Search results for: clinical document retrieval

Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Omer Ibrahim Abdallh Omer

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Cancer patients often face complex medication regimens, leading to challenges in treatment adherence and clinical outcomes. Pharmacist-led medication therapy management (MTM) has emerged as a potential solution to optimize medication use and improve patient outcomes in oncology settings. In this prospective intervention study, we aimed to evaluate the impact of pharmacist-led MTM on treatment adherence and clinical outcomes among cancer patients. Participants were randomized to receive either pharmacist-led MTM or standard care, with assessments conducted at baseline and follow-up visits. Pharmacist interventions included medication reconciliation, adherence counseling, and personalized care plans. Our findings reveal that pharmacist-led MTM significantly improved medication adherence rates and clinical outcomes compared to standard care. Patients receiving pharmacist interventions reported higher satisfaction levels and perceived value in pharmacist involvement in their cancer care. These results underscore the critical role of pharmacists in optimizing medication therapy and enhancing patient-centered care in oncology settings. Integration of pharmacist-led MTM into routine cancer care pathways holds promise for improving treatment outcomes and quality of life for cancer patients.

Keywords: cancer, medications adherence, medication therapy management, pharmacist

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Authors: Mahdi Asghari Ozma, Fatemeh Aghamohammadzadeh, Mahin Ahangar Oskouee

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In late 2019, the people of the world were involved with a new infection by the coronavirus, named SARS-COV-2 (COVID-19), which disseminated around the world quickly. This infection has the ability to affect various systems of the body, including respiratory, gastrointestinal, urinary, and hematology, which can be transmitted by various body samples in different ways. To control this fast-transmitted infection by preventing its transmission to other people, rapid diagnosis is vital, which can be done by examining the patient's clinical symptoms and also using various serological, molecular, and radiological methods. Symptoms caused by COVID-19 in patients include fever, cough, sore throat, headache, fatigue, shortness of breath, loss of taste or smell, skin rash, myalgia, and conjunctivitis. These clinical features were appearing gradually in different time periods from the onset of the infection, and patients showed varied and new symptoms at different times, which show the variety of symptoms over time during the spread of the infection.

Keywords: COVID-19, diagnosis, symptom, variation, novel coronavirus

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Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

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Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

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HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

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Authors: S. Grinnell

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A PhD Research Project exploring the Social Health and Well-Being Impacts associated with Hydraulic Fracturing, with an aim to produce a Best Practice Support Guidance for those anticipating dealing with planning applications or submitting Environmental Impact Assessments (EIAs). Amid a possible global energy crisis, founded upon a number of factors, including unstable political situations, increasing world population growth, people living longer, it is perhaps inevitable that Hydraulic Fracturing (commonly referred to as ‘fracking’) will become a major player within the global long-term energy and sustainability agenda. As there is currently no best practice guidance for governing bodies the Best Practice Support Document will be targeted at a number of audiences including, consultants undertaking EIAs, Planning Officers, those commissioning EIAs Industry and interested public stakeholders. It will offer a robust, evidence-based criteria and recommendations which provide a clear narrative and consistent and shared approach to the language used along with containing an understanding of the issues identified. It is proposed that the Best Practice Support Document will also support the mitigation of health impacts identified. The Best Practice Support Document will support the newly amended Environmental Impact Assessment Directive (2011/92/EU), to be transposed into UK law by 2017. A significant amendment introduced focuses on, ‘higher level of protection to the environment and health.’ Methodology: A qualitative research methods approach is being taken with this research. It will have a number of key stages. A literature review has been undertaken and been critically reviewed and analysed. This was followed by a descriptive content analysis of a selection of international and national policies, programmes and strategies along with published Environmental Impact Assessments and associated planning guidance. In terms of data collection, a number of stakeholders were interviewed as well as a number of focus groups of local community groups potentially affected by fracking. These were determined from across the UK. A theme analysis of all the data collected and the literature review will be undertaken, using NVivo. Best Practice Supporting Document will be developed based on the outcomes of the analysis and be tested and piloted in the professional fields, before a live launch. Concluding statement: Whilst fracking is not a new concept, the technology is now driving a new force behind the use of this engineering to supply fuels. A number of countries have pledged moratoria on fracking until further investigation from the impacts on health have been explored, whilst other countries including Poland and the UK are pushing to support the use of fracking. If this should be the case, it will be important that the public’s concerns, perceptions, fears and objections regarding the wider social health and well-being impacts are considered along with the more traditional biomedical health impacts.

