Disease In Users Research Articles

The Impact of Electronic Cigarettes Smoking on the Health of Adolescents and Young Adults

Introduction: Electronic cigarettes, or electronic nicotine delivery devices, have recently appeared on the global market and become very popular with adolescents and young adults. Manufacturers and distributors of e-cigarettes position them as harmless innovative products that reduce or eliminate exposures to harmful tobacco combustion products and help quit smoking, but this is not true. Objective: To establish health effects of electronic cigarettes and the associated risks for young people by reviewing recent research findings. Material and methods: We have searched eLibrary,PubMed, CyberLeninka databases for publications on the topic using the following keywords: electronic cigarettes, vapes, health effects, adolescents, and youth. Of 328 sources initially selected, we included 38 papers published in 2017 to 2023 and reporting results of prevalence of smoking electronic cigarettes, assessing health risks posed by the use of e-cigarettes in the review. Results: Our study revealed the extensive use of electronic cigarettes, specifics of their health effects in young people, the potential for developing nicotine dependence and a whole number of diseases of the respiratory, cardiovascular and digestive systems and other disorders in e-cigarette smokers. According to our findings, e-cigarettes are widely available and easily accessible to schoolchildren and are used not only at home, but also at school. These devices and chemicals contained in the generated aerosols, many of which are carcinogenic to humans, can induce multiple diseases in users. It also demonstrated that young people are poorly aware of adverse outcomes of using the devices. Conclusions: Electronic cigarettes and the substances contained in vaping liquids, many of which are carcinogenic, can have negative effects on health. In order to ensure the health savings of the child population and youth, strict compliance with the already existing introduced legislative restrictions, the implementation of measures restricting the sale of electronic cigarettes and their advertising, as well as the development and implementation of preventive programs for children, adolescents and youth in educational organizations is necessary. Vaping prevention programs implemented at schools should include information about adverse human health effects of electronic cigarettes and possible consequences in case of non-compliance with restrictive legislative measures.

Heart Disease Prediction using Machine Learning Algorithms

Presently, health conditions are on the rise primarily due to lifestyle factors and genetic predispositions. Among these, heart disease has notably surged, posing a significant risk to people's lives. Each person possesses unique benchmarks for vital health indicators like blood pressure, cholesterol levels, and pulse rates. However, according to established medical standards, normal values typically fall within certain ranges: Blood pressure ideally registers at 120/90, cholesterol between 100-129 mg/dL, pulse rate around 72, fasting blood sugar level at 100 mg/dL, heart rate ranging from 60-100 beats per minute (bpm), normal ECG readings, and major vessel widths spanning from 25 mm (1 inch) in the aorta to a mere 8 μm in capillaries. This study explores various classification techniques employed to predict the risk levels of individuals based on parameters such as age, gender, blood pressure, cholesterol levels, and pulse rate. The "Disease Prediction" system relies on predictive modeling to anticipate a user's disease risk by analyzing symptoms provided as input. By evaluating user-input symptoms, the system computes the probability of specific diseases as an output. Disease prediction involves the implementation of five techniques: Naïve Bayes, KNN, Decision Tree, Linear Regression, and Random Forest Algorithms. These methods gauge the likelihood of an individual developing a particular ailment. Consequently, the collective average prediction accuracy probability stands at an impressive 83%. Keywords: Naïve Bayes, KNN, Decision Tree, Linear Regression & Random Forest.

Disease- and Drug-Related Knowledge Extraction for Health Management from Online Health Communities Based on BERT-BiGRU-ATT.

