCT) meanwhile is easier to use, and may let us to measure the High Frequency Content (HFC) of the QRS and QT intervals, which also correlates with the risk of SCD [2,3]. Whether the HFC of the QRS and QT measured with the WCT is a possible subrogate of LP, has never been demonstrated.

Objective
To demonstrate if there is any relationship between the HFC measured with the WCT and the LP analyzed with the SAECG.

Methods
Data from 50 consecutive healthy individuals. The standard ECG was digitally collected for 3 consecutive minutes. For the WCT Analysis 8 consecutive QT complexes were used and for the SAECG Analysis all available QRS were used. The time-frequency data of each QT complex were collected using the WCT as previously described [3] and the Total, QRS and QT power were obtained from each patient. For the SAECG, bipolar X, Y and Z leads were used with a bidirectional filter at 40 to 250 Hz [1]. LP were defined as less than 0.05 z in the terminal part of the filtered QRS and the duration (SAECG LP duration) and root mean square (SAECG LP Content) of this LP were calculated. Pearson's test was used to correlate the Power content with WCT analysis and the LP in the SAECG.

Results
There is a strong correlation between Total Power and the SAECG LP content (r=0.621, p&lt;0.001). Both ST Power (r=0.567, p&lt;0.001) and QRS Power (r=0.404, p=0.004) are related with the SAECG LP content. No correlation were found between the Power content (Total, QRS or ST Power) and the SAECG LP duration. Also no correlation was found between de SAECG LP content and duration.

Conclusions
Total, QRS and ST Power measured with the WCT are good surrogates of SAECG LP content. No correlation were found between WCT analysis and the SAECG LP duration. Also no correlation was found between the SAECG LP content and duration. This can be of high interest, since WCT is an easier technique, not needing long recordings and being less affected by noise.

Funding Acknowledgement
Type of funding source: None
The value of a novel model of remote monitoring alert classification of cardiac implantable devices
Authors: Mendez Zurita F , Grande Osorio M , Gonzalez Matos C , Rodriguez Font E , Guerra Ramos J , Alonso Martin C , Campos Garcia B , Moreno Weidmann Z , Ramirez De Diego I , Bote Collazo M , Paz Jaen E , Velasco Nieves A , Mogro Carranza J , Garcia Mancebo S , Vinolas Prat X 
Published: November 2020

Abstract

Introduction
Remote monitoring (RM) is commonly used in the follow-up of patients with cardiac implantable devices (CID). However, there are a significant amount of automatic alerts of low clinical relevance. An alert classification model designed to optimize the management of RM alert in CID receivers can improve the analysis.

Purpose
Assess the effectiveness of a local protocol for review and classification of MR alerts.

Methods
Retrospective study, single center. We included all patients with ICD +/− CRT in the RM program between september 2016 and december 2019. All transmission received were analyzed. The priority of the transmissions was established based on clinical criteria and device parameters, classified into 3 categories from lowest to highest priority: green, yellow and red. Each category involved a specific action protocol (Figure 1). The categorization by colors was initially carried out by a remote support center, based on data from the devices; and later, reviewed by arrhythmia nurse team who incorporated clinical information data. In case of discrepancy, the alert was again evaluated together with the cardiologist. The degree of concordance in the categorization of alerts was analyzed, as well as the transmission response time (TRT): support center- care team.

Results
In our center a total of 1013 patients were included (68±14 years old, 76% male), who completed 8755 remote transmissions. The initial classification of transmissions by the support center was: 6890 (78.7%) green, 1497 (17.1%) yellow and 368 (4.2%) red. Only 0.62% of transmissions required reclassification by the healthcare team. No alert initially classified as yellow or green should be reclassified to red. The TRT was 3.35 hours for the red transmissions and 5.6 hours for the yellow ones.

Conclusion
The categorization of alerts in our RM system allows an efficient and safe organization of assitance to patients with CID.