Keywords: fracking, hydraulic fracturing, socio-economic health, well-being

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Authors: Zhipeng Yan, Janice Wing-Tung Kwong, Ching-Lung Lai

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Background: Advanced melanoma accounts for the majority of skin cancer death due to its poor prognosis. Nivolumab and ipilimumab are monoclonal antibodies targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocytes antigen 4 (CTLA-4). Nivolumab and ipilimumab combination therapy has been proven to be effective for advanced melanoma. This systematic review and meta-analysis are to evaluate its clinical efficacy and adverse events. Method: A systematic search was done on databases (Pubmed, Embase, Medline, Cochrane) on 21 June 2020. Search keywords were nivolumab, ipilimumab, melanoma, and randomised controlled trials. Clinical trials fulfilling the inclusion criteria were selected to evaluate the efficacy of combination therapy in terms of prolongation of progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). The odd ratios and distributions of grade 3 or above adverse events were documented. Subgroup analysis was performed based on PD-L1 expression-status and BRAF-mutation status. Results: Compared with nivolumab monotherapy, the hazard ratios of PFS, OS and odd ratio of ORR in combination therapy were 0.64 (95% CI, 0.48-0.85; p=0.002), 0.84 (95% CI, 0.74-0.95; p=0.007) and 1.76 (95% CI, 1.51-2.06; p < 0.001), respectively. Compared with ipilimumab monotherapy, the hazard ratios of PFS, OS and odd ratio of ORR were 0.46 (95% CI, 0.37-0.57; p < 0.001), 0.54 (95% CI, 0.48-0.61; p < 0.001) and 6.18 (95% CI, 5.19-7.36; p < 0.001), respectively. In combination therapy, the odds ratios of grade 3 or above adverse events were 4.71 (95% CI, 3.57-6.22; p < 0.001) compared with nivolumab monotherapy, and 3.44 (95% CI, 2.49-4.74; p < 0.001) compared with ipilimumab monotherapy, respectively. High PD-L1 expression level and BRAF mutation were associated with better clinical outcomes in patients receiving combination therapy. Conclusion: Combination therapy is effective for the treatment of advanced melanoma. Adverse events were common but manageable. Better clinical outcomes were observed in patients with high PD-L1 expression levels and positive BRAF-mutation.

Keywords: nivolumab, ipilimumab, advanced melanoma, systematic review, meta-analysis

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Suchana Marahatta, Sabina Bhattarai, Bishnu Hari Paudel, Dilip Thakur

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Background: Every year thousands of patients develop nerve damage and disabilities as a result of leprosy which can be prevented by early detection and treatment. So, early detection and treatment of nerve function impairment is of paramount importance in leprosy. Objectives: To assess the electrophysiological pattern of the peripheral nerves in leprosy patients and to compare it with clinical assessment tools. Materials and Methods: In this comparative cross-sectional study, 74 newly diagnosed leprosy patients without reaction were enrolled. They underwent thorough evaluation for peripheral nerve function impairment using clinical tests [i.e. nerve palpation (NP), monofilament (MF) testing, voluntary muscle testing (VMT)] and nerve conduction study (NCS). Clinical findings were compared with that of NCS using SPSS version 11.5. Results: NCS was impaired in 43.24% of leprosy patient at the baseline. Among them, sensory NCS was impaired in more patients (32.4%) in comparison to motor NCS (20.3%). NP, MF, and VMT were impaired in 58.1%, 25.7%, and 9.4% of the patients, respectively. Maximum concordance of monofilament testing and sensory NCS was found for sural nerve (14.7%). Likewise, the concordance of motor NP and motor NCS was the maximum for ulnar nerve (14.9%). When individual parameters of the NCS were considered, amplitude was found to be the most frequently affected parameter for both sensory and motor NCS. It was impaired in 100% of cases with abnormal NCS findings. Conclusion: Since there was no acceptable concordance between NCS findings and clinical findings, we should consider NCS whenever feasible for early detection of neuropathy in leprosy. The amplitude of both sensory nerve action potential (SNAP) and compound nerve action potential (CAMP) could be important determinants of the abnormal NCS if supported by further studies.

Keywords: leprosy, nerve function impairment, neuropathy, nerve conduction study

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Authors: Michael Zhang, Nicholas Marriage, Valerie Astle, Marie-Louise Ratican, Jonathan Ash, Haddijatou Hughes

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Objective: Young infants are often brought to the Emergency Department (ED) with a variety of complaints, some of them are non-specific and present as a diagnostic challenge to the attending clinician. Whilst invasive investigations such as blood tests and lumbar puncture are necessary in some cases to exclude serious infections, some basic clinical tools in additional to thorough clinical history can be useful to assess the risks of serious conditions in these young infants. This study aimed to examine the utilization of one of clinical tools in this regard. Methods: This retrospective observational study examined the medical records of infants under 6 months presenting to a mixed urban ED between January 2013 and December 2014. The infants deemed to have non-specific complaints or diagnoses by the emergency clinicians were selected for analysis. The ones with clear systemic diagnoses were excluded. Among all relevant clinical information and investigation results, utilization of Standard Paediatric Observation Chart (SPOC) was particularly scrutinized in these medical records. This specific chart was developed by the expert clinicians in local health department. It categorizes important clinical signs into some color-coded zones as a visual cue for serious implication of some abnormalities. An infant is regarded as SPOC positive when fulfills 1 red zone or 2 yellow zones criteria, and the attending clinician would be prompted to investigate and treat for potential serious conditions accordingly. Results: Eight hundred and thirty-five infants met the inclusion criteria for this project. The ones admitted to the hospital for further management were more likely to have SPOC positive criteria than the discharged infants (Odds ratio: 12.26, 95% CI: 8.04 – 18.69). Similarly, Sepsis alert criteria on SPOC were positive in a higher percentage of patients with serious infections (56.52%) in comparison to those with mild conditions (15.89%) (p < 0.001). The SPOC sepsis criteria had a sensitivity of 56.5% (95% CI: 47.0% - 65.7%) and a moderate specificity of 84.1% (95% CI: 80.8% - 87.0%) to identify serious infections. Applying to this infant population, with a 17.4% prevalence of serious infection, the positive predictive value was only 42.8% (95% CI: 36.9% - 49.0%). However, the negative predictive value was high at 90.2% (95% CI: 88.1% - 91.9%). Conclusions: Standard Paediatric Observation Chart has been applied as a useful clinical tool in the clinical practice to help identify and manage young sick infants in ED effectively.

