Clinical and socio-demographic factors associated with electroencephalographic abnormalities in children with epilepsy

Electroencephalography (EEG) makes critical contribution to the management of epilepsies. Few studies have examined the clinical and socio-demographic factors that are likely to predict finding an abnormal or epileptiform EEG in children with epilepsy (CWE). Knowledge of clinical variables and socio demographic factors that determine EEG abnormalities may inform careful selection of children for EEG and improve the cost-effectiveness of this investigation. Therefore, this study was carried out to assess the relationship between the occurrence of EEG abnormalities and certain factors such as age, gender, clinical neurologic state, seizure type, anti-epileptic drug therapy, activation procedure such as sleep and etiology of epilepsy in children who had EEG in Owerri, Nigeria. The clinical and EEG records of children who had EEG at a tertiary referral center over a period of two years were retrospectively reviewed. Relevant data including demographics, clinical neurologic state, seizure type, EEG findings were extracted. Statistical analysis was used to determine association between categorical variables. The variables noted to be significantly associated with abnormal EEG recordings were the presence of abnormal neurologic findings (p=0.020) and etiology of epilepsy (p=0.045). There were no significant association between abnormal EEG findings and age (p=0.680), gender (p=0.802) and seizure types (p=0.157). The clinical neurological state and etiology of epilepsy in children were significantly associated with the occurrence of abnormalities and yield of interictal scalp EEG. Children with epilepsy who are neurologically abnormal or have multiple etiological factors could be prioritized in EEG appointments in resource-poor settings. Further research in children with epilepsy is needed to confirm these findings.

Download Full-text

Features importance in seizure classification using scalp EEG reduced to single timeseries

10.1101/2021.07.28.21261310 ◽

2021 ◽

Author(s):

Sebastien Naze ◽

Jianbin Tang ◽

James Kozloski ◽

Stefan Harrer

Keyword(s):

Support Vector ◽

Seizure Type ◽

Low Frequencies ◽

Scalp Eeg ◽

Eeg Spectrum ◽

Wearable Systems ◽

Vector Machines ◽

Eeg Recordings ◽

Single Trace ◽

Scalp Electroencephalogram

Seizure detection and seizure-type classification are best performed using intra-cranial or full-scalp electroencephalogram (EEG). In embedded wearable systems however, recordings from only a few electrodes are available, reducing the spatial resolution of the signals to a handful of timeseries at most. Taking this constraint into account, we tested the performance of multiple classifiers using a subset of the EEG recordings by selecting a single trace from the montage or performing a dimensionality reduction over each hemispherical space. Our results support that Random Forest (RF) classifiers lead most efficient and stable classification performances over Support Vector Machines (SVM). Interestingly, tracking the feature importances using permutation tests reveals that classical EEG spectrum power bands display different rankings across the classifiers: low frequencies (delta, theta) are most important for SVMs while higher frequencies (alpha, gamma) are more relevant for RF and Decision Trees. We reach up to 94.3% +/- 5.3% accuracy in classifying absence from tonic-clonic seizures using state-of-art sampling methods for unbalanced datasets and leave-patients-out 3-fold cross-validation policy.

Download Full-text

Money Attitude and Socio-Demographic Factors as Determinants of University Students’ Spending Behavior in Shah Alam, Malaysia

JURNAL ILMIAH AKUNTANSI UNIVERSITAS PAMULANG ◽

10.32493/jiaup.v9i1.7075 ◽

2021 ◽

Vol 9 (1) ◽

pp. 65

Author(s):

Jamilah Kamis ◽

Norhasbi Abdul Samad ◽

Lee Siew Pheng ◽

Salina Rasli ◽

Salbiah Hanum Mohd Hajali ◽

...

Keyword(s):

College Students ◽

Demographic Factors ◽

University Management ◽

Two Factors ◽

Spending Behavior ◽

Money Attitude ◽

Socio Demographic Factors ◽

The Cost ◽

The Relationship ◽

Value Of Money

ABSTRACTNowadays, uncontrollable spending habit towards Malaysian young generations are becoming progressively. They have a tendency to have less value of money compared to the elder generations in spending their money. Since the cost of living in Malaysia has improved remarkably, the young generations enjoyed spending their money heavenly, therefore Malaysia faced changes in lifestyle and spending trend. This study proposes to investigate the relationship between money attitude and socio-demographic as determinants of college students’ spending behaviours. As such, the correlation between money attitude factors (power-prestige, distrust, retention-time and anxiety) and spending behaviours among Malaysian college students is a topic worthy of further exploration. At the same time, this study also attempts to explore whether college students’ spending behaviours are affected by their socio-demographic factors such as gender, age. The sample of this study consists of 176 students from three different universities in the Shah Alam area i.e University Selangor (UNISEL), University Management Science (MSU) and Universiti Teknologi Malaysia (UiTM). The regression analysis showed that there were only two factors of money attitude (power-prestige, and anxiety) that had a significant effect on spending behaviour among these universities’ students. However, from the analysis, it can be revealed that none of the socio-demographic factors had a significance (more than 0.05) towards the spending behaviour of the students. Thus, age (positive result) is the most influenced factor of the students’ spending behaviour. Consequently, several suggestions have been put forward and hoped that it will assist students in managing their fund effectively

Download Full-text

ASSOCIATION OF SOCIO-DEMOGRAPHIC FACTORS WITH DIARRHEA IN CHILDREN LESS THAN FIVE YEARS: A SECONDARY ANALYSIS OF MULTIPLE INDICATOR CLUSTER SURVEY SINDH 2014

Pakistan Journal of Public Health ◽

10.32413/pjph.v7i2.39 ◽

1970 ◽

Vol 7 (2) ◽

pp. 85-89

Author(s):

Muhammad Irfan ◽

Syed Mustansir Hussain Zaidi ◽

Hira Fatima Waseem

Keyword(s):

Rural Areas ◽

Demographic Factors ◽

Wealth Index ◽

Household Wealth ◽

Cluster Survey ◽

Multiple Indicator Cluster Survey ◽

Increased Risk ◽

Multiple Indicator ◽

Mother Education ◽

Socio Demographic Factors

Background: Diarrhea founds to be the major cause of morbidity and mortality in children less than five years. Various factors are associated with diarrhea but socio-demographic factors are the main key elements, which associated with diarrhea. Methods: This study was examined association of socio-demographic factors with diarrhea in children less than five years of age of Sindh, Pakistan, using data from the Multiple Indicator Cluster Survey (MICS) conducted from January 2014 to August 2014. Data were collected for 18,108 children in whom 16,449 children had complete data of demographic variables being included in the analysis. Bivariate analysis was done using Pearson's Chi square test and multivariate analysis being done using binary logistic regression. Results: We found increased risk of diarrhea among children lives in rural areas while household wealth index quintile was also associated with diarrhea. Children in the poor, middle and fourth wealth index quintiles being at increased risk of diarrhea compared to children in the richest wealth index quintile. The highest risk of diarrhea was found for the child having mother with no education as well as children aged 12-23 months. Conclusion: Age of child, mother education and wealth index found significant with diarrhea while Male children, child aged 12-23 months, child with no mother education, child from rural areas and child from poor households found with high risk of diarrhea.

Download Full-text