Funding Acknowledgement
Type of funding source: None
Cuffless systolic and diastolic blood pressure estimation at the wrist via an optical device: comparison to intra-arterial measurements
Authors: Pellaton C , Vybornova A , Fallet S , Marques L , Grossenbacher O , De Marco B , Chapuis V , Olivero E , Bertschi M , Alpert B.S , Sola J 
Published: November 2020

Abstract

The diagnosis and management of hypertension usually requires the estimation of blood pressure (BP) by means of an inflatable cuff. This procedure generates discomfort and limits patient compliance. Cuffless devices capture BP readings without performing any arterial occlusion. We believe that comfortable and cuffless BP monitoring devices can significantly aid in the fight against hypertension and support the expansion of ambulatory and remote patient monitoring programs, provided that these devices provide reliable BP readings.
The purpose of this study was to compare the systolic (S) and diastolic (D) blood pressure (BP) estimations from a new optical device at the wrist (figure) against invasive measurements performed on patients scheduled for radial arterial catheterization. The first results from this study were recently published and demonstrated good agreement for the overall study population. Here we report expanded statistical analyses for different population subgroups such as gender, age, body mass index (BMI) and skin color.
The study protocol consisted of the simultaneous recording of reflective photo-plethysmographic signals (PPG) from the optical device, and BP values recorded by a contralateral radial arterial catheter. The PPG signals were processed to generate estimates of SBP and DBP. Agreement of paired BP estimations was further calculated in terms of standard deviation (SD) of differences. The mean of differences were systematically zero because BP estimations from the optical device were calibrated for each patient.
The table shows that, for the overall population, both SBP and DBP differences SDs were smaller than 8 mmHg (as already published). Furthermore, across different population groups, both genders, all BMIs and all skin colors also resulted in SDs smaller than 8 mmHg. Only patients whose age was above 65 years were associated with a higher SD.
For the overall population and most subgroups the new optical technique appears to be capable of replacing more traditional methods of BP estimation. Only the SBP differences for the subgroup of older patients were larger. Additional studies are needed to confirm and expand these very encouraging results.
Table 1. SD of measured BP differences Population N SD of SBP differences SD of DBP differences (mmHg) (mmHg) All 16 7.1 2.9 Gender Male 10 6.4 2.8 Female 6 8.0 3.1 Age (years) &lt;65 7 4.0 2.3 &gt;65 9 *9.3 3.4 BMI (kg/m2) &lt;26 10 7.9 2.9 &gt;26 6 5.7 2.8 Skin Color (Fitzpatrick) 2 13 7.7 3.0 3 3 4.5 2.6 *Only subgroup with a SD larger than 8mmHg.
Figure 1. The investigational device

Funding Acknowledgement
Type of funding source: Private company. Main funding source(s): Aktiia SA
A novel approach using hand-held echocardiography to guide the diagnosis of heart failure in pregnant women in a low-resource setting; Maternal and Perinatal Health Research Collaboration
Authors: Alsharqi M , Arnold L , Dockerill C , Baigent C , Leeson P , Nair M 
Published: November 2020

Abstract

Background
Point of care imaging devices are promising tools for cardiovascular imaging in low-resource settings.

Purpose
Our aim was to determine whether hand-held echocardiography scans performed by obstetricians can help to identify the cardiac phenotypes in pregnant women with heart failure in India.

Methods
In November 2018, eighteen obstetricians from 10 hospitals across the states of Assam, Meghalaya and Uttar Pradesh were given 2 days of hands-on training in image acquisition using Philips Lumify devices. Obstetricians were asked to follow a simplified protocol of image acquisition and optimisation designed by the Oxford Cardiovascular Clinical Research Facility team. The protocol includes 3 key echocardiography views; parasternal long axis, parasternal short axis, and apical four chamber. Remote supervision and constructive feedback on performance was provided to improve image quality. Echocardiographic images of 269 pregnant women (with and without suspected heart failure) were acquired by the trained obstetricians, between February 2018 and January 2020. The first 147 scans were transferred with end-to-end encryption to the University of Oxford Research Echocardiography Core Laboratory (ORECL). Image interpretation and formal quality assessment was performed by 2 experienced echocardiographers.

Results
Parasternal long axis image quality was assessed as good in 78.3%, and was superior to both the parasternal short axis view (76.5%) and the apical 4-chamber view (61.9%). Image depth and gain optimisation was the main reason for loss of quality. The acquisition quality was related to reported clinical disease severity, and advanced pregnancy status. Left ventricular systolic function was impaired in 32 participants (21.9%), and 23.3% of the cohort had a dilated left atrium. Rheumatic heart disease was found in 12 participants (8.3%), in which the mitral valve was stenotic; 10 severe and 1 moderate. Mitral regurgitation was reported in 29 cases (20.8%); 6 severe, 7 moderate and 16 mild. Tricuspid and aortic valve abnormalities were also detected. Pericardial effusion was reported in 45 participants (30.8%).

