Matches in SemOpenAlex for { <https://semopenalex.org/work/W4229691715> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W4229691715 endingPage "S191" @default.
- W4229691715 startingPage "S191" @default.
- W4229691715 abstract "Introduction Cardiovascular risk prediction tools are important for cardiovascular disease (CVD) prevention, however, which algorithms are appropriate for people with severe mental illness (SMI) is unclear. Objectives/aims To determine the cost-effectiveness using the net monetary benefit (NMB) approach of two bespoke SMI-specific risk algorithms compared to standard risk algorithms for primary CVD prevention in those with SMI, from an NHS perspective. Methods A microsimulation model was populated with 1000 individuals with SMI from The Health Improvement Network Database, aged 30–74 years without CVD. Four cardiovascular risk algorithms were assessed; (1) general population lipid, (2) general population BMI, (3) SMI-specific lipid and (4) SMI-specific BMI, compared against no algorithm. At baseline, each cardiovascular risk algorithm was applied and those high-risk (> 10%) were assumed to be prescribed statin therapy, others received usual care. Individuals entered the model in a ‘healthy’ free of CVD health state and with each year could retain their current health state, have cardiovascular events (non-fatal/fatal) or die from other causes according to transition probabilities. Results The SMI-specific BMI and general population lipid algorithms had the highest NMB of the four algorithms resulting in 12 additional QALYs and a cost saving of approximately £37,000 (US$ 58,000) per 1000 patients with SMI over 10 years. Conclusions The general population lipid and SMI-specific BMI algorithms performed equally well. The ease and acceptability of use of a SMI-specific BMI algorithm (blood tests not required) makes it an attractive algorithm to implement in clinical settings. Disclosure of interest The authors have not supplied their declaration of competing interest." @default.
- W4229691715 created "2022-05-11" @default.
- W4229691715 creator A5001489240 @default.
- W4229691715 creator A5012277006 @default.
- W4229691715 creator A5014176628 @default.
- W4229691715 creator A5023241166 @default.
- W4229691715 creator A5024962501 @default.
- W4229691715 creator A5029503629 @default.
- W4229691715 creator A5032352489 @default.
- W4229691715 creator A5048633862 @default.
- W4229691715 creator A5049780205 @default.
- W4229691715 creator A5059386114 @default.
- W4229691715 creator A5062179324 @default.
- W4229691715 creator A5063357686 @default.
- W4229691715 creator A5073245125 @default.
- W4229691715 creator A5078028015 @default.
- W4229691715 date "2016-03-01" @default.
- W4229691715 modified "2023-09-30" @default.
- W4229691715 title "Effectiveness and cost-effectiveness of a cardiovascular risk prediction algorithm for people with severe mental illness" @default.
- W4229691715 doi "https://doi.org/10.1016/j.eurpsy.2016.01.433" @default.
- W4229691715 hasPublicationYear "2016" @default.
- W4229691715 type Work @default.
- W4229691715 citedByCount "0" @default.
- W4229691715 crossrefType "journal-article" @default.
- W4229691715 hasAuthorship W4229691715A5001489240 @default.
- W4229691715 hasAuthorship W4229691715A5012277006 @default.
- W4229691715 hasAuthorship W4229691715A5014176628 @default.
- W4229691715 hasAuthorship W4229691715A5023241166 @default.
- W4229691715 hasAuthorship W4229691715A5024962501 @default.
- W4229691715 hasAuthorship W4229691715A5029503629 @default.
- W4229691715 hasAuthorship W4229691715A5032352489 @default.
- W4229691715 hasAuthorship W4229691715A5048633862 @default.
- W4229691715 hasAuthorship W4229691715A5049780205 @default.
- W4229691715 hasAuthorship W4229691715A5059386114 @default.
- W4229691715 hasAuthorship W4229691715A5062179324 @default.
- W4229691715 hasAuthorship W4229691715A5063357686 @default.
- W4229691715 hasAuthorship W4229691715A5073245125 @default.
- W4229691715 hasAuthorship W4229691715A5078028015 @default.
- W4229691715 hasConcept C11413529 @default.
- W4229691715 hasConcept C118552586 @default.
- W4229691715 hasConcept C126322002 @default.
- W4229691715 hasConcept C134362201 @default.
- W4229691715 hasConcept C2776674806 @default.
- W4229691715 hasConcept C2779134260 @default.
- W4229691715 hasConcept C2780221984 @default.
- W4229691715 hasConcept C2908647359 @default.
- W4229691715 hasConcept C41008148 @default.
- W4229691715 hasConcept C71924100 @default.
- W4229691715 hasConcept C99454951 @default.
- W4229691715 hasConceptScore W4229691715C11413529 @default.
- W4229691715 hasConceptScore W4229691715C118552586 @default.
- W4229691715 hasConceptScore W4229691715C126322002 @default.
- W4229691715 hasConceptScore W4229691715C134362201 @default.
- W4229691715 hasConceptScore W4229691715C2776674806 @default.
- W4229691715 hasConceptScore W4229691715C2779134260 @default.
- W4229691715 hasConceptScore W4229691715C2780221984 @default.
- W4229691715 hasConceptScore W4229691715C2908647359 @default.
- W4229691715 hasConceptScore W4229691715C41008148 @default.
- W4229691715 hasConceptScore W4229691715C71924100 @default.
- W4229691715 hasConceptScore W4229691715C99454951 @default.
- W4229691715 hasIssue "S1" @default.
- W4229691715 hasLocation W42296917151 @default.
- W4229691715 hasOpenAccess W4229691715 @default.
- W4229691715 hasPrimaryLocation W42296917151 @default.
- W4229691715 hasRelatedWork W11071520 @default.
- W4229691715 hasRelatedWork W1233668 @default.
- W4229691715 hasRelatedWork W1321646 @default.
- W4229691715 hasRelatedWork W20193070 @default.
- W4229691715 hasRelatedWork W22763787 @default.
- W4229691715 hasRelatedWork W2519724 @default.
- W4229691715 hasRelatedWork W25703538 @default.
- W4229691715 hasRelatedWork W3407363 @default.
- W4229691715 hasRelatedWork W4728133 @default.
- W4229691715 hasRelatedWork W860634 @default.
- W4229691715 hasVolume "33" @default.
- W4229691715 isParatext "false" @default.
- W4229691715 isRetracted "false" @default.
- W4229691715 workType "article" @default.