Statistical analyses were conducted with SPSS software (version 23.0; SPSS, Chicago, IL, USA). No formal sample size estimation was made because there has not been any published nationwide data on COVID-19. Nonetheless, our sample size was deemed sufficient to power the statistical analysis given its representativeness of the national patient population. Continuous variables were presented as mean±sd or median (interquartile ranges (IQR)) as appropriate, and the categorical variables were presented as counts and percentages. Since no random sampling was conducted, all statistical analyses were descriptive and no p-values were presented for the statistical comparisons except for the Cox proportional hazards regression model. Cox proportional hazards regression models were applied to determine the potential risk factors associated with the composite end-points, with the hazard ratio and 95% confidence interval being reported. Our findings indicated that the statistical assumption of proportional hazards analysis was not violated. Moreover, a Cox regression model was considered more appropriate than a logistic regression model because it took into account the potential impact of the various durations of follow-up from individual patients. Age and smoking status were adjusted for in the proportional hazards regression model because they had been recognised as the risk factors of comorbidities even in the general population. Smoking status was stratified as current smoker, ex-smoker and never-smoker in the regression models.
>
Living Beings
>
Population Group
>
Ex-Smokers
Ex-Smokers
Ex-Smokers refers to individuals who have previously smoked but have since quit the habit.
These individuals face unique challenges in maintaining their abstinence and preventing relapse.
PubCompare.ai's AI-driven platform can assist ex-smokers in optimizeing their research protocols, ensuring reproducibility and accuracy.
The platform enables users to locate relevant protocols from literature, pre-prints, and patents, and leverages AI-driven comparisons to identify the best protocols and products.
This takes the guesswork out of research, empowering ex-smokers to make informed decisions and achieve their health goals.
With PubCompare.ai's powerful tools, ex-smokers can navigate the complexities of their journey with confidence and ease.
These individuals face unique challenges in maintaining their abstinence and preventing relapse.
PubCompare.ai's AI-driven platform can assist ex-smokers in optimizeing their research protocols, ensuring reproducibility and accuracy.
The platform enables users to locate relevant protocols from literature, pre-prints, and patents, and leverages AI-driven comparisons to identify the best protocols and products.
This takes the guesswork out of research, empowering ex-smokers to make informed decisions and achieve their health goals.
With PubCompare.ai's powerful tools, ex-smokers can navigate the complexities of their journey with confidence and ease.
Most cited protocols related to «Ex-Smokers»
COVID 19
Ex-Smokers
Patient Representatives
Patients
Patients were randomised if they met the following main inclusion criteria: outpatients aged ≥40 years with a history of moderate to very severe COPD (GOLD stage 2–4) [23 ]; post-bronchodilator FEV1 <80% of predicted normal; post-bronchodilator FEV1/forced vital capacity (FVC) <70%; current or ex-smokers with a smoking history of >10 pack–years.
Patients with a significant disease other than COPD were excluded from the trials. Other exclusion criteria included: clinically relevant abnormal baseline laboratory parameters or a history of asthma; myocardial infarction within 1 year of screening; unstable or life-threatening cardiac arrhythmia; known active tuberculosis; clinically evident bronchiectasis; cystic fibrosis or life-threatening pulmonary obstruction; hospitalised for heart failure within the past year; diagnosed thyrotoxicosis or paroxysmal tachycardia; previous thoracotomy with pulmonary resection; regular use of daytime oxygen if patients were unable to abstain during clinic visits; or currently enrolled in a pulmonary rehabilitation programme (or completed in the 6 weeks before screening).
Patients with moderate or severe renal impairment (creatinine clearance ≤50 mL·min−1) were not excluded from the study but were closely monitored by the investigator.
Both studies were performed in accordance with the Declaration of Helsinki, International Conference on Harmonisation Harmonised Tripartite Guideline for Good Clinical Practice and local regulations. The protocols were approved by the authorities and the ethics committees of the respective institutions, and signed informed consent was obtained from all patients.