Conclusion
Obstetricians with supervised training, using hand-held echocardiography have demonstrated acceptable image acquisition quality which could be assessed through core laboratory analysis to detect cardiac abnormalities. Such an approach could be useful to guide the diagnosis of heart failure in pregnant women in low-resource settings. Further training for the obstetricians and image quality assurance have been implemented in the ongoing MaatHRI study with plans to conduct a validation analysis.

Funding Acknowledgement
Type of funding source: Public grant(s) – National budget only. Main funding source(s): Medical Research Council (MRC), UK Fellowship for M Nair.
Innovation in health care: continuous wireless monitoring to improve management of critically ill atients: LIMS study preliminary results
Authors: Pietrantonio F , Alessi E , Pascucci M , Delli Castelli M , D'Amico R , Ronchetti M 
Published: November 2020

Abstract

Background
Wireless vital parameter continuous monitoring (WVPCM) is compared to regular nurse monitoring in order to provide data on the clinical and economic impact of critically ill patients (CIPs) in Internal Medicine Units (IMU).

Study Design
Pilot prospective randomized controlled open-label multi-center study with WIN@Hospital wearable wireless system creating alerts on portable devices (ipad). Experimental Arm: CIPs with MEWS (Modified Early Warning Score) ≥3 and/or NEWS (National Early Warning Score) ≥5 at admission underwent WCPCM over the first 72 h. Active Comparator: CIPs with MEWS ≥3 and/or NEWS ≥5 at admission undergoing regular nurse monitoring.

Method
Primary outcomes: Reduction of major complications (MC) from 15% to 5%. Secondary outcomes: One day reduction in length of stay (LOS); reduced nurse monitoring time; accurate patient stratification and definition of end stage disease.

Results
Preliminary results: Enrolled 145 and evaluable 125 patients (51 M/74 F), mean age 80.5 years, Comorbidity: Cumulative Illness Rating Scale CIRS-CI: 4, CIRS SI: 1.8. About 38% scored a BRASS (Blaylock Risk Assessment Screening Score) ≥20 indicating need for discharge planning requiring step-down care. More than 50% of patients present IIA index &gt;3 indicating high dependency from nursing assistance. Nurses saved a minimum of 49,6 minutes to a maximum of 58,1 minutes on time spent monitoring each patient per day. A trend towards reduction of major complications in the experimental group appears to be seen (31% versus 45%). Decrease in re-admissions (7% versus 11%) and mortality (7.3% versus 23.9%) has been observed. Arrhythmic and ischemic complications detection doubled in the experimental arm. More than 30% of the patients meet the criteria defining end stage disease.

Conclusion
WVPCM, detecting early deterioration in CIPs, may facilitate timely response in at-risk patients, increasing safety and reducing costs.
Telemedicine Network

Funding Acknowledgement
Type of funding source: None
Implication of real-time telemonitoring system in the diagnostics of cardiac diseases
Authors: Petrov I , Boichev B , Garvanski I 
Published: November 2020

Abstract

Objectives
We assessed the implication of a live telemonitoring system Check Point Cardio with real-time remote diagnostics in the diagnosis of a wide range of cardiac diseases- from rhythm disturbances to ischaemic heart disease.

Methods and results
In the period between 10.01.2017 and 10.01.2019 a total of 14172 patients were monitored. The mean monitoring period for the whole group was 7.76 (±4.5) days. The primary indication for real-time monitoring was rhythm and conduction abnormalities (66%) and ischemia detection (34%). In 2087 (14,8%) of the patient a clinically significant pathological finding was observed. A total of 603 (4,3%) patients were referred to a planned hospitalization with the most common reasons- ST segment deviation (450 pts), clinically significant bradycardia due to AV block- (21 pts); Sinus arrest/SA block (90 pts) and pacemaker malfunction in 20 patients, wide complex tachycardia was observed in 7 patients.
In addition to that 42 patients were referred to an emergent hospitalization after a contact by our team. From those patients 30 were with ST segment elevation, 10 were with ST- segment depression and 2 were with sustained wide complex tachycardia.

