Correlates of residual fatigue in patients with major depressive disorder: The role of psychotropic medication

Chung, Ka Fai; Yu, Branda Yee Man; Yeung, Wing‐Fai

doi:10.1016/j.jad.2015.07.026

Cited by 22 publications

(12 citation statements)

References 38 publications

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“…Because the DDD of sedatives could not represent properly the clinical usage of benzodiazepines as anxiolytics or hypnotics (34), this study converted all types of sedatives into equivalent dose of lorazepam, according to the Ashton manual (35). The method of equivalent conversion has been widely used in clinical studies (36–38), clinical practice (39, 40), and epidemiological studies (34). The equivalent doses not provided in the original Ashton manual, including brotizolam, midazolam, oxazolam, and fludiazepam, were determined following the consensus of all researchers involved in the present study.…”

Section: Methodsmentioning

confidence: 99%

The Association Between the Sedative Loads and Clinical Severity Indicators in the First-Onset Major Depressive Disorder

Wang

Lin

et al. 2019

Front. Psychiatry

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Background: High sedative use in a major depressive episode may imply specific clinical features. This study aims to examine the correlation between sedative use and clinical severity indicators in the initial treatment phase of first-onset major depressive disorder.Methods: A study cohort in the first episode of major depressive disorder was used to conduct pharmacological dissection. All participants had at least a 2-year follow-up period with a complete treatment record. The defined daily dose of antidepressants and augmentation agents were calculated as the antidepressant load and augmentation load, respectively. Sedative use, which was calculated as the equivalent dosage of lorazepam, were defined as the sedative load. These psychotropic loads were measured monthly and the averaged psychotropic loads for each day were obtained.Results: A total of 106 individuals (75.5% female) were included. The mean duration of disease course in participants was 5.5 ± 3.5 years. In the multiple regression analysis, after controlling for other classes of psychotropics and comorbid anxiety disorders, the sedative load independently correlated with higher number of antidepressants used, higher number of antidepressant used with an adequate dose and duration, more psychiatric emergency and outpatient visits within 2 years of disease onset.Conclusion: High loading of sedatives correlated with several indicators of clinical severity in major depressive disorder. The sedative load may be used as a specifier to identify subgroups in patients with major depressive disorder.

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Section: Methodsmentioning

confidence: 99%

The Association Between the Sedative Loads and Clinical Severity Indicators in the First-Onset Major Depressive Disorder

Wang

Lin

et al. 2019

Front. Psychiatry

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“…The neurocognitive profile of our Narc2/IH group with a dominant deficit in sustaining attention and intact complex attention functions matches with the findings in ADHD quite well (Marchetta et al, 2008). The sEDS group with widespread cognitive deficits would rather fit to CFS (Neu et al, 2014;Sulheim et al, 2015) or a depressive disorder (Baldwin and Papakostas, 2006;Chung et al, 2015). However, the more reliable correlation between the ESS and cognitive impairment in our study and the fact that patients with sEDS and patients with oEDS did not differ in respect to the severity of fatigue and depressive symptoms challenge this hypothesis.…”

Section: Can the Waf Tests Distinguish Different Types Of Chronic Eds?mentioning

confidence: 99%

The Perception and Attention Functions test battery as a measure of neurocognitive impairment in patients with suspected central disorders of hypersomnolence

Ramm

Jafarpour

Boentert

et al. 2017

Journal of Sleep Research

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The aim of the current study was to evaluate an attention test as a discriminative tool to measure neurocognitive impairment in patients with disorders of hypersomnolence. Chronic excessive daytime sleepiness is the main symptom in central disorders of hypersomnolence. For diagnostic purposes and treatment evaluation, reliable assessment of excessive daytime sleepiness is required. Thirty-six patients with central disorders of hypersomnolence were compared with 20 healthy controls. All participants performed the 'Perception and Attention Functions' (WAF) of the Vienna Test System. Patients underwent polysomnography, Multiple Sleep Latency Test and Maintenance of Wakefulness Test. Patients were divided into two groups: (i) patients who met the criteria of disorder of hypersomnolence (objective excessive daytime sleepiness); and (ii) patients with subjective excessive daytime sleepiness, i.e. with normal Multiple Sleep Latency Test results. Group 1 consisted of 23 patients with objective excessive daytime sleepiness (11 with idiopathic hypersomnia, nine with narcolepsy type 1, three with narcolepsy type 2); group 2 included 13 patients with subjective excessive daytime sleepiness. The results showed cognitive impairment in patients with objective excessive daytime sleepiness and even in patients with subjective excessive daytime sleepiness. WAF tests identified distinct attention profiles in patients with narcolepsy type 1, idiopathic hypersomnia/narcolepsy type 2, and patients with subjective excessive daytime sleepiness. WAF test measures correlated with Maintenance of Wakefulness Test and the Epworth Sleepiness Scale, but not with Multiple Sleep Latency Test and the Fatigue Severity Scale. In conclusion, the multidimensional WAF test battery detects cognitive impairment even in patients that complain of excessive daytime sleepiness but have normal Multiple Sleep Latency Test results. WAF tests offer valuable information that adds to the existing polysomnographic measures in discriminating patients with different types of chronic excessive daytime sleepiness. The results provide new insights into cognitive dysfunction underlying different types of chronic excessive daytime sleepiness.

