Factors associated with depression and severe depression in patients with COPD

Miravitlles, Marc; Molina, Jesús; Quintano, José Antonio; Campuzano, Anna; Pérez, Joselín; Roncero, Carlos; Investigators, Deprepoc Study

doi:10.1016/j.rmed.2014.08.010

Cited by 71 publications

(64 citation statements)

References 38 publications

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“…2013 [16]State-Trait Anxiety Inventory (anxiety)Beck Depression Inventory (depression)Brief Fatigue Inventory (fatigue)SGRQ (COPD symptoms)UCSD Shortness of Breath Questionnaire (dyspnea)6MWT (functional capacity)Anxiety and depression associated with higher fatigue, dyspnea, and frequency of COPD symptoms (all p < 0.001); more so in patients with lower functional capacity ( p = 0.02–0.009) Miravitlles et al Respir Med. 2014 [44]Beck Depression Inventory (depression)mMRC scale (dyspnea)Greater dyspnea in patients with depression vs no depression (mean dyspnea grade: 2.07 vs 1.32; p < 0.0001) Miravitlles et al Respir Res. 2014 [3]HADS (depression)Patient questionnaire (COPD symptoms time of day)Experiencing symptoms in the morning, daytime, and nighttime was associated with anxiety and depression ( p < 0.001) Martinez Rivera et al Lung 2016 [45]HADS (depression)MRC scale (dyspnea)Greater dyspnea in patients with depression Sleep Partridge et al Curr Med Res Opin.…”

Section: Discussionmentioning

confidence: 99%

“…Two observational, cross-sectional, multicenter studies investigating factors associated with depression and anxiety in COPD found that patients with depression had greater dyspnea that those without. In the DEPREPOC (Depression in Chronic Obstructive Pulmonary Disease) study of 836 patients (83% male; mean age, 68.3 years), depressive symptoms were measured using the Beck Depression Inventory questionnaire and the study found that the presence of depression in patients with COPD was associated with greater dyspnea as measured by the modified Medical Research Council dyspnea scale (depression, 2.07; no depression, 1.32; p < 0.0001) [44]. Furthermore, an observational study conducted in 115 patients with stable COPD found that patients with depression (measured by the Hospital Anxiety and Depression Scale [HADS]) showed greater dyspnea compared with patients without depression [45].…”

Section: Impact Of Copd Symptoms On Anxiety and Depressionmentioning

confidence: 99%

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Understanding the impact of symptoms on the burden of COPD

2017

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Chronic obstructive pulmonary disease (COPD) imposes a substantial burden on individuals with the disease, which can include a range of symptoms (breathlessness, cough, sputum production, wheeze, chest tightness) of varying severities. We present an overview of the biomedical literature describing reported relationships between COPD symptoms and disease burden in terms of quality of life, health status, daily activities, physical activity, sleep, comorbid anxiety, and depression, as well as risk of exacerbations and disease prognosis. In addition, the substantial variability of COPD symptoms encountered (morning, daytime, and nighttime) is addressed and their implications for disease burden considered. The findings from this narrative review, which mainly focuses on real-world and observational studies, demonstrate the impact of COPD symptoms on the burden of disease and that improved recognition and understanding of their impact is central to alleviating this burden.

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Section: Discussionmentioning

confidence: 99%

Section: Impact Of Copd Symptoms On Anxiety and Depressionmentioning

confidence: 99%

Understanding the impact of symptoms on the burden of COPD

2017

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Section: Number and Type Of Comorbiditiesmentioning

confidence: 96%

“…202,206,221 The greatest differences were found between those with and without depression. Both Martinez Rivera et al 202 and Miravitlles et al 206 found that patients with COPD and depression had a lower mean HSUV than patients with COPD only (0.40 and 0.55 vs. 0.76 and 0.83, respectively). Miravitlles et al 221 also found that those with comorbid cardiovascular disease had a lower mean HSUV (0.78) than patients with COPD only (0.82); however, no differences were found for patients with and without diabetes, and patients with comorbid haematological malignancies had similar HSUVs.…”

Section: Number and Type Of Comorbiditiesmentioning

confidence: 96%

The health impacts of energy performance investments in low-income areas: a mixed-methods approach

et al. 2018

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BackgroundCold homes and fuel poverty contribute to health inequalities in ways that could be addressed through energy efficiency interventions.ObjectivesTo determine the health and psychosocial impacts of energy performance investments in low-income areas, particularly hospital admissions for cardiorespiratory conditions, prevalence of respiratory symptoms and mental health status, hydrothermal conditions and household energy use, psychosocial outcomes, cost consequences to the health system and the cost utility of these investments.DesignA mixed-methods study comprising data linkage (25,908 individuals living in 4968 intervention homes), a field study with a controlled pre-/post-test design (intervention,n = 418; control,n = 418), a controlled multilevel interrupted time series analysis of internal hydrothermal conditions (intervention,n = 48; control,n = 40) and a health economic assessment.SettingLow-income areas across Wales.ParticipantsResidents who received energy efficiency measures through the intervention programme and matched control groups.Main outcome measuresPrimary outcomes – emergency hospital admissions for cardiorespiratory conditions, self-reported respiratory symptoms, mental health status, indoor air temperature and indoor relative humidity. Secondary outcomes – emergency hospital admissions for chronic obstructive pulmonary disease-related cardiorespiratory conditions, excess winter admissions, health-related quality of life, subjective well-being, self-reported fuel poverty, financial stress and difficulties, food security, social interaction, thermal satisfaction and self-reported housing conditions.MethodsAnonymously linked individual health records for emergency hospital admissions were analysed using mixed multilevel linear models. A quasi-experimental controlled field study used a multilevel repeated measures approach. Controlled multilevel interrupted time series analyses were conducted to estimate changes in internal hydrothermal conditions following the intervention. The economic evaluation comprised cost–consequence and cost–utility analyses.Data sourcesThe Patient Episode Database for Wales 2005–14, intervention records from 28 local authorities and housing associations, and scheme managers who delivered the programme.ResultsThe study found no evidence of changes in physical health. However, there were improvements in subjective well-being and a number of psychosocial outcomes. The household monitoring study found that the intervention raised indoor temperature and helped reduce energy use. No evidence was found of substantial increases in indoor humidity levels. The health economic assessment found no explicit cost reductions to the health service as a result of non-significant changes in emergency admissions for cardiorespiratory conditions.LimitationsThis was a non-randomised intervention study with household monitoring and field studies that relied on self-response. Data linkage focused on emergency admissions only.ConclusionAlthough there was no evidence that energy performance investments provide physical health benefits or reduce health service usage, there was evidence that they improve social and economic conditions that are conducive to better health and improved subjective well-being. The intervention has been successful in reducing energy use and improving the living conditions of households in low-income areas. The lack of association of emergency hospital admissions with energy performance investments means that we were unable to evidence cost saving to health-service providers.Future workOur research suggests the importance of incorporating evaluations with follow-up into intervention research from the start.FundingThe National Institute for Health Research Public Health Research programme.

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“…Finally, the Charlson's comorbidity index may not include all potential physical conditions related with depression. Despite this, previous study [51] had already demonstrated that Charlson's index is significantly associated with depression and could therefore reflect the impact of comorbidities toward depression. Besides, the confounding effect of comorbidities is unlikely a result of the similarity of Charlson's index between the COPD and control groups.…”

Section: Strengths and Limitationsmentioning

confidence: 83%