Conclusion
Real-time telemonitoring accompanied with real-time remote diagnostics is a reliable method for diagnosis of wide-range cardiac diseases. The possibility of immediate diagnosis and contact with the patient, combined with GPS localization, allows a fast reaction in case of an emergent situation.

Funding Acknowledgement
Type of funding source: None
Building a predictive model for warfarin dosing via machine learning
Authors: Tan O , Wu J.Z , Yeo K.K , Lee S.Y.A , Hon J.S , Chiang P , Lau Y.H , Moh R , Fam J.M 
Published: November 2020

Abstract

Background
Warfarin titration via International Normalised Ratio (INR) monitoring can be a challenge for patients on long term anticoagulation due to its multiple drug interactions, long half life and patient's individual reponse, yet critically important due to its narrow therapeutic index. Machine learning may have a role in learning and replicating existing warfarin prescribing practices, to be potentially incorporated into an automated warfarin titration model.

Purpose
We aim to explore the feasibility of using machine learning to develop a model that can learn and predict actual warfarin titration practices.

Methods
A retrospective dataset of 4,247 patients with 48,895 data points of INR values were obtained from our institutional database. Patients who had less than 5 visits recorded, invalid or missing values were excluded. Variables studied included age, warfarin indication, warfarin dose, target INR range, actual INR values, time between titration and time in therapeutic range (TTR as defined by the Rosenthal formula).
The machine learning model was developed on an unbiased training data set (1,805 patients), further refined on a handpicked balanced validation set (400 patients), before being evaluated on two balanced test sets of 100 patients each. The test sets were handpicked based on the criteria of TTR (“in vs out of range”) and stability of INR results (“low vs high fluctuation”) (Table 1). Given the time series nature of the data, a Recurrent Neural Network (RNN) was chosen to learn warfarin prescription practices. Long-short term memory (LSTM) cells were further employed to address the problem of time gaps between warfarin titration visits which could result in vanishing gradients.

Results
A total of 2,163 patients with 42,622 data points were studied (mean age 65±11.7 years, 54.7% male). The mean TTR was 65.4%. The total warfarin dose per week as predicted by the RNN was compared with actual total warfarin dose per week prescribed for each patient in the test sets. The coefficient of determination for the RNN in the “in vs out of range” and “low vs high fluctuation” test sets were 0.941 and 0.962 respectively (Figure 1).

Conclusion
This proof of concept study demonstrated that a RNN based machine learning model was able to learn and predict warfarin dosage changes with reasonable accuracy. The findings merit further evaluation of the potential use of machine learning in an automated warfarin titration model.

Funding Acknowledgement
Type of funding source: None
Virtual reality, the start of a new era for patient education in cardiology?
Authors: Hooglugt J.Q , Oudkerk Pool M.D , Mulder B.J.M , De Winter R.J , Bouma B.J , Winter M.M 
Published: November 2020

Abstract

Background
Anxiety, perceived in patients undergoing percutaneous cardiac intervention is a known problem, which is negatively correlated with quality of life, adherence to recommended clinical practice and medication, health promoting behavior, hospitalization, and patient experience and satisfaction. Hence, preprocedural interventions to alleviate anxiety are interesting. While preoperative education interventions were proven to be effective as anxiety reduction modality, especially those modalities that provide immersive experience appeared to be even more effective within this context. Given the non-invasive nature of these modalities and the introduction of innovative techniques such as Virtual Reality (VR), the question arises whether VR can be successfully introduced as an effective tool to alleviate anxiety in cardiology patients undergoing PFO or ASD closure.

Purpose
The purpose of the study was to alleviate pre-procedural anxiety in patients undergoing percutaneous PFO or ASD closure using a VR film as an innovative and immersive patient education modality.

Methods
Patients were randomized to either the VR-group or the control group. The control group received traditional patient information by their cardiologist. The intervention group additionally viewed a 4-minute VR-film, that was designed to create a representative patient-experience of the day of the procedure. The primary outcome was patient anxiety in the VR group compared to the control group, as measured with anxiety scores derived from the State Trait Anxiety Inventory (STAI) questionnaire. Measurements were performed directly after the informed consent visit and one week prior to the procedure. Secondary outcome measure was the duration of anesthesia during the procedure.