Knowledge extraction from rich text in online health communities can supplement and improve the existing knowledge base, supporting evidence-based medicine and clinical decision making. The extracted time series health management data of users can help users with similar conditions when managing their health. By annotating four relationships, this study constructed a deep learning model, BERT-BiGRU-ATT, to extract disease-medication relationships. A Chinese-pretrained BERT model was used to generate word embeddings for the question-and-answer data from online health communities in China. In addition, the bidirectional gated recurrent unit, combined with an attention mechanism, was employed to capture sequence context features and then to classify text related to diseases and drugs using a softmax classifier and to obtain the time series data provided by users. By using various word embedding training experiments and comparisons with classical models, the superiority of our model in relation to extraction was verified. Based on the knowledge extraction, the evolution of a user's disease progression was analyzed according to the time series data provided by users to further analyze the evolution of the user's disease progression. BERT word embedding, GRU, and attention mechanisms in our research play major roles in knowledge extraction. The knowledge extraction results obtained are expected to supplement and improve the existing knowledge base, assist doctors' diagnosis, and help users with dynamic lifecycle health management, such as user disease treatment management. In future studies, a co-reference resolution can be introduced to further improve the effect of extracting the relationships among diseases, drugs, and drug effects.

Association between serum uric acid levels and incidence of nonalcoholic fatty liver disease in users of preventive medicine service in southern Brazil: a retrospective study

BackgroundNonalcoholic fatty liver disease (NAFLD) is a silent disease with increasing prevalence. High levels of serum uric acid (SUA) have been associated with cardiometabolic diseases, yet the possible association between SUA levels and NAFLD is not elucidated. This article aim is to evaluate the possible association between SUA and NAFLD in a Brazilian population.MethodsThis retrospective study evaluated patients submitted to two evaluations between 2015 and 2016 at a preventive medicine service. The diagnosis of NAFLD was performed through abdominal ultrasound, and its progression was defined as favorable or unfavorable according to the degrees of steatosis. Patients with hyperthyroidism, pregnancy, viral hepatitis, use of methotrexate or anabolic steroids, significant alcohol consumption were excluded. Possible confounding factors were evaluated through a multivariate model.ResultsA total of 279 patients were included in the final sample. In the first evaluation, 20.1% were women and the mean age was 46.9 (± 7.9) years, with a mean body mass index of 27.3 (± 4.0) kg/m2. About 26.9% of the individuals were diagnosed with NAFLD, and the mean of SUA levels was 5.7 (± 1.4) mg/dL; a favorable progression of NAFLD was observed in 79.2% of the patients, and the SUA levels at baseline were not significantly associated with the NAFLD progression (p = 0.43).ConclusionsDespite NAFLD high prevalence, SUA levels were not significantly associated with NAFLD progression in one year in this sample.

Heart Attack Prediction System Using IoT and Machine Learning

Abstract: Nowadays, health diseases are increasing day by day due to lifestyle, hereditary. Especially heart attack has become more common lately, i.e., the life of people is at risk. Each individual has different values for vital sign, cholesterol, and pulse. But consistent with medically proven results the traditional values of vital sign are 120/90, Cholesterol is 100- 129 mg/dL, pulse is 72, Fasting blood glucose level is 100 mg/dL, Heart rate is 60-100bpm, ECG is normal, Width of major vessels is 25 mm (1 inch) in the aorta to only 8 m in the capillaries. This paper analyses various classification systems for determining a person's risk level based on age, gender, blood pressure, cholesterol, and pulse rate. A predictive modelling-based "Ailment Prediction" system predicts the user's disease based on the symptoms provided as input to the system. The system takes the input from user and analyses the symptoms and gives the output as a probability of the disease. Five approaches are used to predict disease: Naive Bayes, KNN, Decision Tree, Linear Regression, and Random Forest Algorithms. These methods are used to evaluate the disease's probability. Therefore, the average prediction accuracy probability of 83 % is obtained. Keywords: Heart rate sensor Pulse, Android smartphone, Pulse Sensors, ECG sensor, Internet of Things.