Keywords: clinical tool, infants, non-specific complaints, Standard Paediatric Observation Chart

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Authors: Gulcan Sahal, Nermin Hande Avcioglu, Isil Seyis Bilkay

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Klebsiella species which are natural colonizers of human upper respiratory and human gastrointestinal tracts are also responsible for every reoccurring nosocomial infections by means of having ability to form slimy layers known as biofilm on many surfaces. Therefore, in this study, investigation of biofilm formation in K. pneumoniae and K. rhinoscleromatis and examination of each Klebsiella strains’ clinical information in the light of their biofilm formation results were aimed. In this respect, biofilm formation of Klebsiella strains was analyzed via crystal violet binding assay. According to our results, biofilm formation levels of K. pneumoniae and K. rhinoscleromatis strains were different from each other. Additionally, in comparison to K. rhinoscleromatis strains, K. pneumoniae was observed to include higher amounts of strong biofilm forming strains. Besides, it was also seen that clinical information of patients from which strong biofilm forming Klebsiella strains were isolated were similar to each other. Our results indicate that there should be more precautions against K. pneumoniae which includes higher amount of strong biofilm forming strains.

Keywords: biofilm formation, Klebsiella pneumoniae, Klebsiella rhinoscleromatis, biosystems engineering

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Authors: Ayubova Nargiza Mirzabixulaevna, Kiryakov Dmitriy Andreyevich

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Relevance: According to experts from the World Health Organization, in 80% of cases, the causes of skin cancer are external factors: polluted air, radioactive substances, solar flares, and free radicals. In dermatology, one of the most common related to obligate diseases is actinic keratosis. Actinic keratosis (AC) is an area of abnormal proliferation and differentiation of keratinocytes, which carry the risk of progression into invasive squamous cell carcinoma of the skin. The purpose of the study is to study the prevalence of various forms of actinic keratosis among the population of Uzbekistan. Materials and methods of research: The study is based on the observation and clinical laboratory examination of 96 patients who were divided by gender and age. Women made up 45% and men made up 55%. The youngest patient was 43 years old, and the oldest was 92 years old. The control group consisted of 40 patients. The following clinical signs were evaluated: peeling, hyperkeratosis, erythema, pigmentation, atrophy. Results: Studies have shown that of all forms of actinic keratosis, erythematous (36%), hyperkeratotic (27%), pigmented (12%), cutaneous horn (7.0%), atrophic (7.0%), Actinic cheilitis (6%), lichenoid (5%) are common. Conclusion: Thus, the data we have obtained indicate that the main and pronounced clinical sign in the erythematous form is erythema and the hyperkeratic form is often found. With cutaneous horn, there is a sharp hyperkeratosis of the epidermis.

Keywords: actinic keratosis, patient, skin cancer, obligate diseases

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Authors: Sayantika Biswas, Dipanshu Sur, Amitoj Athwal, Ratnabali Chakravorty

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Title: Impact of serum estrogen and progesterone levels in the outcome pregnancy rate in frozen embryo transfer cycles. A prospective cohort study Objective: The aim of the current study was to evaluate the effect of serum estradiol (E2) and progesterone (P4) levels at different time points on pregnancy outcomes in frozen embryo transfer (FET) cycles. Materials & Method: A prospective cohort study was performed in patients undergoing frozen embryo transfer. Patients under age 37 years of age with at least one good blastocyst or three good day 3 embryos were included in the study. For endometrial preparation, 14 days of oral estradiol use (2X2 mg for 5 days. 3X2 mg for 4 days, and 4X2 mg for 5 days) was followed by vaginal progesterone twice a day and 50 mg intramuscular progesterone twice a day. Embryo transfer was scheduled 72-76 hrs or 116-120hrs after the initiation of progesterone. Serum E2 and P4 levels were examined at 4 times a) at the start of the menstrual cycle prior to the hormone supplementation. b) on the day of P4 start. c) on the day of ET. d) on the third day after ET. Result: A total 41 women were included in this study (mean age 31.8; SD 2.8). Clinical pregnancy rate was 65.55%. Serum E2 levels on at the start of the menstrual cycle prior to the hormone supplementation and on the day of P4 start were high in patients who achieved pregnancy compared to who did not (P=0.005 and P=0.019 respectively). P4 levels on on the day of ET were also high in patients with clinical pregnancy. On the day of P4 start, a serum E2 threshold of 186.4 pg/ml had a sensitivity of 82%, and P4 had a sensitivity of 71% for the prediction of clinical pregnancy at the threshold value 16.00 ng/ml. Conclusion: In women undergoing FET with hormone replacement, serum E2 level >186.4 pg/ml on the day of the start of progesterone and serum P4 levels >16.00 ng/ml on embryo transfer day are associated with clinical pregnancy.