Patients with a significant disease other than COPD were excluded from the trials. Other exclusion criteria included: clinically relevant abnormal baseline laboratory parameters or a history of asthma; myocardial infarction within 1 year of screening; unstable or life-threatening cardiac arrhythmia; known active tuberculosis; clinically evident bronchiectasis; cystic fibrosis or life-threatening pulmonary obstruction; hospitalised for heart failure within the past year; diagnosed thyrotoxicosis or paroxysmal tachycardia; previous thoracotomy with pulmonary resection; regular use of daytime oxygen if patients were unable to abstain during clinic visits; or currently enrolled in a pulmonary rehabilitation programme (or completed in the 6 weeks before screening).
Patients with moderate or severe renal impairment (creatinine clearance ≤50 mL·min−1) were not excluded from the study but were closely monitored by the investigator.
Both studies were performed in accordance with the Declaration of Helsinki, International Conference on Harmonisation Harmonised Tripartite Guideline for Good Clinical Practice and local regulations. The protocols were approved by the authorities and the ethics committees of the respective institutions, and signed informed consent was obtained from all patients.
Airway Obstruction
Asthma
Bronchiectasis
Bronchodilator Agents
Cardiac Conduction System Disease
Chronic Obstructive Airway Disease
Clinic Visits
Conferences
Creatinine
Cystic Fibrosis
Ex-Smokers
Forced Vital Capacity
Gold
Heart Failure
Institutional Ethics Committees
Lung
Myocardial Infarction
Outpatients
Oxygen
Patients
Rehabilitation
Renal Insufficiency
Tachycardia, Paroxysmal
Thoracotomy
Thyrotoxicosis
Tuberculosis
Power calculation was based on precision of effect estimates in COPD subgroups for rate of decline in FEV1 over 3 years (confidence interval width of at most 15 mL/year in rate of FEV1 decline). The sizes of the control groups were based on both the ability to detect a difference of at least 16.5 mL/year rate of decline in FEV1 between COPD patients and controls, and to detect a 50% increase in exposure (required 5-7 COPD patients per control) for any diagnostic test. Based upon these calculations, we studied 2164 patients with COPD (GOLD stage 2-4), 337 smoking controls and 245 non-smoking controls (Figure 1 ). Inclusion criteria were as follows [4 (link)]. COPD patients : (1) Male/female subjects aged 40-75 years; (2) Baseline post-bronchodilator FEV1 < 80% of the reference value and FEV1/FVC ≤0.7; and, (3) Current or ex-smokers with a smoking history of ≥10 pack-years. Smoker controls : (1) Male/female subjects aged 40-75 years, who are free from significant disease as determined by history, physical examination and screening investigations; (2) Baseline post-bronchodilator FEV1 > 85% of the reference value and FEV1/FVC > 0.7; and, (3) Current or ex-smokers with a smoking history ≥10 pack-years. Non smoking controls : (1) Male/female subjects aged 40-75 years, who are free from significant disease as determined by history, physical examination and screening investigations; (2) Baseline post-bronchodilator FEV1 > 85% of the reference value and FEV1/FVC > 0.7; and, (3) Smoking history of <1 pack-year. Besides, all participants: (4) signed and dated their written informed consent prior to participation (which had been approved by the Ethics Committees of all participating institutions); and, (5) had to have the ability to comply with the requirements of the protocol and be available for study visits over 3 years. Key exclusion criteria were the presence of a respiratory disorder other than COPD, other significant inflammatory diseases or a reported COPD exacerbation within 4 weeks of enrolment [4 (link)]. COPD patients were recruited from the outpatient clinics of the participating centres (Figure 1 ). Smoker and non-smoker controls were recruited through site databases and other methods (advertisements in local newspapers and television/radio stations) where appropriate. Figure 2 presents the variability of age (panel A), gender (panel B), smoking status (panel C) and FEV1 (panel D) in the three groups of individuals recruited into ECLIPSE (COPD patients, smokers and non-smokers with normal lung function) by each of the 46 participating centres.
