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Emergency department triage scales and their components: a systematic review of the scientific evidence.

https://arctichealth.org/en/permalink/ahliterature133295
Source
Scand J Trauma Resusc Emerg Med. 2011;19:42
Publication Type
Article
Date
2011
Author
Nasim Farrohknia
Maaret Castrén
Anna Ehrenberg
Lars Lind
Sven Oredsson
Håkan Jonsson
Kjell Asplund
Katarina E Göransson
Author Affiliation
The Swedish Council for Health Technology Assessment and Dep of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden. Nasim.farrokhnia@medsci.uu.se
Source
Scand J Trauma Resusc Emerg Med. 2011;19:42
Date
2011
Language
English
Publication Type
Article
Keywords
Emergencies
Emergency Service, Hospital - organization & administration
Hospitalization - statistics & numerical data
Humans
Reproducibility of Results
Severity of Illness Index
Sweden
Triage - classification
Abstract
Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED?2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (= 15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted.We found ED triage scales to be supported, at best, by limited and often insufficient evidence.The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity).
Notes
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PubMed ID
21718476 View in PubMed
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Intracranial volume estimated with commonly used methods could introduce bias in studies including brain volume measurements.

https://arctichealth.org/en/permalink/ahliterature259190
Source
Neuroimage. 2013 Dec;83:355-60
Publication Type
Article
Date
Dec-2013
Author
Richard Nordenskjöld
Filip Malmberg
Elna-Marie Larsson
Andrew Simmons
Samantha J Brooks
Lars Lind
Håkan Ahlström
Lars Johansson
Joel Kullberg
Source
Neuroimage. 2013 Dec;83:355-60
Date
Dec-2013
Language
English
Publication Type
Article
Keywords
Aged
Algorithms
Artifacts
Bias (epidemiology)
Brain - anatomy & histology - physiology
Female
Humans
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional - methods - statistics & numerical data
Magnetic Resonance Imaging - methods - statistics & numerical data
Male
Organ Size - physiology
Reproducibility of Results
Sensitivity and specificity
Sweden
Abstract
In brain volumetric studies, intracranial volume (ICV) is often used as an estimate of pre-morbid brain size as well as to compensate for inter-subject variations in head size. However, if the estimated ICV is biased by for example gender or atrophy, it could introduce errors in study results. To evaluate how two commonly used methods for ICV estimation perform, computer assisted reference segmentations were created and evaluated. Segmentations were created for 399 MRI volumes from 75-year-old subjects, with 53 of these subjects having an additional scan and segmentation created at age 80. ICV estimates from Statistical Parametric Mapping (SPM, version 8) and Freesurfer (FS, version 5.1.0) were compared to the reference segmentations, and bias related to skull size (approximated with the segmentation measure), gender or atrophy were tested for. The possible ICV related effect on associations between normalized hippocampal volume and factors gender, education and cognition was evaluated by normalizing hippocampal volume with different ICV measures. Excellent agreement was seen for inter- (r=0.999) and intra- (r=0.999) operator reference segmentations. Both SPM and FS overestimated ICV. SPM showed bias associated with gender and atrophy while FS showed bias dependent on skull size. All methods showed good correlation between time points in the longitudinal data (reference: 0.998, SPM: 0.962, FS: 0.995). Hippocampal volume showed different associations with cognition and gender depending on which ICV measure was used for hippocampal volume normalization. These results show that the choice of method used for ICV estimation can bias results in studies including brain volume measurements.
PubMed ID
23827332 View in PubMed
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Evaluation of a scoring scheme, including proinsulin and the apolipoprotein B/apolipoprotein A1 ratio, for the risk of acute coronary events in middle-aged men: Uppsala Longitudinal Study of Adult Men (ULSAM).

https://arctichealth.org/en/permalink/ahliterature53267
Source
Am Heart J. 2004 Oct;148(4):596-601
Publication Type
Article
Date
Oct-2004
Author
Kristina Dunder
Lars Lind
Björn Zethelius
Lars Berglund
Hans Lithell
Author Affiliation
Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden. kristina.dunder@pubcare.uu.se
Source
Am Heart J. 2004 Oct;148(4):596-601
Date
Oct-2004
Language
English
Publication Type
Article
Keywords
Apolipoprotein A-I - blood
Apolipoproteins B - blood
Biological Markers - blood
Electrocardiography
Health Surveys
Humans
Longitudinal Studies
Male
Middle Aged
Myocardial Infarction - epidemiology - mortality
Prognosis
Proinsulin - blood
Proportional Hazards Models
Reproducibility of Results
Research Support, Non-U.S. Gov't
Risk Assessment - methods
Risk factors
Abstract
BACKGROUND: In recent years, the importance of circulating levels of proinsulin and apolipoproteins as risk factors for myocardial infarction (MI) has been highlighted. The aims of the current study were to investigate whether introduction of these new markers of coronary risk could improve the performance of a risk prediction score and to compare this new score with traditional scoring schemes, such as the Framingham Study and the Prospective Cardiovascular Munster (PROCAM) Study schemes. METHODS: From 1970 to 1973 all 50-year-old men in Uppsala, Sweden, were invited to participate in a health survey aimed at identifying risk factors for cardiovascular disease (the Uppsala Longitudinal Study of Adult Men [ULSAM] cohort). The current study investigated metabolic characteristics at baseline and the incidence of fatal and nonfatal MI (n = 251) during 28.7 years of follow-up in 1108 men who were free of coronary heart disease at baseline. RESULTS: The risk prediction score was derived from one half of the population sample from the ULSAM cohort and included systolic blood pressure, smoking, family history of MI, serum proinsulin, and the ratio between apolipoprotein B and apolipoprotein A1.The score was highly predictive for future MI (hazard ratio, 1.77 for a 1 SD increase; 95% CI, 1.49 to 2.10, P
PubMed ID
15459588 View in PubMed
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How many measurements are needed to estimate blood pressure variability without loss of prognostic information?

