Gout and hospital admission for ambulatory care sensitive conditions:risks and trajectories. Kiadaliri, A., Neogi, T., & Englund, M. The Journal of Rheumatology, April, 2022. Publisher: The Journal of Rheumatology Section: Accepted Article![Gout and hospital admission for ambulatory care sensitive conditions:risks and trajectories [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Objective To investigate the risks and trajectories of hospital admission for ambulatory care sensitive conditions (HACSCs) in gout. Methods Among individuals aged 35-85 years residing in Skåne, Sweden, in 2005, those with no doctor-diagnosed gout during 1998–2005 (n=576,700) were followed from January 1st 2006 until an HACSC, death, relocation outside Skåne, or December 31st 2016. Treating a new gout diagnosis (ICD 10 code: M10) as a time-varying exposure, we used Cox proportional and additive hazard models to estimate the effects of gout on HACSCs. We investigated the trajectory of HACSCs from 3 years before to 3 years after gout diagnosis using generalized estimating equations and group-based trajectory modelling in an age- and sex-matched cohort study. Results Gout was associated with 41% increased rate of HACSCs (hazard ratio 1.41; 95% CI: 1.35, 1.47), corresponding to 121 (104, 138) more HACSCs per 10,000 person-years compared with those without gout. Our trajectory analysis showed that higher rates of HACSCs among persons with gout were observed from 3 years before to 3 years after diagnosis with the highest prevalence rate ratio (2.22, 95% CI: 1.92, 2.53) at the 3-month period after diagnosis. We identified three classes with distinct trajectories of HACSCs among gout persons: almost none (88.5%), low-rising (9.7%), and moderate-sharply rising (1.8%). Charlson comorbidity index was the most important predictor of trajectory class membership. Conclusion Increased risk of HACSCs in gout highlights the need for better management of the disease at outpatient care, especially among foreign-born older patients with comorbidities.
@article{kiadaliri_gout_2022,
title = {Gout and hospital admission for ambulatory care sensitive conditions:risks and trajectories},
copyright = {© 2022 The Journal of Rheumatology},
issn = {0315-162X, 1499-2752},
shorttitle = {Gout and hospital admission for ambulatory care sensitive conditions},
url = {https://www.jrheum.org/content/early/2022/04/11/jrheum.220038},
doi = {10.3899/jrheum.220038},
abstract = {Objective To investigate the risks and trajectories of hospital admission for ambulatory care sensitive conditions (HACSCs) in gout.
Methods Among individuals aged 35-85 years residing in Skåne, Sweden, in 2005, those with no doctor-diagnosed gout during 1998–2005 (n=576,700) were followed from January 1st 2006 until an HACSC, death, relocation outside Skåne, or December 31st 2016. Treating a new gout diagnosis (ICD 10 code: M10) as a time-varying exposure, we used Cox proportional and additive hazard models to estimate the effects of gout on HACSCs. We investigated the trajectory of HACSCs from 3 years before to 3 years after gout diagnosis using generalized estimating equations and group-based trajectory modelling in an age- and sex-matched cohort study.
Results Gout was associated with 41\% increased rate of HACSCs (hazard ratio 1.41; 95\% CI: 1.35, 1.47), corresponding to 121 (104, 138) more HACSCs per 10,000 person-years compared with those without gout. Our trajectory analysis showed that higher rates of HACSCs among persons with gout were observed from 3 years before to 3 years after diagnosis with the highest prevalence rate ratio (2.22, 95\% CI: 1.92, 2.53) at the 3-month period after diagnosis. We identified three classes with distinct trajectories of HACSCs among gout persons: almost none (88.5\%), low-rising (9.7\%), and moderate-sharply rising (1.8\%). Charlson comorbidity index was the most important predictor of trajectory class membership.
