Search results for: diagnostic biomarker

Authors: D. Sigirli

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The Receiver Operating Characteristic (ROC) curve is a commonly used statistical tool for evaluating the diagnostic performance of screening and diagnostic test with continuous or ordinal scale results which aims to predict the presence or absence probability of a condition, usually a disease. When the test results were measured as numeric values, sensitivity and specificity can be computed across all possible threshold values which discriminate the subjects as diseased and non-diseased. There are infinite numbers of possible decision thresholds along the continuum of the test results. The ROC curve presents the trade-off between sensitivity and the 1-specificity as the threshold changes. The empirical ROC curve which is a non-parametric estimator of the ROC curve is robust and it represents data accurately. However, especially for small sample sizes, it has a problem of variability and as it is a step function there can be different false positive rates for a true positive rate value and vice versa. Besides, the estimated ROC curve being in a jagged form, since the true ROC curve is a smooth curve, it underestimates the true ROC curve. Since the true ROC curve is assumed to be smooth, several smoothing methods have been explored to smooth a ROC curve. These include using kernel estimates, using log-concave densities, to fit parameters for the specified density function to the data with the maximum-likelihood fitting of univariate distributions or to create a probability distribution by fitting the specified distribution to the data nd using smooth versions of the empirical distribution functions. In the present paper, we aimed to propose a smooth ROC curve estimation based on the boundary corrected kernel function and to compare the performances of ROC curve smoothing methods for the diagnostic test results coming from different distributions in different sample sizes. We performed simulation study to compare the performances of different methods for different scenarios with 1000 repetitions. It is seen that the performance of the proposed method was typically better than that of the empirical ROC curve and only slightly worse compared to the binormal model when in fact the underlying samples were generated from the normal distribution.

Keywords: empirical estimator, kernel function, smoothing, receiver operating characteristic curve

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Authors: Eltayeb Hamad Elneel Yousif

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This paper describes occupational radiation doses of workers in non-destructive testing (NDT) and some medical practices during the year 2007. The annual doses received by the workers of a public hospital are presented in this report. The Department is facilitated with HARSHAW Reader model 6600 and assigned the rule of personal monitoring to contribute in controlling and reducing the doses received by radiation workers. TLD cards with two TLD chips type LiF: Mg, Ti (TLD-100) were calibrated to measure the personal dose equivalent Hp(10). Around 150 medical radiation workers were monitored throughout the year. Each worker received a single TLD card worn on the chest above lead apron and returned for laboratory reading every two months. The average annual doses received by the workers of radiotherapy, nuclear medicine and diagnostic radiology were evaluated. The annual doses for individual radiation workers ranged between 0.55-4.42 mSv, 0.48-1.86 mSv, and 0.48-0.91 mSv for the workers of radiotherapy, nuclear medicine and diagnostic radiology, respectively. The mean dose per worker was 1.29±1, 1.03±0.4, and 0.69±0.2 mSv, respectively. The results showed compliance with international dose limits. Our results reconfirm the importance of personal dosimetry service in assuring the radiation protection of medical staff in developing countries.

Keywords: radiation medicine, non-destructive testing, TLD, public hospital

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Authors: Jun Won Kim

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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

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Authors: Pavel Damborsky, Martina Zamorova, Jaroslav Katrlik

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Prostate cancer is annually the most common newly diagnosed cancer among men. An extensive number of evidence suggests that traditional serum Prostate-specific antigen (PSA) assay still suffers from a lack of sufficient specificity and sensitivity resulting in vast over-diagnosis and overtreatment. Thus, the early-stage detection of prostate cancer (PCa) plays undisputedly a critical role for successful treatment and improved quality of life. Over the last decade, particular altered glycans have been described that are associated with a range of chronic diseases, including cancer and inflammation. These glycans differences enable a distinction to be made between physiological and pathological state and suggest a valuable biosensing tool for diagnosis and follow-up purposes. Aberrant glycosylation is one of the major characteristics of disease progression. Consequently, the aim of this study was to develop a more reliable tool for early-stage PCa diagnosis employing lectins as glyco-recognition elements. Biosensor and biochip technology putting to use lectin-based glyco-profiling is one of the most promising strategies aimed at providing fast and efficient analysis of glycoproteins. The proof-of-concept experiments based on sandwich assay employing anti-PSA antibody and an aptamer as a capture molecules followed by lectin glycoprofiling were performed. We present a lectin-based biosensing assay for glycoprofiling of serum biomarker PSA using different biosensor and biochip platforms such as label-free surface plasmon resonance (SPR) and microarray with fluorescent label. The results suggest significant differences in interaction of particular lectins with PSA. The antibody-based assay is frequently associated with the sensitivity, reproducibility, and cross-reactivity issues. Aptamers provide remarkable advantages over antibodies due to the nucleic acid origin, stability and no glycosylation. All these data are further step for construction of highly selective, sensitive and reliable sensors for early-stage diagnosis. The experimental set-up also holds promise for the development of comparable assays with other glycosylated disease biomarkers.

