bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inter operator variability of machine learning researchers predicting all-cause mortality in patients admitted to intensive care unit
Authors: Jones Y , Cleland J , Li C , Pellicori P , Friday J 
Published: October 2021

Abstract

Background
The number of publications using machine learning (ML) to predict cardiovascular outcomes and identify clusters of patients at greater risk has risen dramatically in recent years. However, research papers which use ML often fail to provide sufficient information about their algorithms to enable results to be replicated by others in the same or different datasets.

Aim
To test the reproducibility of results from ML algorithms given three different levels of information commonly found in publications: model type alone, a description of the model, and complete algorithm.

Methods
MIMIC-III is a healthcare dataset comprising detailed information from over 60,000 intensive care unit (ICU) admissions from the Beth Israel Deaconess Medical Centre between 2001 and 2012. Access is available to everyone pending approval and completion of a short training course.
Using this dataset, three models for predicting all-cause in-hospital mortality were created, two from a PhD student working in ML, and one from an existing research paper which used the same dataset and provided complete model information. A second researcher (a PhD student in ML and cardiology) was given the same dataset and was tasked with reproducing their results. Initially, this second researcher was told what type of model was created in each case, followed by a brief description of the algorithms. Finally, the complete algorithms from each participant were provided. In all three scenarios, recreated models were compared to original models using Area Under the Receiver Operating Characteristic Curve (AUC).

Results
After excluding those younger than 18 years and events with missing or invalid entries, 21,139 ICU admissions remained from 18,094 patients between 2001 and 2012, including 2,797 in-hospital deaths. Three models were produced: two Recurrent Neural Networks (RNNs) which differed significantly in internal weights and variables, and a Boosted Tree Classifier (BTC). The AUC of the first reproduced RNN matched that of the original RNN (Figure 1), however the second RNN and the BTC could not be reproduced given model type alone. As more information was provided about these algorithms, the results from the reproduced models matched the original results more closely.

Conclusions
In order to create clinically useful ML tools with results that are reproducible and consistent, it is vital that researchers share enough detail about their models. Model type alone is not enough to guarantee reproducibility. Although some models can be recreated with limited information, this is not always the case, and the best results are found when the complete algorithm is shared. These findings have huge relevance when trying to apply ML in clinical practice.

Funding Acknowledgement
Type of funding sources: None.
Detecting cardiomyopathies in pregnancy and the postpartum period using ECG
Authors: Adedinsewo D , Johnson P W , Douglass E J , Attia Z I , Phillips S D , Goswami R M , Yamani M H , Connolly H M , Rose C H , Sharpe E E , Lopez-Jimenez F , Friedman P A , Carter R E , Noseworthy P A 
Published: October 2021

Abstract

Background
Cardiovascular disease (CVD) has been identified as a major threat to maternal health in the US and UK with cardiomyopathy being one of the most common acquired CVD in the pregnant and postpartum period. Diagnosing cardiomyopathy in pregnancy is challenging due to an overlap of cardiovascular symptoms with normal pregnancy symptoms.

Purpose
The purpose of this study was to evaluate the effectiveness of an ECG based deep learning model in identifying cardiomyopathy among pregnant and postpartum women.

Methods
We utilized an ECG based deep learning model to detect cardiomyopathy in a cohort of pregnant or postpartum women seen at multiple hospital sites. Model performance was evaluated using area under the curve (AUC), accuracy, sensitivity, and specificity. We compared the diagnostic probabilities of the deep learning model with natriuretic peptides and a multivariable model consisting of demographic and clinical parameters.

Results
1,807 women were included. 7%, 10% and 13% had LVEF ≤35%, &lt;45% and &lt;50% respectively. The ECG based deep learning model identified cardiomyopathy with an AUC of 0.92 for left ventricular ejection fraction (LVEF) ≤35%, 0.89 for LVEF &lt;45% and 0.87 for LVEF &lt;50%. For LVEF ≤35%, AUC was higher in Black (0.95) and Hispanic (0.98) women compared to white (0.91). Natriuretic peptides and the multivariable model had AUCs of 0.85 and 0.72 respectively.