Keywords: serum estradiol, serum progesterone, clinical pregnancy, frozen embryo transfer

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Authors: Ricardo Munguia-Perez, Nayeli Remigio-Alvarado, M.Miriam Hernandez-Arroyo, Elsa Castañeda-Roldan

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Fungi have emerged as important pathogens causing morbidity and mortality mainly in immunosuppressed, malnourished and elderly patients. It has detected an increase in resistance to azoles primarily to fluconazol. The fungal infections have become a problem of public health for the resistance to antifungal agents, they have developed new antifungals with broad-spectrum. The aim of this study was determine the antifungal susceptibility of yeasts isolated from clinical samples (respiratory secretions, exudates, wounds, blood cultures, urine cultures) obtained from inpatients and outpatients of a tertiary hospital from State of Puebla. The antifungal susceptibility of the yeast from several clinical samples were determined by the CLS M44-A disk diffusion methods. 149 samples of yeast were analyzed. All species were 100% susceptible to nystatin and amphotericin B. Candida albicans showed resistance of 95.5 % to fluconazole, 50.7 % to 5-flurocytosine and 55.2 % intermediate susceptibility to ketoconazole. Candida glabrata 81.3 % was susceptibility to ketoconazole and 75 % to fluconazole, for the case of 5-flurocytosine the 56.3 % was susceptible. Candida krusei 100 % was susceptible to ketoconazole, 50 % to fluconazole and 37.5 % to 5-flurocytosine. The internal medicine have greater diversity of yeast, the samples have susceptibility of 64.7% to ketoconazole, 47.1 % to fluconazole and 27.5 % to 5-flurocytosine. Hospitalized patients are more resistant to fluconazole and nystatin, but in the case of outpatients presents resistance to ketoconazole.

Keywords: antifungal, susceptibility, yeast, clinical samples

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Authors: Suin Seo, Sung-Il Cho

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Background: The use of mobile apps for smoking cessation has grown exponentially in recent years. Yet, there were limited researches which evaluated the quality of smoking cessation apps to our knowledge. In most cases, a clinical practice guideline which is focused on clinical physician was used as an evaluation tool. Objective: The objective of this study was to develop a user-centered measure for quality of mobile smoking cessation apps. Methods: A literature search was conducted to identify articles containing explicit smoking cessation guideline for smoker published until January 2018. WHO’s guide for tobacco users to quit was adopted for evaluation tool which assesses smoker-oriented contents of smoking cessation apps. Compared to the clinical practice guideline, WHO guideline was designed for smokers (non-specialist). On the basis of existing criteria which was developed based on 2008 clinical practice guideline for Treating Tobacco Use and Dependence, evaluation tool was modified and developed by an expert panel. Results: There were five broad categories of criteria that were identified including five objective quality scales: enhancing motivation, assistance with a planning and making quit attempts, preparation for relapse, self-efficacy, connection to smoking. Enhancing motivation and assistance with planning and making quit attempts were similar to contents of clinical practice guideline, but preparation for relapse, self-efficacy and connection to smoking (environment or habit which reminds of smoking) only existed on WHO guideline. WHO guideline had more user-centered elements than clinical guideline. Especially, self-efficacy is the most important determinant of behavior change in accordance with many health behavior change models. With the WHO guideline, it is now possible to analyze the content of the app in the light of a health participant, not a provider. Conclusion: The WHO guideline evaluation tool is a simple, reliable and smoker-centered tool for assessing the quality of mobile smoking cessation apps. It can also be used to provide a checklist for the development of new high-quality smoking cessation apps.

Keywords: smoking cessation, evaluation, mobile application, WHO, guideline

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Authors: Debjyoti Bhakat, Indranil Mondal, Asish K. Mukhopadayay, Nabendu S. Chatterjee

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Enterotoxigenic Escherichia coli is one of the leading causes of diarrhea in infants and travelers in developing countries. Colonization factors play an important role in pathogenesis and are one of the main targets for Enterotoxigenic Escherichia coli (ETEC) vaccine development. However, ETEC vaccines had poorly performed in the past, as the prevalence of colonization factors is region-dependent. There are more than 25 classical colonization factors presently known to be expressed by ETEC, although all are not expressed together. Further, there are other multiple non-classical virulence factors that are also identified. Here the presence and expression of common classical and non-classical virulence factors were studied. Further studies were done on the expression of prevalent colonization factors in different strains. For the prevalence determination, multiplex polymerase chain reaction (PCR) was employed, which was confirmed by simplex PCR. Quantitative RT-PCR was done to study the RNA expression of these virulence factors. Strains negative for colonization factors expression were confirmed by SDS-PAGE. Among the clinical isolates, the most prevalent toxin was est+elt, followed by est and elt, while the pattern was reversed in the control strains. There were 29% and 40% strains negative for any classical colonization factors (CF) or non-classical virulence factors (NCVF) among the clinical and control strains, respectively. Among CF positive ETEC strains, CS6 and CS21 were the prevalent ones in the clinical strains, whereas in control strains, CS6 was the predominant one. For NCVF genes, eatA was the most prevalent among the clinical isolates and etpA for control. CS6 was the most expressed CF, and eatA was the predominantly expressed NCVF for both clinical and controlled ETEC isolates. CS6 expression was more in strains having CS6 alone. Different strains express CS6 at different levels. Not all strains expressed their respective virulence factors. Understanding the prevalent colonization factor, CS6, and its nature of expression will contribute to designing an effective vaccine against ETEC in this region of the globe. The expression pattern of CS6 also will help in examining the relatedness between the ETEC subtypes.