Keywords: biomarker, glycosylation, lectin, prostate cancer

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Authors: Lloyd A. Taylor

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An increase in the prevalence of Attention Deficit-Hyperactivity Disorder (ADHD) highlights the need to consider factors that may be exacerbating symptom presentation. Traditional diagnostic criteria provide a little framework for healthcare providers to consider as they attempt to diagnose and treat children with behavioral problems. In fact, aside from exclusion criteria, limited alternative considerations are available, and approaches fail to consider the impact of outside factors that could increase or decrease the likelihood of appropriate diagnosis and success of interventions. This paper will consider specific systems-based factors that influence behavior and intervention successes that, when not considered, could account for the upsurge of diagnoses. These include understanding (1) challenges in the healthcare system, (2) the influence and impact of educators and the educational system, (3) technology use, and (4) patient and parental attitudes about the diagnosis of ADHD. These factors must be considered both individually and as a whole when considering both the increase in diagnoses and the subsequent increases in prescriptions for psychostimulant medication. A theoretical model based on a risk management approach will be presented. Finally, data will be presented that demonstrates pediatric provider satisfaction with this approach to diagnoses and treatment of ADHD as it relates to practice trends.

Keywords: ADHD, diagnostic criteria, risk management model, pediatricians

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Authors: Wilfred A. Abiaa, Chibundu N. Ezekiel, Benedikt Warth, Michael Sulyok, Paul C. Turner, Rudolf Krska, Paul F. Moundipa

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Mycotoxins are a wide range of toxic secondary metabolites of fungi that contaminate various food commodities worldwide especially in sub-Saharan Africa (SSA). Such contamination seriously compromises food safety and quality posing a serious problem for human health as well as to trade and the economy. Their concentrations depend on various factors, such as the commodity itself, climatic conditions, storage conditions, seasonal variances, and processing methods. When humans consume foods contaminated by mycotoxins, they exert toxic effects to their health through various modes of actions. Rural populations in sub-Saharan Africa, are exposed to dietary mycotoxins, but it is supposed that exposure levels and health risks associated with mycotoxins between SSA countries may vary. Dietary exposures and health risk assessment studies have been limited by lack of equipment for the proper assessment of the associated health implications on consumer populations when they eat contaminated agricultural products. As such, mycotoxin research is premature in several SSA nations with product evaluation for mycotoxin loads below/above legislative limits being inadequate. Few nations have health risk assessment reports mainly based on direct quantification of the toxins in foods ('external exposure') and linking food levels with data from food frequency questionnaires. Nonetheless, the assessment of the exposure and health risk to mycotoxins requires more than the traditional approaches. Only a fraction of the mycotoxins in contaminated foods reaches the blood stream and exert toxicity ('internal exposure'). Also, internal exposure is usually smaller than external exposure thus dependence on external exposure alone may induce confounders in risk assessment. Some studies from SSA earlier focused on biomarker analysis mainly on aflatoxins while a few recent studies have concentrated on the multi-biomarker analysis of exposures in urine providing probable associations between observed disease occurrences and dietary mycotoxins levels. As a result, new techniques that could assess the levels of exposures directly in body tissue or fluid, and possibly link them to the disease state of individuals became urgent.