https://arctichealth.org/en/permalink/ahliterature107969
Source
Am J Hypertens. 2014 Jan;27(1):46-55
Publication Type
Article
Date
Jan-2014
Author
Luis J Mena
Gladys E Maestre
Tine W Hansen
Lutgarde Thijs
Yanping Liu
José Boggia
Yan Li
Masahiro Kikuya
Kristina Björklund-Bodegård
Takayoshi Ohkubo
Jørgen Jeppesen
Christian Torp-Pedersen
Eamon Dolan
Tatiana Kuznetsova
Katarzyna Stolarz-Skrzypek
Valérie Tikhonoff
Sofia Malyutina
Edoardo Casiglia
Yuri Nikitin
Lars Lind
Edgardo Sandoya
Kalina Kawecka-Jaszcz
Jan Filipovsky
Yutaka Lmai
Jiguang Wang
Eoin O'Brien
Jan A Staessen
Author Affiliation
Departamento de Informática, Universidad Politécnica de Sinaloa, Mazatlán, México.
Source
Am J Hypertens. 2014 Jan;27(1):46-55
Date
Jan-2014
Language
English
Publication Type
Article
Keywords
Aged
Antihypertensive Agents - therapeutic use
Blood Pressure - drug effects
Blood Pressure Monitoring, Ambulatory
Cause of Death
Chi-Square Distribution
Denmark
Female
Humans
Hypertension - diagnosis - drug therapy - mortality - physiopathology
Male
Middle Aged
Multivariate Analysis
Predictive value of tests
Prognosis
Proportional Hazards Models
Reproducibility of Results
Risk factors
Time Factors
Abstract
Average real variability (ARV) is a recently proposed index for short-term blood pressure (BP) variability. We aimed to determine the minimum number of BP readings required to compute ARV without loss of prognostic information.
ARV was calculated from a discovery dataset that included 24-hour ambulatory BP measurements for 1,254 residents (mean age = 56.6 years; 43.5% women) of Copenhagen, Denmark. Concordance between ARV from full (=80 BP readings) and randomly reduced 24-hour BP recordings was examined, as was prognostic accuracy. A test dataset that included 5,353 subjects (mean age = 54.0 years; 45.6% women) with at least 48 BP measurements from 11 randomly recruited population cohorts was used to validate the results.
In the discovery dataset, a minimum of 48 BP readings allowed an accurate assessment of the association between cardiovascular risk and ARV. In the test dataset, over 10.2 years (median), 806 participants died (335 cardiovascular deaths, 206 cardiac deaths) and 696 experienced a major fatal or nonfatal cardiovascular event. Standardized multivariable-adjusted hazard ratios (HRs) were computed for associations between outcome and BP variability. Higher diastolic ARV in 24-hour ambulatory BP recordings predicted (P
PubMed ID
23955605 View in PubMed
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Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease.

https://arctichealth.org/en/permalink/ahliterature268418
Source
PLoS Genet. 2014 Dec;10(12):e1004801
Publication Type
Article
Date
Dec-2014
Author
Andrea Ganna
Samira Salihovic
Johan Sundström
Corey D Broeckling
Asa K Hedman
Patrik K E Magnusson
Nancy L Pedersen
Anders Larsson
Agneta Siegbahn
Mihkel Zilmer
Jessica Prenni
Johan Arnlöv
Lars Lind
Tove Fall
Erik Ingelsson
Source
PLoS Genet. 2014 Dec;10(12):e1004801
Date
Dec-2014
Language
English
Publication Type
Article
Keywords
Aged
Biomarkers - blood
C-Reactive Protein - metabolism
Coronary Disease - blood - epidemiology - genetics
Female
Follow-Up Studies
Gene Expression Profiling
Genetic Association Studies
Humans
Incidence
Linear Models
Longitudinal Studies
Lysophosphatidylcholines - blood
Male
Metabolomics
Middle Aged
Monoglycerides - blood
Polymorphism, Single Nucleotide
Prospective Studies
Reproducibility of Results
Risk assessment
Risk factors
Sphingomyelins - blood
Sweden
Abstract
Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease (CHD). We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1,028 individuals (131 events; 10 y. median follow-up) with validation in 1,670 individuals (282 events; 3.9 y. median follow-up). Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18:1 (hazard ratio [HR] per standard deviation [SD] increment?=?0.77, P-value
Notes
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PubMed ID
25502724 View in PubMed
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Inflammatory biomarker pentraxin 3 (PTX3) in relation to obesity, body fat depots and weight loss.