Full text: Click here
Bronchodilator Agents
Chronic Obstructive Airway Disease
Ex-Smokers
Gender
Gold
Inflammation
Institutional Ethics Committees
Males
Non-Smokers
Patients
Physical Examination
Respiration Disorders
Respiratory Physiology
Tests, Diagnostic
Woman
Data analysis was performed using SPSS version 9.0 (SPSS Inc, USA). Data are expressed as medians (range) unless stated otherwise. Internal consistency of the CCQ was evaluated by determining the Cronbach's α coefficient (for the three domains and the total questionnaire). Non parametrical testing (Mann-Whitney U test) was used to determine the discriminant validity of the CCQ to differentiate among healthy (ex) smokers, patients with COPD (stages 0 to III). Spearman's rank correlations were used to examine convergent (HRQoL) and divergent (lung function) validity. Test-retest reliability analysis was done by calculating the Intraclass Correlation Coefficient (ICC). Responsiveness was tested using the Wilcoxon U test. A p value < 0.05 was considered as statistically significant. A priori assumptions of the relations between the CCQ and convergent and divergent measures were made by the research team in advance of the validation study
Chronic Obstructive Airway Disease
Ex-Smokers
Patients
Respiratory Physiology
All subjects were recruited from the Respiratory Medicine Unit of the ‘Fondazione Salvatore Maugeri’ (Veruno, Italy), the Section of Respiratory Diseases of the University Hospital of Ferrara, Italy and the Section of Respiratory Diseases of the University Hospital of Katowice, Poland for immunohistochemistry and ELISA experiments. The severity of the airflow limitation, as determined by spirometry, was graded using Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria.19 (link) All former smokers had stopped smoking for at least 1 year. COPD and chronic bronchitis were defined, according to international guidelines: COPD, presence of a post-bronchodilator forced expiratory volume in 1s (FEV1)/forced vital capacity ratio <70%; chronic bronchitis, presence of cough and sputum production for at least 3 months in each of two consecutive years (http://www.goldcopd.com ). All patients with COPD were stable. The study conformed to the Declaration of Helsinki. We obtained and studied bronchial biopsies from 55 subjects: 32 had a diagnosis of COPD in a stable clinical state,20 (link) 12 were current or ex-smokers with normal lung function, and 11 were non-smokers with normal lung function (table 1 ). The smoking history was similar in the three smoker groups: mild/moderate and severe/very severe COPD, and healthy smokers with normal lung function. Clinical details of the patients in whom BAL was collected are summarised in table 2 . The results provided are the data from 26 patients with COPD and 18 control smokers with normal lung function. Due to the necessity to concentrate the BAL supernatants the results provided for each ELISA are the data from 15 patients with COPD and 14 control smokers with normal lung function which are not the same patients for all mediators measured.
A detailed description of subjects, lung function tests, fibreoptic bronchoscopy and processing of bronchial biopsies and BAL, immunohistochemistry, scoring system for immunohistochemistry, double staining and confocal microscopy, ELISA tests performed on the BAL fluid and ‘in vitro’ experiments performed on normal human bronchial epithelial (NHBE) cells and details of statistical analysis are provided in the online supplementary data repository.
A detailed description of subjects, lung function tests, fibreoptic bronchoscopy and processing of bronchial biopsies and BAL, immunohistochemistry, scoring system for immunohistochemistry, double staining and confocal microscopy, ELISA tests performed on the BAL fluid and ‘in vitro’ experiments performed on normal human bronchial epithelial (NHBE) cells and details of statistical analysis are provided in the online supplementary data repository.
