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      Modified and simplified clinically important deterioration: multidimensional indices of short-term disease trajectory to predict future exacerbations in patients with chronic obstructive pulmonary disease

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          Abstract

          Background and aims:

          Various prediction indices based on the single time point observation have been proposed in chronic obstructive pulmonary disease (COPD), but little was known about disease trajectory as a predictor of future exacerbations. Our study explored the association between disease trajectory and future exacerbations, and validated the predictive value of the modified and simplified short-term clinically important deterioration (CID).

          Methods:

          This study was a multicenter, prospective observational study. Patients with COPD were recruited into our study and followed up for 18 months. The modified CID (CID-C) was defined as a decrease of 100 mL in forced expiratory volume in 1 second (FEV1), or suffering exacerbations, or increase of 2 units in COPD Assessment Test (CAT) during the first 6 months follow-up. Simplified CID was defined when excluding CAT from the CID-C model.

          Results:

          A total of 127 patients were enrolled in our final analysis. Compared with patients without exacerbations during the period of the 6th to the 18th month, patients with exacerbations were more likely to have frequent short-term exacerbations in the first 6 months (2.14 versus 0.21, p < 0.001). The short-term exacerbations were the best predictor for future exacerbations [odds ratio (OR): 13.25; 95% confidence interval: 5.62–34.67; p < 0.001], followed by the history of exacerbation before study entry, short-term changes in FEV1 and CAT. CID-C and Simplified CID were both significantly associated with exacerbations (OR: 7.14 and 9.74, both p < 0.001). The receiver operating characteristic curves showed that the Simplified CID had slightly better predictive capacity for future exacerbation than CID-C (0.754 versus 0.695, p = 0.02).

          Conclusion:

          Disease trajectory, including both the CID-C and the Simplified CID had significant predictive value for future exacerbations.

          The reviews of this paper are available via the supplemental material section.

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          Most cited references25

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          Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

          Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Susceptibility to exacerbation in chronic obstructive pulmonary disease.

            Although we know that exacerbations are key events in chronic obstructive pulmonary disease (COPD), our understanding of their frequency, determinants, and effects is incomplete. In a large observational cohort, we tested the hypothesis that there is a frequent-exacerbation phenotype of COPD that is independent of disease severity. We analyzed the frequency and associations of exacerbation in 2138 patients enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study. Exacerbations were defined as events that led a care provider to prescribe antibiotics or corticosteroids (or both) or that led to hospitalization (severe exacerbations). Exacerbation frequency was observed over a period of 3 years. Exacerbations became more frequent (and more severe) as the severity of COPD increased; exacerbation rates in the first year of follow-up were 0.85 per person for patients with stage 2 COPD (with stage defined in accordance with Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages), 1.34 for patients with stage 3, and 2.00 for patients with stage 4. Overall, 22% of patients with stage 2 disease, 33% with stage 3, and 47% with stage 4 had frequent exacerbations (two or more in the first year of follow-up). The single best predictor of exacerbations, across all GOLD stages, was a history of exacerbations. The frequent-exacerbation phenotype appeared to be relatively stable over a period of 3 years and could be predicted on the basis of the patient's recall of previous treated events. In addition to its association with more severe disease and prior exacerbations, the phenotype was independently associated with a history of gastroesophageal reflux or heartburn, poorer quality of life, and elevated white-cell count. Although exacerbations become more frequent and more severe as COPD progresses, the rate at which they occur appears to reflect an independent susceptibility phenotype. This has implications for the targeting of exacerbation-prevention strategies across the spectrum of disease severity. (Funded by GlaxoSmithKline; ClinicalTrials.gov number, NCT00292552.)
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              Development and first validation of the COPD Assessment Test.

              There is need for a validated short, simple instrument to quantify chronic obstructive pulmonary disease (COPD) impact in routine practice to aid health status assessment and communication between patient and physician. Current health-related quality of life questionnaires provide valid assessment of COPD, but are complex, which limits routine use. The aim of the present study was to develop a short validated patient-completed questionnaire, the COPD Assessment Test (CAT), assessing the impact of COPD on health status. 21 candidate items identified through qualitative research with COPD patients were used in three prospective international studies (Europe and the USA, n = 1,503). Psychometric and Rasch analyses identified eight items fitting a unidimensional model to form the CAT. Items were tested for differential functioning between countries. Internal consistency was excellent: Cronbach's alpha = 0.88. Test re-test in stable patients (n = 53) was very good (intra-class correlation coefficient 0.8). In the sample from the USA, the correlation with the COPD-specific version of the St George's Respiratory Questionnaire was r = 0.80. The difference between stable (n = 229) and exacerbation patients (n = 67) was five units of the 40-point scale (12%; p<0.0001). The CAT is a short, simple questionnaire for assessing and monitoring COPD. It has good measurement properties, is sensitive to differences in state and should provide a valid, reliable and standardised measure of COPD health status with worldwide relevance.
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                Author and article information

                Contributors
                Journal
                Ther Adv Respir Dis
                Ther Adv Respir Dis
                TAR
                sptar
                Therapeutic Advances in Respiratory Disease
                SAGE Publications (Sage UK: London, England )
                1753-4658
                1753-4666
                23 December 2020
                Jan-Dec 2020
                : 14
                : 1753466620977376
                Affiliations
                [1-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [2-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [3-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [4-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [5-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [6-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [7-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [8-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [9-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [10-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [11-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [12-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [13-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [14-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [15-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [16-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [17-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [18-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [19-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [20-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan, China
                [21-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan, China
                [22-1753466620977376]Division 4 of Occupational Disease, Hunan Occupational Disease Prevention and Treatment Hospital, Changsha, Hunan, China
                [23-1753466620977376]Department of Respiratory and Critical Care medicine, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China
                [24-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second People’s Hospital of Guilin, Guilin, Guangxi, China
                [25-1753466620977376]Department of Respiratory and Critical Care Medicine, The Third Hospital of Changsha, Changsha, Hunan, China
                [26-1753466620977376]Department of Respiratory and Critical Care Medicine, No.1 Traditional Chinese Medicine Hospital of Changde City, Changde, Hunan, China
                [27-1753466620977376]Department of Respiratory and Critical Care Medicine, The First People’s Hospital of Huaihua City, Huaihua, Hunan, China
                [28-1753466620977376]Department of Respiratory and Critical Care Medicine, The Second Xiangya Hospital, Central South University, 139 Renmin Middle Road, Changsha, Hunan 410011, China
                [29-1753466620977376]Research Unit of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
                [30-1753466620977376]Diagnosis and Treatment Center of Respiratory Disease, Central South University, Changsha, Hunan 410011, China
                Author notes
                Author information
                https://orcid.org/0000-0001-5975-8025
                Article
                10.1177_1753466620977376
                10.1177/1753466620977376
                7768878
                33357117
                0b4a5302-0041-41ec-8902-5b4bc77578e7
                © The Author(s), 2020

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 9 May 2020
                : 4 November 2020
                Funding
                Funded by: National Natural Science Foundation of China, FundRef https://doi.org/10.13039/501100001809;
                Award ID: 81770046
                Funded by: National Natural Science Foundation of China, FundRef https://doi.org/10.13039/501100001809;
                Award ID: 81970044
                Funded by: Hunan Provincial Innovation Foundation for Postgraduate, FundRef https://doi.org/10.13039/501100010083;
                Award ID: CX20190157
                Categories
                Original Research
                Custom metadata
                January-December 2020
                ts1

                chronic obstructive pulmonary disease,clinically important deterioration,exacerbation,predictor,prevention

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