Predicting the outcomes of traumatic brain injury using accurate and dynamic predictive model

Predictive models have been used widely to predict the diseases outcomes in health sector. These predictive models are emerged with new information and communication technologies. Traumatic brain injury has recognizes as a serious and crucial health problem all over the world. In order to predict brain injuries outcomes, the predictive models are still suffered with predictive performance. In this paper, we propose a new predictive model and traumatic brain injury predictive model to improve the predictive performance to classifying the disease predictions into different categories. These proposed predictive models support to develop the traumatic brain injury predictive model. A primary dataset is constructed which is based on approved set of features by the neurologist. The results of proposed model is indicated that model has achieved the best average ranking in terms of accuracy, sensitivity and specificity

Introducing a precise system for determining volume percentages independent of scale thickness and type of flow regime

When fluids flow into the pipes, the materials in them cause deposits to form inside the pipes over time, which is a threat to the efficiency of the equipment and their depreciation. In the present study, a method for detecting the volume percentage of two-phase flow by considering the presence of scale inside the test pipe is presented using artificial intelligence networks. The method is non-invasive and works in such a way that the detector located on one side of the pipe absorbs the photons that have passed through the other side of the pipe. These photons are emitted to the pipe by a dual source of the isotopes barium-133 and cesium-137. The Monte Carlo N Particle Code (MCNP) simulates the structure, and wavelet features are extracted from the data recorded by the detector. These features are considered Group methods of data handling (GMDH) inputs. A neural network is trained to determine the volume percentage with high accuracy independent of the thickness of the scale in the pipe. In this research, to implement a precise system for working in operating conditions, different conditions, including different flow regimes and different scale thickness values as well as different volume percentages, are simulated. The proposed system is able to determine the volume percentages with high accuracy, regardless of the type of flow regime and the amount of scale inside the pipe. The use of feature extraction techniques in the implementation of the proposed detection system not only reduces the number of detectors, reduces costs, and simplifies the system but also increases the accuracy to a good extent

Optimizing the Gamma Ray-Based Detection System to Measure the Scale Thickness in Three-Phase Flow through Oil and Petrochemical Pipelines in View of Stratified Regime

As the oil and petrochemical products pass through the oil pipeline, the sediment scale settles, which can cause many problems in the oil fields. Timely detection of the scale inside the pipes and taking action to solve it prevents problems such as a decrease in the efficiency of oil equipment, the wastage of energy, and the increase in repair costs. In this research, an accurate detection system of the scale thickness has been introduced, which its performance is based on the attenuation of gamma rays. The detection system consists of a dual-energy gamma source ( 241 Am and 133 Ba radioisotopes) and a sodium iodide detector. This detection system is placed on both sides of a test pipe, which is used to simulate a three-phase flow in the stratified regime. The three-phase flow includes water, gas, and oil, which have been investigated in different volume percentages. An asymmetrical scale inside the pipe, made of barium sulfate, is simulated in different thicknesses. After irradiating the gamma-ray to the test pipe and receiving the intensity of the photons by the detector, time characteristics with the names of sample SSR, sample mean, sample skewness, and sample kurtosis were extracted from the received signal, and they were introduced as the inputs of a GMDH neural network. The neural network was able to predict the scale thickness value with an RMSE of less than 0.2, which is a very low error compared to previous research. In addition, the feature extraction technique made it possible to predict the scale value with high accuracy using only one detector

Adherence to antidiabetic medication during the month of Ramadan among diabetes mellitus patients in the kingdom of Saudi Arabia

