Ziaeian Hospital

OBJECTIVE: The present study assessed the prevalence of adverse drug reactions (ADRs) among HIV positive patients taking antiretroviral therapy referred to Imam Khomeini Hospital in Tehran, Iran. METHODS: This is a cross sectional study regarding side effects of Highly Active Antiretroviral Therapy (HAART) in HIV positive patients referred to Voluntary Counseling and Testing (VCT) center in Imam Khomeini Hospital of Tehran, Iran during a period of the year 2009 to 2010. Two hundred patients under antiretroviral treatment evaluated for the side effects of drug based on available records, face to face interviews and written lab data. RESULTS: Data was collected from a sample of 200 HIV positive patients (72% male). Injection drug use was the most common route of HIV transmission. Co-Infections with Hepatitis C virus (HCV) found in the majority of patients (60.5%). Tuberculosis was the most prevalent opportunistic infection. One hundred eighty eight (94%) patients experienced at least one adverse drug reaction. The most frequent clinical and paraclinical findings were skin rash (28%) and abnormal liver function tests (36%). CONCLUSION: Given the high prevalence of adverse drug reactions among HIV positive patients taking antiretroviral therapy (ART) in this study, clinicians should be aware of ADRs at the initiation of ART as complications can affect patients' adherence to the therapy.

Legionella pneumophila is the causative agent of more than 95% cases of severe Legionella pneumonia. Nosocomial pneumonias in different hospital wards is an important medical and pharmaceutical concern. This study aimed to detect Legionella with two methods: polymerase chain reaction (PCR) and detection of urine antigenic test (UAT) in patients suffering from nosocomial pneumonia admitted to pediatric intensive care unit (PICU) of children hospitals. This study was conducted in PICU wards of Rasool Akram and Bahrami children hospitals, Tehran, Iran during 2013 - 2014. In patients diagnosed with hospital-acquired pneumonia, intratracheal secretion samples for PCR and urine sample for UAT were taken. Simultaneously, PCR and urinary antigen test were conducted using commercial kits. The results of urinary antigen test and PCR were analyzed by SPSS v.19 for statistical comparison. In this study, 96 patients aging 2.77 years on average with two age peaks of less than 1 year and 7-8 year were enrolled. More than half of the patients were under 1 year old. The most common underlying diseases were seizure, Acute Lymphoblastic Lymphoma, Down syndrome and metabolic syndromes. The positivity rate of Legionella urinary antigen test was 16.7% and positivity rate of PCR test was 19.8%. There were no significant associations between the results obtained by both assays with age, gender or underlying diseases. In conclusion, PCR is a better detection method for Legionella infection than urinary antigen test, but the difference between the two methods was not significant.

Abstract Background We have developed the Integrated Cognitive Assessment (ICA), a 5‐minute, self‐administered, computerised test that is independent of language, cultural background and education and aims at screening for cognitive impairment in a way that can simplify and accelerate the diagnosis of Alzheimer's Dementia (AD) and Mild Cognitive Impairment (MCI). The ICA utilises artificial intelligence to analyse high‐dimensional clinical and demographic data. Method We carried out head‐to‐head studies comparing classification performance of the ICA with widely used cognitive assessments (MoCA and ACE) in participants with MCI and mild AD. The ICA test measures patterns of reaction time and categorisation accuracy which are utilised by an AI engine, alongside demographic data, to provide a predictive score about participant’s cognitive status. We also investigated the use of a deep (50 layers) neural network to extract informative features from the ICA test response patterns. Result On a population of 200 participants (84 healthy, 68 MCI, 48 mild AD), the ICA achieved an area under the ROC accuracy of 91% in distinguishing between healthy and impaired (MCI and mild AD) participants. In comparison MoCA achieved an AUC of 82%, and ACE 84%. Utilising the deep learning network for automatic feature extraction significantly improved the specificity and sensitivity compared to only using a linear classifier. The ICA Spearman correlation of 0.67 (p‐value <0.0001) with MoCA, and 0.73 (p‐value<0.0001) with ACE establishes convergent validity with these cognitive tests. ICA results were not biased by participants level of education (i.e. no significant correlation), whereas MoCA and ACE had correlations of 0.31 (p<0.0001) and 0.31 (p<0.001) respectively with the level of education in the same set of subjects. Conclusion The ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large‐scale screening of cognitive impairment. The ICA has advantages over MoCA and ACE because of its shorter duration, automatic scoring and potential for medical record or research database integration. ICA’s AI engine is able to learn from additional data and utilise deep learning, further improving the predictive power of the ICA test.