Keywords: classical virulence factors, CS6, diarrhea, enterotoxigenic escherichia coli, expression, non-classical virulence factors

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Authors: Caio E. G. Reis, Jose G. Dórea, Teresa H. M. da Costa

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Objective: Epidemiological data shows an inverse association of coffee consumption with risk of type 2 diabetes mellitus. However, the clinical effects of coffee consumption on the glucose metabolism biomarkers remain controversial. Thus, this paper reviews clinical trials that evaluated the effects of coffee consumption on glucose metabolism. Research Design and Methods: We identified studies published until December 2014 by searching electronic databases and reference lists. We included randomized clinical trials which the intervention group received caffeinated and/or decaffeinated coffee and the control group received water or placebo treatments and measured biomarkers of glucose metabolism. The Jadad Score was applied to evaluate the quality of the studies whereas studies that scored ≥ 3 points were considered for the analyses. Results: Seven clinical trials (total of 237 subjects) were analyzed involving adult healthy, overweight and diabetic subjects. The studies were divided in short-term (1 to 3h) and long-term (2 to 16 weeks) duration. The results for short-term studies showed that caffeinated coffee consumption may increase the area under the curve for glucose response, while for long-term studies caffeinated coffee may improve the glycemic metabolism by reducing the glucose curve and increasing insulin response. These results seem to show that the benefits of coffee consumption occur in the long-term as has been shown in the reduction of type 2 diabetes mellitus risk in epidemiological studies. Nevertheless, until the relationship between long-term coffee consumption and type 2 diabetes mellitus is better understood and any mechanism involved identified, it is premature to make claims about coffee preventing type 2 diabetes mellitus. Conclusion: The findings suggest that caffeinated coffee may impairs glucose metabolism in short-term but in the long-term the studies indicate reduction of type 2 diabetes mellitus risk. More clinical trials with comparable methodology are needed to unravel this paradox.

Keywords: coffee, diabetes mellitus type 2, glucose, insulin

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Authors: Kingston Rajiah, Mari Kannan Maharajan, Si Jen Yeen, Sara Lew

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Parkinson’s disease (PD) is a progressive neurodegenerative disorder with evolving layers of complexity. Both motor and non-motor symptoms of PD may affect patients’ quality of life (QoL). Life expectancy for an individual with Parkinson’s disease depends on the level of care the individual has access to, can have a direct impact on length of life. Therefore, improvement of the QoL is a significant part of therapeutic plans. Patients with PD, especially those who are in advanced stages, are in great need of assistance, mostly from their family members or caregivers in terms of medical, emotional, and social support. The role of a caregiver becomes increasingly important with the progression of PD, the severity of motor impairment and increasing age of the patient. The nature and symptoms associated with PD can place significant stresses on the caregivers’ burden. As the prevalence of PD is estimated to more than double by 2030, it is important to recognize and alleviate the burden experienced by caregivers. This study focused on the impact of the clinical features on the QoL of PD patients, and of their caregivers. This study included PD patients along with their caregivers and was undertaken at the Malaysian Parkinson's Disease Association from June 2016 to November 2016. Clinical features of PD patients were assessed using the Movement Disorder Society revised Unified Parkinson Disease Rating Scale (MDS-UPDRS); the Hoehn and Yahr Staging of Parkinson's Disease were used to assess the severity and Parkinson's disease activities of daily living scale were used to assess the disability of Parkinson’s disease patients. QoL of PD patients was measured using the Parkinson's Disease Questionnaire-39 (PDQ-39). The revised version of the Zarit Burden Interview assessed caregiver burden. At least one of the clinical features affected PD patients’ QoL, and at least one of the QoL domains affected the caregivers’ burden. Clinical features ‘Saliva and Drooling’, and ‘Dyskinesia’ explained 29% of variance in QoL of PD patients. The QoL domains ‘stigma’, along with ‘emotional wellbeing’ explained 48.6% of variance in caregivers’ burden. Clinical features such as saliva, drooling and dyskinesia affected the QoL of PD patients. The PD patients’ QoL domains such as ‘stigma’ and ‘emotional well-being’ influenced their caregivers’ burden.

