scholarly journals Population characteristics of patients with coxarthrosis

2019 ◽  
Vol 16 (2) ◽  
pp. 156-165
Author(s):  
A. S. Korolko ◽  
V. V. Suschevich ◽  
Ya. I. Evko ◽  
O. P. Kezlya
Keyword(s):  
Risk Factors ◽  
Statistical Processing ◽  
Population Level ◽  
Population Characteristics ◽  
Hip Joints ◽  
Stage Of Development ◽  
Osteoarthritis Of Hip

We examined 150 patients with osteoarthritis of hip joints. The stage of development of arthrosis is II–III (according to Kellgren-Lawrence). Statistical processing was carried out, and the risk factors at the population level were revealed, which provide the emergence of coxarthrosis and affect the patient’s circulation.

Population level risk factors associated with childhood obesity

2019 ◽  
Author(s):  
Claire Beynon ◽  
Nora Pashyan ◽  
Elizabeth Fisher ◽  
Dougal Hargreaves ◽  
Linda Bailey ◽  
...  
Keyword(s):  
Risk Factors ◽  
Childhood Obesity ◽  
Population Level ◽  
Factors Associated

scholarly journals Risk factors for cholesterol polyp formation in the gallbladder are closely related to lipid metabolism

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhihao Yu ◽  
Changlin Yang ◽  
Xuesong Bai ◽  
Guibin Yao ◽  
Xia Qian ◽  
...  
Keyword(s):  
Risk Factors ◽  
Low Density Lipoprotein ◽  
Univariate Analysis ◽  
Density Lipoprotein ◽  
High Volume ◽  
Population Characteristics ◽  
Polyp Formation ◽  
Logistic Analysis ◽  
Cholesterol Polyp ◽  
Independent Risk Factors

Abstract Background The purpose of this study was to assess the risk factors for cholesterol polyp formation in the gallbladder. Methods This was a multicenter retrospective study based on pathology. From January 2016 to December 2019, patients who underwent cholecystectomy and non-polyp participants confirmed by continuous ultrasound follow-ups were reviewed. Patients in the cholesterol polyp group were recruited from three high-volume centers with a diagnosis of pathologically confirmed cholesterol polyps larger than 10 mm. Population characteristics and medical data were collected within 24 h of admission before surgery. The non-polyp group included participants from the hospital physical examination center database. They had at least two ultrasound examinations with an interval longer than 180 days. Data from the final follow-up of the non-polyp group were analyzed. The risk factors for cholesterol polyp formation were analyzed by comparing the two groups. Results A total of 4714 participants were recruited, including 376 cholesterol polyp patients and 4338 non-polyp participants. In univariate analysis, clinical risk factors for cholesterol polyps were age, male sex, higher body mass index (BMI), higher low-density lipoprotein (LDL), lower high-density lipoprotein (HDL), and higher aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels. In multivariate logistic analysis, independent risk factors were age > 50 years (odds ratio [OR] = 3.02, 95% confidence interval [CI] 2.33–3.91, P < 0.001], LDL > 2.89 mmol/L (OR = 1.38, 95% CI 1.08–1.78, P = 0.011), lower HDL (OR = 1.78 95% CI 1.32–2.44, P < 0.001), AST > 40 IU/L (OR = 3.55, 95% CI 2.07–6.07, P < 0.001), and BMI > 25 kg/m 2 (OR = 1.32, 95% CI 1.01–1.72, P = 0.037). Conclusions Age, LDL, HDL, AST, and BMI are strong risk factors for cholesterol polyp formation. Older overweight patients with polyps, accompanied by abnormal lipid levels, are at high risk for cholesterol polyps.

scholarly journals Combating escalating harms associated with pharmaceutical opioid use in Australia: the POPPY II study protocol

BMJ Open ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. e025840 ◽  
Author(s):  
Natasa Gisev ◽  
Sallie-Anne Pearson ◽  
Timothy Dobbins ◽  
David C Currow ◽  
Fiona Blyth ◽  
...  
Keyword(s):  
Risk Factors ◽  
Opioid Dependence ◽  
Service Use ◽  
Population Level ◽  
Ethics Committee ◽  
Adverse Outcomes ◽  
Opioid Use ◽  
Research Committee ◽  
Services Research ◽  
Wide Range