Full text: Click here
Biopsy
Bronchi
Bronchitis, Chronic
Bronchodilator Agents
Bronchoscopy
Chronic Obstructive Airway Disease
Cough
Diagnosis
Enzyme-Linked Immunosorbent Assay
Epithelial Cells
Ex-Smokers
Gold
Homo sapiens
Immunohistochemistry
Microscopy, Confocal
Non-Smokers
Patients
Respiration Disorders
Respiratory Physiology
Spirometry
Sputum
Tests, Pulmonary Function
Vital Capacity
Volumes, Forced Expiratory
Most recents protocols related to «Ex-Smokers»
This section elicited data regarding socio-demographic characteristics, academia-related factors, and lifestyle factors. Data concerning socio-demographic characteristics included age, gender, family's monthly income, marital status, father's education, parents' marital status, birth order, body mass index (BMI), and smoking. The academia-related factors included year of study and self-reported Grade Point Average (GPA). The years of study were grouped into two academic levels (Junior: second and third year; Senior: fourth to sixth year). Lifestyle factors included smoking status, physical exercise, tea consumption, coffee consumption, and energy drink consumption. Smoking status was defined as follows: current smoker is any person who smoked regularly in the past month at the time of responding; ex-smoker, who quit smoking at least 1 month prior to the study; and nonsmoker as someone who has never smoked.
Coffee
Energy Drinks
Ex-Smokers
Gender
Index, Body Mass
Non-Smokers
Parent
Age, sex, co-morbidities including hypertension, diabetes, dyslipidemia, heart failure, prior stroke, prior myocardial infarction, peripheral artery disease, chronic kidney disease, chronic obstructive pulmonary disease (COPD), and cancer, CHA2DS2-VASc score, Charlson Comorbidity Index (CCI), and concomitant use of antiplatelet agents were evaluated as covariates. The operational definitions of co-morbidities were based on diagnostic codes, drug dispensing records, and inpatient/outpatient hospital visits within 3 years prior to the index date. Complete definitions of each covariate are presented in Supplementary Tables S1 and S2 (5 (link), 15 (link), 16 (link)).
Among the total study population, 67.4% of patients had the data from the baseline national health examination, and 23.4% had the data from both baseline and at least one follow-up national health examination. From the health examination data, body weight, body mass index (kg/m2), serum creatinine (mg/dL) and eGFR (mL/min/1.73 m2) were collected. eGFR was calculated by a creatinine-based equation used from Modification of Diet in Renal Disease. In addition, smoking status (never smoker, ex-smoker, or current smoker), alcohol consumption (heavy drinker, ≥ 30 g/day), and physical activity were also evaluated from the self-reported questionnaires of health examination. Regular exercise was defined as performing moderate-intensity exercise ≥ 5 times per week or vigorous-intensity exercise ≥ 3 times per week (17 (link)).
Among the total study population, 67.4% of patients had the data from the baseline national health examination, and 23.4% had the data from both baseline and at least one follow-up national health examination. From the health examination data, body weight, body mass index (kg/m2), serum creatinine (mg/dL) and eGFR (mL/min/1.73 m2) were collected. eGFR was calculated by a creatinine-based equation used from Modification of Diet in Renal Disease. In addition, smoking status (never smoker, ex-smoker, or current smoker), alcohol consumption (heavy drinker, ≥ 30 g/day), and physical activity were also evaluated from the self-reported questionnaires of health examination. Regular exercise was defined as performing moderate-intensity exercise ≥ 5 times per week or vigorous-intensity exercise ≥ 3 times per week (17 (link)).
Full text: Click here
Alcoholic Intoxication
Antiplatelet Agents
Body Weight
Cerebrovascular Accident
Chronic Kidney Diseases
Chronic Obstructive Airway Disease
Creatinine
Diabetes Mellitus
Diagnosis
Dietary Modification
Dyslipidemias
EGFR protein, human
Ex-Smokers
Heart Failure
High Blood Pressures
Index, Body Mass
Inpatient
Kidney Diseases
Malignant Neoplasms
Myocardial Infarction
Outpatients
Patients
Peripheral Arterial Diseases
Pharmaceutical Preparations
Self-Examination
Serum
For this cross-sectional study, a self-administered online questionnaire-based survey was conducted, between April and October 2019, among a group of pulmonologists who were members of the Turkish Thoracic Society. The TTS is an organization for healthcare professionals, akin to various pulmonology associations worldwide, and most of its members are pulmonologists.
