Quality of life and symptom experience measurement tools in adults with atrial fibrillation

Abstract Background Prevalence of hearing loss increases with age. Its estimated prevalence is 40–50 % in people over 75 years of age. Recent studies agree that declinein hearing threshold contribute to deterioration in sociality, sensitivity, cognition, and quality of life for elderly subjects. The aim of the study presented in this paper is to verify whether or not rehabilitation using first time applied Hearing Aids (HA) in a cohort of old people with hearing impairment improves both speech perception in a noisy environment over time and the overall health-related quality of life. Methods The monocentric, prospective, repeated measurements, single-subject, clinical observational study is to recruit 100 older adults, first-time HA recipients (≥ 65 years).The evaluation protocol is designed to analyze changes in specific measurement tools a year after the first HA usage in comparison with the evaluation before HA fitting. Evaluations will consist of multiparametric details collected through self-report questionnaires completed by the recipients and a series of commonly used audiometric measures and geriatric assessment tools. The primary indicator of changes in speech perception in noise to be used is the Italian version of Oldenburg Satz (OLSA) test whereas the indicator of changes in overall quality of life will be the Assessment of Quality of Life (AQoL) and Hearing Handicap Inventory for the Elderly (HHIE) questionnaires. The Montreal Cognitive Assessment (MoCA) will help in screening the cognitive state of the subjects. Discussion The protocol is designed to make use of measurement tools that have already been applied to the hearing-impaired population in order to compare the effects of HA rehabilitation in the older adults immediately before first HA usage (Pre) and after 1 year of experience (Post). This broad approach will lead to a greater understanding of how useful hearing influences the quality of life in older individuals, and therefore improves potentials for healthy aging. The data is to be analyzed by using an intrasubject endpoint comparison. Outcomes will be described and analyzed in detail. Trial registration This research was retrospectively registered underno. NCT04333043at ClinicalTrials.gov (http://www.clinicaltrials.gov/) on the 26 March 2020. This research has been registered with the Ethics Committee of the Area Vasta Emilia Nord under number 104, date of approval 17/07/2017.

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Anxiety-depressive disorders and quality of life in patients with atrial fibrillation

European Heart Journal ◽

10.1093/ehjci/ehaa946.0384 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

T Demenko ◽

G.A Chumakova

Keyword(s):

Quality Of Life ◽

Physical Activity ◽

Atrial Fibrillation ◽

Correlation Analysis ◽

Depressive Disorders ◽

Life Assessment ◽

Mild Depression ◽

Group 2 ◽

Group 1

Abstract Background Mental disorders in patients with cardiovascular disease have a significant impact on the course, the prognosis of the underlying disease and quality of life (QOL). Objective We aimed to examine the prevalence of anxiety and depressive disorders and their impact on the quality of life in patients with atrial fibrillation (AF). Materials and methods In 52 with permanent AF and 50 with paroxysmal AF patients, we administered the depression scale Tsung, the scale of situational anxiety (SA) and personal anxiety (PA) Spielberger-Hanin; QOL was assessed the SF-36 quality of life assessment scale. Correlation analysis using Spearman's rank correlation coefficient. Results The prevalence symptoms mild depression situational or neurotic genesis was 21.1% (12 patients) in Group 1 and 12.0% (6 patients) in Group 2 (p>0.05). Subdepressive state was two percents of patients in Group 1 and Group 2. The incidence SA was 59.6% (31 patients) in Group 1 and 52.0% (26 patients) in Group 2. The incidence PA was 74.0% (37 patients) in Group 2 and 67.3% (35 patients) in Group 1. The average score the physical component of health (PCH) was 29,8±4,3 in Group 1, the mental component of health (MCH) – 49.5±7.4 points; p<0.05. In Group 2: PCH – 44.8±6.6 points, MCH – 26.6±7.5 points; p<0.05. Correlation analysis showed negative strong correlations between SA and MCH (r=−0.64, p=0.0005) and between PA and MCH (r=−0.69, p<0.0001), between SA and PCH (r=−0.71, p=0.0001), between depression and PCH (r=−0.69, p=0.023). Negative statistically significant correlation between depression and MCH (r=−0.69, p=0.54) and negative medium correlation between depression and PCH (r=−0.64, p=0.23). Conclusion These findings suggest that we did not identify patients with symptoms of a true depressive (that can cause pseudodementia and influenced to complete tests). 16.5% patients with AF had mild depression of situational or neurotic genesis. Depression may be a pathogenetic factor of AF or develop because of paroxysms AF – psychological stress. More than 50% patients in Group 1 and Group 2 had an increased anxiety score. SA is more common in patients with permanent AF, probably because older people difficult to adapt to a new situation. PA is more common in patient with paroxysmal AF, probably because disease is sudden and causes anxiety. The PCH of QOL is more impairment in patients with permanent AF, because complications (for example heart failure) impairment physical activity. However, PCH also reduced in patient with paroxysmal AF, because disease is sudden may occur during physical activity. The MCH of QOL is more impairment in patients with paroxysmal AF, because waiting attack effect on mental health and social functioning. An increased level of anxiety and depression negatively affected the mental and physical health of patients with AF. Funding Acknowledgement Type of funding source: None