Abstract Background High‐level cognitive processes such as binding the processed data from sensory modules with elements stored in the memory involve the activity of long‐range pyramidal cells. These excitatory neuronal populations also provide input to a population of GABA A ergic inhibitory interneurons, which in turn recruit feedback links to suppress the activity of the pyramidal cells. Interneuron networks generate rhythmic synchronization in the Gamma band driven by the time constant of the GABA receptors. Disrupted or desynchronized Gamma oscillations have been observed in patients of Alzheimer’s disease (AD). Earlier works have proposed the deficit in coherence between oscillations measured by EEG electrodes across the frontal lobe in the Gamma band in response to olfactory stimulation as a diagnostic marker of AD. This study examines the strength and spatial spread of Gamma band activity induced by auditory chirp stimulation as a marker for AD. The chirp signal is designed to entrain a target frequency of 40Hz at which the populations of inhibitory interneurons are known to operate. Method A session comprising 11 interleaved periods of 40sec ON and 20sec OFF auditory stimuli of 5kHz tone modulated by a 40Hz chirp at 0.1 duty cycle was administered to mild AD patients and non‐AD elderly participants with memory complaints, and EEG data were collected by a 10/20 system. Magnitude of 40Hz oscillations at different scalp positions during the ON cycles was measured as an indicator of the entrained Gamma oscillations. Result While 40Hz oscillations were recorded across a majority of electrodes in non‐AD demented participants with particular strengths in the temporal and frontal areas, the 40Hz entrainment occurred for a limited number of electrodes in AD patients. Conclusion Auditory chirp stimulation at 40Hz results in spatially distinguishable patterns of entrained Gamma oscillations in AD patients and non‐AD demented participants, and hence suggests a marker for AD. Despite this difference, the fact that 40Hz entrainment still occurs in regions of the brain in AD patients offers a positive indication for the possibility to employ such stimulation to reinvigorate the operation of the involved neural circuitry in therapy campaigns. Further studies are needed to assess such possibility.

Abstract Background Non‐invasive 40Hz sensory‐induced brain entrainment has shown promising results in Alzheimer’s disease (AD) therapy (Chan et al., medRxiv, 2021; Chan et al., Alzheimer’s & Dementia, 2021). We previously reported on the network‐level mechanisms underlying the spatial and temporal coherence of the induced brain rhythms during gamma entrainment in dementia patients (Lahijanian et al., bioRxiv, 2021). Here, we posit that the induced gamma oscillations propagate as traveling waves circling each hemisphere of the cortex, and that the induction of such waves can explain the spatiotemporal coherence between the frontal and parietal/occipital regions reported to be involved in cognitive processes. Method EEG data were recorded from two healthy young adults during multi‐trial visual entrainment sessions with 22Hz flickering light. Due to the harmonic property of the brain’s entrained response (Jones et al., Journal of Alzheimer’s Disease, 2019), gamma entrainment was achieved at 44Hz. Separately, EEG data were recorded from 11 dementia patients in multi‐trial auditory entrainment sessions with 40Hz chirp input. The phase of the spatiotemporal pattern at the target gamma frequency was calculated across the entire scalp as an indicator of traveling waves. Result Shortly after the stimulation onset in the young healthy adults, a circling traveling wave is observed in each hemisphere (Fig. 1). The onset and the homogeneity of the induced wave pattern is modulated by the power of the 44Hz entrained oscillations (Fig. 2). The dementia patients can be divided into two groups of entrained and non‐entrained according to the induced gamma power (see Lahijanian et al., bioRxiv, 2021), and the travelling wave effect can be occasionally observed during the stimulation in the entrained group and not in the non‐entrained group. Conclusion Cortical traveling waves modulate the brain dynamics and play a critical role in functions ranging from sensory processing to memory consolidation (Muller et al., Nature Reviews Neuroscience, 2018). Gamma entrainment induces traveling waves that connect the occipital/parietal regions of the cortex to the frontal region through the temporal region. The traveling wave promotes spatiotemporal coherence across the brain and hence can serve as a network‐level mechanism for explaining the therapeutic effects of gamma entrainment.