Results
In total 40 patients have been included (mean age = 45 yrs ± 11, male = 21), mean FU duration = 37 days ± 23). So far, 27 patients (VR-group n=14; Control group n=13) completed follow-up. At baseline the control and intervention group were equally anxious (37±9 vs 38±14). During follow-up we found a significant increase in anxiety in the control group (37±9 vs 46±12; p=0.034; figure 1), whereas anxiety in the VR-group remained unchanged (38±14 vs 36±9; figure 1). One week prior to the procedure, the control group was significantly more anxious compared to the VR group (+ 11±4; p=0.012; figure 2). The mean duration of the anesthesia was significantly shorter within the VR-group in comparison with the control group (57±10 min vs 71±18 min; p=0,029). This may be an indication that decreased anxiety could have beneficial effects on the complete duration of anesthesia.

Conclusion
Our results demonstrate that immersive VR patient education is both innovative and effective in alleviating anxiety prior to a cardiological procedure and may have beneficial effects on patient experience and anesthesia duration.

Funding Acknowledgement
Type of funding source: None
Inequalities after STEMI in National Health Service: is there really a postcode lottery?
Authors: Ferreira C , Baptista R , Ribeiro A.I , Freitas A , Ferreira J.A , Milner J , Martinho A , Almeida J.P , Goncalves V , Campos G , Rosa J , Goncalves F , Monteiro S , Monteiro P , Goncalves L 
Published: November 2020

Abstract

Background and purpose
Failure to address the impact of social determinants of health attenuates efficacy of proven prevention recommendations, namely because important considerations related to socioeconomic disadvantage are not captured by existing cardiovascular disease (CDV) risk stratification methods. We aimed to assess how socioeconomic determinants influence recurrent MI and all-cause death after myocardial infarction (MI) in Portugal.

Methods
We conducted a retrospective, observational cohort study, including all patients with a ST-elevation MI (STEMI) admitted to and discharged alive from an intensive cardiac care unit between 2004 and 2017 (n=1809). The median (interquartile range) follow-up was 6 (4–9) years. We used survival models to assess the relationship between their municipal (i) income by purchasing power per capita (PPC), (ii) geographical accessibility to health care, (iii) illiteracy, iv) residential socioeconomic deprivation and recurrent MI and all-cause mortality. To assess residential socioeconomic deprivation, each individual's residential postcode was matched to the recently validated Portuguese version of European Deprivation Index (EDI). The index was categorized into quintiles (Q1-least deprived to Q5-most deprived).

Results
The mean age was 64±14 years; 74% were male. Regarding individual socioeconomic variables, PPC (HR 1.19; 95% CI 0.97–1.47 for Tertile 1 vs Tertile 2; HR 1.28; 95% CI 1.04–1.56 for Tertile 1 vs Tertile 3 and HR 1.07; 95% CI 0.85–1.34 for Tertile 2 vs Tertile 3) and medical appointments in primary health centers per inhabitant (HR 0.90; 95% CI 0.75–1.09 for Tertile 1 vs Tertile 2; HR 1.23; 95% CI 0.95–1.61 for Tertile 1 vs Tertile 3 and HR 1.37; 95% CI 1.06–1.76 for Tertile 2 vs Tertile 3) were predictors of all-cause mortality, but not recurrent MI; however, in multivariate analysis adjusted for sex, age and ejection fraction, this association was no longer significant (HR 1.00; 95% CI 0.99–1.00 and, HR 1.00; 95% CI 0.89–1.17, respectively). Additionally, no evident association between illiteracy and all-cause mortality or MI was present. Concerning EDI, demographic data was similar among the quintiles (Table 1). Although EDI quintiles were not associated with all-cause mortality (HR 1.17; 95% CI 0.82–1.66 for Q5 vs Q1), the EDI was an independent predictor of recurrent MI (Figure 1). On multivariate analysis, adjusted for age, sex, hypertension, diabetes and LDL cholesterol, the HR for the most deprived (Q5) to the least deprived (Q1) quintile was 1.91 (95% CI 1.05–3.49) for MI.

Conclusions
Our study shows clear socioeconomic differentials in cardiovascular outcomes in patients with STEMI which suggests that accounting for socioeconomic deprivation might improve risk prediction and therefore disease prognosis.

Funding Acknowledgement
Type of funding source: None