Keywords: mycotoxins, biomarkers, exposure assessment, health risk assessment, sub-Saharan Africa

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Authors: Iván Castelló, Georgiana Stoica, Emilio Palomares, Fernando Bravo

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We present herein two colour encoded silica nanospheres (2nanoSi) for the fluorescence quantitative ratiometric determination of trypsin in humans. The system proved to be a faster (minutes) method, with two times higher sensitivity than the state-of-the-art biomarkers based sensors for cystic fibrosis (CF), allowing the quantification of trypsin concentrations in a wide range (0-350 mg/L). Furthermore, as trypsin is directly related to the development of cystic fibrosis, different human genotypes, i.e. healthy homozygotic (> 80 mg/L), CF homozygotic (< 50 mg/L), and heterozygotic (> 50 mg/L), respectively, can be determined using our 2nanoSi nanospheres.

Keywords: cystic fibrosis, trypsin, quantum dots, biomarker, homozygote, heterozygote

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Authors: Bennasser Samira

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Meningitis, especially the meningococcal one, is a serious problem of public health. A system of vigilanceand surveillance is in place to allow effective actions to be taken on actual or potential health problems caused by all forms of meningitis. Objectives: 1. Describe the epidemiological surveillance system for meningitis in the province of Taza. 2. Evaluate the quality and responsiveness of the epidemiological surveillance system for meningitis in the province of Taza. 3. Propose measures to improve this system at the provincial level. Methods: This was a descriptive study with a purely quantitative approach by evaluating the quality and responsiveness of the system during 5 years between January 2016 and December 2020. We usedfor that the investigation files of meningitis cases and the provincial database of meningitis. We calculated some quality indicators of surveillance system already defined by the National Program for the Prevention and Control of Meningitis. Results: The notification is passive, the completeness of the data is quite good (94%), and the timeliness don’t exceed 71%. The quality of the data is acceptable (91% agreement). The systematic and rapid performance of lumbar punctures increases the diagnostic capabilities of the system. The local response actions are effected in 100%. Conclusion: The improvement of this surveillance system depends on strengthening the staff skills in diagnostic, reviewing surveillance tools, and encouraging judicious use of the data.

Keywords: evaluation, meningitis, system, taza, morocco

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Authors: F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. Gadea, J. M. Monzó, R. J. Colom

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There is a great diversity of diseases that affect the integrity of the walls of the esophagus, generally of a digestive nature. Among them, gastroesophageal reflux is a common disease in the general population, affecting the patient's quality of life; however, there are still unmet diagnostic and therapeutic issues. The consequences of untreated or asymptomatic acid reflux on the esophageal mucosa are not only pain, heartburn, and acid regurgitation but also an increased risk of esophageal cancer. Currently, the diagnostic methods to detect problems in the esophageal tract are invasive and annoying, as 24-hour impedance-pH monitoring forces the patient to be uncomfortable for hours to be able to make a correct diagnosis. In this work, the development of a sensor able to measure in depth is proposed, allowing the detection of liquids circulating in the esophageal tract. The multisensor detection system is based on radiofrequency photospectrometry. At an experimental level, consumers representative of the population in terms of sex and age have been used, placing the sensors between the trachea and the diaphragm analyzing the measurements in vacuum, water, orange juice and saline medium. The results obtained have allowed us to detect the appearance of different liquid media in the esophagus, segregating them based on their ionic content.

Keywords: bioimpedance, dielectric spectroscopy, gastroesophageal reflux, GERD

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Authors: Sandeep Pandey, Nimra Habib, Ranjana Singh, Abbas Ali Mahdi

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Leukemia is a malignancy of blood that mainly affects children and young adults; while advancement in the early diagnosis will have the potential to improve the outcome of diseases. A wide range of disease including leukemia shows inflammatory signals in their pathogenesis. In a pilot study conducted in our laboratory, 52 people were screened, of which 26 had leukemia and 26 were free from any kind of malignancy. We performed the estimation of the inflammatory cytokine Interleukin-8 and it was found significantly raised in all the leukemia patients concerning healthy volunteers who participated in the study. Flow cytometry had been performed for the confirmation of leukemia and further genomic, and proteomic, analyses of the sample revealed that IL-8 levels showed a positive correlation in patients with leukemia. The results had shown constitutive secretion of interleukin-8 by leukemia cells. So, our finding demonstrated that IL-8 is considered to have a role in the pathogenesis of leukemia, and quantification of IL-8 levels in leukemia conditions might be more useful and feasible in the clinical setting for the prediction of drug responses where it may represent a putative target for innovative diagnostic toward effective therapeutic approaches. However, further research explorations in this area are needed that include a greater number of patients with all different forms of leukemia, and estimating their IL-8 levels may hold the key for the additional predictive values on the recurrence of leukemia and its prognosis.