Humidifier disinfectant, sodium dichloroisocyanurate (NaDCC): assessment of respiratory effects to protect workers’ health

In South Korea, it has been found that biocides used to control and eliminate harmful organisms are used as humidifier disinfectants and cause lung disease in users. Hence, efforts have been focused on studying the toxicity of biocides in workers who handle them. The purpose of this study was to evaluate the effects of inhalation exposure to sodium dichloroisocyanurate (NaDCC) to protect the health of workers handling NaDCC. F344 rats were exposed to 0.8-, 4-, and 20-mg/m3 of NaDCC for 6 h per day, 5 days per week for 14 days, and the recovery period after exposure was 14 days. In the 20-mg/m3-exposure group, we observed a decrease in food intake in females, a weight loss in males, and a decrease in partially active thromboplastin time in males and females 2 weeks after exposure. We noted a decrease in white blood cells in males in the 4- and 20-mg/m3-exposed groups. Both males and females in the 20-mg/m3 group and males in the 4-mg/m3 group showed irritation in the larynx related to test substance exposure. However, these findings were not observed in the recovery group. The main target organs affected by repeated 2-week inhalation exposure to NaDCC were the nasal cavity and larynx in the upper respiratory tract. The No Observed Adverse Effect Level (NOAEL) was considered to be 0.8 mg/m3 because effects related to NaDCC exposure were observed even at of 4 mg/m3, and these effects were found to be reversible.

The Human Salivary Proteome Wiki: A Community-Driven Research Platform

Saliva has become an attractive body fluid for on-site, remote, and real-time monitoring of oral and systemic health. At the same time, the scientific community needs a saliva-centered information platform that keeps pace with the rapid accumulation of new data and knowledge by annotating, refining, and updating the salivary proteome catalog. We developed the Human Salivary Proteome (HSP) Wiki as a public data platform for researching and retrieving custom-curated data and knowledge on the saliva proteome. The HSP Wiki is dynamically compiled and updated based on published saliva proteome studies and up-to-date protein reference records. It integrates a wide range of available information by funneling in data from established external protein, genome, transcriptome, and glycome databases. In addition, the HSP Wiki incorporates data from human disease–related studies. Users can explore the proteome of saliva simply by browsing the database, querying the available data, performing comparisons of data sets, and annotating existing protein entries using a simple, intuitive interface. The annotation process includes both user feedback and curator committee review to ensure the quality and validity of each entry. Here, we present the first overview of features and functions the HSP Wiki offers. As a saliva proteome–centric, publicly accessible database, the HSP Wiki will advance the knowledge of saliva composition and function in health and disease for users across a wide range of disciplines. As a community-based data- and knowledgebase, the HSP Wiki will serve as a worldwide platform to exchange salivary proteome information, inspire novel research ideas, and foster cross-discipline collaborations. The HSP Wiki will pave the way for harnessing the full potential of the salivary proteome for diagnosis, risk prediction, therapy of oral and systemic diseases, and preparedness for emerging infectious diseases. Database URL: https://salivaryproteome.nidcr.nih.gov/

Disinfection of Water Systems in Accordance with Eu Directives on Health and Safety in Working Environments: Use of A Technologically Advanced ClO2 Generator

One of the main problems in the management of water in buildings is the risk of legionnaires’ disease for users and workers...

Diabetes medications and risk of Parkinson's disease: a cohort study of patients with diabetes.

