Institute Salud Musculoesqueletica InMusc

Madrid, Spain

Institute Salud Musculoesqueletica InMusc

Madrid, Spain

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Andres M.,Hospital General Universitario Of Alicante | Sivera F.,Hospital General Universitario Of Elda | Vela P.,Hospital General Universitario Of Alicante | Vela P.,University Miguel Hernández | Carmona L.,Institute Salud Musculoesqueletica inMusc
Rheumatology International | Year: 2016

Objective: To describe the variability in rheumatology visits and referrals to other medical specialties of patients with spondyloarthritis (SpA) and to explore factors that may influence such variability. Methods: Nation-wide cross-sectional study performed in 2009–2010. Randomly selected records of patients with a diagnosis of SpA and at least one visit to a rheumatology unit within the previous 2 years were audited. The rates of rheumatology visits and of referrals to other medical specialties were estimated—total and between centres—in the study period. Multilevel regression was used to analyse factors associated with variability and to adjust for clinical and patient characteristics. Results: 1168 patients’ records (45 centres) were reviewed, mainly ankylosing spondylitis (55.2 %) and psoriatic arthritis (22.2 %). The patients had incurred in 5908 visits to rheumatology clinics (rate 254 per 100 patient-years), 4307 visits to other medical specialties (19.6 % were referrals from rheumatology), and 775 visits to specialised nurse clinics. An adjusted variability in frequenting rheumatology clinics of 15.7 % between centres was observed. This was partially explained by the number of faculties and trainees. The adjusted intercentre variability for referrals to other specialties was 12.3 %, and it was associated with urban settings, number of procedures, and existence of SpA dedicated clinics; the probability of a patient with SpA of being referred to other specialist may increase up to 25 % depending on the treating centre. Conclusion: Frequenting rheumatology clinics and referrals to other specialists significantly varies between centres, after adjustment by patient characteristics. © 2016 Springer-Verlag Berlin Heidelberg


Marques A.,Centro Hospitalar iversitario Of Coimbra | Marques A.,Health science Research Unit Nursing UICiSA E | Ferreira R.J.O.,Centro Hospitalar iversitario Of Coimbra | Ferreira R.J.O.,Health science Research Unit Nursing UICiSA E | And 6 more authors.
Annals of the Rheumatic Diseases | Year: 2015

Objectives To identify and synthesise the best available evidence on the accuracy of the currently available tools for predicting fracture risk. Methods We systematically searched PubMed MEDLINE, Embase and Cochrane databases to 2014. Two reviewers independently selected articles, collected data from studies, and carried out a hand search of the references of the included studies. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist was used, and the primary outcome was the area under the curve (AUC) and 95% CIs, obtained from receiver operating characteristic (ROC) analyses. We excluded tools if they had not been externally validated or were designed for specific disease populations. Random effects meta-analyses were performed with the selected tools. Results Forty-five studies met inclusion criteria, corresponding to 13 different tools. Only three tools had been tested more than once in a population-based setting: FRAX (26 studies in 9 countries), GARVAN (6 studies in 3 countries) and QFracture (3 studies in the UK, 1 also including Irish participants). Twenty studies with these three tools were included in a total of 17 meta-analyses (for hip or major osteoporotic fractures; men or women; with or without bone mineral density). Conclusions Most of the 13 tools are feasible in clinical practice. FRAX has the largest number of externally validated and independent studies. The overall accuracy of the different tools is satisfactory (>0.70), with QFracture reaching 0.89 (95% CI 0.88 to 0.89). Significant methodological limitations were observed in many studies, suggesting caution when comparing tools based solely on the AUC. © 2015 BMJ Publishing Group Ltd & European League Against Rheumatism. All rights reserved.