Keywords: carers, quality of life, clinical features, Malaysia

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Authors: Alejandro Rodríguez-Molinero, Carlos Pérez-López, Jorge Hernández-Vara, Àngels Bayes-Rusiñol, Juan Carlos Martínez-Castrillo, David A. Pérez-Martínez

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Background: Monitoring motor symptoms in Parkinson's patients is often a complex and time-consuming task for clinicians, as Hauser's diaries are often poorly completed by patients. Recently, new automatic devices (Parkinson's holter: STAT-ON®) have been developed capable of monitoring patients' motor fluctuations. The MoMoPa-EC clinical trial (NCT04176302) investigates which of the two methods produces better clinical results. In this sub-analysis, the concordance between both methods is analyzed. Methods: In the MoMoPa-EC clinical trial, 164 patients with moderate-severe Parkinson's disease and at least two hours a day of Off will be included. At the time of patient recruitment, all of them completed a seven-day motor fluctuation diary at home (Hauser’s diary) while wearing the Parkinson's holter. In this sub-analysis, 71 patients with complete data for the purpose of this comparison were included. The intraclass correlation coefficient was calculated between the patient diary entries and the Parkinson's holter data in terms of time On, Off, and time with dyskinesias. Results: The intra-class correlation coefficient of both methods was 0.57 (95% CI: 0.3-0.74) for daily time in Off (%), 0.48 (95% CI: 0.14-0.68) for daily time in On (%), and 0.37 (95% CI %: -0.04-0.62) for daily time with dyskinesias (%). Conclusions: Both methods have a moderate agreement with each other. We will have to wait for the results of the MoMoPa-EC project to estimate which of them has the greatest clinical benefits. Acknowledgment: This work is supported by AbbVie S.L.U, the Instituto de Salud Carlos III [DTS17/00195], and the European Fund for Regional Development, 'A way to make Europe'.

Keywords: Parkinson, sensor, motor fluctuations, dyskinesia

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Authors: Christine Böckmann, Julia Rosemann

Abstract:

We present an inversion algorithm that is used in the European Aerosol Lidar Network for the inversion of data collected with multi-wavelength Raman lidar. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. The algorithm is based on manually controlled inversion of optical data which allows for detailed sensitivity studies and thus provides us with comparably high quality of the derived data products. The algorithm allows us to derive particle effective radius, volume, surface-area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light-absorption needs to be known with high accuracy. Single-scattering albedo (SSA) can be computed from the retrieve microphysical parameters and allows us to categorize aerosols into high and low absorbing aerosols. From mathematical point of view the algorithm is based on the concept of using truncated singular value decomposition as regularization method. This method was adapted to work for the retrieval of the particle size distribution function (PSD) and is called hybrid regularization technique since it is using a triple of regularization parameters. The inversion of an ill-posed problem, such as the retrieval of the PSD, is always a challenging task because very small measurement errors will be amplified most often hugely during the solution process unless an appropriate regularization method is used. Even using a regularization method is difficult since appropriate regularization parameters have to be determined. Therefore, in a next stage of our work we decided to use two regularization techniques in parallel for comparison purpose. The second method is an iterative regularization method based on Pade iteration. Here, the number of iteration steps serves as the regularization parameter. We successfully developed a semi-automated software for spherical particles which is able to run even on a parallel processor machine. From a mathematical point of view, it is also very important (as selection criteria for an appropriate regularization method) to investigate the degree of ill-posedness of the problem which we found is a moderate ill-posedness. We computed the optical data from mono-modal logarithmic PSD and investigated particles of spherical shape in our simulations. We considered particle radii as large as 6 nm which does not only cover the size range of particles in the fine-mode fraction of naturally occurring PSD but also covers a part of the coarse-mode fraction of PSD. We considered errors of 15% in the simulation studies. For the SSA, 100% of all cases achieve relative errors below 12%. In more detail, 87% of all cases for 355 nm and 88% of all cases for 532 nm are well below 6%. With respect to the absolute error for non- and weak-absorbing particles with real parts 1.5 and 1.6 in all modes the accuracy limit +/- 0.03 is achieved. In sum, 70% of all cases stay below +/-0.03 which is sufficient for climate change studies.

Keywords: aerosol particles, inverse problem, microphysical particle properties, regularization

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Authors: Shideh Mohseni Movahed, Mansoureh Safari

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Intelligent drug delivery systems (IDDS) are innovative technological innovations and clinical way to advance current treatments. These systems differ in technique of therapeutic administration, intricacy, materials and patient compliance to address numerous clinical conditions that require different pharmacological therapies. IDDS capable of releasing an active molecule at the proper site and at a amount that adjusts in response to the progression of the disease or to certain functions/biorhythms of the organism is particularly appealing. In this paper, we describe the most recent advances in the development of intelligent drug delivery systems.

Keywords: drug delivery systems, IDDS, medicine, health

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Authors: Yimeng Zhang

Abstract:

Major depressive disorder (MDD) is a prevalent mental health condition with a substantial economic impact and limited treatment options. Acupuncture has gained attention as a promising non-pharmacological intervention for alleviating depressive symptoms. However, its mechanisms and clinical effectiveness remain incompletely understood. This meta-analysis aims to (1) synthesize existing evidence on the mechanisms and clinical effectiveness of acupuncture for depression and (2) compare these findings with pharmacological interventions, providing insights for future research. Evidence from animal models and clinical studies indicates that acupuncture may enhance hippocampal and network neuroplasticity and reduce brain inflammation, potentially alleviating depressive disorders. Clinical studies suggest that acupuncture can effectively relieve primary depression, particularly in milder cases, and is beneficial in managing post-stroke depression, pain-related depression, and postpartum depression, both as a standalone and adjunctive treatment. Notably, combining acupuncture with antidepressant pharmacotherapy appears to enhance treatment outcomes and reduce medication side effects, addressing a critical issue in conventional drug therapy's high dropout rates. This meta-analysis, encompassing 12 studies and 710 participants, draws data from eight digital databases (PubMed, EMBASE, Web of Science, EBSCOhost, CNKI, CBM, Wangfang, and CQVIP) covering the period from 2012 to 2022. Utilizing Stata software 15.0, the meta-analysis employed random-effects and fixed-effects models to assess the distribution of depression in Traditional Chinese Medicine (TCM). The results underscore the substantial evidence supporting acupuncture's beneficial effects on depression. However, the small sample sizes of many clinical trials raise concerns about the generalizability of the findings, indicating a need for further research to validate these outcomes and optimize acupuncture's role in treating depression.