The elevated risk of Parkinson's disease in patients with diabetes might be mitigated depending on the type of drugs prescribed to treat diabetes. Population data for risk of Parkinson's disease in users of the newer types of drugs used in diabetes are scarce. We compared the risk of Parkinson's disease in patients with diabetes exposed to thiazolidinediones (glitazones), glucagon-like peptide-1 (GLP-1) receptor agonists and dipeptidyl peptidase 4 (DPP4) inhibitors, with the risk of Parkinson's disease of users of any other oral glucose lowering drugs. A population-based, longitudinal, cohort study was conducted using historic primary care data from The Health Improvement Network. Patients with a diagnosis of diabetes and a minimum of two prescriptions for diabetes medications between January 2006 and January 2019 were included in our study. The primary outcome was the first recording of a diagnosis of Parkinson's disease after the index date, identified from clinical records. We compared the risk of Parkinson's disease in individuals treated with glitazones or DPP4 inhibitors and/or GLP-1 receptor agonists to individuals treated with other antidiabetic agents using a Cox regression with inverse probability of treatment weighting based on propensity scores. Results were analysed separately for insulin users. Among 100 288 patients [mean age 62.8 years (standard deviation 12.6)], 329 (0.3%) were diagnosed with Parkinson's disease during the median follow-up of 3.33 years. The incidence of Parkinson's disease was 8 per 10 000 person-years in 21 175 patients using glitazones, 5 per 10 000 person-years in 36 897 patients using DPP4 inhibitors and 4 per 10 000 person-years in 10 684 using GLP-1 mimetics, 6861 of whom were prescribed GTZ and/or DPP4 inhibitors prior to using GLP-1 mimetics. Compared with the incidence of Parkinson's disease in the comparison group (10 per 10 000 person-years), adjusted results showed no evidence of any association between the use of glitazones and Parkinson's disease [incidence rate ratio (IRR) 1.17; 95% confidence interval (CI) 0.76-1.63; P = 0.467], but there was strong evidence of an inverse association between use of DPP4 inhibitors and GLP-1 mimetics and the onset of Parkinson's disease (IRR 0.64; 95% CI 0.43-0.88; P < 0.01 and IRR 0.38; 95% CI 0.17-0.60; P < 0.01, respectively). Results for insulin users were in the same direction, but the overall size of this group was small. The incidence of Parkinson's disease in patients diagnosed with diabetes varies substantially depending on the treatment for diabetes received. The use of DPP4 inhibitors and/or GLP-1 mimetics is associated with a lower rate of Parkinson's disease compared to the use of other oral antidiabetic drugs.

STAPHYLOCOCCUS AUREUS PNEUMONIA AND EMPYEMA AS A COMPLICATION OF E-CIGARETTE USE

SESSION TITLE: Medical Student/Resident Tobacco Cessation and Prevention Posters SESSION TYPE: Med Student/Res Case Rep Postr PRESENTED ON: October 18-21, 2020 INTRODUCTION: Electronic-cigarettes (e-cigarettes), popularized in the late 2000s, were introduced as a safer alternative to traditional tobacco cigarettes. However, emerging data suggests a considerable risk for developing pulmonary diseases in users of e-cigarettes. Despite this concern, e-cigarette use is on the rise with up to 20% of Americans aged 25 to 44 now using e-cigarettes [1]. We present an interesting case which explores the relationship between e-cigarettes and the development of methicillin sensitive Staphylococcus aureus (MSSA) pneumonia. CASE PRESENTATION: A 38-year-old female was admitted with a five-day history of fever, dyspnea, and a productive cough. Her medical history was only notable for daily use of nicotine products via an e-cigarette. Vital signs on arrival revealed a temperature of 37.9 degrees centigrade, tachycardia with a pulse rate of 133 beats per minute, and tachypnea with a respiratory rate of 26 breaths per minute. She was able to maintain appropriate oxygen saturations on room air. Physical examination was notable for diminished air movement in left lower lung base. Admission labs were notable for a white blood cell (WBC) count of 12.83 x10(9)/L, and a procalcitonin of 11.3 ng/mL. Notably, both urine streptococcus and legionella antigens were negative. A chest radiograph demonstrated a left lower lobe opacity with associated effusion [Figure 1], which was also present on a computed tomography scan of her chest [Figure 2A-B]. Therefore, a diagnostic thoracentesis was performed from which pleural fluid analysis revealed a pH of 6.6, lactate dehydrogenase of 1,478 units/L, protein of 4.7g/dL, and WBC count of 5,082 cells/mL. Subsequent cultures from both the pleural fluid and sputum grew MSSA. The patient was started on empiric antibiotics and had a left-sided chest tube inserted for drainage of her empyema. Given the presence of loculations, additional therapy with intrapleural dornase alpha and tissue plasminogen activator was initiated. The patient clinically improved, her chest tube was removed, and she was discharged home to complete four weeks of nafcillin. The patient reported continued recovery and success in quitting e-cigarettes at her subsequent follow up. DISCUSSION: As the long-term effects of e-cigarette use become more evident, it is clear that they pose significant risks to patients. E-cigarettes decrease host ability to fight infection by promoting virulence in bacterial colonizers of the airways and by increasing pro-inflammatory markers [2]. Furthermore, vapors from e-cigarettes have been implicated in increasing biofilm formation. Biofilms lead to an increase of virulence in a variety of lung pathogens, including Staphylococcus aureus [3]. CONCLUSIONS: Clinicians should be aware of an increase in virulence from bacterial pathogens (particularly MSSA) responsible for community acquired bacterial pneumonia amongst e-cigarette users. Reference #1: Hwang, John H., et al. “Electronic cigarette inhalation alters innate immunity and airway cytokines while increasing the virulence of colonizing bacteria.” Journal of molecular medicine 94.6 (2016): 667-679. Reference #2: Gilpin, Deirdre F., et al. “Electronic cigarette vapour increases virulence and inflammatory potential of respiratory pathogens.” Respiratory Research 20.1 (2019): 267. Reference #3: Shi, L., Wu, Y., Yang, C. et al. Effect of nicotine on Staphylococcus aureus biofilm formation and virulence factors. Sci Rep 9, 20243 (2019). https://doi.org/10.1038/s41598-019-56627-0 DISCLOSURES: No relevant relationships by Ethan Karle, source=Web Response No relevant relationships by Armin Krvavac, source=Web Response No relevant relationships by Tarang Patel, source=Web Response No relevant relationships by SACHIN PATIL, source=Web Response No relevant relationships by Richard Swaney, source=Web Response

