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Background: Mental health related symptoms are common among the population. Current treatment exhibits serious adverse effects, delayed onset of action and low efficacy. Ashwagandha has a variety of beneficial effects in mental health disorders. We did a comparison of two Ashwagandha brands using a variety of scales for anxiety, depression, stress, and sleep quality. Methods: The study was conducted in 80 patients suffering from mental health related symptoms. Test product used was: Herbochem +91 Ashwagandha 500 mg capsules and control used was: KSM 66 Ashwagandha 600 mg capsules. Results: The reduction in the perceived stress scores and Hamilton depression scale scores at day 30/60 from day 0 was higher in the test group as compared with the control group. The reduction in the Beck抯 anxiety inventory scores at day 30/60/90 from day 0 was higher in the test group as compared with the control group. The increase in the Pittsburgh sleep quality index scores at day 30/60 from day 0 was higher in the test group as compared with the control group. The reduction in the serum cortisol scores at day 30 from day 0 was higher in the test group as compared with the control group. Results showed that, the incidence of adverse events was same in both groups. Conclusions: It is important to note that test product having 500 mg Ashwagandha, showed better efficacy as compared to control product having 100 mg more (600 mg) of Ashwagandha.
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Background: Adequate sleep is an essential element for maintaining good health. Sleep disturbances in the general community particularly among university students are an essential health problem to be addressed. "Sleep disturbance" is defined by the sleep foundation as an interruption of sleep that results in arousal or awakening. The goal of this study was to ascertain the prevalence of sleep disruptions and the factors related to sleep. Methods: This was a cross-sectional study, conducted among 256 college-going students. A self-administered questionnaire was used to collect data, which was pre-tested and pre-designed. Descriptive and analytical statistics were utilized, with analytical statistics being conducted using the Chi-square test and binomial logistic regression to find the risk factors associated with sleep disturbances. Results: Out of 256 students, 161 (62.9%) were suffering from sleep disturbances. A majority of participants preferred to sleep after 10 pm. The mean hours of sleep received by 256 participants were 6.67 hours. A strong significant association was found between sleep disturbances and any stress in life affecting sleep, sleep quality after COVID-19, worried about test and exams, smoking, have a bed partner or roommate, Illness during past month and papers, assignments and research papers due. Conclusions: The present study reported a high prevalence of students having sleep disturbance irrespective of their socio-demographic characteristics. Sleep disturbance was increased having to worries due to exams, any illness or having stress of any kind in their lives. The study suggests some measures should be taken to create quality sleep-friendly environment for students reducing academic stress and encouraging healthy life style.
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Background: Aim of this study was to study sleep disturbances in frontline healthcare workers during COVID-19 epidemic. Methods: This is a case control study was conducted in the Department of Physiology at Pt. B. D. Sharma PGIMS, Rohtak. The study included hundred volunteer subjects of age group 25-35years and were divided into two groups (healthcare workers and and professionals from non-medical background). Results: Subjective sleep quality was significantly altered in FHCW with P value of 0.001. Sleep latency was increased in study group with 50% of study group having score of 3 on Pittsburg sleep quality index. The duration of sleep was reduced in study group with increased sleep disturbances. Forty percent of FHCW reported use of medications for sleep. Almost 100% of FHCW reported Day time dysfunction. Conclusions: COVID-19 resulted in significant sleep deprivation, increased latency, poor sleep quality and increased use of medication in FHCW. The FHCW suffered from poor quality of sleep during the COVID pandemic. FHCW were affected by several stress factors including heavy workload, high night shift frequency and constant use of PPE kit. All these stress factors affected their quality of sleep.
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Background: Aim of this study was to study sleep disturbances in frontline healthcare workers during COVID-19 epidemic. Methods: This is a case control study was conducted in the Department of Physiology at Pt. B. D. Sharma PGIMS, Rohtak. The study included hundred volunteer subjects of age group 25-35years and were divided into two groups (healthcare workers and and professionals from non-medical background). Results: Subjective sleep quality was significantly altered in FHCW with P value of 0.001. Sleep latency was increased in study group with 50% of study group having score of 3 on Pittsburg sleep quality index. The duration of sleep was reduced in study group with increased sleep disturbances. Forty percent of FHCW reported use of medications for sleep. Almost 100% of FHCW reported Day time dysfunction. Conclusions: COVID-19 resulted in significant sleep deprivation, increased latency, poor sleep quality and increased use of medication in FHCW. The FHCW suffered from poor quality of sleep during the COVID pandemic. FHCW were affected by several stress factors including heavy workload, high night shift frequency and constant use of PPE kit. All these stress factors affected their quality of sleep.