Keywords: T-ALL, IL-8, leukemia pathogenesis, cancer therapeutics

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Authors: Victor William Harris

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This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.

Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument

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Authors: Sayani Chatterjee, Kusum Lata Pangtey, Sarita Singh, Harvir Singh

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Biodegradation leads to a systematic alteration of the chemical and physical properties of crude oil showing sequential depletion of n-alkane, cycloalkanes, aromatic which increases its specific gravity, viscosity and the abundance of heteroatom-containing compounds. The biodegradation leads to a change in the molecular fingerprints and geochemical parameters of degraded oils, thus make source and maturity identification inconclusive or ambiguous. Asphaltene is equivalent to the most labile part of the respective kerogen and generally has high molecular weight. Its complex chemical structure with substantial microporous units makes it suitable to occlude the hydrocarbon expelled from the source. The occluded molecules are well preserved by the macromolecular structure and thus prevented from secondary alterations. They retain primary organic geochemical information over the geological time. The present study involves the extraction of this occluded hydrocarbon from the asphaltene cage through mild oxidative degradation using mild oxidative reagents like Hydrogen Peroxide (H₂O₂) and Acetic Acid (CH₃COOH) on purified asphaltene of the biodegraded oils of Mansa, Lanwa and Santhal fields in Cambay Basin. The study of these extracted occluded hydrocarbons was carried out for establishing oil to oil and oil to source correlation in the Mehsana block of Cambay Basin. The n-alkane and biomarker analysis through GC and GC-MS of these occluded hydrocarbons show similar biomarker imprint as the normal oil in the area and hence correlatable with them. The abundance of C29 steranes, presence of Oleanane, Gammacerane and 4-Methyl sterane depicts that the oils are derived from terrestrial organic matter deposited in the stratified saline water column in the marine environment with moderate maturity (VRc 0.6-0.8). The oil source correlation study suggests that the oils are derived from Jotana-Warosan Low area. The developed geochemical technique to extract the occluded hydrocarbon has effectively resolved the ambiguity that resulted from the inconclusive fingerprint of the biodegraded oil and the method can be also applied in other biodegraded oils as well.

Keywords: asphaltene, biomarkers, correlation, mild oxidation, occluded hydrocarbon

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: Michael T. Ajayi, Oluwakemi E. Fapojuwo

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Farmers are in need of regular and relevant information relating to new technologies. Production of extension materials has been found to be useful in facilitating the process. Extension materials help to provide information to reach large numbers of farmers quickly and economically. However, as good as extension materials are, previous materials produced are not used by farmers. The reasons for this include lack of involvement of farmers in the production of the extension materials, most of the extension materials are not relevant to the farmers’ environments, the agricultural extension agents lack capacity to prepare the materials, and many extension agents lack commitment. These problems led to this innovative capacity building of extension agents. This innovative approach involves five stages. The first stage is the diagnostic survey of farmers’ environment to collect useful information. The second stage is the development and production of draft extension materials. The third stage is the field testing and evaluation of draft materials by the same farmers that were involved at the diagnostic stage. The fourth stage is the revision of the draft extension materials by incorporating suggestions from farmers. The fifth stage is the action plans. This process improves the capacity of agricultural extension agents in the preparation of extension materials and also promotes engagement of farmers and beneficiaries in the process. The process also makes farmers assume some level of ownership of the exercise and the extension materials.