Implementation of Naive Bayes Method in Classification of Breast Cancer Disease

Less knowledge of early symptoms of breast cancer and how to deal with it early and the number of specialist doctorswho are still limited is one factor contributors because of the increasing number of people affected by breast cancerdisease. The development of breast cancer disease classification system aims to predict the early diagnosis of breastcancer disease in users or patients into two categories of malignant or benign. The initial diagnoses of this systemprediction variable include Clump Thickness, Uniformity of Cell Size, Uniformity of Cell Shape, Marginal Adhesion,Single Epithelial Cell Size (Single Epithelial Cell) Size), Bare nuclei, Bland Chromatin, Normal nucleoli, Mitosis Usingthe naive bayes method to process diagnostic data in patients, the results of this system test show that the system isable to predict and classify breast cancer disease into two categories (malignant or benign) with the amount of datatesting of 500 data. With the output of malignant or YA and benign or NO, the system is able to predict with an accuracyvalue of 98%.

PHR 기반 개인 맞춤형 건강정보 탐사 알고리즘 설계

PHR(Personal Health Record)기반 헬스케어 서비스 플랫폼 지능화를 위해서는 사용자 맞춤형 건강정보 제공서비스가 필요하다. 본 논문에서는 개인 맞춤형 건강정보 추천을 위해서 온톨로지 기반 건강 정보 모델을 제안하였다. 또한 기계학습과 데이터마이닝 기법을 적용한 유사 건강정보 탐사 알고리즘을 설계하였다. 기존의 데이터마이닝 기법중 연관규칙 알고리즘을 확장하여 속성을 기반으로 연관규칙 탐사를 수행하여 지식탐사의 연관성을 높이고 효율적인 탐사시간을 제공할 수 있도록 하였다. 머신러닝의 한 기법인 K근접이웃 알고리즘을 적용하여 사용자 프로파일별 그룹화를 수행하고 유사패턴의 사용자 프로파일을 검색할 수 있도록 하였다. 이는 사용자의 질환과 건강상태에 따른 맞춤형 건강정보 탐사 수행의 효율성을 높인다. 제안된 알고리즘은 개인 맞춤형 헬스케어 서비스 플랫폼에서 추론과정에 적용되어 사용자에게 개인맞춤형건강정보를 추천하는 것을 가능하게 한다. 이는 고령화사회에서 스마트한 자가 건강관리에 활용될 수 있다. It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

Incidence and complications of interstitial lung disease in users of tocilizumab, rituximab, abatacept and anti-tumor necrosis factor α agents, a retrospective cohort study.

