Effects of routine repetitive transcranial magnetic stimulation on the sleep duration of patients with treatment-resistant depression: A prospective cohort study.

Aim: The aim of this study was to evaluate the short-term and long-term effects of routine repetitive transcranial magnetic stimulation (rTMS) on the sleep duration, depressive symptoms, and quality of life of patients with treatment-resistant depression (TRD). Methods: In this prospective cohort study, 25 participants with TRD were assessed using the Insomnia Severity Index (ISI) and four sleep duration components of the Pittsburgh Sleep Quality Index (PSQI). Depression severity was measured with Hamilton's Depression Rating Scale (HDRS) and Beck's Depression Inventory (BDI-II), and patient-perceived quality of life with the 36-Item Short-Form Survey (SF-36). All of these measures were evaluated at baseline (T0), and immediately (T1), 6 weeks (T2), and 12 weeks (T3) after the end of intervention. Results: At T1 endpoint, HDRS, BDI, SF-36, ISI, and three PSQI items (time to wake up, time taken to fall asleep, and Real Sleep Time) significantly improved, though these gains were reduced at follow-up endpoints (T2 and T3). Adjusting for confounders (age, sex, occupational status, BMI, and hypnotic medication) revealed that only improvements in HDRS, BDI, and time taken to fall asleep at T1 remained statistically significant. Linear regression analyses showed no significant association between reduced time taken to fall asleep and depression symptoms, suggesting rTMS can independently enhance this parameter, irrespective of depression resolution. Conclusion: Routine rTMS therapy can potentially enhance sleep duration in TRD individuals, alongside improved depressive symptoms and quality of life. However, these benefits tend to decrease over long-term follow-up, emphasizing a more pronounced short-term efficacy of rTMS.

A hybrid approach for driver drowsiness detection utilizing practical data to improve performance system and applicability.

BACKGROUND: Numerous systems for detecting driver drowsiness have been developed; however, these systems have not yet been widely used in real-time. OBJECTIVE: The purpose of this study was to investigate at the feasibility of detecting alert and drowsy states in drivers using an integration of features from respiratory signals, vehicle lateral position, and reaction time and out-of-vehicle ways of data collection in order to improve the system's performance and applicability in the real world. METHODS: Data was collected from 25 healthy volunteers in a driving simulator-based study. Their respiratory activity was recorded using a wearable belt and their reaction time and vehicle lateral position were measured using tests developed on the driving simulator. To induce drowsiness, a monotonous driving environment was used. Different time domain features have been extracted from respiratory signals and combined with the reaction time and lateral position of the vehicle for modeling. The observer of rating drowsiness (ORD) scale was used to label the driver's actual states. The t-tests and Man-Whitney test was used to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features then combined to investigate the improvement in performance using the Multilayer Perceptron (MLP), the Support Vector Machines (SVMs), the Decision Trees (DTs), and the Long Short Term Memory (LSTM) classifiers. The models were implemented in Python library 3.6. RESULTS: The experimental results illustrate that the support vector machine classifier achieved accuracy of 88%, precision of 85%, recall of 83%, and F1 score of 84% using selected features. CONCLUSION: These results indicate the possibility of very accurate detection of driver drowsiness and a viable solution for a practical driver drowsiness system based on combined measurement using less-intrusive and out-of-vehicle recording methods.

The association between body mass index and risk of obstructive sleep apnea among patients with HIV.

BACKGROUND: Although several studies show a positive association between body mass index (BMI) and a higher risk of obstructive sleep apnea (OSA) in the general population, there are limited data on that in patients living with HIV (PLHIV). The objective of the current study is to determine the prevalence of high risk for OSA and the association between BMI and OSA in PLHIV. MATERIALS AND METHODS: The study was conducted on 316 confirmed HIV cases aged ≥ 18 years who attended consulting centers in Tehran during 2019. For the diagnosis of OSA we used the Persian version of the modified Berlin questionnaire that includes ten questions broken down into three categories. A high risk for breathing problems was defined if the total score is ≥ 2. Logistic regression models were used to evaluate the association between BMI and OSA risk groups. RESULTS: Among PLHIV, 52.1% of men and 41.6% of women were considered as high risk for breathing problems during sleep at the time of the study. Patients with a higher risk for breathing problems had significantly higher BMI levels compared to those categorized as low-risk levels (25.2 vs. 24.3 kg/m2). Each unit increase in the BMI increased the odds of being high risk for OSA by 6% in the multivariable model. (odds ratio [OR]: 95% confidence interval [CI]: 1.06: 1.01-1.13). Considering BMI categories, compared to the normal weight, being obese (BMI ≥ 30 kg/m2) increased the high risk for OSA (OR [95% CI]: 2.54 [1.10-5.89]). CONCLUSION: We observed a significant association between general obesity and prevalence of OSA among PLHIV.

A field indoor air measurement of SARS-CoV-2 in the patient rooms of the largest hospital in Iran.