Keywords: Chinese medicine, acupuncture, depression, meta-analysis

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Authors: Manoj Kumar Reddy Pulim, Lakshmi Muthukrishnan, Geetha Jayapathy, Radhika Raman

Abstract:

Introduction: In the past two decades, noninvasive positive pressure ventilation (NIPPV) emerged as one of the most important advances in the management of both acute and chronic respiratory failure in children. In the acute setting, it is an alternative to intubation with a goal to preserve normal physiologic functions, decrease airway injury, and prevent respiratory tract infections. There is a need to determine the clinical profile and parameters which point towards the need for NIV in the pediatric emergency setting. Objectives: i) To study the clinical profile of children who required non invasive ventilation and invasive ventilation, ii) To study the clinical parameters common to children who required non invasive ventilation. Methods: All children between one month to 18 years, who were intubated in the pediatric emergency department and those for whom decision to commence Non Invasive Ventilation was made in Emergency Room were included in the study. Children were transferred to the Paediatric Intensive Care Unit and started on Non Invasive Ventilation as per our hospital policy and followed up in the Paediatric Intensive Care Unit. Clinical profile of all children which included age, gender, diagnosis and indication for intubation were documented. Clinical parameters such as respiratory rate, heart rate, saturation, grunting were documented. Parameters obtained were subject to statistical analysis. Observations: Airway disease (Bronchiolitis 25%, Viral induced wheeze 22%) was a common diagnosis in 32 children who required Non Invasive Ventilation. Neuromuscular disorder was the common diagnosis in 27 children (78%) who were Intubated. 17 children commenced on Non Invasive Ventilation who later needed invasive ventilation had Neuromuscular disease. High frequency nasal cannula was used in 32, and mask ventilation in 17 children. Clinical parameters common to the Non Invasive Ventilation group were age < 1 year (17), tachycardia n = 7 (22%), tachypnea n = 23 (72%) and severe respiratory distress n = 9 (28%), grunt n = 7 (22%), SPO2 (80% to 90%) n = 16. Children in the Non Invasive Ventilation + INTUBATION group were > 3 years (9), had tachycardia 7 (41%), tachypnea 9(53%) with a male predominance n = 9. In statistical comparison among 3 groups,'p' value was significant for pH, saturation, and use of Ionotrope. Conclusion: Invasive ventilation can be avoided in the paediatric Emergency Department in children with airway disease, by commencing Non Invasive Ventilation early. Intubation in the pediatric emergency department has a higher association with neuromuscular disorders.

Keywords: clinical parameters, indications, non invasive ventilation, paediatric emergency room

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Authors: Daly M. J, Condron C, Mulhall C, Eppich W, O'Neill J.

Abstract:

Introduction: In contemporary clinical cardiology, comprehensive and holistic bedside evaluation including accurate cardiac auscultation is in decline despite having positive effects on patients and their outcomes. Methods: Scripted histories and scoring checklists for three clinical scenarios in cardiology were co-created and refined through iterative consensus by a panel of clinical experts; these were then paired with recordings of auscultatory findings from three actual patients with known valvular heart disease. A wearable vest with embedded pressure-sensitive panel speakers was developed to transmit these recordings when examined at the standard auscultation points. RCSI medical students volunteered for a series of three formative long case examinations in cardiology (LC1 – LC3) using this hybrid simulation. Participants were randomised into two groups: Group 1 received individual teaching from an expert trainer between LC1 and LC2; Group 2 received the same intervention between LC2 and LC3. Each participant’s long case examination performance was recorded and blindly scored by two peer participants and two RCSI examiners. Results: Sixty-eight participants were included in the study (age 27.6 ± 0.1 years; 74% female) and randomised into two groups; there were no significant differences in baseline characteristics between groups. Overall, the median total faculty examiner score was 39.8% (35.8 – 44.6%) in LC1 and increased to 63.3% (56.9 – 66.4%) in LC3, with those in Group 1 showing a greater improvement in LC2 total score than that observed in Group 2 (p < .001). Using the novel checklist, intraclass correlation coefficients (ICC) were excellent between examiners in all cases: ICC .994 – .997 (p < .001); correlation between peers and examiners improved in LC2 following peer grading of LC1 performances: ICC .857 – .867 (p < .001). Conclusion: Hybrid simulation and quantitative grading improve learning, standardisation of assessment, and direct comparisons of both performance and acumen in clinical cardiology.

