Assessment of health-related quality of life in different phenotypes of COPD

Corlăteanu, Alexandru; Botnaru, Victor; Rusu, Doina; Scutaru, Eugenia; Covanţev, Serghei

doi:10.1183/1393003.congress-2017.pa3581

Cited by 12 publications

(34 citation statements)

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“…8849 patients from ten studies [9][10][11][12][13][14][15][16][17][18] were included, of which 2699 patients with the FE-CB phenotype and 6150 patients with the NE phenotype. Study characteristics are summarized in Table 1.…”

Section: Basic Characteristics Of the Included Studiesmentioning

confidence: 99%

“…Ten studies [9][10][11][12][13][14][15][16][17][18] reported FEV 1 %pred of COPD patients with the FE-CB and NE phenotypes. In nine studies [9][10][11][12][13][14][15][16][17] , the FEV 1 %pred of the FE-CB phenotype was significantly lower than that of the NE phenotype, while one other study [18] found no significant between-group difference in this respect. Owing to significant heterogeneity among the studies, the random-effects model was used for analysis.…”

Section: Fev 1 %Predmentioning

confidence: 99%

“…Six studies [9][10][11][12][13][14] had reported the FVC%pred values of COPD patients with the FE-CB and NE phenotypes. In all six studies, the FVC%pred of patients with the FE-CB phenotype was significantly lower than that of the NE phenotype.…”

Section: Fvc%predmentioning

confidence: 99%

“…Five studies [9][10][11][12]14] had reported FEV 1 /FVC of COPD patients with the FE-CB and NE phenotypes. In three studies [11,12,14] , the FEV 1 /FVC of the FE-CB phenotype was significantly lower than that of the NE phenotype, while two studies [9,10] found no significant between-group difference in this respect. [21] .…”

Section: Fev 1 /Fvcmentioning

confidence: 99%

“…Among all phenotypes, FE-CB was associated with more than three complications [8] . In some studies, patients with the FE-CB phenotype showed lower forced vital capacity percent predicted (FVC%pred) [9][10][11][12][13][14] , forced expiratory volume in one second percent predicted (FEV 1 %pred) [9][10][11][12][13][14][15][16][17] , forced expiratory volume in one second/ forced vital capacity (FEV 1 /FVC) [10][11][12]14] , and forced expiratory volume in one second (FEV 1 ) [14,17] as compared to those with the NE phenotype;…”

mentioning

confidence: 99%

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The characteristics of the frequent exacerbator with chronic bronchitis phenotype and non-exacerbator phenotype in patients with chronic obstructive pulmonary disease: a meta-analysis and system review

Zhang³

et al. 2020

Preprint

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Objective: To investigate the clinical characteristics between the frequent exacerbator with chronic bronchitis (FE-CB) phenotype and the non-exacerbator (NE) phenotype among patients with chronic obstructive pulmonary disease (COPD). Methods: We searched CNKI, Wan fang, Chongqing VIP, China Biology Medicine disc, PubMed, Cochrane Library, and EMBASE databases for relevant studies published as of April 30, 2019. All studies that investigated COPD patients with the FE-CB and NE phenotypes and which qualified the inclusion criteria were included. Cross-Sectional/Prevalence Study Quality recommendations were used to measure methodological quality. RevMan5.3 software was used for meta-analysis. Results: Ten case-control studies (n=8848) were included. Compared with the NE phenotype, patients with the FE-CB phenotype showed significantly lower forced vital capacity percent predicted (FVC%pred) [mean difference (MD) -6.69, 95% confidence interval (CI) -7.73–-5.65, P<0.001, I2=5%], forced expiratory volume in one second percent predicted (FEV1%pred) (MD -8.50, 95% CI -11.36–-5.65, P<0.001, I2=91%), and forced expiratory volume in one second/forced vital capacity (FEV1/FVC) (MD -3.76, 95% CI -4.58–-2.95,P<0.001, I2=0%); in contrast, the quantity of cigarettes smoked (pack-years) (MD 3.09, 95% CI 1.60–4.58, P<0.001, I2=41%), COPD assessment test (CAT) score (MD 5.61, 95% CI 4.62–6.60, P<0.001, I2=80%), modified Medical British Research Council (mMRC) score (MD 0.72, 95% CI 0.63–0.82, P<0.001, I2=57%), exacerbations in previous year (2.65, 95% CI 2.32–2.97, P<0.001, I2=91%), body mass index (BMI), obstruction, dyspnea, exacerbations (BODEx) (MD 1.78, 95% CI 1.28–2.28, P<0.001, I2=91%), I2=34%), and Charlson comorbidity index (MD 0.47, 95% CI 0.37–0.58, P<0.001, I2=0] were significantly higher in patients with FE-CB phenotype. No significant between-group difference was observed with respect to BMI (MD-0.14, 95% CI -0.70–0.42, P=0.62, I2=75%). Conclusion: COPD patients with the FE-CB phenotype had poorer pulmonary function and higher CAT score, the quantity of cigarettes smoked (pack-years), frequency of acute exacerbations, and mMRC scores than those with the NE phenotype.