Conclusions
A deep learning model effectively identifies cardiomyopathy in pregnant or postpartum women, outperforms natriuretic peptides and traditional clinical parameters with the potential to become a powerful initial screening tool for cardiomyopathy in the obstetric care setting.

Funding Acknowledgement
Type of funding sources: Other. Main funding source(s): This study was made possible using resources supported by the Mayo Clinic Women's Health Research Center and the Mayo Clinic Building Interdisciplinary Research Careers in Women's Health (BIRCWH) Program funded by the National Institutes of Health (NIH), grant number K12 HD065987. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The relationships among the pulse rate, use of beta-blockers, and prognosis in patients with ischemic heart disease in a real-world database using a storage system
Authors: Oba Y , Kohro T , Sato H , Nochioka K , Nakayama M , Fujita H , Mizuno Y , Kiyosue A , Iwanaga Y , Miyamoto Y , Matoba T , Tsutsui H , Nakamura T , Usuku K , Nagai R 
Published: October 2021

Abstract

Background
The use of β-blockers has the effect of improving the prognosis of patients with ischemic heart disease (IHD). One of the underlying mechanisms is a decrease in the cardiac load due to a reduction in the heart rate.

Purpose
To clarify the relationships among the pulse rate, the use of β-blockers, and the prognosis in patients with IHD in a multicenter study using a storage system.

Methods
The Clinical Deep Data Accumulation System (CLIDAS) collects (1) basic patient information, prescriptions, and laboratory data from electronic medical records from the Standardized Structured Medical Information eXchange (SS-MIX2) standard storage, and (2) the results of physiological tests, cardiac catheterization, and cardiac catheter intervention reports from the SS-MIX2 extended storage. 8540 cases who underwent cardiac catheterization from 6 university hospitals and the national cardiovascular center in Japan were registered (male: 77%, average age: 70.2 years). We evaluated these patients' pulse rate at admission and at the discharge of cardiac catheterization in 6,598 patients. We divided the pulse rates at discharge into quartiles (Q1: &lt;60, Q2: 60–66, Q3: 67–75, Q4: ≥76 bpm), and we analyzed the relationship between the pulse rate and the prognosis by dividing the patients into the stable angina group (n=2,631) and the acute coronary syndrome (ACS) group (n=2,394). Regarding the use of β-blockers, we compared the pulse rates of the patients taking carvedilol (n=1,728) and those taking bisoprolol (n=2,761) at admission and discharge. Major adverse cardiovascular events (MACE) were defined as cardiovascular death, non-fatal myocardial infarction, unstable angina, heart failure, stroke, and other hospitalized cardiovascular events.

Results
A total of 600 MACEs occurred during an average observation period of 890 days. The incidence of cardiovascular events was significantly higher in the Q4 patients in the stable angina group (hazard ratio 1.79, 95% confidence interval 1.32–2.41, but there was no significant difference among the four pulse rate subgroups in the ACS group. The bisoprolol-treated patients had lower pulse rates at discharge (67.4±12.2 vs. 68.8±11.8 bpm, p&lt;0.001) and a lower percentage of patients in the Q4 group (21.2 vs. 24.9%, p=0.005) compared to the carvedilol-treated patients. The pulse rate at admission was similar in the bisoprolol- and carvedilol-treated patients (74.3±19.3 vs. 73.2±29.5 bpm, p=0.328).

Conclusion
In a real-world database using a storage system, a pulse rate of ≤75 bpm was associated with a good prognosis in patients with ACS. Compared to carvedilol, bisoprolol was associated with a decreased pulse rate at discharge.

