bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incorporating AI into cardiovascular diseases prevention - insights from Singapore
Authors: Dalakoti M , Wong S , Lee W , Lee J , Ngiam K Y , Foo R 
Published: June 2024

Abstract

Introduction
Improved upstream primary prevention of cardiovascular disease (CVD) would enable more individuals to lead lives free of CVD. However, there remain gaps in provision of CVD primary prevention, namely a) addressing social determinants of health in an equitable way and b) enabling convenient and accessible CVD primary prevention across the spectrum of primary to specialist care.

Methods
A battle map for CVD prevention- CardioSight.
Using the data informatics capabilities at the National University Health System (NUHS), Singapore, empowered by the Endeavour AI system, and combined large language model (LLM) tools, our team has created a real-time dashboard able to capture and showcase information on cardiovascular risk factors at both individual and geographical level- CardioSight. Being Streambased AI, the dashboard can interface in real time with our healthcare cluster’s Electronic Medical Records System (EMR) to achieve live data feeds for real time analysis and visualisation (Figure 1).
Real time data is pinned on a geographical heat map alongside nearest primary care providers, providing a battle map to target individuals at various levels of cardiovascular risk. Further insights such as medication records and data on area-level socioeconomic determinants allow a whole-of-systems approach to promote healthcare delivery, while also allowing for outcomes to be tracked effectively.

Results
Figure 2 shows the Glycated hemoglobin (HBA1c) and low-density lipoprotein- C (LDL-C) values of 93,200 patients with diabetes managed in NUHS from 1/6/23 to 31/10/23, mapped to where they live in Singapore. Light green spots represent HBA1c &lt; 7, yellow spots represent HBA1c 7-10%, and red spots represent HBA1c &gt; 10%. Diamonds represent LDL-C 1.8 to &lt;= 2.6, up-pointing triangles represent LDL-C 2.6 to &lt;= 3, and down-pointing triangles represent LDL-C &gt; 3. 13,728 (14.7%) patients have concurrently HBA1c &gt; 7% and LDL-C &gt; 1.8.

Discussion
A significant proportion of the population of diabetics has risk factors not at target. There is also a geographical overrepresentation of some of these patients in certain areas. These would represent key groups and individuals to deliver preventive interventions.

Conclusion
In its complete form, CardioSight supports the execution of personalised yet high-level preventive cardiology initiatives within our healthcare system. Importantly, knowledge of baseline epidemiology of CVD and risk factors will allow assessment of the effectiveness of ongoing interventions over not just a geographical location but also across a timeline. Fig 1.NUHS AI Tribrid Architecture Fig 2.Hba1c, LDL-C control in diabetics
Implementation and willingness-to-pay of a hybrid remote training programme in a population with obesity
Authors: Falter M , Kizilkilic E , Scherrenberg M , Tukanov E , Gerits M L , Marneffe W , Sinnaeve P R , Dendale P 
Published: June 2024

Abstract

Background/Introduction
Remote training has demonstrated effectiveness in multiple trials. Implementation trials are the next step to achieve this as standard of care.

Purpose
The pilot study is a next step in our centre’s road towards implementation of cardiac rehabilitation. It is performed in a relatively young, obese population without known cardiac disease. The primary aim of the study was to assess implementation parameters.

Methods
This is a single-arm implementation study in 45 patients in the setting of an on-site training programme. Patients received a FitBit Charge 5, step count and heart rate "zone minutes" goals and follow-up by a physiotherapist. The program consisted of 3 months of hybrid training and 3 months of remote training. A monthly 6-minute-walking-test (6MWT) was performed remotely by use of the patient’s smartphone.

Results and discussion
Results of the first 3 months (hybrid training) are discussed. Results are shown in Table 1. Overall, acceptance and satisfaction were favorable. 6MWT results are depicted in Figure 1. At Month 3, we observed a sustained beneficial effect on physical fitness.

Conclusion
Our hybrid training intervention was successfully implemented, with acceptable willingness to pay, and durable benefits in physical fitness and weight loss.
Impact of behavioral and social factors compared to conventional risk factors in the development of coronary artery disease in Switzerland: SWISSHEART
Authors: Durandi V E , Van Der Stouwe J G , Biniasch S , Djurdjevic A , Burkard T , Yuzuak B , Jordan F , Haegele M , Storni M , Pfister O 
Published: June 2024

Abstract

Background
Conventional risk factors for coronary artery disease (CAD) are well established and are key for cardiovascular prevention and risk stratification. In addition to conventional risk factors, behavioral and social factors may influence CAD risk, but their impact remains ill defined.