Background: Ramadan may lead to reduced adherence to antidiabetic medications among Saudi diabetes patients due to fasting, changes in daily routine, social and cultural influences, health risks, and inadequate awareness. This study aimed to assess the Saudi population adherence to the diabetes management medication in Ramadan. Methodology: A convenience sampling method was used to recruit participants for the study. Participants were sourced from social media platforms, diabetes mellitus patient groups, and healthcare providers groups. The Medication Adherence Rating Scale (MARS), a tool, was used to assess medication compliance. Results: A total of 384 individuals were included in this study, 20.3% were from Riyadh, 52.3% were males, 35% aged 31-50 years, and 64.1% had type 2 diabetes mellitus of participants. Age between 31-50 years was negatively associated with compliance (β = -1.06, p = 0.002), while age between 51-65 years is positively associated ((β= 1.00, p = 0.003). Being male was negatively associated with compliance (β= -0.72, p = 0.001). Different fasting behaviors like non-fasting one day or more (β = -2.92, p < 0.001) and fasting all month (β = -2.90, p < 0.001), significantly affect compliance scores with negative associations indicating lower compliance during fasting periods. Various HbA1c levels were significant predictors of compliance. Higher HbA1c levels were associated with increased compliance. Conclusions: The study reveals that age, gender, fasting behaviors and HbA1c levels significantly impact medication compliance among patients with diabetes mellitus during Ramadan

Molecular characterization of Leishmania species from stray dogs and human patients in Saudi Arabia

Leishmania major and Leishmania tropica cause cutaneous leishmaniasis in humans and dogs in several parts of the world, with a large number of cases recorded in the Middle East. However, when they occur in sympatry, the role of each species of Leishmania in the epidemiology of cutaneous leishmaniasis (CL) is not clear. To assess the frequency and to identify the species of Leishmania that infect humans and stray dogs in Riyadh and Al-Qaseem (Saudi Arabia), 311 stray dogs and 27 human patients who were suspected for Leishmania infection were examined for CL by a nested polymerase chain reaction (nPCR). Seven (25.9%) out of 27 human patients scored positive for Leishmania spp. (i.e., L. major in five patients from Riyadh and L. tropica in two patients from Al-Qaseem). Out of 311 dogs, five (1.6%) were infected by L. tropica. Data herein presented demonstrate the occurrence of L. tropica in dogs and humans in Saudi Arabia, as well as the occurrence of L. major in humans

Chlorhexidine versus Povidone-Iodine for the prevention of ‎Surgical Site ‎Infections: A review.‎

BackgroundSurgical Site Infections (SSIs) are the third most frequently reported health care-associated ‎infection‎ and it remain a major clinical problem despite improvements in prevention, as they ‎are associated with ‎significant mortality and morbidity. Prevention strategies for SSIs are based ‎on reducing the risk of infection by bacteria, So many antiseptic agents are ‎used, the most ‎common one are Chlorhexidine and Povidone-Iodine.‎AimsTo discuss the ‎findings of RCTs that compare Chlorhexidine versus Povidone-Iodine in the prevention of ‎Surgical ‎Site ‎Infections (SSIs).‎Methods This systematic review was carried out, including PubMed, Google Scholar, and EBSCO that ‎examining randomized trials of Chlorhexidine and Povidone-Iodine to summarize the major ‎RCT that compare Chlorhexidine versus Povidone-Iodine in the prevention of Surgical Site ‎Infections (SSIs).‎Results The review included six randomized studies that compare between Chlorhexidine and Povidone-‎Iodine for the prevention of SSIs. The findings showed that many studies prefer using ‎Chlorhexidine over Povidine-Iodine to reduce SSIs, few studies prefer using PVI as antiseptic ‎and other studies reported that there is no significant difference between both. ConclusionMajority of results prefer using Chlorhexidine than Povidone-Iodine‎ as antiseptics but ‎there were few findings prefer ‎PVI and other studies reported that there was no significant ‎difference between using them as ‎antiseptics.

Assessment of Sewage Molecular Markers in Port Dickson Coast and Kim Kim River with Sediment Linear Alkylbenzenes

