scholarly journals Development and validation of two SCORE-based cardiovascular risk prediction models for Eastern Europe: a multicohort study

2020 ◽  
Vol 41 (35) ◽  
pp. 3325-3333 ◽  
Author(s):  
Taavi Tillmann ◽  
Kristi Läll ◽  
Oliver Dukes ◽  
Giovanni Veronesi ◽  
Hynek Pikhart ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prediction Models ◽  
Validation Cohort ◽  
European Countries ◽  
Eastern European ◽  
Risk Prediction Models ◽  
Derivation Cohort ◽  
Score Model ◽  
Eastern European Countries

Abstract Aims Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model. Methods and results We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02–0.11] in the derivation cohort and 0.14 (95% CI 0.04–0.25) in the validation cohort. Conclusion Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy.

P3429A novel prediction model for mortality after cardiac surgery using institutional case volume

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
S Lee ◽  
J B Park ◽  
Y J Cho ◽  
H G Ryu ◽  
E J Jang
Keyword(s):  
Cardiac Surgery ◽  
Hospital Mortality ◽  
Risk Prediction ◽  
Prediction Models ◽  
Validation Cohort ◽  
Mortality Data ◽  
P Value ◽  
Case Volume ◽  
Risk Prediction Models ◽  
Derivation Cohort

Abstract Purpose A number of risk prediction models have been developed to identify short term mortality after cardiovascular surgery. Most models include patient characteristics, laboratory data, and type of surgery, but no consideration for the amount of surgical experience. With numerous reports on the impact of case volume on patient outcome after high risk procedures, we attempted to develop a risk prediction models for in-hospital and 1-year mortality that takes institutional case volume into account. Methods We identified adult patients who underwent cardiac surgery from January 2008 to December 2017 from the National Health Insurance Service (NHIS) database by searching for patients with procedure codes of coronary artery bypass grafting, valve surgery, and surgery on thoracic aorta during the hospitalization. Study subjects were randomly assigned to either the derivation cohort or the validation cohort. In-hospital mortality and 1-year mortality data were collected using the NHIS database. Risk prediction models were developed from the derivation cohort using Cox proportional hazards regression. The prediction performances of models were evaluated in the validation cohort. Results The models developed in this study demonstrated fair discrimination for derivation cohort (N=22,004, c-statistics, 0.75 for in-hospital mortality; 0.73 for 1-year mortality) and acceptable calibration in the validation cohort. (N=22,003, Hosmer-Lemeshow χ2-test, P=0.08 and 0.16, respectively). Case volume was the key factor of mortality prediction models after cardiac surgery. (50≤ x <100 case per year. 100≤ x <200 case per year, ≥200 case per year are correlated with OR 3.29, 2.49, 1.85 in in-hospital mortality, 2.76, 1.99, 1.69 in 1-year mortality respectively, P value <0.001.) Annual case volume as risk factor Variables In-hospital mortality 1-year mortality OR (95% CI) p-value OR (95% CI) p-value Annual case-volume (reference: ≥200) – – 100–200 1.69 (1.48, 1.93) <0.001 1.85 (1.58, 2.18) <0.001 50–100 1.99 (1.75, 2.25) <0.001 2.49 (2.15, 2.89) <0.001 <50 2.76 (2.44, 3.11) <0.001 3.29 (2.85, 3.79) <0.001 OR: Odds ratio; CI: confidence interval; Ref: Reference. Discrimination and calibration Conclusion We developed and validated new risk prediction models for in-hospital and 1-year mortality after cardiac surgery using the NHIS database. These models may provide useful guides to predict mortality risks of patients with basic information and without laboratory findings.

scholarly journals The Admit-AF risk score: a clinical risk score for predicting hospital admissions in patients with atrial fibrillation

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
P Meyre ◽  
S Aeschbacher ◽  
S Blum ◽  
M Coslovsky ◽  
J.H Beer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
High Risk ◽  
Risk Score ◽  
Hospital Admissions ◽  
Validation Cohort ◽  
Funding Source ◽  
Prediction Tool ◽  
Derivation Cohort