The findings of this study were produced by reanalyzing part of the data obtained from an overarching TTS scientific research project entitled ‘Knowledge, attitudes, and behavior of the pulmonologist members of TTS towards tobacco and new tobacco products’. The study protocol was approved by the TTS Scientific Project Committee. After a pre-test, the TTS secretariat emailed a link to a self-administered online questionnaire on Survey Monkey (surveymonkey.com) containing a written informed consent form to 2941 pulmonologist members of TTS. Weekly reminders were made to boost the number of participants. As we could not confirm if the e-mails were received and read by all these members, we estimated the response rate as the number of total completed surveys divided by the number of registered TTS pulmonologists. The questionnaire asked about gender, age, medical school graduation date, academic position, smoking status, the existence and the source of training on smoking cessation care (SCC), and about the presence of providing outpatient-based SCC. Outpatient-based SCC includes providing both counselling and smoking cessation medication in a dedicated smoking cessation outpatient clinic that is offered as an outpatient health service in Turkey. The categorical variables were dichotomized, e.g. academic position was dichotomized as having or not having any academic employment.
The WHO classification system was used to determine smoking status16 . Individuals who had smoked for at least six months in their lives and who were smoking continually at the time of the survey were categorized as ‘current smokers’. Ex-smokers (smoked for at least 6 months during their lifetime but not within the 6 months prior to the survey), recent quitters (smoked for at least 6 months during their lifetime but not within the 6 months prior to the survey), and never smokers (never smoked or had smoked for less than 6 months or fewer than 100 cigarettes during the survey) were classified as ‘non-current smokers’.
The findings of this study were produced by reanalyzing part of the data obtained from an overarching TTS scientific research project entitled ‘Knowledge, attitudes, and behavior of the pulmonologist members of TTS towards tobacco and new tobacco products’. The study protocol was approved by the TTS Scientific Project Committee. After a pre-test, the TTS secretariat emailed a link to a self-administered online questionnaire on Survey Monkey (surveymonkey.com) containing a written informed consent form to 2941 pulmonologist members of TTS. Weekly reminders were made to boost the number of participants. As we could not confirm if the e-mails were received and read by all these members, we estimated the response rate as the number of total completed surveys divided by the number of registered TTS pulmonologists. The questionnaire asked about gender, age, medical school graduation date, academic position, smoking status, the existence and the source of training on smoking cessation care (SCC), and about the presence of providing outpatient-based SCC. Outpatient-based SCC includes providing both counselling and smoking cessation medication in a dedicated smoking cessation outpatient clinic that is offered as an outpatient health service in Turkey. The categorical variables were dichotomized, e.g. academic position was dichotomized as having or not having any academic employment.
The WHO classification system was used to determine smoking status16 . Individuals who had smoked for at least six months in their lives and who were smoking continually at the time of the survey were categorized as ‘current smokers’. Ex-smokers (smoked for at least 6 months during their lifetime but not within the 6 months prior to the survey), recent quitters (smoked for at least 6 months during their lifetime but not within the 6 months prior to the survey), and never smokers (never smoked or had smoked for less than 6 months or fewer than 100 cigarettes during the survey) were classified as ‘non-current smokers’.
Full text: Click here
Ex-Smokers
Gender
Health Care Professionals
Health Services, Outpatient
Monkeys
Non-Smokers
Outpatients
Pharmaceutical Preparations
Pulmonologists
Tobacco Products
An index date was considered, which is deemed for each case as the day of appearance of dark vomiting or in coffee grounds, melena, and/or hematemesis (signs and symptoms of UGIB) and for controls the index date was defined as the date of the interview (13 (link)). To assess an association between the use of NSAIDs and LDA with the risk of UGIB, a 7-day etiologic window dated from the index date was considered, in line with other published studies (12 (link), 14 (link)).
For CYP2C9 analysis, NSAIDs use was grouped into NSAIDs metabolized at least 50% by CYP2C9 (piroxicam, celecoxib, naproxen, aceclofenac, indomethacin, diclofenac, and ibuprofen) and into NSAIDs metabolized less than 50% by CYP2C9 (other NSAIDs) (12 (link)). It is known that NSAIDs, as they are substrates of CYP2C9, are not metabolized at the same proportion of this enzyme and to perform an analysis considering the proportion of each NSAIDs metabolized by CYP2C9 increases the sample size power (7 (link)). LDA use was deemed the continuous use of aspirin at doses below 300 mg per day in the indication of prevention of primary and secondary cardiovascular events (15 (link)).