Funding Acknowledgement
Type of funding sources: Foundation. Main funding source(s): Kowa Company, Ltd.
Improving adherence to cholesterol lowering guidelines through an interactive digital tool
Authors: Rashid S , Suero-Abreu G A , Tysarowki M , Um H , Zhang Y , Shah K , Douglas A , Matassa D 
Published: October 2021

Abstract

Background
Statins are the cornerstone of primary and secondary prevention of atheroscleoric cardiovascular disease (ASCVD). Our previous retrospective analysis of 1042 consecutive patient encounters at a large urban academic institution found that one in five patients were not prescribed an appropriate statin therapy. These patients tended to be younger, of Black race, and met statin-eligibility solely via a 10-year ASCVD risk score ≥7.5%. Only one-third of patients had follow-up cholesterol levels ordered to monitor treatment efficacy.

Purpose
To improve adherence to cholesterol guidelines at our academic institution.

Methods
We implemented multiple interventions over a four-month period to support clinical decision making of guideline directed statin therapy: a) development of an online interactive tool, b) physician education on updated cholesterol guidelines and utilization of the tool, c) display of guideline summary in the workspace, and d) a documentation reminder in the electronic health record. We randomly selected encounter dates, from which 622 consecutive patient visits were analyzed. The primary outcome measures were: prescription rates of statins, documentation of a 10-year ASCVD risk score, and follow-up cholesterol levels ordered to monitor treatment efficacy.

Results
Out of the 622 patients, 232 met statin indication. In this post-intervention group, statin prescriptions rates improved when compared to the pre-intervention group (90.5% vs 82.3%, p=0.006). Among the patients who met statin indication solely via a 10-year ASCVD risk score ≥7.5%, there was an increase in documentation of the calculated 10-year ASCVD risk score (72.3% vs 57.8%; p=0.039) and in statin prescription rate (90.8% vs 67.6%; p&lt;0.001). In addition, there was an increase in follow-up cholesterol levels ordered in all patients included in our study who met statin indication (64.1% vs 33.3%; p&lt;0.001).

Conclusion
Our study showed higher rates of statin prescription, 10-year ASCVD risk score documentation, and treatment monitoring after multiple interventions, including an easily accessible online interactive tool, at a large urban academic institution.

Funding Acknowledgement
Type of funding sources: None. Statin Prescription Rates
Racial disparities of internet access in the united states: a multiyear analysis of the national behavioral risk factors surveillance system
Authors: Ahmed A I , Soliman A , Han Y , Qureshi W T , Al-Mallah M H 
Published: October 2021

Abstract

Introduction
The COVID 19 pandemic has led to a dramatic rise in the use of Telehealth. Studies have shown racial/ethnic disparities in internet access, a basic prerequisite for telehealth. However, little is known on the extent of this “digital divide” amongst racial minorities with cardiovascular comorbidities.

Purpose
To investigate racial disparities in internet access amongst those with cardiovascular diseases and risk factors, and explore the degree to which this exists amongst those with different levels of comorbidities.

Methods
Behavioral Risk Factors Surveillance System data from the years 2013–2017, during which survey respondents were asked the main outcome of interest (“Have you used the internet in the past 30 days”) were pooled. Respondents were included if they responded yes to questions on selected cardiovascular diseases and risk factors of interest. Multivariable logistic regression was used to analyze the odds of internet use by racial groups adjusting for several socioeconomic factors.

Results
There were a total of 1,478,214 individuals representing 150,235,244 million adults (non-Hispanic Blacks 11.31% and Hispanics 13.75%). Hispanics and Non-Hispanic Blacks reported the lowest prevalence of internet use (66.1% and 64.4% respectively) compared to Non-Hispanic Whites (81.9%). On regression analysis, racial minorities consistently reported lower rates of internet use, averaging 50% lower odds compared to non-Hispanic Whites. Results remained statistically significant even after controlling for several sociodemographic variables.

Conclusion
Using a large nationally representative cohort, we demonstrated differences in internet access amongst racial minorities and those with multiple comorbidities, placing them at distinct disadvantage with access to telecare. Our study adds to a growing body of literature that shows the disproportionate impact of the pandemic on minorities and calls for a concerted effort to reduce disparities in healthcare delivery.