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Background:Lack of adequate sleep affects the mental health, emotional balance, immune function and reaction times. The alarming sedentary habit which would affect the sleep quality in the recent time is screen media exposure or increased screen time. Moderate use of ST (4hours/day) associated with lower psychological well-being. Objective: Tostudy the association between ST usage and sleep quality amongst young adults. Material And Methods:The study was conducted among medical students at Physiology department, Government medical college, Vadodara. Google form was created, which consisted of basic information. Self-reported ST usage per day. PSQI scale assessed 7components of sleep scaling from 0 to 3, and higher global score (>5) means lower sleep quality. The Google form was sent to participants who were given informed consent and the results were computed. Result:Among 204 participants, 78 males and 126 females, the median age was 19 years, the mean duration of screen time was 5.3 Hrs.(SD=2.7). ST > 5Hrs. in 57.8% and PSQI ?5 in 52.9% was seen. Chi Square test analysis for ST& PSQI, the p-value came out to be 0.094(p-value > 0.005), and was not statistically significant. Conclusion:This study shows more than half of participants had poor sleep quality and increased screen time usage. Though the results came out statistically insignificant we cannot exclude the association without further research. However,exposure to high screen time may negatively impact sleep outcome.
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Background: Metabolic syndrome (MetS) is common among patients who have been exposed to second generation antipsychotics (SGA). Obstructive sleep apnoea (OSA) and sleep quality may also contribute to MetS. Aims: To study the contribution of sleep quality and OSA on the development of MetS in patients taking SGA. Methods: Total 60 patients taking SGA for more than three months were taken for the study. It was an observational, cross-sectional study. The diagnosis of OSA was done using Hindi translation of Berlin questionnaire. Hindi version of the Pittsburg Sleep Quality Index was used to assess the sleep quality. MetS was diagnosed using Adult Treatment Panel III criteria. Results: Forty two subjects did not have MetS, out of which 35 had low risk of OSA and seven had high risk of OSA, while 18 subjects had MetS of which nine each had high and low risk of OSA. The results were highly significant with a p-value of 0.007 (p?0.05). Subjects without MetS (n=42) comprised four good sleepers and 38 poor sleepers. Subjects with MetS (n=18) comprised of one good sleeper and 17 poor sleepers. The results were non-significant with a p-value of 0.525 (p?0.05). The high risk of OSA had around seven times higher likelihood of contribution to MetS. Conclusions: Sleep quality did not play a significant role in increasing the likelihood of MetS and OSA increased the likelihood of MetS in subjects exposed to SGA by seven times.
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Background: Rapid urbanization has caused increase in the incidence of Diabetes and Sleep debt. This study is intended to see any correlation between Diabetes and sleep quality.Methods: Diabetes subjects who had there HbA1c done in the past three months were enrolled and their sleep was studied using Pittsburg sleep quality index (PSQI) which is simple, reliable epidemiological tool with high sensitivity and specificity. Subjects with chronic pain were excluded.Results: The mean PSQI score of males was more than that of female which was statistically insignificant. Urban diabetes subjects had a higher PSQI score than rural subjects. Pearson correlation (r) was 0.22 for HbA1c and PSQI score which was statistically significant with p=0.04. Though the subjects with less than 5 hours of sleep had a higher HbA1c compared to those with more than 5 hours of sleep this was statistically insignificant.Conclusions: This study showed positive correlation between sleep quality and Diabetes.
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OBJECTIVE: Rapid eye movement sleep behavior disorder (RBD) is associated with α-synucleinopathies, such as Parkinson's disease (PD). We aimed to assess the differences in the clinical characteristics of PD with and without RBD. METHODS: Forty-two patients previously diagnosed with PD were evaluated for clinical history, motor and cognitive functioning using the Unified Parkinson's Disease Rating Scale (UPDRS) and Mini-Mental State Examination (MMSE), autonomic symptoms, sleep characteristics using the Pittsburg Sleep Quality Index (PSQI), and the presence of RBD using the Korean version of the RBD screening questionnaire (RBDSQ). The prevalence of RBD and the patients' demographic features were evaluated. The patients were classified into two groups, PD with RBD and PD without RBD, based on the RBDSQ scores. The motor and cognitive functions, as well as other clinical features of the two groups were compared. RESULTS: A total of 42 PD patients were enrolled. Eighteen patients were classified as PD with RBD. Compared to PD without RBD, PD with RBD showed higher scores of rigidity in the UPDRS subscale. Regarding sleep problems, PD with RBD revealed higher sleep disturbance, lower sleep efficiency, and lower overall sleep quality in the PSQI. There was no difference in cognitive dysfunction between the two groups according to the Korean version of the MMSE. CONCLUSIONS: PD with RBD was associated with poorer sleep and motor symptoms. Therefore, RBD symptoms in PD are possibly poor prognostic markers.