Purpose
To determine the impact of behavioral, social and conventional cardiovascular (CV) risk factors on CAD risk in Switzerland.

Methods
We used a 1:3 case-control design including 1776 individuals with CAD from the Swiss Secondary Prevention and Rehabilitation Registry (SwissPR,) and 5328 age- and sex-matched control subjects without established CAD from the Swiss National Health Survey. All individuals were recruited between January 2017 and September 2023. Data for conventional cardiovascular risk factors (arterial hypertension, diabetes mellitus, dyslipidemia, smoking status and BMI) were obtained from patient charts, patient history and questionnaires. Data for behavioral factors (dietary habits, alcohol consumption, physical activity) and social factors (marital status, children) were collected using standardized questionnaires. Odds ratios for the association of individual factors with CAD were calculated using univariate and multivariate logistic regression models.

Results
In average, patients were 62 years old, predominantly male (79%) and of European origin (99%). Among conventional risk factors dyslipidemia (OR 5.7; 95% CI, 5.02-6.47) showed the strongest independent association with CAD followed by arterial hypertension (OR 2.66; 95% CI, 2.34-3.03), diabetes mellitus (OR 1.95; 95% CI, 1.63-2.34) and a history of smoking (OR 1.57; 95% CI, 1.38-1.78). Among behavioral factors intense physical exercise (OR 0.75; 95% CI, 0.7-0.79) and regular alcohol consumption (OR 0.95; 95% CI, 0.91-0.98) were inversely associated with CAD but dietary habits including fish, meat, fruit and vegetable consumption had no independent association with CAD risk. Being single (OR 2.54; 95% CI, 1.79-3.59), divorced (OR 1.9; 95% CI, 1.42-2.51) or widowed (OR 1.66; 95% CI, 1.08-2.46) significantly increased the odds for CAD compared to being married but having children had no independent association with CAD.

Conclusion
These results establish a strong association between marital status with CAD and underpin the protective role of intense physical activity. Conventional CV risk factors remain the main drivers of CAD risk with dyslipidemia and arterial hypertension accounting for most of the risk.
Data mining insights: mapping patient journeys and guiding complementary test prescriptions in atrial fibrillation
Authors: Flores Soler J , Canadas-Godoy V , Garcia Gonzalez F , Llorente Sanz L , Luaces Mendez M , Bengoa Terrero C , Perez-Castellano N , Perez-Villacastin Dominguez J 
Published: June 2024

Abstract

Introduction
Atrial fibrillation (AF), a prevalent cardiac arrhythmia, often leads to an extensive array of complementary tests and treatments. While crucial for effective treatment, the frequent prescription of various complementary tests often leads to an excessive burden on healthcare resources, resulting in prolonged waiting times and potential mismanagement of patient care. Addressing this challenge necessitates a strategic approach to understanding and optimizing test prescriptions. Through the lens of data mining, to dissect these complexities in AF patient management. The study's objective is to employ data mining techniques to trace the trajectory of patients with atrial fibrillation and analyze the prescription of complementary tests across various departments of a tertiary hospital.

Methods
We employed advanced Big Data preprocessing, data mining, process mining, and business intelligence methods. Data was analysed from 2016 to 2020, including clinical and administrative records on hospital discharges, complex procedures, emergency care, and speciality practices. Patients with primary or secondary atrial fibrillation (AF) diagnosis were selected. Data from the Basic Minimum Set of Data (BMSD), encompassing discharge information and Cardiology outpatient resources was refined to remove inconsistencies and duplicates. We then streamlined this into smaller, more manageable subsets. Our focus was mapping AF patient trajectories between cardiology service (cardiology group) and other hospital services (others groups) and prescribed complementary tests (CT) like transthoracic and transesophageal echocardiograms (TTE and TEE, respectively), Holter electrocardiograms (H-ECG), and cardiac ablations, specifically, pulmonary vein isolation. Integrating these subsets and applying data transformation and reduction techniques created a unified dataset for in-depth analysis using process mining and business intelligence tools.