Conclusion Increased risk of HACSCs in gout highlights the need for better management of the disease at outpatient care, especially among foreign-born older patients with comorbidities.},
language = {en},
urldate = {2023-08-28},
journal = {The Journal of Rheumatology},
author = {Kiadaliri, Ali and Neogi, Tuhina and Englund, Martin},
month = apr,
year = {2022},
pmid = {35428711},
note = {Publisher: The Journal of Rheumatology
Section: Accepted Article},
}
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Methods Among individuals aged 35-85 years residing in Skåne, Sweden, in 2005, those with no doctor-diagnosed gout during 1998–2005 (n=576,700) were followed from January 1st 2006 until an HACSC, death, relocation outside Skåne, or December 31st 2016. Treating a new gout diagnosis (ICD 10 code: M10) as a time-varying exposure, we used Cox proportional and additive hazard models to estimate the effects of gout on HACSCs. We investigated the trajectory of HACSCs from 3 years before to 3 years after gout diagnosis using generalized estimating equations and group-based trajectory modelling in an age- and sex-matched cohort study. Results Gout was associated with 41% increased rate of HACSCs (hazard ratio 1.41; 95% CI: 1.35, 1.47), corresponding to 121 (104, 138) more HACSCs per 10,000 person-years compared with those without gout. Our trajectory analysis showed that higher rates of HACSCs among persons with gout were observed from 3 years before to 3 years after diagnosis with the highest prevalence rate ratio (2.22, 95% CI: 1.92, 2.53) at the 3-month period after diagnosis. We identified three classes with distinct trajectories of HACSCs among gout persons: almost none (88.5%), low-rising (9.7%), and moderate-sharply rising (1.8%). Charlson comorbidity index was the most important predictor of trajectory class membership. Conclusion Increased risk of HACSCs in gout highlights the need for better management of the disease at outpatient care, especially among foreign-born older patients with comorbidities.","language":"en","urldate":"2023-08-28","journal":"The Journal of Rheumatology","author":[{"propositions":[],"lastnames":["Kiadaliri"],"firstnames":["Ali"],"suffixes":[]},{"propositions":[],"lastnames":["Neogi"],"firstnames":["Tuhina"],"suffixes":[]},{"propositions":[],"lastnames":["Englund"],"firstnames":["Martin"],"suffixes":[]}],"month":"April","year":"2022","pmid":"35428711","note":"Publisher: The Journal of Rheumatology Section: Accepted Article","bibtex":"@article{kiadaliri_gout_2022,\n\ttitle = {Gout and hospital admission for ambulatory care sensitive conditions:risks and trajectories},\n\tcopyright = {© 2022 The Journal of Rheumatology},\n\tissn = {0315-162X, 1499-2752},\n\tshorttitle = {Gout and hospital admission for ambulatory care sensitive conditions},\n\turl = {https://www.jrheum.org/content/early/2022/04/11/jrheum.220038},\n\tdoi = {10.3899/jrheum.220038},\n\tabstract = {Objective To investigate the risks and trajectories of hospital admission for ambulatory care sensitive conditions (HACSCs) in gout.\nMethods Among individuals aged 35-85 years residing in Skåne, Sweden, in 2005, those with no doctor-diagnosed gout during 1998–2005 (n=576,700) were followed from January 1st 2006 until an HACSC, death, relocation outside Skåne, or December 31st 2016. Treating a new gout diagnosis (ICD 10 code: M10) as a time-varying exposure, we used Cox proportional and additive hazard models to estimate the effects of gout on HACSCs. We investigated the trajectory of HACSCs from 3 years before to 3 years after gout diagnosis using generalized estimating equations and group-based trajectory modelling in an age- and sex-matched cohort study.\nResults Gout was associated with 41\\% increased rate of HACSCs (hazard ratio 1.41; 95\\% CI: 1.35, 1.47), corresponding to 121 (104, 138) more HACSCs per 10,000 person-years compared with those without gout. Our trajectory analysis showed that higher rates of HACSCs among persons with gout were observed from 3 years before to 3 years after diagnosis with the highest prevalence rate ratio (2.22, 95\\% CI: 1.92, 2.53) at the 3-month period after diagnosis. We identified three classes with distinct trajectories of HACSCs among gout persons: almost none (88.5\\%), low-rising (9.7\\%), and moderate-sharply rising (1.8\\%). Charlson comorbidity index was the most important predictor of trajectory class membership.\nConclusion Increased risk of HACSCs in gout highlights the need for better management of the disease at outpatient care, especially among foreign-born older patients with comorbidities.},\n\tlanguage = {en},\n\turldate = {2023-08-28},\n\tjournal = {The Journal of Rheumatology},\n\tauthor = {Kiadaliri, Ali and Neogi, Tuhina and Englund, Martin},\n\tmonth = apr,\n\tyear = {2022},\n\tpmid = {35428711},\n\tnote = {Publisher: The Journal of Rheumatology\nSection: Accepted Article},\n}\n\n","author_short":["Kiadaliri, A.","Neogi, T.","Englund, M."],"key":"kiadaliri_gout_2022","id":"kiadaliri_gout_2022","bibbaseid":"kiadaliri-neogi-englund-goutandhospitaladmissionforambulatorycaresensitiveconditionsrisksandtrajectories-2022","role":"author","urls":{"Paper":"https://www.jrheum.org/content/early/2022/04/11/jrheum.220038"},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://api.zotero.org/groups/5155143/items?key=IVTAjWy1U5EkGJqE2Z2qQCfh&format=bibtex&limit=100","dataSources":["7PYyrRz6AvkoBBchz","NGDbv8dMYDaDn8kqm","5jEuhQhgRx3py8LmG","LPTeGao77ndnG4Tks"],"keywords":[],"search_terms":["gout","hospital","admission","ambulatory","care","sensitive","conditions","risks","trajectories","kiadaliri","neogi","englund"],"title":"Gout and hospital admission for ambulatory care sensitive conditions:risks and trajectories","year":2022}