To perform an analysis of dose-effect, two researchers calculated the defined daily dose (DDD) by the World Health Organization (WHO) for NSAIDs for all participants. DDD was defined as the average maintenance dose per day of a drug used for its main indication in adults in the 7-day etiologic window preceding the data index. The dose-response effect was assessed using three categories: NSAIDs non-users (NSAIDs DDD = 0), NSAIDs users of 0.50 DDD or less (>0 NSAIDs DDD ≤0.50), and NSAIDs users of over 0.50 DDD (NSAIDs DDD >0.50) based on the proposal by Figueiras et al. (12 (link)). This approach considered each type of NSAIDs and the recommended DDD, enabling different NSAIDs to be compared with one another (7 (link)).
Regarding lifestyle, the mean daily consumption of tobacco, alcohol, and coffee over the 2 months preceding the index was calculated. Smoking habit was stratified according to the number of cigarettes consumed per day: non-smokers and ex-smokers (zero cigarette); 1 to 15 cigarettes/day; and >15 cigarettes/day. Alcohol intake was stratified in abstainers (0 g), >0 to ≤30 g of alcohol/day, and >30 g of alcohol. Coffee intake was stratified into none consumed (0 mL), >0 mL ≤ 100, >100 > mL ≤ 300, and >300 mL.
For CYP2C9 analysis, NSAIDs use was grouped into NSAIDs metabolized at least 50% by CYP2C9 (piroxicam, celecoxib, naproxen, aceclofenac, indomethacin, diclofenac, and ibuprofen) and into NSAIDs metabolized less than 50% by CYP2C9 (other NSAIDs) (12 (link)). It is known that NSAIDs, as they are substrates of CYP2C9, are not metabolized at the same proportion of this enzyme and to perform an analysis considering the proportion of each NSAIDs metabolized by CYP2C9 increases the sample size power (7 (link)). LDA use was deemed the continuous use of aspirin at doses below 300 mg per day in the indication of prevention of primary and secondary cardiovascular events (15 (link)).
To perform an analysis of dose-effect, two researchers calculated the defined daily dose (DDD) by the World Health Organization (WHO) for NSAIDs for all participants. DDD was defined as the average maintenance dose per day of a drug used for its main indication in adults in the 7-day etiologic window preceding the data index. The dose-response effect was assessed using three categories: NSAIDs non-users (NSAIDs DDD = 0), NSAIDs users of 0.50 DDD or less (>0 NSAIDs DDD ≤0.50), and NSAIDs users of over 0.50 DDD (NSAIDs DDD >0.50) based on the proposal by Figueiras et al. (12 (link)). This approach considered each type of NSAIDs and the recommended DDD, enabling different NSAIDs to be compared with one another (7 (link)).
Regarding lifestyle, the mean daily consumption of tobacco, alcohol, and coffee over the 2 months preceding the index was calculated. Smoking habit was stratified according to the number of cigarettes consumed per day: non-smokers and ex-smokers (zero cigarette); 1 to 15 cigarettes/day; and >15 cigarettes/day. Alcohol intake was stratified in abstainers (0 g), >0 to ≤30 g of alcohol/day, and >30 g of alcohol. Coffee intake was stratified into none consumed (0 mL), >0 mL ≤ 100, >100 > mL ≤ 300, and >300 mL.