IntroductionOpioid prescribing has increased 15-fold in Australia in the past two decades, alongside increases in a range of opioid-related harms such as opioid dependence and overdose. However, despite concerns about increasing opioid use, extramedical use and harms, there is a lack of population-level evidence about the drivers of long-term prescribed opioid use, dependence, overdose and other harms.Methods and analysisWe will form a cohort of all adult residents in New South Wales (NSW), Australia, who initiated prescribed opioids from 2002 using Pharmaceutical Benefits Scheme dispensing records. This cohort will be linked to a wide range of other datasets containing information on sociodemographic and clinical characteristics, health service use and adverse outcomes (eg, opioid dependence and non-fatal and fatal overdose). Analyses will initially examine patterns and predictors of prescribed opioid use and then apply regression and survival analysis to quantify the risks and risk factors of adverse outcomes associated with prescribed opioid use.Ethics and disseminationThis study has received full ethical approval from the Australian Institute of Health and Welfare Ethics Committee, the NSW Population and Health Services Research Committee and the ACT Health Human Research Ethics Committee. This will be the largest postmarketing surveillance study of prescribed opioids undertaken in Australia, linking exposure and outcomes and examining risk factors for adverse outcomes of prescribed opioids. As such, this work has important translational promise, with direct relevance to regulatory authorities and agencies worldwide. Project findings will be disseminated at scientific conferences and in peer-reviewed journals. We will also conduct targeted dissemination with policy makers, professional bodies and peak bodies in the pain, medicine and addiction fields through stakeholder workshops and advisory groups. Results will be reported in accordance with the REporting of studies Conducted using Observational Routinely collected Data (RECORD) Statement.

scholarly journals Association of Conventional Cardiovascular Risk Factors with Carotid Atherosclerosis Prevalence in General Population

2018 ◽  
Vol 14 (4) ◽  
pp. 552-557
Author(s):  
V. S. Kaveshnikov ◽  
V. N. Serebryakova ◽  
I. A. Trubacheva ◽  
S. A. Shalnova
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Carotid Atherosclerosis ◽  
Population Level ◽  
Educational Status ◽  
Population Based ◽  
High Density Lipoproteins ◽  
Ultrasound Screening ◽  
Cross Sectional ◽  
Working Age

Material and methods. In the cross-sectional population-based study of general unorganized population of Tomsk aged 25-64 years ultrasound screening examination of the carotid arteries was done for detection of atherosclerotic plaques (plaque). As potential plaque determinants the following factors were studied: age, gender, smoking, low and high density lipoproteins (LDL-C and HDL-C), triglycerides, arterial hypertension, body mass index (BMI), low educational status (LES), high-sensitive C-reactive protein, glucose, diabetes mellitus, antihypertensive and hypolipidemic therapy. Study of relationships was carried out with logistic regression analysis. The error probability of less than 5% was considered statistically significant.Results. In the crude analysis most of the determinants under study showed statistically significant relationship with plaque presence. After adjustment for age and sex, LDL-C, smoking and LES were associated with CAS prevalence. In multivariable regression analysis 9 risk factors appeared to be independently associated with plaque presence, wherein age, male sex, LDL-C, BMI and HDL-C were the most significant. In the participants of 50 years and older the smoking effect was the next in significance after LDL-C.Conclusion. The results obtained focus attention on the comparative value of the major atherogenic risk factors and suggest that currently effective and timely control of LDL-C is of primary importance for prevention of carotid atherosclerosis in the general working-age population. As well the findings of the study evidence that at the population level smoking is still one of the leading atherogenic risk factors.

scholarly journals Association of rs3025058 polymorphism with the development of acute cerebrovascular event

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
A Chernova ◽  
S Nikulina ◽  
D Nikulin
Keyword(s):  
Risk Factors ◽  
Genetic Research ◽  
Statistical Processing ◽  
Main Group ◽  
Control Group ◽  
Cerebrovascular Event ◽  
Siberian Population ◽  
Cardiovascular Pathology ◽  
Daily Monitoring ◽  
Arterial Blood

Abstract Purpose To study SNP rs3025058 association (5a/6a) with development of Acute Cerebrovascular Event in the patients with cardiovascular pathology and risk factors of its development who are representatives of the east Siberian population. Material and methods 260 patients with Acute Cerebrovascular Event participated in a research (age [57.0; 51.0–62.0]) and 272 patients of control group (age [55.0; 51.0–62.0].). Among the patients who transferred Acute Cerebrovascular Event, 157 men and 103 women. The control group included 170 men and 102 women. Inspection of the main group included: collecting complaints, anamnesis, clinical examination, computer tomography of a brain, electrocardiography, echo, ultrasonic of arteries, daily monitoring of arterial blood pressure and cardiac rhythm, analysis of a coagulant system of blood. Patients of the main group had the following cardiovascular pathology and risk factors: arterial hypertension, supraventricular tachycardia, dislipidemiya, atherosclerosis brachiocephalic of arteries, disturbances of a system of a hemostasis. The control group is examined within the international HAPIEE project. The molecular and genetic research was conducted by PCR method in real time. Statistical processing of material was carried out with use of set of the Statistica for Windows 7.0, Excel and SPSS 22 application programs. Results In all analyzed groups and subgroups of patients statistically significant connection between a genotype of 5a/5a and an allele of 5a and in subgroup of women with Acute Cerebrovascular Event, subgroups of patients with AG and hypercoagulation of significant associations of polymorphism rs3025058 (5a/6a) with Acute Cerebrovascular Eventis not revealed. Conclusion A genotype 5a/5a and an allele 5a SNP rs3025058 (5a/6a) increase risk of development of an Acute Cerebrovascular Event in persons of the east Siberian population, including with such risk factors as atherosclerosis the brachiocephalic of arteries and a dislipidemiya. FUNDunding Acknowledgement Type of funding sources: None.