Marques A.,Centro Hospitalar Universitario Of Coimbra | Marques A.,Health science Research Unit Nursing UICiSA E | Ferreira R.J.O.,Centro Hospitalar Universitario Of Coimbra | Ferreira R.J.O.,Health science Research Unit Nursing UICiSA E | And 6 more authors.
Annals of the Rheumatic Diseases | Year: 2015

Objectives: To identify and synthesise the best available evidence on the accuracy of the currently available tools for predicting fracture risk. Methods: We systematically searched PubMed MEDLINE, Embase and Cochrane databases to 2014. Two reviewers independently selected articles, collected data from studies, and carried out a hand search of the references of the included studies. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist was used, and the primary outcome was the area under the curve (AUC) and 95% CIs, obtained from receiver operating characteristic (ROC) analyses. We excluded tools if they had not been externally validated or were designed for specific disease populations. Random effects meta-analyses were performed with the selected tools. Results: Forty-five studies met inclusion criteria, corresponding to 13 different tools. Only three tools had been tested more than once in a population-based setting: FRAX (26 studies in 9 countries), GARVAN (6 studies in 3 countries) and QFracture (3 studies in the UK, 1 also including Irish participants). Twenty studies with these three tools were included in a total of 17 meta-analyses (for hip or major osteoporotic fractures; men or women; with or without bone mineral density). Conclusions: Most of the 13 tools are feasible in clinical practice. FRAX has the largest number of externally validated and independent studies. The overall accuracy of the different tools is satisfactory (>0.70), with QFracture reaching 0.89 (95% CI 0.88 to 0.89). Significant methodological limitations were observed in many studies, suggesting caution when comparing tools based solely on the AUC.


Cross M.,University of Sydney | Smith E.,University of Sydney | Hoy D.,University of Queensland | Carmona L.,Institute Salud Musculoesqueletica InMusc | And 12 more authors.
Annals of the Rheumatic Diseases | Year: 2014

Objectives To estimate the global burden of rheumatoid arthritis (RA), as part of the Global Burden of Disease 2010 study of 291 conditions and how the burden of RA compares with other conditions. Methods The optimum case definition of RA for the study was the American College of Rheumatology 1987 criteria. A series of systematic reviews were conducted to gather age-sex-specific epidemiological data for RA prevalence, incidence and mortality. Cause-specific mortality data were also included. Data were entered into DisMod-MR, a tool to pool available data, making use of study-level covariates to adjust for country, region and super-region random effects to estimate prevalence for every country and over time. The epidemiological data, in addition to disability weights, were used to calculate years of life lived with disability (YLDs). YLDs were added to the years of life lost due to premature mortality to estimate the overall burden (disabilityadjusted life years (DALYs)) for RA for the years 1990, 2005 and 2010. Results The global prevalence of RA was 0.24% (95% CI 0.23% to 0.25%), with no discernible change from 1990 to 2010. DALYs increased from 3.3 million (M) (95% CI 2.6 M to 4.1 M) in 1990 to 4.8 M (95% CI 3.7 M to 6.1 M) in 2010. This increase was due to a growth in population and increase in aging. Globally, of the 291 conditions studied, RA was ranked as the 42nd highest contributor to global disability, just below malaria and just above iodine deficiency (measured in YLDs). Conclusions RA continues to cause modest global disability, with severe consequences in the individuals affected.


PubMed | Institute Salud Musculoesqueletica inMusc, Hospital General Universitario Of Alicante and Hospital General Universitario Of Elda
Type: Journal Article | Journal: Rheumatology international | Year: 2016