IntroductionInterstitial lung disease (ILD) is a common extra-articular condition in rheumatoid arthritis (RA), but few studies have systematically investigated its incidence and risk factors in patients receiving anti-tumor necrosis factor-alpha (anti-TNFα) agents or alternate mechanisms of action (MOAs) (e.g., T-cell, B-cell, and interleukin-6 inhibitors).MethodsRA patients at least 18 years old were selected from the MarketScan databases (2010–2012) if they had at least one prescription/administration of abatacept, rituximab, tocilizumab, or anti-TNF after having discontinued a different biologic agent and meeting enrollment criteria. Cox models estimated the risk of incident ILD and ILD-related hospitalization. Sensitivity analyses used an alternate ILD case definition.ResultsWe identified 13,795 episodes of biologic exposure in 11,219 patients. Mean (standard deviation) follow-up was 0.7 (0.5) years. Patients receiving alternate MOA agents were more likely to have had recent exposure to steroids, prior exposure to a greater number of biologics, and history of ILD, anemia, chronic obstructive pulmonary disease, and other pulmonary conditions. When the sensitive definition was used, unadjusted ILD incidence rates (95 % confidence interval, or CI) ranged from 4.0 (1.6–8.2, abatacept) to 12.2 (5.6–23.2, infliximab) per 1000 person-years. Being older (hazard ratio (HR) 3.5; 95 % CI 2.1–6.0), being male (HR 3.1; 95 % CI 1.2–8.4), and having another pulmonary condition (HR 4.8; 95 % CI 1.7–13.7) were associated with increased ILD incidence in either sensitive and/or specific models. There were no significant differences by biologic class. Hospitalization rates (95 % CI) when the sensitive definition was used ranged from 55.6 (6.7–200.7, tocilizumab) to 262.5 (71.5–672.2, infliximab). In Cox models, recent methotrexate exposure was associated with reduced ILD hospitalization (HR 0.16; 95 % CI 0.06–0.46), whereas being male (HR 2.5; 95 % CI 1.3–4.8) and having had a hospitalization for asthma (HR 3.4; 95 % CI 1.2–9.8) or ILD/pneumonia (HR 2.3; 95 % CI 1.1–4.7) in the 12 months prior to index were associated with increased hospitalization risk.ConclusionsThere were no significant differences in the risk of ILD and its related complications between RA patients receiving anti-TNFα agents and those receiving alternate MOA agents. Further studies are needed that account for differences in baseline characteristics in order to fully evaluate the risk of ILD and its complications.

Necesidades de información sobre salud y enfermedad de usuarios de servicios sanitarios de atención primaria de Salamanca

ObjectiveTo learn, interpret and understand the information needs of health and disease in users of the healthcare services of the urban Primary Care of Salamanca. DesignQualitative research corresponding an exploratory qualitative/structural perspective. LocationPrimary Care. Urban area, Salamanca in 2007. ParticipantsTen discussion groups, 2 composed of members of health-related associations and 8 primary care users, involved a total of 83 people. The structural variables considered are: gender, age, educational level and membership or not associations. MethodGenerate information to achieve information saturation in the discussion groups. Upon obtaining their informed consent, all subjects in the study participated in videotaped conversations, which were transcribed verbatim. Four researchers categorized the content, intentionality of discourse and developed the concept map. After categorization, triangulation and coding, content obtained was analysed with the NudistQ6 program. ResultsInformative content suggest four information needs: health and prevention, early diagnosis, first aid and disease. Different intentions (information needs, watching, claim and improvement) and needs profiles are detected as structural variables. Major information needs are relate to diagnosis, prognosis and therapeutic options. There is agreement between the groups that the information transmitted to the patient must be intelligible, updated and coordinated among the different professionals and care levels. ConclusionsParticipants require information of a clinical nature to exercise their right to autonomy translating tendency to empower users as part of the social change.

