id:"swepub:oai:gup.ub.gu.se/317455"
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- Shah, Syed A (author)
Development and validation of a multivariable mortality risk prediction model for COPD in primary care.
- Article/chapterEnglish2022
Publisher, publication year, extent ...
- 2022-05-31
- Springer Science and Business Media LLC,2022
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- LIBRIS-ID:oai:gup.ub.gu.se/317455
- https://gup.ub.gu.se/publication/317455URI
- https://doi.org/10.1038/s41533-022-00280-0DOI
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- Language:English
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- Risk stratification of chronic obstructive pulmonary disease (COPD) patients is important to enable targeted management. Existing disease severity classification systems, such as GOLD staging, do not take co-morbidities into account despite their high prevalence in COPD patients. We sought to develop and validate a prognostic model to predict 10-year mortality in patients with diagnosed COPD. We constructed a longitudinal cohort of 37,485 COPD patients (149,196 person-years) from a UK-wide primary care database. The risk factors included in the model pertained to demographic and behavioural characteristics, co-morbidities, and COPD severity. The outcome of interest was all-cause mortality. We fitted an extended Cox-regression model to estimate hazard ratios (HR) with 95% confidence intervals (CI), used machine learning-based data modelling approaches including k-fold cross-validation to validate the prognostic model, and assessed model fitting and discrimination. The inter-quartile ranges of the three metrics on the validation set suggested good performance: 0.90-1.06 for model fit, 0.80-0.83 for Harrel's c-index, and 0.40-0.46 for Royston and Saurebrei's [Formula: see text] with a strong overlap of these metrics on the training dataset. According to the validated prognostic model, the two most important risk factors of mortality were heart failure (HR 1.92; 95% CI 1.87-1.96) and current smoking (HR 1.68; 95% CI 1.66-1.71). We have developed and validated a national, population-based prognostic model to predict 10-year mortality of patients diagnosed with COPD. This model could be used to detect high-risk patients and modify risk factors such as optimising heart failure management and offering effective smoking cessation interventions.
Subject headings and genre
- MEDICIN OCH HÄLSOVETENSKAP Hälsovetenskap Arbetsmedicin och miljömedicin hsv//swe
- MEDICAL AND HEALTH SCIENCES Health Sciences Occupational Health and Environmental Health hsv//eng
- MEDICIN OCH HÄLSOVETENSKAP Hälsovetenskap Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi hsv//swe
- MEDICAL AND HEALTH SCIENCES Health Sciences Public Health, Global Health, Social Medicine and Epidemiology hsv//eng
- Cohort Studies
- Heart Failure
- Humans
- Primary Health Care
- Proportional Hazards Models
- Pulmonary Disease
- Chronic Obstructive
- diagnosis
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- Nwaru, Bright I,1978Gothenburg University,Göteborgs universitet,Krefting Research Centre(Swepub:gu)xnwabr (author)
- Sheikh, Aziz (author)
- Simpson, Colin R (author)
- Kotz, Daniel (author)
- Göteborgs universitetKrefting Research Centre (creator_code:org_t)
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- In:NPJ primary care respiratory medicine: Springer Science and Business Media LLC32:12055-1010
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