https://arctichealth.org/en/permalink/ahliterature259513
Source
Obesity (Silver Spring). 2014 May;22(5):1373-9
Publication Type
Article
Date
May-2014
Author
Anna Witasp
Juan Jesús Carrero
Karl Michaëlsson
Håkan Ahlström
Joel Kullberg
Viola Adamsson
Ulf Risérus
Anders Larsson
Johanna Helmersson-Karlqvist
Lars Lind
Peter Stenvinkel
Johan Arnlöv
Source
Obesity (Silver Spring). 2014 May;22(5):1373-9
Date
May-2014
Language
English
Publication Type
Article
Keywords
Adiposity
Adult
Aged
Biological Markers - blood
Body mass index
C-Reactive Protein - genetics - metabolism
Cardiovascular Diseases - blood - genetics
Cross-Sectional Studies
Female
Follow-Up Studies
Food Habits
Genetic markers
Humans
Inflammation - blood - genetics
Longitudinal Studies
Male
Middle Aged
Obesity - genetics - metabolism
Prospective Studies
Reproducibility of Results
Serum Amyloid P-Component - genetics - metabolism
Sweden
Waist Circumference
Weight Loss
Abstract
The relation between inflammatory markers, adiposity and disease is under extensive study. Here we tested the hypothesis that the immunomodulatory protein pentraxin 3 (PTX3) is associated with adiposity in the general population.
Serum PTX3 concentrations, body mass index (BMI), waist circumference (WC) and fat depots, as quantified by dual-energy X-ray absorptiometry and magnetic resonance imaging, were assessed in three community-based cohorts: ULSAM, n = 790, mean age 78 years; PIVUS, n = 1003, mean age 70 years, women 50%; and the NORDIET-trial, n = 86, mean age 53 years, women 63%. Participants were re-examined after 5 years (PIVUS, n = 804) or following a 6-week randomized controlled dietary intervention (NORDIET).
PTX3 levels were inversely associated with BMI and WC as well as with total and visceral fat (P
PubMed ID
24415446 View in PubMed
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The effects of antihypertensive treatment on the doppler-derived myocardial performance index in patients with hypertensive left ventricular hypertrophy: results from the Swedish irbesartan in left ventricular hypertrophy investigation versus atenolol (SILVHIA).

https://arctichealth.org/en/permalink/ahliterature99002
Source
Echocardiography. 2009 Aug;26(7):753-8
Publication Type
Article
Date
Aug-2009
Author
Stefan Liljedahl
Thomas Kahan
Lars Lind
Johan Arnlöv
Author Affiliation
Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden.
Source
Echocardiography. 2009 Aug;26(7):753-8
Date
Aug-2009
Language
English
Publication Type
Article
Keywords
Adult
Aged
Antihypertensive Agents - therapeutic use
Atenolol - therapeutic use
Biphenyl Compounds - therapeutic use
Comorbidity
Echocardiography, Doppler - methods - statistics & numerical data
Female
Humans
Hypertension - drug therapy - epidemiology - ultrasonography
Hypertrophy, Left Ventricular - drug therapy - epidemiology - ultrasonography
Image Interpretation, Computer-Assisted - methods
Male
Middle Aged
Myocardial Perfusion Imaging - methods
Prevalence
Reproducibility of Results
Sensitivity and specificity
Sweden - epidemiology
Tetrazoles - therapeutic use
Treatment Outcome
Abstract
OBJECTIVES: To investigate the effects of antihypertensive treatment on the Doppler-derived myocardial performance index (MPI) in patients with hypertensive left ventricular hypertrophy. METHODS: The MPI was measured at baseline and after 48 weeks of antihypertensive treatment in 93 participants of the SILVHIA trial, where individuals with primary hypertension and left ventricular hypertrophy were randomized to double blind treatment with either irbesartan or atenolol. RESULTS: Antihypertensive treatment lowered MPI (mean difference -0.03 +/- 0.01, P = 0.04). Changes in MPI by treatment were associated with changes in left ventricular ejection fraction (beta-coefficient -0.35 P = 0.005), stroke volume/pulse pressure (reflecting arterial compliance, beta-coefficient -0.39 P
PubMed ID
19486119 View in PubMed
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7 records – page 1 of 1.