Reduced Risk of Parkinson's Disease in Users of Calcium Channel Blockers: A Meta-Analysis.

Aim. To pool the data currently available to determine the association between calcium channel blockers (CCBs) and risk of Parkinson's disease (PD). Methods. Literature search in PubMed, EBSCO, and Cochrane library was undertaken through March 2014, looking for observational studies evaluating the association between CCBs use and PD. Pooled relative risk (RR) estimates and 95% confidence intervals (CIs) were calculated using random-effects model. Subgroup analyses, sensitivity Analysis, and cumulative meta-analysis were also performed. Results. Six studies were included in our meta-analysis according to the selection criteria, including three cohort studies and three case-control studies involving 27,67,990 subjects including 11,941 PD cases. We found CCBs use was associated with significant decreased risk of PD, compared with not using CCBs (random effects model pooled RR, 0.81 (95% CI, 0.69–0.95)); a significant heterogeneity was found between studies (P = 0.031; I 2 54.6%). Both the classes of CCB, that is, dihydropyridine calcium channel blockers (DiCCB) (0.80 (95% CI, 0.65–0.98) P = 0.032) and non-DiCCB (0.70 (95% CI, 0.53–0.92) P = 0.013), were found to be reducing the risk of PD. Conclusion. In our analysis, we found that CCBs use was associated with a Significantly decreased risk of PD compared with non-CCB use.

Current practices in manufacturing locally-made ceramic pot filters for water treatment in developing countries

Locally produced ceramic pot filters have been shown to improve the microbiological quality of household drinking water and reduce the burden of diarrheal disease in users. They are considered one of the most promising household water treatment methods. However, overarching manufacturing and quality control guidelines do not exist for the 35 decentralized filter factories in 18 countries that currently produce filters. In this study, we conducted manufacturing process surveys with 25 filter factories worldwide to document production methods and identify areas where manufacturing and quality control guidelines are needed. Our results show that manufacturing processes vary widely both between and within factories, including the consistency of materials, manufacturing methods, and quality control practices. These variations pose concerns about the consistency and quality of locally produced filters in the absence of standardized quality control procedures. We propose areas where manufacturing guidelines are needed to assist factories in producing consistently high quality filters, and identify topics where further research is needed to refine manufacturing recommendations. These results guided the development of a best practice manual that described consensus-based recommendations to advance consistent, quality-controlled filter production world-wide.

Is lipid profile determination necessary in women wishing to use oral contraceptives?

IntroductionAlthough coronary heart disease in users of combined oral contraceptives (COCs) is rare, one of the principal risk factors for its occurrence is dyslipidemia. ObjectiveTo evaluate the prevalence of dyslipidemia in women wishing to use COCs, and its association with known clinical risk factors in order to evaluate the need to determine the lipid profile in this population. Study DesignCross-sectional study involving 516 women aged 18–40 years, 54% nulligravid, who wished to use COCs and presented no contraindications. Dyslipidemia was classified according to the National Cholesterol Educational Project Adult Treatment Panel III guidelines, which define levels of total cholesterol ≥200 mg/dL, high-density lipoprotein cholesterol <40 mg/dL, triglycerides >150 mg/dL, and low-density lipoprotein cholesterol ≥160 mg/dL as an abnormal lipid profile. The lipid profile was determined, and the association between clinical risk factors and the presence of dyslipidemia was evaluated by the chi-squared test and logistic regression. The receiver operating characteristic curve was constructed to compare body mass index (BMI) and smoking relevance for dyslipidemia. ResultsThe prevalence of dyslipidemia was 33.9%. Smoking and BMI were significantly associated with the presence of dyslipidemia, with sensitivity of 31.3–54% and specificity of 41.9–67.7% for diagnosis of dyslipidemia, respectively. ConclusionThe high prevalence of dyslipidemia could justify lipid profile evaluation before prescribing a COC. BMI and smoking represent modest predictive markers for the presence of dyslipidemia in candidates for the use of combined oral contraceptives.