Result
After analyzing 71014 individual BMSD records, we quantified the visits to cardiology consultations, arrhythmia clinics, CT prescribed from cardiology services or not to perform TTE, Holter-ECG, and ablation from 10742 unique patients from 2016 to 2020: 28276 TTE and TEE were perform, 60,82% were prescribed from the other hospital services, the rest from cardiology; 6933 Holter ECG were prescribed, mostly from other services different than cardiology (67,7%) 2274 cardiac ablation were identified coming from other services 72,3%.

Conclusions
Most subjects involved in the AF patient journey and the Complementary tests prescribed come mainly from different services than cardiology. Healthcare strategies should involve other departments to improve results in terms of delays, health economics and clinical outcomes.
Predictors of worsening kidney function and their relation to SGLT2 inhibitor dapagliflozin administration in type 2 diabetes mellitus patients with chronic heart failure
Authors: Berezin A E , Lichtenauer M , Hoppe U , Berezina T A , Obradovic Z , Berezin O O 
Published: June 2024

Abstract

Background
Sodium-glucose cotransporter 2 inhibitors (SGLT2i) had a favorable impact on the kidney function in heart failure (HF) patients, while there is no clear evidence of what factors predict this effect. The aim of the study was to identify plausible predictors for kidney function outcome among HF patients and investigate their association with SGLT2i.

Methods
We prospectively enrolled 480 patients with established type 2 diabetes mellitus (T2DM) and concomitant chronic HF I-IV New York Heart Association functional classes and followed them for 52 weeks. In the study, we determined the kidney outcome as a composite of a sustained declined in estimated glomerular filtration rate by 40% from baseline, or newly end-stage of kidney disease, or kidney replacement therapy. The relevant medical information, measurement of the biomarkers (N-terminal natriuretic pro-peptide, irisin, apelin, adropin, C-reactive protein, tumor necrosis factor-alpha) were collected at baseline and at the end of the study.

Results
The composite kidney outcome was detected in 88 (18.3%) patients of entire population. Amongst these individuals, 51 patients demonstrated declined in eGFR by 40% from baseline at the end of the follow-up period, 35 individuals had newly diagnosed ESKD and consequently two patients required kidney replacement therapy (hemodialysis). All patients received guideline-recommended optimal therapy, which was adjusted to phenotype / severity of HF, CV risk and comorbidity profiles and fasting glycaemia. The changes of the biomarkers levels during the dapagliflosin administration are reported Figure 1. We used Received Operation Curve analysis to identify the well-balanced cut-off points for the biomarkers (Figure 2). The multivariate logistic regression revealed that use of SGLT2i (OP = 0.92; p = 0.048), baseline serum levels of irisin less 4.50 ng/mL (OR = 1.51; p = 0.001), adropin less 2.10 ng/mL (OR = 1.15; p = 0.001) along with increase in the levels of these biomarkers less 15% (OR = 1.60; p = 0.001) and less 6% (OR = 1.21; p = 0.001) respectively retained an independent predictor for composite kidney end-point. We noticed that irisin serum levels less 4.50 ng/mL at the baseline and the increase in irisin less 15% added more valuable predictive information than the reference variable. Yet, the combination of irisin less 4.50 ng/mL at the baseline and the increase in irisin serum levels less 15% (AUC = 0.91; 95% CI = 0.87–0.95) improved discriminative value of each biomarker alone.

Conclusions
we suggest that low levels of irisin and its inadequate increase during administration of SGLT2i are promising predictors for unfavorable kidney outcome among T2DM patients with concomitant HF. The dynamic changes of the biomarkers ROC curve analysis
Red cell distribution width - prognostic parameter that could be used in heart failure patients
Authors: Catana A 
Published: June 2024

Abstract

Background
Heart failure (HF) is one of the cardiovascular diseases with high mortality and morbidity and high hospitalization rate, associated with a high degree of disability in terms of quality of life, by reducing exercise capacity and limiting the possibilities to make individual physical effort.
Although diagnostic and treatment methods are increasingly complex, mortality and hospitalization rates are still very high, which equals a large consumption of financial resources.