Keywords: capacity building, extension agents, dissemination, information/technologies

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Authors: N. A. D. P. Niwunhella, W. G. R. C. K. Sirisena

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Appendicitis is one of the most encountered abdominal emergencies worldwide. Proper clinical diagnosis and appendicectomy with minimal post operative complications are therefore priorities. Aim of this study was to ascertain the overall management of acute appendicitis in Sri Lanka in special preference to delayed primary suturing of the surgical site, comparing other local and international treatment outcomes. Data were collected prospectively from 155 patients who underwent appendicectomy following clinical and radiological diagnosis with ultrasonography. Histological assessment was done for all the specimens. All perforated appendices were managed with delayed primary closure. Patients were followed up for 28 days to assess complications. Mean age of patient presentation was 27 years; mean pre-operative waiting time following admission was 24 hours; average hospital stay was 72 hours; accuracy of clinical diagnosis of appendicitis as confirmed by histology was 87.1%; post operative wound infection rate was 8.3%, and among them 5% had perforated appendices; 4 patients had post operative complications managed without re-opening. There was no fistula formation or mortality reported. Current study was compared with previously published data: a comparison on management of acute appendicitis in Sri Lanka vs. United Kingdom (UK). The diagnosis of current study was equally accurate, but post operative complications were significantly reduced - (current study-9.6%, compared Sri Lankan study-16.4%; compared UK study-14.1%). During the recent years, there has been an exponential rise in the use of Computerised Tomography (CT) imaging in the assessment of patients with acute appendicitis. Even though, the diagnostic accuracy without using CT, and treatment outcome of acute appendicitis in this study match other local studies as well as with data compared to UK. Therefore CT usage has not increased the diagnostic accuracy of acute appendicitis significantly. Especially, delayed primary closure may have reduced post operative wound infection rate for ruptured appendices, therefore suggest this approach for further evaluation as a safer and an effective practice in other hospitals worldwide as well.

Keywords: acute appendicitis, computerised tomography, diagnostic accuracy, delayed primary closure

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Authors: Annisa Amalina, Lintang Sekar Sari, Khairunnisa Salsabila, Astya Gema Ramadhan, M. Fatkhi, Andani Eka Putra

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Gonorrhea is one of the sexually transmitted diseases by genito-genital, oro-genital and anogenital. Gonorrhea disease will cause complications if not treated properly. The diagnostic tool that has been used nowadays is microscopic. Thus a rapid diagnostic tool for gonorrhea is required, using polyclonal antibodies. The purpose of this study was to determine the effectiveness of injections of intravenous, subcutaneous and intracutaneous crude protein gonorrhea. The research method used in this research is experimental explorative. This research was conducted in Molecular Microbiology Laboratory of Faculty of Medicine, Andalas University for 3 months from April to June 2017. This study used 3 groups of rabbit with intravenous, subcutaneous, and intracutaneous injections. Each group was treated on days 1, 7, 21, and 28 with crude protein injection. After that, the examination of antibody levels held by using ELISA, followed by the antibody comparative tests contained in all three groups. The results examined by One Way ANOVA test on SPSS 21 and showed that there is no significant difference between intravenous, subcutaneous, and intracutaneous use p=0.69 (p < 0.05). However, there is an increased level (0.047 to 1.171) in antibodies from day 1 to day 14. In addition, subcutaneous use is preferred because it has minimal side effects compared to intravenous and intracutaneous use.

Keywords: crude protein, Neisseria gonorrhea, polyclonal antibodies, subcutaneous

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Authors: M. Dieb, T. Hodairi