Full text: Click here
aceclofenac
Adult
Anti-Inflammatory Agents, Non-Steroidal
Aspirin
Cardiovascular System
Celecoxib
Coffee
Diclofenac
Enzymes
Ethanol
Ex-Smokers
Hematemesis
Ibuprofen
Indomethacin
Melena
Naproxen
Non-Smokers
Pharmaceutical Preparations
Piroxicam
Primary Prevention
As previously mentioned21 (link), the researchers used questionnaires, physical examinations, and blood tests to obtain baseline data from the participants. Subjects were categorized depending on average weekly ethanol and type of alcohol intake. Alcohol intake of less than 40 g per week is defined as no or minimal alcohol consumption23 (link). Weekly alcohol intake of 40 g to 140 g is defined as light alcohol consumption23 (link). Alcohol intake of 140 g to 280 g per week is defined as moderate alcohol consumption23 (link). Weekly alcohol intake greater than 280 g is defined as heavy alcohol consumption23 (link). Participants were divided into non-smokers, ex-smokers, and current smokers based on their smoking status at baseline. Non-smokers were defifined as participants who never smoked cigarettes, ex-smokers as participants who had smoked in the past but who quit smoking until the baseline visit, and current-smokers as participants who smoked at the baseline visit21 (link).
Regular participation in sports > 1x/week is defined as regular exercise. 24 (link). Body mass index is calculated as the number of kilograms of body weight divided by the square of the number of meters of height25 (link). The ratio of TG/HDL-C was measured by dividing the fasting triglyceride level (mmol/L) into the fasting High-density lipoprotein cholesterol level (mmol/L). Gastroenterologists diagnose fatty liver by reviewing abdominal ultrasound based on four known criteria (liver brightness, liver, and kidney echo contrast, vascular blurring, and depth attenuation)26 (link).
Regular participation in sports > 1x/week is defined as regular exercise. 24 (link). Body mass index is calculated as the number of kilograms of body weight divided by the square of the number of meters of height25 (link). The ratio of TG/HDL-C was measured by dividing the fasting triglyceride level (mmol/L) into the fasting High-density lipoprotein cholesterol level (mmol/L). Gastroenterologists diagnose fatty liver by reviewing abdominal ultrasound based on four known criteria (liver brightness, liver, and kidney echo contrast, vascular blurring, and depth attenuation)26 (link).
Full text: Click here
Abdomen
Blood Vessel
Body Weight
Diagnosis
ECHO protocol
Ethanol
Ex-Smokers
Fatty Liver
Gastroenterologist
Hematologic Tests
High Density Lipoprotein Cholesterol
Index, Body Mass
Kidney
Light
Liver
Non-Smokers
Physical Examination
Triglycerides
Ultrasonics
Top products related to «Ex-Smokers»
Sourced in United States, Austria, Japan, Cameroon, Germany, United Kingdom, Canada, Belgium, Israel, Denmark, Australia, New Caledonia, France, Argentina, Sweden, Ireland, India
SAS version 9.4 is a statistical software package. It provides tools for data management, analysis, and reporting. The software is designed to help users extract insights from data and make informed decisions.
Sourced in United States, United Kingdom, Spain, Germany, Austria
SPSS v24 is a software application for statistical analysis. It provides tools for data management, analysis, and visualization. The core function of SPSS v24 is to assist users in processing and analyzing data, including the ability to perform various statistical tests and generate reports.
Sourced in United States, Japan, United Kingdom, Germany, Austria, Belgium, Denmark, China, Israel, Australia
SPSS version 21 is a statistical software package developed by IBM. It is designed for data analysis and statistical modeling. The software provides tools for data management, data analysis, and the generation of reports and visualizations.
Sourced in United States, Japan, Austria, Germany, United Kingdom, France, Cameroon, Denmark, Israel, Sweden, Belgium, Italy, China, New Zealand, India, Brazil, Canada
SAS software is a comprehensive analytical platform designed for data management, statistical analysis, and business intelligence. It provides a suite of tools and applications for collecting, processing, analyzing, and visualizing data from various sources. SAS software is widely used across industries for its robust data handling capabilities, advanced statistical modeling, and reporting functionalities.
Sourced in United States, Austria, Japan, Belgium, Brazil, United Kingdom, Cameroon
SAS software version 9.4 is a comprehensive data analysis and management solution. It provides advanced statistical and analytical capabilities for organizations to manage, analyze, and report on their data. The software includes a range of tools and features to support various data-driven tasks, such as data manipulation, statistical modeling, and predictive analytics.