To describe the variability in rheumatology visits and referrals to other medical specialties of patients with spondyloarthritis (SpA) and to explore factors that may influence such variability.Nation-wide cross-sectional study performed in 2009-2010. Randomly selected records of patients with a diagnosis of SpA and at least one visit to a rheumatology unit within the previous 2years were audited. The rates of rheumatology visits and of referrals to other medical specialties were estimated-total and between centres-in the study period. Multilevel regression was used to analyse factors associated with variability and to adjust for clinical and patient characteristics.1168 patients records (45 centres) were reviewed, mainly ankylosing spondylitis (55.2%) and psoriatic arthritis (22.2%). The patients had incurred in 5908 visits to rheumatology clinics (rate 254 per 100 patient-years), 4307 visits to other medical specialties (19.6% were referrals from rheumatology), and 775 visits to specialised nurse clinics. An adjusted variability in frequenting rheumatology clinics of 15.7% between centres was observed. This was partially explained by the number of faculties and trainees. The adjusted intercentre variability for referrals to other specialties was 12.3%, and it was associated with urban settings, number of procedures, and existence of SpA dedicated clinics; the probability of a patient with SpA of being referred to other specialist may increase up to 25% depending on the treating centre.Frequenting rheumatology clinics and referrals to other specialists significantly varies between centres, after adjustment by patient characteristics.


PubMed | University of Washington, Mayo Medical School, University of Queensland, University of New South Wales and 4 more.
Type: Journal Article | Journal: Annals of the rheumatic diseases | Year: 2014

To estimate the global burden of rheumatoid arthritis (RA), as part of the Global Burden of Disease 2010 study of 291 conditions and how the burden of RA compares with other conditions.The optimum case definition of RA for the study was the American College of Rheumatology 1987 criteria. A series of systematic reviews were conducted to gather age-sex-specific epidemiological data for RA prevalence, incidence and mortality. Cause-specific mortality data were also included. Data were entered into DisMod-MR, a tool to pool available data, making use of study-level covariates to adjust for country, region and super-region random effects to estimate prevalence for every country and over time. The epidemiological data, in addition to disability weights, were used to calculate years of life lived with disability (YLDs). YLDs were added to the years of life lost due to premature mortality to estimate the overall burden (disability-adjusted life years (DALYs)) for RA for the years 1990, 2005 and 2010.The global prevalence of RA was 0.24% (95% CI 0.23% to 0.25%), with no discernible change from 1990 to 2010. DALYs increased from 3.3 million (M) (95% CI 2.6 M to 4.1 M) in 1990 to 4.8 M (95% CI 3.7 M to 6.1 M) in 2010. This increase was due to a growth in population and increase in aging. Globally, of the 291 conditions studied, RA was ranked as the 42nd highest contributor to global disability, just below malaria and just above iodine deficiency (measured in YLDs).RA continues to cause modest global disability, with severe consequences in the individuals affected.


PubMed | Institute Salud Musculoesqueletica InMusc, University of Coimbra and Centro Hospitalar iversitario Of Coimbra
Type: Journal Article | Journal: Annals of the rheumatic diseases | Year: 2015

To identify and synthesise the best available evidence on the accuracy of the currently available tools for predicting fracture risk.We systematically searched PubMed MEDLINE, Embase and Cochrane databases to 2014. Two reviewers independently selected articles, collected data from studies, and carried out a hand search of the references of the included studies. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) checklist was used, and the primary outcome was the area under the curve (AUC) and 95% CIs, obtained from receiver operating characteristic (ROC) analyses. We excluded tools if they had not been externally validated or were designed for specific disease populations. Random effects meta-analyses were performed with the selected tools.Forty-five studies met inclusion criteria, corresponding to 13 different tools. Only three tools had been tested more than once in a population-based setting: FRAX (26 studies in 9 countries), GARVAN (6 studies in 3 countries) and QFracture (3 studies in the UK, 1 also including Irish participants). Twenty studies with these three tools were included in a total of 17 meta-analyses (for hip or major osteoporotic fractures; men or women; with or without bone mineral density).Most of the 13 tools are feasible in clinical practice. FRAX has the largest number of externally validated and independent studies. The overall accuracy of the different tools is satisfactory (>0.70), with QFracture reaching 0.89 (95% CI 0.88 to 0.89). Significant methodological limitations were observed in many studies, suggesting caution when comparing tools based solely on the AUC.

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