Purpose
Identifying a potential prognostic parameter could represent in future a salutary solution for prophylactic intervention in the management of patients with decompensated HF.
Through the present study, I aimed to identify a potential predictive factor by means of which the risk of rehospitalization and mortality in the first year after the last discharge can be evaluated right from the admission of a patient with decompensated HF.
The parameter I set out to research is red cell distribution width (RDW), a parameter easy to obtain by collecting blood samples, that is included in any usual blood count, and expressed in percentages (%), and its normal values are between 12-15%.
The data from the current medical literature regarding the prognostic impact of RDW in the population of patients with HF are minimal, being a topic poorly explored.

Methods
The research was carried out in a retrospective manner on a number of 260 patients with HF, the parameter of interest being RDW.
The main objective of my study was to determine if RDW could represent o possible prognostic parameter in HF patients, by exploring if there is a correlation between its increased values and 3 months, 6 months rehospitalization, and 1 year death.
The statistical analysis was based on the logistic regression model by which I conceived a mathematical formula represented by the following model: Score (of event occurrence) = event estimation coefficient + RDW estimation coefficient * RDW value (Yi= β0+β1Xi+εi ).
To convert the value of the score obtained by applying the above-mentioned formula into probabilities, I applied the following equation: p=1/1+e-score.

Results
Based on the logistic regression model, the statistical results revealed that HF patients with high RDW (at least 14%) had a higher probability of being readmitted at 3 months, 6 months, and of dying at 1 year, the model being considered statistically significant at a p-value below 0.05.

Conclusions
Using logistic regression models, the results of my study revealed that certain negative events in patients with HF such as rehospitalization and 1-year death, can be predicted based on the RDW value, therefore we can consider RDW as a future prognostic predictor in patients with HF. 3-month rehospitaliztion based on RDW 6-month rehospitaliztion based on RDW
Effects of inspiratory muscle training on NT-proBNP level, functional exercises capacity and quality of life in patients with cardiac resynchronization therapy: a pilot study
Authors: Erturk N , Yerlikaya M G , Sayin M R 
Published: June 2024

Abstract

Introduction
It is known that cardiac rehabilitation has improvement effects on exercise capacity and healthy quality of life in patients receiving Cardiac Resynchronization Therapy. However, we did not find a study examining the effect of inspiratory muscle strength training (IMT) on NT-ProBNP, exercise capacity, and health-related quality of life in patients with CRT. Therefore, we planned this study as a pilot study.

Objective
To test the effectiveness of inspiratory muscle training (IMT) on NT-ProBNP level, functional exercise capacity, and quality of life in patients with cardiac resynchronization therapy (CRT).

Methods
Ten individuals with CRT (age: 62.5±12.7; man 60%; NYHA:2; LVEF: 43.5±11.3) were included in this study. The patients underwent a 12-week inspiratory muscle training program (30% of their maximal inspiratory pressures, MIP) using a threshold loading device for 30 minutes per day, seven days per week at home. All patients underwent echocardiographycal examination, assessement of NT-proBNP level, assessed of functional exercises capacity by a 6-minute walk test, and evaluation of quality of life by the Nottingham Health Profile (NHP) questionnaire.

Results
After the IMT, there was no significantly improvement in the LVEF levels (p&gt;0,005). There was a significant decrease in the NT-ProBNP level of 777.6 ng/L ( 1801 to 1103 ng/L, p=0.005) and a significant increase in the 6MWT of 64.21meters (408.5 to 472.7, p=0.005), total NHP score of -121.55 points (244.31 to 122.76, p=0.009).

Conclusions
The 12-week IMT program was able to improve the NT-ProBNP level, functional exercise capacity, and quality of life levels in patients with CRT. The results suggest that IMT can be added to CRT patients' CR program. Randomized controlled studies are needed to investigate the effects of IMT.
Pulse pressure amplification as a predictor of cardiovascular risk in shift workers: an analysis based on PARTAGE
Authors: Abraham F , Leao G , Beltrao C , Gusmao W D , Paiva A , Mota M , Moreno C 
Published: June 2024

Abstract

Background/Introduction
Shift workers are known to have a higher risk of cardiovascular diseases, however there is no precise description of the etiology of these problems. One of the hypotheses refers to the increase in blood pressure due to desynchronization of biological rhythms, in view of work activity, at a time when biologically they should be at rest, which deregulates the endogenous mechanisms of pressure control and vascular elasticity. The Predictive Values of Blood Pressure and Arterial Stiffness in Institutionalized Very Aged Population (PARTAGE) study aimed to evaluate the value of blood pressure and pulse pressure amplification as a predictor of cardiovascular risk. According to the study, when pulse pressure amplification was greater than 10% in the elderly population there was an association with a higher risk of mortality and cardiovascular outcomes.