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Section: Basic Characteristics Of the Included Studiesmentioning

confidence: 99%

Section: Fev 1 %Predmentioning

confidence: 99%

Section: Fvc%predmentioning

confidence: 99%

Section: Fev 1 /Fvcmentioning

confidence: 99%

mentioning

confidence: 99%

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The characteristics of the frequent exacerbator with chronic bronchitis phenotype and non-exacerbator phenotype in patients with chronic obstructive pulmonary disease: a meta-analysis and system review

Zhang³

et al. 2020

Preprint

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Evaluation of dyspnea severity and sleep quality in patients with novel coronavirus

et al. 2021

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Aim Dyspnea, a common symptom of novel coronavirus, can negatively affect sleep quality. The aim of this study was to evaluate the relationship between dyspnea severity and sleep quality in patients with COVID‐19. Study Design A cross‐sectional design was used. Methods Using the researcher's mobile phone, data were collected via an online questionnaire from patients (n = 100) who agreed to participate in the study. The data‐collection form comprised three parts: a patient descriptive information form, the Dyspnea–12 Questionnaire, and the Richards–Campbell Sleep Questionnaire (RCSQ). Results The mean age of patients was 46.39 ± 12.61 years and 66.0% were men. Patients who were treated in the intensive care unit had bachelor's degree or more and patients with comorbid diseases had low mean scores from the RCSQ and high mean scores from the Dyspnea–12 Questionnaire ( P < .001, P < .001; P = .047, P < .001; P < .001, P < .001, respectively). Patients who were not receiving oxygen therapy had higher RCSQ mean scores and lower Dyspnea–12 Questionnaire scores ( P < .001, P < .001; P < .001, P < .001, respectively). There was a strong negative relationship between the total scores obtained from the RCSQ and the Dyspnea–12 Questionnaire ( r = −.701, P < .001). Conclusions Sleep quality is affected by dyspnea severity in patients with COVID‐19. Sleep quality and dyspnea severity are also influenced by quite different factors, and these should be addressed and eliminated by nurses as part of a holistic approach. The results of this study will help nurses, especially those providing treatment and care for patients with COVID‐19, to identify the factors affecting dyspnea and sleep quality and to plan, implement and evaluate nursing interventions that will reduce their workload.

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Clinical phenotypes and heath-related quality of life of COPD patients in a rural setting in Malaysia – a cross-sectional study

Chai

Mos

et al. 2020

BMC Pulm Med

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Background The Spanish chronic obstructive pulmonary disease (COPD) guideline phenotypes patients according to the exacerbation frequency and COPD subtypes. In this study, we compared the patients’ health-related quality of life (HRQoL) according to their COPD phenotypes. Methods This was a cross-sectional study of COPD patients who attended the outpatient clinic of the Serian Divisional Hospital and Bau District Hospital from 23th January 2018 to 22th January 2019. The HRQoL was assessed using modified Medical Research Council (mMRC), COPD Assessment Test (CAT), and St George’s Respiratory Questionnaire for COPD (SGRQ-c). Results Of 185 patients, 108 (58.4%) were non-exacerbators (NON-AE), 51 (27.6%) were frequent exacerbators (AE), and the remaining 26 (14.1%) had asthma-COPD overlap (ACO). Of AE patients, 42 (82.4%) had chronic bronchitis and only 9 (17.6%) had emphysema. Of the 185 COPD patients, 65.9% had exposure to biomass fuel and 69.1% were ex- or current smokers. The scores of mMRC, CAT, and SGRQ-c were significantly different between COPD phenotypes (p < 0.001). There were significantly more patients with mMRC 2–4 among AE (68.6%) (p < 0.001), compared to those with ACO (38.5%) and NON-AE (16.7%). AE patients had significantly higher total CAT (p = 0.003; p < 0.001) and SGRQ-c (both p < 0.001) scores than those with ACO and NON-AE. Patients with ACO had significantly higher total CAT and SGRQ-c (both p < 0.001) scores than those with NON-AE. AE patients had significantly higher score in each item of CAT and component of SGRQ-c compared to those with NON-AE (all p < 0.001), and ACO [(p = 0.003–0.016; p = < 0.001–0.005) except CAT 1, 2 and 7. ACO patients had significantly higher score in each item of CAT and component of SGRQ-c (p = < 0.001–0.040; p < 0.001) except CAT 2 and activity components of SGRQ-c. Conclusions The HRQoL of COPD patients was significantly different across different COPD phenotypes. HRQoL was worst in AE, followed by ACO and NON-AE. This study supports phenotyping COPD patients based on their exacerbation frequency and COPD subtypes. The treatment of COPD should be personalised according to these two factors.

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Assessment of health-related quality of life in different phenotypes of COPD

Cited by 12 publications

References 0 publications

The characteristics of the frequent exacerbator with chronic bronchitis phenotype and non-exacerbator phenotype in patients with chronic obstructive pulmonary disease: a meta-analysis and system review

The characteristics of the frequent exacerbator with chronic bronchitis phenotype and non-exacerbator phenotype in patients with chronic obstructive pulmonary disease: a meta-analysis and system review

Evaluation of dyspnea severity and sleep quality in patients with novel coronavirus

Clinical phenotypes and heath-related quality of life of COPD patients in a rural setting in Malaysia – a cross-sectional study

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