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“…It is not only a physiological manifestation of the body's self-regulation, but also a pathological result of a symptom in some disease states [1] .Study found that more than 50 percent of people were suffered from chronic fatigue and more than 30 percent suffered from fatigue which has a serious impact on their living standards and work e ciency [2] .Some studies have de ned fatigue as a symptom of disabling participants with limited physical and mental perception, which is a unique, complex, multifactorial and heterogeneous physiological and pathological state [3] .Fatigue is a kind of non-speci c symptom and have certain heritability [4] ,which has become one of the main factors that harmful to human's physical and mental health. It is ubiquitous in sub-health and various diseases, such as parkinson [5] ,major depressive disorder [6],schizophrenia [7],cancer [8], which affects human's health, work e ciency and quality of life seriously. Studies have shown that chronic fatigue was most common among women and caucasians and signi cantly related to depression, mixed anxiety and depressive disorder, and generalized anxiety disorder [9] .The etiology and pathogenesis of fatigue are largely unknown.…”

Section: Introductionmentioning

confidence: 99%

Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population

Shi

Cui

et al. 2020

Preprint

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BackgroundFatigue is a kind of non-specific symptom, which is widely found in sub-health and various diseases. It is closely related to people's physical and mental health.Due to lack of objective evidence, it is often neglected in clinical diagnosis,especially in the early stage of disease.A large number of clinical practices and studies have shown that tongue and pulse image are reflection of overall state of the body.Establishing an objective evaluation method for diagnosis of disease fatigue and non-disease fatigue by combining clinical symptom and index and tongue and pulse data is of great significance for timely and effective clinical treatment.MethodsIn this study, 2362 physical examination subjects were divided into healthy control, the group of sub-health fatigue and disease fatigue ,used complex network technology to screen out the core symptoms and western medicine indexes of fatigue,respectively. Constructed the core symptom network and the core symptom-index network. At the same time, used canonical correlation analysis to get the associated relationship of tongue and pulse, and analyzed the characteristic of the tongue and pulse data.ResultsThere were some similarities between the core symptoms of sub-health fatigue and disease fatigue,as well as differences. Symptom-index associated analysis of disease fatigue showed that the core indexes in the group of disease fatigue group had a significant canonical correlation, with the canonical correlation coefficient was 0.42 (P < 0.05). There was no statistically significant correlation between the tongue and pulse data in sub-health fatigue group.ConclusionsThe complex network technology was suitable for the correlation analysis of symptoms and indexes in the fatigue population, and the tongue and pulse objective data had certain diagnostic contribution to the classification of fatigue population.Name of the registry: Chinese Clinical Trial RegistryTrial registration number: ChiCTR-IOR-15006502; ChiCTR1900026008Date of registration: Jun. 04th, 2015URL of trial registry record:http://www.chictr.org.cn/showprojen.aspx?proj=11119;http://www.chictr.org.cn/edit.aspx?pid=38828&htm=4 (This is a retrospective registration)

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Correlates of residual fatigue in patients with major depressive disorder: The role of psychotropic medication

Cited by 22 publications

References 38 publications

The Association Between the Sedative Loads and Clinical Severity Indicators in the First-Onset Major Depressive Disorder

The Association Between the Sedative Loads and Clinical Severity Indicators in the First-Onset Major Depressive Disorder

The Perception and Attention Functions test battery as a measure of neurocognitive impairment in patients with suspected central disorders of hypersomnolence

Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population

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