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In the Southwest Libya area, the Palaeozoic deposits are an important petroleum system, with Silurian shale considered a hydrocarbon source rock and Cambro-Ordovician recognized as a good reservoir. The Palaeozoic petroleum system has the greatest potential for conventional and is thought to represent the significant prospect of unconventional petroleum resources in Southwest Libya. Until now, the lateral and vertical heterogeneity of the source rock was not well evaluated, and oil-source correlation is still a matter of debate. One source rock, which is considered the main source potential in Marzuq Basin, was investigated for its uranium contents using gamma-ray logs, rock-eval pyrolysis, and organic petrography for their bulk kinetic characteristics to determine the petroleum potential qualitatively and quantitatively. Thirty source rock samples and fifteen oil samples from the Tannezzuft source rock were analyzed by Rock-Eval Pyrolysis, microscopely investigation, GC, and GC-MS to detect acyclic isoprenoids and aliphatic, aromatic, and NSO biomarkers. Geochemistry tools were applied to screen source and age-significant biomarkers to high-spot genetic relationships. A grating heterogeneity exists among source rock zones from different levels of depth with varying uranium contents according to gamma-ray logs, rock-eval pyrolysis results, and kinetic features. The uranium-rich Tannezzuft Formations (Hot Shales) produce oils and oil-to-gas hydrocarbons based on their richness, kerogen type, and thermal maturity. Biomarker results such as C₂₇, C₂₈, and C₂₉ steranes concentrations and C₂₄ tetracyclic terpane/C₂₉ tricyclic terpane ratios, with sterane and hopane ratios, are considered the most promising biomarker information in differentiating within the Silurian Shale Tannezzuft Formation and in correlating with its expelled oils. The Tannezzuft Hot Shale is considered the main source rock for oil and gas accumulations in the Cambro-Ordovician reservoirs within the Marzuq Basin. Migration of the generated and expelled oil and gas from the Tannezzuft source rock to the reservoirs of the Cambro-Ordovician petroleum system was interpreted to have occurred along vertical and lateral pathways along the faults in the Palaeozoic Strata. The Upper Tannezzuft Formation (cold shale) is considered the primary seal in the Marzuq Basin.

Keywords: heterogeneity, hot shale, kerogen, Silurian, uranium

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: time series modelling, stochastic processes, ARIMA model, Karkheh river

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Andreas Latz, Daniela Heinz, Fatima Hashemi, Melek Baygül

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Introduction: Feline leukemia virus (FeLV), feline immunodeficiency virus (FIV), and feline coronavirus (FCoV) are serious infectious diseases affecting cats worldwide. Transmission of these viruses occurs primarily through close contact with infected cats (via saliva, nasal secretions, faeces, etc.). FeLV, FIV, and FCoV infections can occur in combination and are expressed in similar clinical symptoms. Diagnosis can therefore be challenging: Symptoms are variable and often non-specific. Sick cats show very similar clinical symptoms: apathy, anorexia, fever, immunodeficiency syndrome, anemia, etc. Sample volume for small companion animals for diagnostic purposes can be challenging to collect. In addition, multiplex diagnosis of diseases can contribute to an easier, cheaper, and faster workflow in the lab as well as to the better differential diagnosis of diseases. For this reason, we wanted to develop a new diagnostic tool that utilizes less sample volume, reagents, and consumables than multiplesingleplex ELISA assays Methods: The Multiplier from Dynextechonogies (USA) has been used as platform to develop a Multiplex diagnostic tool for the detection of antibodies against FIV and FCoV/FIP and antigens for FeLV. Multiplex diagnostics. The Dynex®Multiplier®is a fully automated chemiluminescence immunoassay analyzer that significantly simplifies laboratory workflow. The Multiplier®ease-of-use reduces pre-analytical steps by combining the power of efficiently multiplexing multiple assays with the simplicity of automated microplate processing. Plastic beads have been coated with antigens for FIV and FCoV/FIP, as well as antibodies for FeLV. Feline blood samples are incubated with the beads. Read out of results is performed via chemiluminescence Results: Bead coating was optimized for each individual antigen or capture antibody and then combined in the multiplex diagnostic tool. HRP: Antibody conjugates for FIV and FCoV antibodies, as well as detection antibodies for FeLV antigen, have been adjusted and mixed. 3 individual prototyple batches of the assay have been produced. We analyzed for each disease 50 well defined positive and negative samples. Results show an excellent diagnostic performance of the simultaneous detection of antibodies or antigens against these feline diseases in a fully automated system. A 100% concordance with singleplex methods like ELISA or IFA can be observed. Intra- and Inter-Assays showed a high precision of the test with CV values below 10% for each individual bead. Accelerated stability testing indicate a shelf life of at least 1 year. Conclusion: The new tool can be used for multiplex diagnostics of the most important feline infectious diseases. Only a very small sample volume is required. Fully automation results in a very convenient and fast method for diagnosing animal diseases.With its large specimen capacity to process over 576 samples per 8-hours shift and provide up to 3,456 results, very high laboratory productivity and reagent savings can be achieved.