Funding Acknowledgement
Type of funding sources: None.
Assessment of ECG during hybrid comprehensive telerehabilitation in heart failure patients – subanalysis of the TELEREHabilitation in heart failure patients – TELEREH-HF randomized clinical trial
Authors: Piotrowicz E , Orzechowski P , Zareba W , Glowczynska R , Szalewska D , Pluta S , Irzmanski R , Kalarus Z , Banach M , Opolski G , Pencina M , Kowalik I , Piotrowicz R 
Published: October 2021

Abstract

Background
Exercise training in heart failure (HF) patients (pts) should be monitored to ensure patients safety. That is why we use ECG telemonitoring during hybrid comprehensive telerehabilitation (HCTR).

Purpose
Assessment of frequency of cardiac arrhythmias during telerehabilitation in HF patients.

Methods
The present analysis formed part of TELEREH-HF multicenter, randomized (1:1), controlled trial that enrolled 850 HF pts with New York Heart Association class I, II, or III and left ventricular ejection fraction (LVEF) of 40% or less. Patients were randomized 1:1 to 9 week HCTR plus usual care or usual care only. This subanalysis focuses on 386 pts (aged 62±11 years, LVEF 31±7%) randomized to HCTR based on Nordic walking training 5 times/week. HCTR was tele-monitored with an EHO mini device adjusted to record 16-second fragments of ECG (from three precordial leads) and to transmit the data via mobile phone network to the monitoring center. The timing of automatic ECG recording were pre-set and coordinated with exercise training.

Results
In all, 16622 HCTR sessions were registered and 66488 ECGs transmitted fragments were evaluated (four 16-second recording per patient per one session were recorded). A sinus rhythm was present in 320 (83%) pts, permanent atrial fibrillation in 66 (17%) pts. Assessment of ECG during HCTR procedure is presented in Table 1.

Conclusions
Telerehabilitation in heart failure patients is safe without evidence for symptomatic cardiac arrhythmias requiring discontinuation of training.
Non-sustained ventricular tachycardia and paroxysmal atrial fibrillation episodes were rare but have required adjustment of the telerehabilitation regimen.
The most common arrhythmias were ventricular and supraventricular premature beats.
These arrhythmias did not result in any changes in rehabilitation and therapy regimens.

Funding Acknowledgement
Type of funding sources: Other. Main funding source(s): The National Centre for Research and Development, Warsaw, Poland.
Gene and protein expression profiles of selected molecular targets mediating electrophysiological function in pgc-1-alpha deficient murine ventricles
Authors: Saadeh K , Chadda K R , Ahmad S , Valli H , Nanthakumar N , Fazmin I T , Edling C E , Huang C L H , Jeevaratnam K 
Published: October 2021

Abstract

Background
The risk of cardiac arrhythmias increases significantly in patients with metabolic disorders such as obesity and diabetes mellitus. The mechanisms linking metabolic conditions and electrophysiological changes underlying cardiac arrhythmias remain poorly understood. Central to the energetic abnormalities characterising these conditions is mitochondrial dysfunction. Peroxisome proliferator activated receptor-γ (PPARγ) coactivator-1 (Pgc-1) regulate mitochondrial biogenesis and function. Their expression is impaired in metabolic disorders. Murine Pgc-1α−/− hearts replicate disrupted mitochondrial function and model the associated pro-arrhythmic electrophysiological abnormalities.

Purpose
To explore the molecular mechanisms underlying the pro-arrhythmic electrophysiological changes in the Pgc-1α−/− murine model of mitochondrial dysfunction.

Methods
Ventricular tissue samples were obtained from aged (&gt;12 months) wild-type (WT) and homozygous Pgc-1α−/− mice. Quantitative PCR was used to examine transcription of 60 genes underlying cardiac tissue excitability, western blotting was used to examine expression of proteins relating to cardiac conduction velocity, and histological analysis was used to examine cardiac tissue fibrotic change.