Abstract Background Patients with atrial fibrillation (AF) have a high risk of hospital admissions, but there is no validated prediction tool to identify those at highest risk. Purpose To develop and externally validate a risk score for all-cause hospital admissions in patients with AF. Methods We used a prospective cohort of 2387 patients with established AF as derivation cohort. Independent risk factors were selected from a broad range of variables using the least absolute shrinkage and selection operator (LASSO) method fit to a Cox regression model. The developed risk score was externally validated in a separate prospective, multicenter cohort of 1300 AF patients. Results In the derivation cohort, 891 patients (37.3%) were admitted to the hospital over a median follow-up 2.0 years. In the validation cohort, hospital admissions occurred in 719 patients (55.3%) during a median follow-up 1.9 years. The most important predictors for admission were age (75–79 years: adjusted hazard ratio [aHR], 1.33; 95% confidence interval [95% CI], 1.00–1.77; 80–84 years: aHR, 1.51; 95% CI, 1.12–2.03; ≥85 years: aHR, 1.88; 95% CI, 1.35–2.61), prior pulmonary vein isolation (aHR, 0.74; 95% CI, 0.60–0.90), hypertension (aHR, 1.16; 95% CI, 0.99–1.36), diabetes (aHR, 1.38; 95% CI, 1.17–1.62), coronary heart disease (aHR, 1.18; 95% CI, 1.02–1.37), prior stroke/TIA (aHR, 1.28; 95% CI, 1.10–1.50), heart failure (aHR, 1.21; 95% CI, 1.04–1.41), peripheral artery disease (aHR, 1.31; 95% CI, 1.06–1.63), cancer (aHR, 1.33; 95% CI, 1.13–1.57), renal failure (aHR, 1.18, 95% CI, 1.01–1.38), and previous falls (aHR, 1.44; 95% CI, 1.16–1.78). A risk score with these variables was well calibrated, and achieved a C-index of 0.64 in the derivation and 0.59 in the validation cohort. Conclusions Multiple risk factors were associated with hospital admissions in AF patients. This prediction tool selects high-risk patients who may benefit from preventive interventions. The Admit-AF risk score Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): The Swiss National Science Foundation (Grant numbers 33CS30_1148474 and 33CS30_177520), the Foundation for Cardiovascular Research Basel and the University of Basel

scholarly journals The Landscape of Mucopolysaccharidosis in Southern and Eastern European Countries: A Survey from 19 Specialistic Centers.

2021 ◽  
Author(s):  
Anna Tylki-Szymańska ◽  
Zsuzsanna Almássy ◽  
Violetta Christophidou Anastasiadou ◽  
Daniela Avdjieva-Tzavella ◽  
Ingeborg Barisic ◽  
...  
Keyword(s):  
European Countries ◽  
Eastern European ◽  
Survey Analysis ◽  
Lysosomal Storage ◽  
European Regions ◽  
Enzyme Replacement ◽  
European Guidelines ◽  
Mps Iva ◽  
Eastern European Countries

Abstract Background: Mucopolysaccharidoses (MPS) are a group of lysosomal storage disorders caused by defects in genes coding for different lysosomal enzymes which degrade glycosaminoglycans. Impaired lysosomal degradation causes cell dysfunction leading to progressive multiorgan involvement, disabling consequences and poor life expectancy. Enzyme replacement therapy (ERT) is now available for most MPS types, offering beneficial effects on disease progression and improving quality of life of patients. The landscape of MPS in Europe is not completely described and studies on availability of treatment show that ERT is not adequately implemented, particularly in Southern and Eastern Europe. In this study we performed a survey analysis in main specialist centers in Southern and Eastern European countries, to outline the landscape of disease management in the region and understand ERT implementation, with particular reference to MPS IVA.Results: 19 experts from 14 Southern and Eastern European countries in total responded to the survey. Results outlined a picture of MPS management in the region, with a high number of MPS patients managed in the centers and a high level of care. MPS II was the most prevalent followed by MPS IVA, with a particular high number of adult patients. The study particularly focused on management and treatment of MPS IVA patients. Adherence to current European Guidelines for follow-up of MPS IVA patients is generally adequate, although some important assessments are reported as difficult due to the lack of MPS skilled specialists. Availability of ERT in Southern and Eastern European countries is generally in line with other European regions, even though regulatory, organizational and reimbursement constrains are demanding. Conclusions: The landscape of MPS in Southern and Eastern European countries is generally comparable to that of other European regions on the epidemiology, treatment accessibility and follow up difficulties. However, issues limiting ERT availability and reimbursement should be simplified, to start treatment as early as possible and make it available for more patients. Besides, educational programs dedicated to specialists should be implemented, particularly for pediatricians, clinical geneticists, surgeons, anesthesiologists and neurologists.

Knowledge about basic life support in European students

2014 ◽  
Vol 155 (21) ◽  
pp. 833-837 ◽  
Author(s):  
József Marton ◽  
Attila Pandúr ◽  
Emese Pék ◽  
Krisztina Deutsch ◽  
Bálint Bánfai ◽  
...  
Keyword(s):  
Basic Life Support ◽  
Life Support ◽  
European Countries ◽  
Eastern European ◽  
Knowledge And Skills ◽  
European Students ◽  
Western European ◽  
Eastern European Countries ◽  
European Youth

Introduction: Better knowledge and skills of basic life support can save millions of lives each year in Europe. Aim: The aim of this study was to measure the knowledge about basic life support in European students. Method: From 13 European countries 1527 volunteer participated in the survey. The questionnaire consisted of socio-demographic questions and knowledge regarding basic life support. The maximum possible score was 18. Results: Those participants who had basic life support training earned 11.91 points, while those who had not participated in lifesaving education had 9.6 points (p<0.001). Participants from former socialist Eastern European countries reached 10.13 points, while Western Europeans had average 10.85 points (p<0.001). The best results were detected among the Swedish students, and the worst among the Belgians. Conclusions: Based on the results, there are significant differences in the knowledge about basic life support between students from different European countries. Western European youth, and those who were trained had better performance. Orv. Hetil., 2014, 155(21), 833–837.

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