Abstract Background Altered gamma oscillations have been observed in patients of Alzheimer’s disease (AD). A large number of studies have linked the quality of gamma oscillations in the frontal cortex to the performance of memory retrieval tasks. Synchronization of gamma oscillations has a strong correlation with cognitive functions (Fell et al., Nature Reviews Neuroscience 2011), and deficit in gamma synchronization in the frontal cortex has been reported as a marker for AD (Sedghizadeh et al., PLOS One 2020). In this study, we examine the phase synchronization of gamma oscillations in the EEG data recorded from the frontal cortex during olfactory stimulation as a marker for AD. Method Twenty‐four elderly participants (13 Normal and 11 mild AD patients) participated in this study. The cognitive status of the participants was quantified using the MMSE test. Then, each participant underwent an olfactory stimulation session consisting of 120 trials of 2s stimuli presentation with a random selection of two odors (lemon as the frequent and rose as the rare odor) followed by 8s of rest. EEG data were simultaneously recorded and pre‐processed for artifact and noise removal and trial averaging. To analyze gamma band synchronization, the phase‐locking value (PLV) for lower gamma oscillations (35‐45Hz) was calculated between the Fz and Cz electrodes. Fig. 1 illustrates the measurement and processing flow. Result Our study shows that the PLV is significantly higher for normal participants compared to AD patients (Fig. 2). Also, the phase difference between the Fz and Cz electrodes in the lower gamma band remains unchanged across trials for normal participants while it widely varies between ‐180 and 180 degrees for AD patients (Fig. 3). Conclusion This study shows that there is a significant difference between normal participants and AD patients in terms of the synchronization of gamma oscillations in the frontal cortex in response to olfactory stimulation. These results suggest that the PLV between the Fz and Cz electrodes under olfactory stimulation can be used as a marker for AD diagnosis.

Background: Migraine is a chronic condition characterized by moderate to severe headache attacks, adversely affecting individual and social quality of life. Given the chronic nature of this disease, it is crucial to find medications that offer fewer side effects and enhanced effectiveness. Agomelatine, a synthetic analogue of the hormone melatonin, shares similar pharmacodynamics, such as stimulating melatonin receptors and inhibiting the 5HT2c receptor. Due to its favorable side-effect profile and high tolerability, agomelatine presents a viable alternative to traditional preventive treatments for migraines. Objectives: The primary objective of this trial is to evaluate the effectiveness of agomelatine in reducing the severity and frequency of episodic migraine attacks without aura. Methods: This study utilizes a parallel, triple-blind controlled trial design. Patients, aged between 18 and 60 years, who have been definitively diagnosed with episodic migraine without aura and have not received prior severity treatment, are eligible for this randomized controlled trial (RCT). A convenience sample of patients will be recruited from individuals visiting the clinic for migraine issues. If these individuals agree to participate and meet the inclusion criteria, they will be randomly assigned to either the intervention or control group using a random number table or software. The intervention group will receive 25 mg of agomelatine daily, while the control group will be given vitamin B1 as a placebo. Both the frequency and severity of migraine attacks will be monitored, along with the mean monthly migraine days (MMD) and migraine disability assessment (MIDAS) scores, before and after the intervention.

Abstract Background Brain oscillations known for handling various information across brain. The gamma rhythms observed in high‐level cognitive process (Fries et al., Trends in neurosciences 2018) and theta cycle observed to process sensory information and interact with gamma oscillations (Amemiya et al., Cell Reports 2018). Disruption in synchronization of gamma oscillations have been observed in Alzheimer’s disease patients (Uhlhaas et al., Neuron 2006). Gamma stimulation had been shown to reduce the mentioned dysfunction and reported to have therapeutic results (Martorell et al., Cell 2019; Suk et al. Alzheimer’s and Dementia 2020). This study examines the effect of gamma band activity induced by auditory chirp stimulation as a driver for other frequency sources. The chirp signal is designed to entrain 40Hz which had been shown to have therapeutics effects. Method 33 participants were included in this study including 17 mild AD, 6 MCI and 10 healthy elderlies. A session consists of interleaved periods of forty second stimulation and twenty second silence. The stimulation is a 5kHz tone modulated by a 40Hz chirp at 0.1 duty cycle. EEG data were collected by a 10/20 system. Relative magnitude of the 40Hz oscillations with respect to neighbors’ magnitude during the stimulation was measured as an indicator of the entrained gamma oscillations. Total participants are categorized into entrained and not‐entrained group based on the indicator. Phase locking Value (PLV) is then calculated in theta frequency band. Result 40Hz entrainment have been observed in healthy participants and also some Alzheimer’s disease patients. Based on the power spectral density (PSD) at forty hertz 23 entrained and 10 not‐entrained participants are separated and PLV analysis have been calculated for the two groups. Theta oscillatory asymmetry have been observed in posterior temporal cortex during auditory stimulation. Conclusion Entraining gamma oscillations using auditory stimulation results in cross frequency variation. Phase‐amplitude or phase‐phase coupling measures the simultaneous correlation between specific oscillations. This study suggests that despite the concurrent association of theta‐gamma frequencies, some brain network changes occur in response to gamma oscillation which should be more discussed in related researches.