Results
qPCR analysis implicated downregulation of genes related to Na+-K+ ATPase activity (Atp1b1), surface Ca2+ entry (Cacna1c), action potential repolarisation (Kcnn1), autonomic function (Adra1d, Adcy4, Pde4d, Prkar2a), and morphological properties (Myh6, Tbx3) in murine Pgc-1α−/− ventricles. Western blotting revealed reduced NaV1.5 but normal Cx43 expression. Histological analysis revealed increased tissue fibrosis in the Pgc-1α−/− ventricles.

Conclusions
These results identified molecular mechanisms underlying previously reported electrophysiological abnormalities such as impaired ventricular activation and reduced conduction velocity in arrhythmic substrate associated with Pgc-1 deficiencies. Results also correlated with earlier findings including functional effects of elevated Ca2+ concentrations. The present findings clarify possible mechanisms by which mitochondrial dysfunction affects electrophysiological function and identify potential pharmacological targets for anti-arrhythmic therapy.

Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): Medical Research Council; the Wellcome Trust; British Heart Foundation
Investigations regarding the role of NOS1AP in the heart using a conditional overexpression mouse model
Authors: Jaensch M , Trum M , Williams T , Schmitt J , Schuh K , Qadri F , Maier L , Bader M , Ritter O 
Published: October 2021

Abstract

Background
35.3% of deaths in 2019 in Germany are caused by cardiovascular diseases (Destatis). 95% of these people were 60 years and older. To increase survival rate in elderly patients we investigate the relevance of altered expression of neuronal nitric oxide synthase 1 (NOS1) adaptor protein (NOS1AP) acting as an L-type calcium channel (CaV1.2) modulator via directing NOS1 to CaV1.2 on cardiac electrophysiology. Genome-wide association studies have linked genetic polymorphisms in NOS1AP to variations in QT interval duration (QTc). The QT interval reflects ventricular de- and repolarization. It may predispose individuals to ventricular tachycardia and sudden cardiac death (SCD) if prolonged, shortened or otherwise unregularly. In addition, about 20% of families with a clinically proven diagnosis of long QT syndrome (LQTS) host no mutation in any of the 16 associated genes.

Methods and results
Transgenic mice with conditional overexpression of NOS1AP in cardiac myocytes were used as model organism. We confirmed the interaction of NOS1AP with NOS1 and CaV1.2. Electrocardiography in NOS1AP overexpressing mice showed atrial and ventricular tachycardia both spontaneously and upon programmed stimulation associated with a significant decrease in QTc. Heart rates in NOS1AP overexpressing mice were similar to non-induced animals. Survival was significantly reduced (only 60% after 12 weeks vs. 100% in non-induced mice). Induced QTc alterations and accompanied deaths subsided upon re-administration of doxycycline.
Whole-cell patch-clamp measurements in isolated adult ventricular myocytes were performed and action potential duration at 90% of repolarization (APD90) was significantly reduced in induced transgenic NOS1AP overexpressing mice compared to control littermates.
In addition, we investigated the functional effect of the human SNP rs16847548 (T/C) located within the NOS1AP promoter. The SNP was found to decrease the transcriptional activity of NOS1AP in vitro and therefore, potentially leading to a decrease in NOS1AP expression in humans.

Conclusion
Myocardial overexpression of NOS1AP leads to short QT syndrome with increased susceptibility to atrial and ventricular arrhythmias and cardiac death. In accordance, APD90 is significantly shortened in overexpressing animals. The human SNP rs16847548, which is located in the promoter region of NOS1AP, results in a reduced NOS1AP promoter activity in vitro, hereby providing an explanation for the frequently published elongation of QT intervals. In summary, not only mutations in ion channels themselves but also genetic alterations in the expression of ion channel modulators such as NOS1AP, have an impact on QTc and arrhythmogenesis and represent a promising therapeutic target for LQTS patients.

Funding Acknowledgement
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Gesundheitscampus Brandenburg (MWFK)