The present study aimed to determine linear alkylbenzenes (LABs) concentrations as organic molecular marker for sewage pollution in the sediment samples collected from Coast of Port Dickson and Kim Kim River, Peninsular Malaysia. The adverse effects of anthropogenic inputs into the rivers and coastal environment could be detected by molecular organic markers such as LABs. The sediments were processed; their sources were identified and tested by gas chromatography-mass spectrometry (GC-MS). The significance of the differences among sampling stations for LAB concentrations and distribution at p < 0.05 was performed by analysis of variance and Post Hoc Tests, LSD procedures (ANOVA) and Pearson correlation coefficient. LABs indices which include internal to external (I/E) congeners, long to short chains L/S and homologs C13/C12 were used to identify the sewage treatment and degradation levels. Results of this study are statistically uncovered that the range of RLABs concentration in the investigated locations was between 112.0; 88.3 and 256.0; 119.0 ng�g1 dw, respectively. There was significant difference (p < 0.05) of LAB homologs with high percentage of C13-LAB homologs along sampling locations. The calculated LAB ratios (I/E) were within the range between 2.0; 1.7 and 4.1, 2.0, demonstrated that, the treated effluents from primary and secondary sources were discharged to the study areas. The degradation of LABs was 40–64% and 34–38% in the studied locations. The findings of this study suggested the powerfully indicators of LABs in tracing anthropogenic sewage contamination and the necessity of continuing wastewater treatment system improvemen

Intraventricular Hemorrhage in Preterm Infants, Review Article

Intraventricular hemorrhage (IVH) or germinal matrix (GM) in other words, is a condition that can occur in premature births and can lead to long-term medical and developmental effects. While GM/IVH can happen in full-term infants, the hemorrhage in this group of infants is different from periventricular hemorrhage (PVH)/IVH in premature infants. Family members and caregivers of preterm infants and those at risk of preterm birth are confronted with two significant uncertainties concerning these newborns: Is the survival of this child likely? Will the child experience long-term sequelae, particularly developmental sequelae, if they survive? The significance of these questions lies in their potential to impact future medical decisions, including the level of intensity in the care provided. Infants born prematurely can suffer from various acquired lesions in the central nervous system (CNS), leading to long-term disability. These lesions include GM/IVH, periventricular white matter injury, hemorrhage, and diffuse injury to the developing brain. GM/IVH continues to be a major contributor to both illness and death in premature newborns.&nbsp; GM/IVH is primarily diagnosed by brain imaging techniques, typically cranial ultrasonography, as depicted below. Screening and serial examinations are essential for diagnosing GM/IVH, as it can occur without any noticeable clinical indications

Evaluation of time to sputum smear conversion and its association with treatment outcomes among drug-resistant tuberculosis patients: a retrospective record-reviewing study

Background: This study examined the time to sputum smear and culture conversion and determinants of conversion, as well as variables associated with treatment outcomes among drug-resistant pulmonary tuberculosis (DR-PTB) cases.Methods: The electronic database and written medical records of patients were utilized to assess the sociodemographic, clinical, microbiological, and treatment characteristics and outcomes of study participants.Results: Among 736 patients with pulmonary tuberculosis (PTB), the mean age was 36.5 ± 16.5 years, with males comprising 53.4% and a mean weight of 47.76 ± 11.97 kg. The median time period for sputum smear conversion and sputum culture conversion was a month. The first-month culture conversion (p &lt; 0.001, aOR = 5.817, and 95% CI = 3.703–9.138) was the determinant of sputum smear conversion and receiver operating curve analysis with AUC = 0.881, 95% CI = 0.855–0.907, and p &lt; 0.001, which showed a high level of predictive ability for the regression model for the initial sputum smear conversion. However, the first-month sputum conversion (p &lt; 0.001, aOR = 7.446, and 95% CI = 4.869–11.388) was attributed to sputum culture conversion, and the model has shown excellent predictive ability for regression with ROC curve analysis demonstrating AUC = 0.862, 95% CI = 0.835–0.889, and p &lt; 0.001. A total of 63.2% of patients showed favorable treatment outcomes, with 63.1% of cases achieving treatment-cured status. The previous use of SLD, history of smoking, duration of illness ≤ 1 year, extensively drug-resistant tuberculosis, and first-month sputum conversion were the variables attributed to favorable treatment outcomes observed in drug-resistant pulmonary tuberculosis cases. ROC curve analysis with AUC = 0.902, 95% CI = 0.877–0.927, and p &lt; 0.001) has shown outstanding ability for regression model prediction for the variables influencing treatment outcomes.Conclusions: Within 2 months of treatment, most patients had converted their sputum cultures and sputum smears. The determinants of early sputum smear and sputum culture conversion, as well as favorable treatment outcomes, were identified. These factors should be considered during the design and implementation of effective strategies for drug-resistant tuberculosis control programs