Keywords: Multiplex, FIV, FeLV, FCoV, FIP

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Stela Papa, Klementina Puto, Migena Pllaha

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HCV is a hepatotropic RNA virus, transmitted primarily via the blood route, which causes progressive disease such as chronic hepatitis, liver cirrhosis, or hepatocellular carcinoma. HCV nowadays is a global healthcare problem. A variety of immunoassays including old and new technologies are being applied to detect HCV in our country. These methods include Immunochromatography assays (ICA), Fluorescence immunoassay (FIA), Enzyme linked fluorescent assay (ELFA), and Enzyme linked immunosorbent assay (ELISA) to detect HCV antibodies in blood serum, which lately is being slowly replaced by more sensitive methods such as rapid automated analyzer chemiluminescence immunoassay (CLIA). The aim of this study is to estimate HCV infection in carriers and chronic acute patients and to evaluate the use of new diagnostic methods. This study was realized from September 2016 to May 2018. During this study period, 2913 patients were analyzed for the presence of HCV by taking samples from their blood serum. The immunoassays performed were ICA, FIA, ELFA, ELISA, and CLIA assays. Concluding, 82% of patients taken in this study, resulted infected with HCV. Diagnostic methods in clinical laboratories are crucial in the early stages of infection, in the management of chronic hepatitis and in the treatment of patients during their disease.

Keywords: CLIA, ELISA, Hepatitis C virus, immunoassay

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Authors: Tarak Barhoumi, Younes Boujelbene

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Nowadays, the problems of freight transport pose logistical constraints on the urban system in the city. The aim of this article is to gain a better understanding of the interactions between local traffic and interurban traffic on the one hand and between the location system and the transport system on the other hand. Thus, in a simulation and analysis approach cannot be restricted to the only transport system. The proposed approach is based on an assessment of the impact of freight transport, which is closely linked to the diagnostic method, based on two surveys carried out on the territory of the urban community of Sfax. These surveys are based on two main components 'establishment component' first and 'driver component' second. The results propose a reorganization of freight transport in the city of Sfax. First, an orientation of the heavy goods vehicles traffic towards the major axes of transport namely the ring roads (ring road N° 2, ring road N° 4 and ring road N° 11) and the penetrating news of the city. Then, the implementation of a retail goods delivery policy and the strengthening of logistics in the city. The creation of a logistics zone at the ring road N° 11 where various modes of freight transport meet, in order to decongest the roads of heavy goods traffic, reduce the cost of transport and thus improve the competitiveness of the economy regional.

Keywords: urban logistics systems, transport freight, diagnostics, evaluation

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Authors: Nina Miklavčič, Urška Kugovnik, Natalia Galkina, Primož Ribarič, Rudi Vončina

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Today, the need for weather predictions is deeply rooted in the everyday life of people as well as it is in industry. The forecasts influence final decision-making processes in multiple areas, from agriculture and prevention of natural disasters to air traffic regulations and solutions on a national level for health, security, and economic problems. Namely, in Slovenia, alongside other existing forms of application, weather forecasts are adopted for the prognosis of electrical current transmission through powerlines. Meteorological parameters are one of the key factors which need to be considered in estimations of the reliable supply of electrical energy to consumers. And like for any other measured value, the knowledge about measurement uncertainty is also critical for the secure and reliable supply of energy. The estimation of measurement uncertainty grants us a more accurate interpretation of data, a better quality of the end results, and even a possibility of improvement of weather forecast models. In the article, we focused on the estimation of measurement uncertainty of the diagnostic microscale meteorological model CALMET. For the purposes of our research, we used a network of meteorological stations spread in the area of our interest, which enables a side-by-side comparison of measured meteorological values with the values calculated with the help of CALMET and the measurement uncertainty estimation as a final result.