scholarly journals Methodology for sampling women at high maternal risk in administrative data

2019 ◽  
Author(s):  
Jennifer Vanderlaan ◽  
Anne Dunlop ◽  
Roger Rochat ◽  
Bryan Williams ◽  
Susan E. Shapiro
Keyword(s):  
Risk Factors ◽  
Administrative Data ◽  
Conventional Method ◽  
Maternal Morbidity ◽  
Sample Selection ◽  
Population Level ◽  
Risk Identification ◽  
Net Benefit ◽  
Maternal Risk ◽  
Risk Scoring

Abstract Background In population level studies, the conventional practice of categorizing women into low and high maternal risk samples relies upon ascertaining the presence of various comorbid conditions in administrative data. Two problems with the conventional method include variability in the recommended comorbidities to consider and inability to distinguish between maternal and fetal risks. High maternal risk sample selection may be improved by using the Obstetric Comorbidity Index (OCI), a system of risk scoring based on weighting comorbidities associated with maternal end organ damage. The purpose of this study was to compare the net benefit of using OCI risk scoring vs the conventional risk identification method to identify a sample of women at high maternal risk in administrative data. Methods This was a net benefit analysis using linked delivery hospitalization discharge and vital records data for women experiencing singleton births in Georgia from 2008-2012. We compared the value identifying a sample of women at high maternal risk using the OCI score to the conventional method of dichotomous identification of any comorbidities. Value was measured by the ability to select a sample of women designated as high maternal risk who experienced severe maternal morbidity or mortality. Results The high maternal risk sample created with the OCI had a small but positive net benefit (+ 0.6), while the conventionally derived sample had a negative net benefit indicating the sample selection performed worse than identifying no woman as high maternal risk. Conclusions The OCI can be used to select women at high maternal risk in administrative data. The OCI provides a consistent method of identification for women at risk of maternal morbidity and mortality and avoids confounding all obstetric risk factors with specific maternal risk factors. Using the OCI may help reduce misclassification as high maternal risk and improve the consistency in identifying women at high maternal risk in administrative data.

Leveraging data science to enhance suicide prevention research: a literature review

2021 ◽  
pp. injuryprev-2021-044322
Author(s):  
Avital Rachelle Wulz ◽  
Royal Law ◽  
Jing Wang ◽  
Amy Funk Wolkin
Keyword(s):  
Risk Factors ◽  
Literature Review ◽  
Injury Prevention ◽  
Suicide Prevention ◽  
Data Science ◽  
Population Level ◽  
Individual Risk ◽  
Prevention Research ◽  
Science Method ◽  
Individual Level

ObjectiveThe purpose of this research is to identify how data science is applied in suicide prevention literature, describe the current landscape of this literature and highlight areas where data science may be useful for future injury prevention research.DesignWe conducted a literature review of injury prevention and data science in April 2020 and January 2021 in three databases.MethodsFor the included 99 articles, we extracted the following: (1) author(s) and year; (2) title; (3) study approach (4) reason for applying data science method; (5) data science method type; (6) study description; (7) data source and (8) focus on a disproportionately affected population.ResultsResults showed the literature on data science and suicide more than doubled from 2019 to 2020, with articles with individual-level approaches more prevalent than population-level approaches. Most population-level articles applied data science methods to describe (n=10) outcomes, while most individual-level articles identified risk factors (n=27). Machine learning was the most common data science method applied in the studies (n=48). A wide array of data sources was used for suicide research, with most articles (n=45) using social media and web-based behaviour data. Eleven studies demonstrated the value of applying data science to suicide prevention literature for disproportionately affected groups.ConclusionData science techniques proved to be effective tools in describing suicidal thoughts or behaviour, identifying individual risk factors and predicting outcomes. Future research should focus on identifying how data science can be applied in other injury-related topics.

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