Purpose
To evaluate whether in shift workers exposed to night work there is an early increase in pulse pressure amplification, as a predictor of cardiovascular risk.

Methods
It was a quantitative, prospective and cross-sectional study. The participants visited collection of sociodemographic data, health conditions, lifestyle habits, work schedules using validated questionnaires and measurements of peripheral blood pressure (PBP) and central blood pressure (CBP), using the Arteris AOP® equipment. Pulse pressure amplification (PPA) was obtained using the following formula: PPA= 100 x (PBP – CBP) / CBP, values are expressed as a percentage.

Results
83 participants were included, with a mean age of 44.4 years, of which 76 (91.6%) were female and 7 (8.4%) were male, only 31 (37.3%) practiced physical activity, 81 (97.6%) were not smokers and 40 (48.2%) were not alcoholics. The average blood pressure values were: PBP 112x80mmHg, CBP 105x81mmHg and PPA was an average of 6.81%. In the univariate regression analysis, no associations were observed between PPA and night work (β = 0.35; p = 0.192) considering adjustments for sex and age, factors that directly influence the central parameters. However, analyzing individually, a total of 7 (8.43%) of shift workers had PPA above the value considered risk for cardiovascular outcomes. Conclusion(s): In the studied population there was no association between PPA and night work, but in some individuals the PPA values were already above the recommended level, that is, they had cardiovascular risk, indicating the need for further studies.
Blood pressure effect of semaglutide in patients with hypertension: an individual patient data analysis of randomised controlled trials
Authors: Kennedy C , Hayes P , Cicero A F G , Dobner S , Le Roux C , Mcevoy J W , Zgaga L , Hennessy M 
Published: June 2024

Abstract

Background
Randomised clinical trials of patients with obesity treated with semaglutide (STEP trials) reported clinically significant reductions in blood pressure (BP). The mean baseline BP of trial participants was in the normal range. The effect of semaglutide on patients with hypertension has yet to be elucidated.

Purpose
To determine the blood pressure effect of semaglutide in patients with uncontrolled BP at randomization (baseline BP).

Methods
Individual participant data from three randomised placebo-controlled trials examining the effect of semaglutide 2.4mg on body weight (STEP 1, 3 and 4) over 68 weeks were included (the Cohort). Participants with systolic BP (SBP) &gt;140mmHg at baseline were identified (HTN140 group). The effect of semaglutide on SBP estimated by ANCOVA with baseline SBP as a covariate. Adjustments of antihypertensive treatment (escalated if treatment started or dose increased; de-escalated if treatment stopped or dose decreased) were assessed using logistic regression analysis adjusted for baseline SBP.

Results
3136 participants were included in the pooled analysis. 397 (13%) had a baseline SBP &gt;140mmHg (semaglutide arm, n=257; placebo arm, n=140). The baseline BP and body weight of the HTN140 group were comparable between treatment arms [Table 1]. The effect of semaglutide on SBP was estimated as -4.09mmHg (95% CI -7.12 to -1.06, p&lt;0.05). This effect was comparable to that for the Cohort (-4.95mmHg; 95% CI -5.86 to -4.05, p&lt;0.05). The observed SBP reduction was 17.41mmHg for those in the semaglutide arm and 12.57mmHg in the placebo arm (Figure 1). This large in-trial effect was partly due to the escalation of anti-hypertensive treatment in 11.3% and 14.3% of participants randomized to semaglutide and placebo respectively (OR 0.76; 95% CI 0.39 to 1.49, p=0.42).

Conclusions
The effect of semaglutide on SBP was not greater in patients with uncontrolled SBP at randomization compared to the Cohort of all patients in STEP 1, 3, 4. The adjustment of anti-hypertensive medications contributed to a large observed reduction in SBP for both trial arms. This demonstrates the Hawthorne effect during these trials. Effect on SBP