Keywords: uncertancy, meteorological model, meteorological measurment, CALMET

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: G. Tanbayeva, Z. Myrzabekov, O. Tagayev, B. Barakhov, M. Tokayeva

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Mastitis is widely spread among dairy cows bringing large economic damage resulting in decreased milk yield, deterioration of the milk quality, gastrointestinal tract disorders among young animals, culling of breeding stock, and expenses for sick animal treatment. Up-to-date and accurate diagnostics of subclinical (latent) mastitis in dairy cows has huge practical and economical significance. The aim of the research was to develop a new optimal alternative rapid method for the diagnosis of subclinical mastitis in cows. The study was performed in the laboratory of the Hygiene and Sanitation of Kazakh National Agrarian University. The first stage was to evaluate the different percentages of “Promastit” preparation. It showed that the best diagnostics capacity had 10% dilution. The second stage was to compare “Promastit” with some of the domestic and foreign analogues “Somatic-Test” (Denmark), “MastTest” (Russia), “Mastidin” (Ukraine), “Diagmast” (Kazakhstan). The observation was carried out on 520 dairy cows with subclinical mastitis on farms of Almaty region of Kazakhstan. The effectiveness was checked by milk sedimentation test. Our research tends to show that the diagnostic test "Promastitis" revealed subclinical mastitis in 193 out of 520 lactating cows (37.1% of those examined). At the same time, in the case of using other diagnostic tests, the given index was as follows: 35.5% (mastidin), 34.4% (masttest-AF), 33.8% (somatic-test Ecotest), 30.7% (diagmast).

Keywords: dairy cows, diagnostics, subclinical mastitis, test Promastit

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Authors: Karissa A. Graham

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Pyoderma gangrenosum (PG) is a prototypic autoinflammatory neutrophilic dermatosis that is a rare disorder. It presents a diagnostic challenge owing to its variable presentation, clinical overlap with other conditions, it is often associated with other systemic conditions, and there is no definitive histological or laboratory characteristic. The Delphai consensus for PG includes the presence of at least one ulcer on the anterior lower limb. Systemic corticosteroids and immunosuppressive therapies are the mainstay treatment for PG. We describe a case report of delayed diagnosis of ulcerative pyoderma gangrenosum in a 44-year-old male on his forearm. The patient presented with an infected ulcer on his right forearm that had been present for over three years. The patient was a Type 2 Diabetic with no personal or family history of inflammatory bowel disease or other autoimmune diseases. The patient was initially investigated for malignancy, but biopsies returned as chronic inflammatory tissue with neutrophilic infiltrate and no malignancy. The patient was commenced on systemic prednisone for the treatment of pyoderma gangrenosum. The diagnosis of ulcerative PG poses a challenge given the vast differential diagnosis for a cutaneous ulcer (i.e., malignant, vascular, autoimmune, trauma, infective, etc.). Diagnostic accuracy is important given that the treatment for PG with steroids does not go without risks and indeed may be contraindicated in other potential causes of the ulcer. Indeed, more common and more sinister causes of ulcers should be investigated first, as death from PG is quite rare.

Keywords: dermatological diagnosis, dermatosis, pyoderma gangrenosum, rare presentation

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Authors: Ayad Dalloo, Sulaf Dalloo

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Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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Authors: Majid Shahbazi

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Subclavian artery stenosis (SAS) is a common vascular disease that can cause a range of symptoms, from arm fatigue and weakness to ischemic stroke. Revascularization procedures, such as percutaneous transluminal angioplasty and stenting, are widely used to treat SAS and improve blood flow to the affected arm. However, the optimal management of patients with SAS is still unclear, and further research is needed to evaluate the safety and efficacy of different treatment options. This study aims to investigate the characteristics of patients with SAS who underwent revascularization procedures in Latvia (Specifically RAKUS). The research part of this paper aims to describe and analyze the demographics, comorbidities, diagnostic methods, types of revascularization procedures, and antiaggregant therapy used. The goal of this study is to provide insights into the current clinical practice in Latvia and help future treatment decision-makers. To achieve this aim, a retrospective study of 76 patients with SAS who underwent revascularization procedures was performed. After statistical analysis of the data, the study provided insights into the characteristics and management of patients with SAS in Latvia, highlighting the most observed comorbidities in these patients, the preferred diagnostic methods, and the most performed procedures. These findings can inform clinical decision-making and may have implications for the management of patients with subclavian artery stenosis in Latvia.

Keywords: subclavian artery stenosis, revascularization, characteristics of patients, comorbidities, retrospective analysis

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