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Exploratory study into the relationship between the symptoms of chronic fatigue syndrome (CFS)/myalgic encephalomyelitis (ME) and fibromyalgia (FM) using a quasiexperimental design

BMJ Open ◽

10.1136/bmjopen-2020-041947 ◽

2021 ◽

Vol 11 (2) ◽

pp. e041947

Author(s):

Pamela G Mckay ◽

Helen Walker ◽

Colin R Martin ◽

Mick Fleming

Keyword(s):

Quality Of Life ◽

Chronic Fatigue Syndrome ◽

Chronic Fatigue ◽

Myalgic Encephalomyelitis ◽

Anxiety And Depression ◽

Symptom Experience ◽

Fatigue Syndrome ◽

The Impact ◽

The Relationship

ObjectiveTo explore the relationship between symptoms of chronic fatigue syndrome (CFS)/myalgic encephalomyelitis (ME) and fibromyalgia (FM). The hypothesis predicated that there would be no significant differences between the group’s symptom experience.DesignA quasiexperimental design. Structural equation modelling (SEM) and invariance testing.ParticipantsMales (M) and females (F) >16 with a confirmed diagnosis of CFS/ME or FM by a general practitioner or specialist. CFS/ME (n=101, F: n=86, M: n=15, mean (M) age M=45.5 years). FM (n=107, F: n=95, M: n=12, M=47.2 years).Outcome measuresDiagnostic criteria: the American Centers for Disease Control and Prevention (CDC) for CFS/ME and the American College of Rheumatology (ACR) criteria for FM. Additional symptom questionnaires measuring: pain, sleep quality, fatigue, quality of life, anxiety and depression, locus of control and self-esteem.ResultsInvariance was confirmed with the exception of the American CDC Symptom Inventory, Fibromyalgia Impact Questionnaire and Hospital Anxiety and Depression Scale (p<0.05) based on five questions. Consequently, it was erroneous to conclude differences. Therefore, the Syndrome Model was created. SEM could not have tested the ACR previously, as it comprised a single data point. Thus, it was combined with these three questionnaires, increasing the data points, to create this new measurable model. Results confirmed no significant differences between groups (p=0.07 (p<0.05)).ConclusionParticipants responded in a similar manner to the questionnaire, confirming the same symptom experience. It is important to consider this in context with differing criteria and management guidelines, as this may influence diagnosis and the trajectory of patient’s management. With the biomedical cause currently unclear, it is the symptom experience and the impact on quality of life that is important. These findings are meaningful for patients, clinicians and policy development and support the requirement for future research.

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