Sourced in United States, Austria, Japan, Cameroon
SAS statistical software is a comprehensive data analysis and visualization tool. It provides a wide range of statistical procedures and analytical capabilities for managing, analyzing, and presenting data. The software is designed to handle large and complex datasets, allowing users to perform advanced statistical modeling, regression analysis, and data mining tasks. The core function of the SAS statistical software is to enable users to extract insights and make data-driven decisions.
Sourced in United States, Denmark, United Kingdom
STATA version 11 is a software package for statistical analysis, data management, and graphics. It provides a wide range of statistical tools and functions for researchers, analysts, and professionals in various fields. The core function of STATA version 11 is to perform advanced statistical analysis and modeling on data.
Sourced in United States, Japan, Germany, United Kingdom, Austria
SPSS Statistics 25 is a software package used for statistical analysis. It provides a wide range of data management and analysis capabilities, including advanced statistical techniques, data visualization, and reporting tools. The software is designed to help users analyze and interpret data from various sources, supporting decision-making processes across different industries and research fields.
Sourced in Japan, United States, Israel, Germany, Australia, United Kingdom
The Digital Scale is a precision measurement device that accurately determines the weight of various objects. It utilizes advanced digital technology to provide reliable and consistent results.
Sourced in United States, Denmark, United Kingdom, Austria, Sweden
Stata 13 is a comprehensive, integrated statistical software package developed by StataCorp. It provides a wide range of data management, statistical analysis, and graphical capabilities. Stata 13 is designed to handle complex data structures and offers a variety of statistical methods for researchers and analysts.
More about "Ex-Smokers"
Former smokers, tobacco cessation, smoking abstinence, relapse prevention, research protocols, reproducibility, accuracy, PubCompare.ai, AI-driven platform, literature, pre-prints, patents, data analysis, statistical software, SAS 9.4, SPSS 24, SPSS 21, Stata 11, SPSS Statistics 25, Stata 13, digital scales.
Ex-smokers face unique challenges in maintaining their abstinence and preventing relapse.
PubCompare.ai's AI-driven platform can assist ex-smokers in optimizing their research protocols, ensuring reproducibility and accuracy.
The platform enables users to locate relevant protocols from literature, pre-prints, and patents, and leverages AI-driven comparisons to identify the best protocols and products.
This takes the guesswork out of research, empowering ex-smokers to make informed decisions and achieve their health goals.
With PubCompare.ai's powerful tools, ex-smokers can navigate the complexities of their journey with confidence and ease.
The platform also integrates with popular statistical software like SAS 9.4, SPSS 24, SPSS 21, Stata 11, SPSS Statistics 25, and Stata 13, allowing ex-smokers to analyze their data and track their progress with precision.
Digital scales can also be used in conjunction with the platform to monitor weight changes during the smoking cessation process.
By leveraging the latest technology and data-driven insights, PubCompare.ai helps ex-smokers optimize their research protocols, stay on track, and achieve their health goals.
Ex-smokers face unique challenges in maintaining their abstinence and preventing relapse.
PubCompare.ai's AI-driven platform can assist ex-smokers in optimizing their research protocols, ensuring reproducibility and accuracy.
The platform enables users to locate relevant protocols from literature, pre-prints, and patents, and leverages AI-driven comparisons to identify the best protocols and products.
This takes the guesswork out of research, empowering ex-smokers to make informed decisions and achieve their health goals.
With PubCompare.ai's powerful tools, ex-smokers can navigate the complexities of their journey with confidence and ease.
The platform also integrates with popular statistical software like SAS 9.4, SPSS 24, SPSS 21, Stata 11, SPSS Statistics 25, and Stata 13, allowing ex-smokers to analyze their data and track their progress with precision.
Digital scales can also be used in conjunction with the platform to monitor weight changes during the smoking cessation process.
By leveraging the latest technology and data-driven insights, PubCompare.ai helps ex-smokers optimize their research protocols, stay on track, and achieve their health goals.