Risk stratification and treatment effect of statins in secondary cardiovascular prevention in old age: additive value of N-terminal pro-B-type natriuretic peptide

Background To date, no validated risk scores exist for prediction of recurrence risk or potential treatment effect for older people with a history of a cardiovascular event. Therefore, we assessed predictive values for recurrent cardiovascular disease of models with age and sex, traditional cardiovascular risk markers, and ‘SMART risk score’, all with and without addition of N-terminal pro-B-type natriuretic peptide (NT-proBNP). Treatment effect of pravastatin was assessed across low and high risk groups identified by the best performing models. Design and methods Post-hoc analysis in 2348 participants (age 70–82 years) with a history of cardiovascular disease within the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) study. Composite endpoint was a recurrent cardiovascular event/cardiovascular mortality. Results The models with age and sex, traditional risk markers and SMART risk score had comparable predictive values (area under the curve (AUC) 0.58, 0.61 and 0.59, respectively). Addition of NT-proBNP to these models improved AUCs with 0.07 (p for difference ((pdiff)) = 0.003), 0.05 (pdiff = 0.009) and 0.06 (pdiff < 0.001), respectively. For the model with age, sex and NT-proBNP, the hazard ratio for the composite endpoint in pravastatin users compared with placebo was 0.67 (95% confidence interval 0.49–0.90) for those in the highest third of predicted risk and 0.91 (0.57–1.46) in the lowest third, number needed to treat 12 and 115 (pdiff = 0.038) respectively. Conclusion In secondary cardiovascular prevention in old age addition of NT-proBNP improves prediction of recurrent cardiovascular disease, cardiovascular mortality and treatment effect of pravastatin. A minimal model including age, sex and NT-proBNP predicts as accurately as complex risk models including NT-proBNP

Ten papers for teachers of evidence-based medicine and health care: Sicily workshop 2019

A previous article sought to signpost papers that were considered helpful when starting on the journey of practicing evidence-based medicine (EBM). The lead author was invited to run a workshop at the Eighth Conference of the International Society for Evidence-Based Health Care run in collaboration with the Gruppo Italiano per la Medicina Basata sulle Evidenze from 6 November to 9 November 2019. The aim of the workshop was to challenge a group of teachers and educators to consider useful papers for the teaching of EBM/evidence-based healthcare (EBHC). The second aim was to start a database of such studies. The third aim was to share learning and foster discussion from the workshop through journal publication. EBM and EBHC are used interchangeably throughout this article

GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

Biomarkers versus traditional risk factors to predict cardiovascular events in very old adults: cross-validated prospective cohort study

OBJECTIVES: To test new cardiovascular (CV) risk models in very old adults with and without a history of CV disease (CVD), based on traditional risk factors and biomarkers. DESIGN: Cross-validated prospective cohort study. The models were tested in the BELFRAIL Study and externally validated in the Leiden 85-plus Study. SETTING: General practice, Belgium and The Netherlands. PARTICIPANTS: The BELFRAIL cohort consisted of 266 patients aged 80 years or older without a history of CVD and 260 with a history of CVD. The Leiden 85-plus Study consisted of 264 patients aged 85 years without a history of CVD and 282 with a history of CVD. OUTCOME MEASURES: The model with traditional risk factors and biomarkers, as well as the model using only biomarkers, was compared with the model with only traditional risk factors to predict 3-year CV morbidity and mortality. A competing-risk analysis was performed, and the continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI) and net benefit were used to compare the predictive value of the different models. RESULTS: Traditional risk factors poorly predicted CV mortality and morbidity. In participants without a history of CVD, adding N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) improved the prediction (NRI 0.56 (95% CI 0.16 to 0.99) and relative IDI 4.01 (95% CI 2.19 to 6.28)). In participants with a history of CVD, the NRI with the addition of NT-pro-BNP and high-sensitivity C reactive protein was 0.38 (95% CI 0.09 to 0.70), and the relative IDI was 0.53 (95% CI 0.23 to 0.90). Moreover, in participants without a history of CVD, NT-pro-BNP performed well as a stand-alone predictor (NRI 0.32 (95% CI -0.12 to 0.74) and relative IDI 3.44 (95% CI 1.56 to 6.09)). CONCLUSIONS: This study tested new risk models to predict CV morbidity and mortality in very old adults. Especially, NT-pro-BNP showed a strong added predictive value. This opens perspectives for clinicians who are in need of an easily applicable strategy for CV risk prediction in very old adults.status: publishe

Biomarkers versus traditional risk factors to predict cardiovascular events in very old adults: cross-validated prospective cohort study

Objectives To test new cardiovascular (CV) risk models in very old adults with and without a history of CV disease (CVD), based on traditional risk factors and biomarkers.Design Cross- validated prospective cohort study. The models were tested in the BELFRAIL Study and externally validated in the Leiden 85- plus Study.setting General practice, Belgium and The Netherlands.Participants The BELFRAIL cohort consisted of 266 patients aged 80 years or older without a history of CVD and 260 with a history of CVD. The Leiden 85- plus Study consisted of 264 patients aged 85 years without a history of CVD and 282 with a history of CVD.Outcome measures The model with traditional risk factors and biomarkers, as well as the model using only biomarkers, was compared with the model with only traditional risk factors to predict 3- year CV morbidity and mortality. A competing- risk analysis was performed, and the continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI) and net benefit were used to compare the predictive value of the different models.results Traditional risk factors poorly predicted CV mortality and morbidity. In participants without a history of CVD, adding N- terminal pro- B- type natriuretic peptide (NT- pro- BNP) improved the prediction (NRI 0.56 (95% CI 0.16 to 0.99) and relative IDI 4.01 (95% CI 2.19 to 6.28)). In participants with a history of CVD, the NRI with the addition of NT- pro- BNP and high- sensitivity C reactive protein was 0.38 (95% CI 0.09 to 0.70), and the relative IDI was 0.53 (95% CI 0.23 to 0.90). Moreover, in participants without a history of CVD, NT- pro- BNP performed well as a stand- alone predictor (NRI 0.32 (95% CI −0.12 to 0.74) and relative IDI 3.44 (95% CI 1.56 to 6.09)).Conclusions This study tested new risk models to predict CV morbidity and mortality in very old adults. Especially, NT- pro- BNP showed a strong added predictive value. This opens perspectives for clinicians who are in need of an easily applicable strategy for CV risk prediction in very old adults

Kaplan-Meier curves, showing cumulative cardiovascular morbidity and mortality.

<p>Kaplan-Meier curves, adjusted for competing risks, showing cumulative cardiovascular morbidity and mortality for tertiles of risk for three different models: traditional risk markers only (left graph), traditional risk markers plus NT-proBNP (middle graph), and traditional risk markers plus all five new markers (a history of major cardiovascular disease, MDRD, CRP, homocysteine and NT-proBNP) (right graph) (N=282).</p