Keywords: cardiology, clinical skills, long case examination, hybrid simulation, checklist

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Authors: Jui-Chien Hsieh

Abstract:

Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: Navkiran Kaur, Apoorva Mathur, Abhishree Agarwal, Sakshi Gupta, Tuhin Rashmi

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Aim: Breast cancer is the most common cancer in women worldwide, and resistance to the current therapeutics, often concurrently, is an increasing clinical challenge. Glycosylation of proteins is one of the most important post-translational modifications. It is widely known that aberrant glycosylation has been implicated in many different diseases due to changes associated with biological function and protein folding. Alterations in cell surface glycosylation, can promote invasive behavior of tumor cells that ultimately lead to the progression of cancer. In breast cancer, there is an increasing evidence pertaining to the role of glycosylation in tumor formation and metastasis. In the present study, an attempt has been made to study the disease associated sialoglycoproteins in breast cancer by using bioinformatics tools. The sequence will be retrieved from UniProt database. A database in the form of a word document was made by a collection of FASTA sequences of breast cancer gene sequence. Glycosylation was studied using yinOyang tool on ExPASy and Differential genes expression and protein analysis was done in context of breast cancer metastasis. The number of residues predicted O-glc NAc threshold containing 50 aberrant glycosylation sites or more was detected and recorded for individual sequence. We found that the there is a significant change in the expression profiling of glycosylation patterns of various proteins associated with breast cancer. Differential aberrant glycosylated proteins in breast cancer cells with respect to non-neoplastic cells are an important factor for the overall progression and development of cancer.

Keywords: breast cancer, bioinformatics, cancer, metastasis, glycosylation

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Authors: Niloufar Yadgari

Abstract:

GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Jungbin Lim, Bohee Kang, Heelim Lee, Sunjin Kim, GeumHee Choi, Jae-Suk Jung, Suk Ji

Abstract:

Nonsurgical periodontal therapies have, for several decades, been the basis of periodontal treatment concepts. The aim of this paper is to investigate the effectiveness of non-surgical periodontal therapy according to the severity of periodontitis disease. Methods: Retrospective data of patients who visited Department of periodontics in Ajou University Medical Center from 2016 to 2022 were collected. Among the patients, those who took full mouth examination of clinical parameters and non-surgical periodontal therapy were chosen for this study. Selected patients were divided into initial, moderate, and severe periodontitis based on severity and complexity of management (2018 World Workshop EFP/AAP consensus). Recall visits with clinical periodontal examination were scheduled for 1,2,3 months or 1,3,6 months after the treatment. The results were evaluated by recordings of mean probing pocket depth (mean PD), mean clinical attachment levels (mean CAL), bleeding on probing (BOP%), mean gingival index (mean GI), mean regression, mean sulcus bleeding index (mean SBI), mean plaque scores (mean PI). All statistical analyses were performed with R software, version 4.3.0. A level of significance, P<0.05, was considered to be statistically significant. Results: A total of 92 patients were included in this study. 15 patients were diagnosed as initial periodontitis, 14 moderate periodontitis, and 63 severe periodontitis. The all parameters except for mean recession decreased over time in all groups. The amount of mean PD decreased were the greatest in severe periodontitis group followed by moderate and initial, which was found to be statistically significant. The changes of mean PD were 0.15±0.05 mm, 0.37±0.06 mm, and 1.01±0.07 mm (initial, moderate, and severe, respectively, P<0.001). When comparing before and after treatment, the reductions in BOP(%), mean GI, mean SBI, and mean PI were statistically significant. Conclusion: All patients who received non-surgical periodontal therapy showed periodontal healing in terms of improvements in clinical parameters, and it was greater in the severe group.

Keywords: periodontology, clinical periodontology, oral treatment, comprehensive preventive dentistry, non-surgical periodontal therapy

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Authors: Karl Owen L. Suan, Juliet Marie S. Lambayan, Floramay P. Salo-Curato

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Objective: To predict the outcome among patients admitted with community-acquired pneumonia (ages 3 months to 59 months old) admitted in Visayas Community Medical Center using the Respiratory Index of Severity in Children (RISC). Design: A cross-sectional study design was used. Setting: The study was done in Visayas Community Medical Center, which is a private tertiary level in Cebu City from January-June 2013. Patients/Participants: A total of 72 patients were initially enrolled in the study. However, 1 patient transferred to another institution, thus 71 patients were included in this study. Within 24 hours from admission, patients were assigned a RISC score. Statistical Analysis: Cohen’s kappa coefficient was used for inter-rater agreement for categorical data. This study used frequency and percentage distribution for qualitative data. Mean, standard deviation and range were used for quantitative data. To determine the relationship of each RISC score parameter and the total RISC score with the outcome, a Mann Whitney U Test and 2x2 Fischer Exact test for testing associations were used. A p value less of than 0.05 alpha was considered significant. Results: There was a statistical significance between RISC score and clinical outcome. RISC score of greater than 4 was correlated with intubation and/or mortality. Conclusion: The RISC scoring system is a simple combination of clinical parameters and a reliable tool that will help stratify patients aged 3 months to 59 months in predicting clinical outcome.

Keywords: RISC, clinical outcome, community-acquired pneumonia, patients

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