0000000000751330

AUTHOR

Olli Saarela

showing 2 related works from this author

Thirty-one novel biomarkers as predictors for clinically incident diabetes.

2010

Background The prevalence of diabetes is increasing in all industrialized countries and its prevention has become a public health priority. However, the predictors of diabetes risk are insufficiently understood. We evaluated, whether 31 novel biomarkers could help to predict the risk of incident diabetes. Methods and Findings The biomarkers were evaluated primarily in the FINRISK97 cohort (n = 7,827; 417 cases of clinically incident diabetes during the follow-up). The findings were replicated in the Health 2000 cohort (n = 4,977; 179 cases of clinically incident diabetes during the follow-up). We used Cox proportional hazards models to calculate the relative risk of diabetes, after adjustin…

AdultMaleRiskmedicine.medical_specialtyDiabetes riskPublic Health and Epidemiologylcsh:Medicine030209 endocrinology & metabolism030204 cardiovascular system & hematologyCohort Studies03 medical and health sciences0302 clinical medicineSex FactorsPredictive Value of TestsDiabetes mellitusInternal medicinemedicineDiabetes MellitusHumansCardiovascular Disorders/Vascular Biologylcsh:ScienceAgedApolipoproteins BProportional Hazards ModelsMultidisciplinaryAdiponectinbiologyProportional hazards modelbusiness.industrylcsh:RC-reactive proteinMiddle Agedmedicine.disease3. Good healthDiabetes and EndocrinologyC-Reactive ProteinROC CurveRelative riskImmunologyCohortFerritinsbiology.proteinlcsh:QFemaleAdiponectinbusinessBiomarkersCohort studyResearch ArticlePloS one
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A multiple biomarker risk score for guiding clinical decisions using a decision curve approach.

2011

Aims: We assessed whether a cardiovascular risk model based on classic risk factors (e.g. cholesterol, blood pressure) could refine disease prediction if it included novel biomarkers (C-reactive protein, N-terminal pro-B-type natriuretic peptide, troponin I) using a decision curve approach which can incorporate clinical consequences. Methods and results: We evaluated whether a model including biomarkers and classic risk factors could improve prediction of 10 year risk of cardiovascular disease (CVD; chronic heart disease and ischaemic stroke) against a classic risk factor model using a decision curve approach in two prospective MORGAM cohorts. This included 7739 men and women with 457 CVD …

AdultMalemedicine.medical_specialtyEpidemiologymedicine.drug_classBlood PressureDiseaseRisk AssessmentDecision Support TechniquesSex FactorsPredictive Value of TestsRisk FactorsInternal medicineTroponin INatriuretic Peptide BrainmedicineNatriuretic peptideHumansRisk thresholdProspective StudiesFramingham Risk Scorebusiness.industryTroponin IAge FactorsMiddle AgedPrognosisPeptide FragmentsSurgeryEuropeBlood pressureC-Reactive ProteinCholesterolCardiovascular DiseasesCohortBiomarker (medicine)FemaleCardiology and Cardiovascular MedicinebusinessBiomarkersEuropean journal of preventive cardiology
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