Abstract Background Depression is considered to be one the most common psychiatric co‐morbidities in Alzheimer’s disease (AD). Besides its prevalence, depression is associated with faster cognitive decline, physical aggression toward caregivers, earlier admission to nursing homes and lower quality of life. Therefore, early prediction of depression and selecting patients with higher risks for developing depression in the course of AD can provide an opportunity for earlier intervention and higher quality of life. This study’s primary intent was to explore the ability of feature selection algorithms to indicate baseline features that can predict the development of depression in AD patients. Method We have selected 28 AD patients from The Alzheimer’s Disease Neuroimaging Initiative (ADNI) that developed probable depression in 3‐5 years of follow‐up and 56 age‐ and sex‐matched AD patients without probable depression developed in the course of the disease. We implemented statistical analyses to identify the top significant markers offering the highest f values . Result Our results indicated that P‐tau csf level, tau csf level, APOE4 genotype, ECogPtLang score (representing the interference of language impairment reported by the participant) and The Mini‐Mental State Exam (MMSE) score were the best features for predicting the development of depression in AD patients ( f values : 7.38, 6.17, 3.96, 3.03 and 2.37, respectively). The first 3 markers possess p values < 0.05. Conclusion These results provide primary evidence in favor of a distinguishable baseline profile in AD patients with higher risk for depression in the future. Therefore, caregivers might be able to classify AD patients prone to developing depression based on these features and provide earlier interventions.

Abstract Background Previous studies have shown that cognitive impairment in early stages of Alzheimer’s disease (AD) is not limited to memory; other cognitive domains are also disrupted including impairment in visual processing (Boucart, Bubbico et al. 2014). Additionally, it is shown that in healthy human subjects, images are categorized by their animacy status (i.e. animate vs. inanimate) in the higher‐level visual areas (Kriegeskorte, Mur et al. 2008). Here we used fMRI to investigate the spatial patterns of animacy processing in the brain of patients with mild cognitive impairment (MCI)/AD in comparison to healthy controls(HC). Method We recruited 20 HCs, 15 MCIs and 10 mild‐ADs. Participants completed the Integrated Cognitive Assessment (ICA) test (Khaligh‐Razavi, Habibi et al. 2019) in the fMRI scanner. ICA is a rapid visual‐categorization task, in which participants indicate whether a presented image contains an animal or not, as fast and accurately as they can. In addition to the conventional univariate analysis –looking at the mean brain responses– we used multivariate‐pattern‐analysis (MVPA) to investigate differences in patterns of brain activity between the three groups. In MVPA, we trained a linear classifier for each brain area, to do animal/non‐animal categorization based on the patterns of brain responses to the images. Result In some of the key brain regions, such as R‐parahippocampus and R‐fusiform, overlapping with early tau‐pathology (Braak, Alafuzoff et al. 2006), both HC and MCI showed a significantly higher level of mean brain activity in response to all images compared to the AD group (p‐value<0.0001). Additionally, looking at the patterns of brain activity in the L‐fusiform, HC and MCI could be discriminated based on their MVPA responses(p‐value<0.0015), while there was no univariate difference between the two groups. Conclusion We demonstrated HC and MCI/AD can be differentiated not only based on univariate analysis, but also by multivariate measures, i.e. patterns of brain responses to images. Moreover, we showed that the rapid visual categorization task used in this study could engage key brain areas affected by tau pathology in early stages of the disease. This highlights the potential application of such task for earlier detection of the disease, ideally before the onset of memory symptoms.