Venous thromboembolic disease in users of low-estrogen combined estrogen-progestin oral contraceptives

Objective To assess the relationship between venous thromboembolic disease (VTE) and use of low-estrogen dose (<50 μg) combined estrogen-progestin oral contraceptives (OC) and three thrombosis-related gene mutations in a United States population. Design This case-control study was conducted in 1998–2000 among women ages 15–44 years who were members of the Kaiser Permanente Medical Care Program [KPMCP] (Northern and Southern California). Cases were women with incident VTE; about three times as many women frequency matched for age were randomly selected as controls from the KPMCP membership in the same years. Data were collected in a 1 h face-to-face interview; blood was drawn to extract DNA to test for gene polymorphisms. The analysis data set comprised 196 cases (mean age 35.3 years) and 746 controls (mean age 36.2 years). Results The adjusted odds ratio (OR) for VTE associated with current OC use was 4.07 (95% confidence interval [CI]: 2.77–6.00). The OR associated with OC use was higher for women who were obese than in the nonobese (p = 0.01 for likelihood test for interaction) and in women without predisposing medical conditions (p = 0.02 for interaction). The adjusted OR for VTE was 7.10 (95% CI: 2.33–21.61) in women with factor V Leiden (G1691A) mutation, 2.83 (95% CI: 0.70–11.63) in women with prothrombin G20210A mutation and 0.26 (95% CI: 0.10–0.65) in women with the MTHFR C677T mutation. The OR for VTE in OC users with factor V Leiden mutation (11.32) was elevated more than in OC users without the mutation (3.20) and women with the mutation who were non-OC users (8.42), but confidence intervals overlapped. Conclusions The risk of VTE is increased in users of low-estrogen OC formulations. Obese women appear to be at greater risk of VTE when using OCs.

Reduced risk of Alzheimer disease in users of antioxidant vitamin supplements: the Cache County Study.

Antioxidants may protect the aging brain against oxidative damage associated with pathological changes of Alzheimer disease (AD). To examine the relationship between antioxidant supplement use and risk of AD. Cross-sectional and prospective study of dementia. Elderly (65 years or older) county residents were assessed in 1995 to 1997 for prevalent dementia and AD, and again in 1998 to 2000 for incident illness. Supplement use was ascertained at the first contact. Cache County, Utah. Among 4740 respondents (93%) with data sufficient to determine cognitive status at the initial assessment, we identified 200 prevalent cases of AD. Among 3227 survivors at risk, we identified 104 incident AD cases at follow-up. Diagnosis of AD by means of multistage assessment procedures. Analyses of prevalent and incident AD yielded similar results. Use of vitamin E and C (ascorbic acid) supplements in combination was associated with reduced AD prevalence (adjusted odds ratio, 0.22; 95% confidence interval, 0.05-0.60) and incidence (adjusted hazard ratio, 0.36; 95% confidence interval, 0.09-0.99). A trend toward lower AD risk was also evident in users of vitamin E and multivitamins containing vitamin C, but we saw no evidence of a protective effect with use of vitamin E or vitamin C supplements alone, with multivitamins alone, or with vitamin B-complex supplements. Use of vitamin E and vitamin C supplements in combination is associated with reduced prevalence and incidence of AD. Antioxidant supplements merit further study as agents for the primary prevention of AD.

Effect of non-steroidal anti-inflammatory drugs on risk of Alzheimer's disease: systematic review and meta-analysis of observational studies

Objectives To quantify the risk of Alzheimer's disease in users of all non-steroidal anti-inflammatory drugs (NSAIDs) and users of aspirin and to determine any influence of duration of use.Design Systematic...