Document Detail


Evidence-based algorithms and the management of falls and syncope presenting to acute medical services.
MedLine Citation:
PMID:  18478859     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Falls and syncope are symptoms that commonly present to medical services. Detailed international guidelines for their management are available but tend to be aimed at specialists rather than generalists. Novel, evidence-based algorithms for the management of these symptoms when they present to acute medical services were formulated and their impact on patient care audited. The percentage of people admitted with falls and syncope was unexpectedly high (10.6% at baseline); this had decreased to 8.2% at repeat audit. Readmission rates decreased from 12% at baseline audit to 0% in repeat audit, while length of inpatient stay was unchanged. Mortality was strikingly high (12%) in both audits. Although inappropriate use of investigations decreased, the use of appropriate management strategies increased. Easy-to-use algorithms can help reduce the number of patients admitted to acute medical services with falls and syncope while optimising the care of those managed as inpatients. The algorithms are provided for use by interested parties.
Authors:
Steve W Parry; Richard Frearson; Nick Steen; Julia L Newton; Prathiba Tryambake; Rose Anne Kenny
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Clinical medicine (London, England)     Volume:  8     ISSN:  1470-2118     ISO Abbreviation:  Clin Med     Publication Date:  2008 Apr 
Date Detail:
Created Date:  2008-05-15     Completed Date:  2008-08-14     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101092853     Medline TA:  Clin Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  157-62     Citation Subset:  IM    
Affiliation:
Falls and Syncope Service and Institute for Ageing and Health, Royal Victoria Infirmary, Newcastle upon Tyne. swparry@hotmail.com
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MeSH Terms
Descriptor/Qualifier:
Accidental Falls* / mortality
Adolescent
Adult
Aged
Aged, 80 and over
Algorithms*
Evidence-Based Medicine
Female
Great Britain / epidemiology
Humans
Internal Medicine / methods*
Male
Medical Audit
Middle Aged
Prospective Studies
Referral and Consultation
Risk Factors
Statistics, Nonparametric
Syncope* / etiology,  mortality,  therapy

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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