The coronavirus disease 2019 (COVID-19) emerged in Wuhan city, China, in late 2019 and has rapidly spread throughout the world. The major route of transmission of SARS-CoV-2 is in contention, with the airborne route a likely transmission pathway for carrying the virus within indoor environments. Until now, there has been no evidence for detection of airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and this may have implication for the potential spread of the COVID-19. We investigated the air of patient rooms with confirmed COVID-19 in the largest hospital in Iran, on March 17, 2020. To collect the SARS-CoV-2 particles, ten air samples were collected into the sterile standard midget impingers containing 20 mL DMEM with 100 µg/mL streptomycin, 100 U/mL penicillin and 1% antifoam reagent for 1 h. Besides, indoor particle number concentrations, CO2, relative humidity and temperature were recorded throughout the sampling duration. Viral RNA was extracted from samples taken from the impingers and Reverse-Transcription PCR (RT-PCR) was applied to confirm the positivity of collected samples based on the virus genome sequence. Fortunately, in this study all air samples which were collected 2 to 5 m from the patients' beds with confirmed COVID-19 were negative. Despite we indicated that all air samples were negative, however, we suggest further in vivo experiments should be conducted using actual patient cough, sneeze and breath aerosols in order to show the possibility of generation of the airborne size carrier aerosols and the viability fraction of the embedded virus in those carrier aerosols.

GCH1 (rs841) polymorphism in the nitric oxide-forming pathway has protective effects on obstructive sleep apnea.

Several studies have recently investigated the contribution of genetic factors in obstructive sleep apnea (OSA). Patients with OSA suffer from a reduction in nitric oxide (NO) serum level. This study investigated rs841, A930G p22phox, and rs1799983 polymorphisms in three critical genes involved in NO formation. A total of 94 patients with OSA and 100 healthy controls were enrolled into the study. Results showed there was no association between rs841, A930G p22phox and rs1799983 polymorphism and the risk of OSA (P = 0.51, P = 0.4 and P = 0.33, respectively). Moreover, rs841 GA genotype had a reverse relationship with the severity of OSA (P = 0.005). On the other hand, rs841 GA and A930G p22phox AA genotypes had a protective effect on daytime sleepiness in OSA patients (P = 0.01and P = 0.02, respectively). Additionally, the combination of rs841 and A930G p22phox (AG/AG and AG/AA) genotypes was significantly associated with a reduction in daytime sleepiness in OSA patients (P = 0.03 and P = 0.03, respectively). According to the results of our study, GA genotype of rs841 and GA/AA genotypes of A930G p22phox polymorphisms significantly reduced the severity of the problem and daytime sleepiness in OSA patients.

Sleep quality and depression among patients with migraine.

The aim of this study was to determine the sleep quality and level of depression among Iranian migraineurs. Among 380 cases that were selected by simple random selection from those who attended Outpatient Neurology Clinic of Imam Khomeini Hospital, 332 patients participated in this cross-sectional study. After an inclusive examination by a neurologist, the participants were asked to fill valid and reliable Persian versions of Pittsburg Sleep Questionnaire (PSQI) and Beck Depression Inventory (BDI). They also requested to score headache severity by means of a visual analogue scale graded from 1-10. According to frequency of attacks, patients were divided into three groups: with 1-4 migraine days per month, 5-7 migraine days in a month and more than 7 migraine days per month. Mean age of participants was 36.3±10.1 years and mean headache severity score was 6.0±1.9. The PSQI total score and headache severity score were highest among patients with frequent attacks. Mean BDI, PSQI and headache severity scores significantly differ between male and female participants. There was significant positive correlation between BDI and PSQI scores (r=0.5, P<0.001) also there was a positive correlation between headache severity score and PSQI score (r=0.6, P<0.001). Decreased sleep quality with other co-morbidities such as depression in migraineurs cases should be considered.

The effect of magnesium supplementation on primary insomnia in elderly: A double-blind placebo-controlled clinical trial.

BACKGROUND: Nearly 50% of older adults have insomnia, with difficulty in getting to sleep, early awakening, or feeling unrefreshed on waking. With aging, several changes occur that can place one at risk for insomnia, including age-related changes in various circadian rhythms, environmental and lifestyle changes, and decreased nutrients intake, absorption, retention, and utilization. The natural N-methyl-D-aspartic acid (NMDA) antagonist and GABA agonist, Mg(2+), seems to play a key role in the regulation of sleep. The objective of this study was to determine the efficacy of magnesium supplementation to improve insomnia in elderly. MATERIALS AND METHODS: A double-blind randomized clinical trial was conducted in 46 elderly subjects, randomly allocated into the magnesium or the placebo group and received 500 mg magnesium or placebo daily for 8 weeks. Questionnaires of insomnia severity index (ISI), physical activity, and sleep log were completed at baseline and after the intervention period. Anthropometric confounding factors, daily intake of magnesium, calcium, potassium, caffeine, calories form carbohydrates, and total calorie intake, were obtained using 24-h recall for 3 days. Blood samples were taken at baseline and after the intervention period for analysis of serum magnesium, renin, melatonin, and cortisol. Statistical analyses were performed using SPSS19 and P values < 0.05 were considered as statistically significant. RESULTS: No significant differences were observed in assessed variables between the two groups at the baseline. As compared to the placebo group, in the experimental group, dietary magnesium supplementation brought about statistically significant increases in sleep time (P = 0.002), sleep efficiency (P = 0.03), concentration of serum renin (P < 0.001), and melatonin (P = 0.007), and also resulted in significant decrease of ISI score (P = 0.006), sleep onset latency (P = 0.02) and serum cortisol concentration (P = 0.008). Supplementation also resulted in marginally between-group significant reduction in early morning awakening (P = 0.08) and serum magnesium concentration (P = 0.06). Although total sleep time (P = 0.37) did not show any significant between-group differences. CONCLUSION: Supplementation of magnesium appears to improve subjective measures of insomnia such as ISI score, sleep efficiency, sleep time and sleep onset latency, early morning awakening, and likewise, insomnia objective measures such as concentration of serum renin, melatonin, and serum cortisol, in elderly people.