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Accuracy of the Third Molar Eruption Predictor in predicting eruption.

https://arctichealth.org/en/permalink/ahliterature194372
Source
Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2001 Jun;91(6):638-42
Publication Type
Article
Date
Jun-2001
Author
I. Ventä
S. Schou
Author Affiliation
Department of Oral Medicine, University of Helsinki, Finland. irja.venta@helsinki.fi
Source
Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2001 Jun;91(6):638-42
Date
Jun-2001
Language
English
Publication Type
Article
Keywords
Adult
Bayes Theorem
Calibration
Denmark
False Negative Reactions
False Positive Reactions
Female
Follow-Up Studies
Forecasting - methods
Humans
Male
Molar - radiography
Molar, Third - physiology - radiography
Observer Variation
Odontometry
Probability
Radiography, Panoramic
Retrospective Studies
Sensitivity and specificity
Tooth Crown - radiography
Tooth Eruption
Tooth, Impacted - physiopathology
Tooth, Unerupted - physiopathology - radiography
Abstract
To evaluate the possibility of applying the Third Molar Eruption Predictor to all panoramic radiographs.
Panoramic radiographs were retrospectively analyzed from a 4-year follow-up study of third molars carried out at the University of Copenhagen, Denmark. The radiographs, taken at a mean age of 20.6 years, included 45 unerupted or partially erupted mandibular third molars in 28 subjects. Because the device was calibrated both with simple proportions and by use of the methods of Bayes' Decision Theory, the separation point of the device was therefore adjusted at 12 mm from the distal surface of the second molar.
The predictions of future eruption or impaction made with the calibrated device and the actual clinical outcome 4 years later were in conformity for 80% of the mandibular third molars.
The Third Molar Eruption Predictor may be applied to all panoramic radiographs, but it seems to require calibration before use.
PubMed ID
11402274 View in PubMed
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All Our Babies Cohort Study: recruitment of a cohort to predict women at risk of preterm birth through the examination of gene expression profiles and the environment.

https://arctichealth.org/en/permalink/ahliterature138214
Source
BMC Pregnancy Childbirth. 2010;10:87
Publication Type
Article
Date
2010
Author
Sara K Gracie
Andrew W Lyon
Heather L Kehler
Craig E Pennell
Siobhan M Dolan
Deborah A McNeil
Jodi E Siever
Sheila W McDonald
Alan D Bocking
Stephen J Lye
Kathy M Hegadoren
David M Olson
Suzanne C Tough
Author Affiliation
Department of Paediatrics, University of Calgary, Calgary, Alberta, Canada.
Source
BMC Pregnancy Childbirth. 2010;10:87
Date
2010
Language
English
Publication Type
Article
Keywords
Adolescent
Canada - epidemiology
Clinical Protocols
Cohort Studies
Environment
Female
Forecasting - methods
Gene Expression Profiling
Humans
Premature Birth - epidemiology - genetics - physiopathology
Prospective Studies
Research Design
Risk factors
Abstract
Preterm birth is the leading cause of perinatal morbidity and mortality. Risk factors for preterm birth include a personal or familial history of preterm delivery, ethnicity and low socioeconomic status yet the ability to predict preterm delivery before the onset of preterm labour evades clinical practice. Evidence suggests that genetics may play a role in the multi-factorial pathophysiology of preterm birth. The All Our Babies Study is an on-going community based longitudinal cohort study that was designed to establish a cohort of women to investigate how a women's genetics and environment contribute to the pathophysiology of preterm birth. Specifically this study will examine the predictive potential of maternal leukocytes for predicting preterm birth in non-labouring women through the examination of gene expression profiles and gene-environment interactions.
Collaborations have been established between clinical lab services, the provincial health service provider and researchers to create an interdisciplinary study design for the All Our Babies Study. A birth cohort of 2000 women has been established to address this research question. Women provide informed consent for blood sample collection, linkage to medical records and complete questionnaires related to prenatal health, service utilization, social support, emotional and physical health, demographics, and breast and infant feeding. Maternal blood samples are collected in PAXgene™ RNA tubes between 18-22 and 28-32 weeks gestation for transcriptomic analyses.
The All Our Babies Study is an example of how investment in clinical-academic-community partnerships can improve research efficiency and accelerate the recruitment and data collection phases of a study. Establishing these partnerships during the study design phase and maintaining these relationships through the duration of the study provides the unique opportunity to investigate the multi-causal factors of preterm birth. The overall All Our Babies Study results can potentially lead to healthier pregnancies, mothers, infants and children.
Notes
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PubMed ID
21192811 View in PubMed
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An assessment of GLOBOCAN methods for deriving national estimates of cancer incidence.

https://arctichealth.org/en/permalink/ahliterature280690
Source
Bull World Health Organ. 2016 Mar 01;94(3):174-84
Publication Type
Article
Date
Mar-01-2016
Author
Sebastien Antoni
Isabelle Soerjomataram
Bjørn Møller
Freddie Bray
Jacques Ferlay
Source
Bull World Health Organ. 2016 Mar 01;94(3):174-84
Date
Mar-01-2016
Language
English
Publication Type
Article
Keywords
Databases, Factual - statistics & numerical data
Female
Forecasting - methods
Humans
Incidence
Male
Neoplasms - classification - mortality
Norway - epidemiology
Registries - statistics & numerical data
Abstract
To assess the validity of the GLOBOCAN methods for deriving national estimates of cancer incidence.
We obtained incidence and mortality data from Norway by region, year of diagnosis, cancer site, sex and 5-year age group for the period 1983-2012 from the NORDCAN database. Estimates for the year 2010 were derived using nine different methods from GLOBOCAN. These included the projection of national historical rates, the use of regional proxies and the combination of national mortality data with mortality to incidence ratios or relative survival proportions. We then compared the national estimates with recorded cancer incidence data.
Differences between the estimates derived using different methods varied by cancer site and sex. Methods based on projections performed better where major changes in recent trends were absent. Methods based on mortality data performed less well for cancers associated with small numbers of deaths and for cancers detectable by screening. In countries with longstanding cancer registries of high quality, regional-based, or trends-based incidence estimates perform reasonably well in comparison with recorded incidence.
Although the performance of the GLOBOCAN methods varies by cancer site and sex in this study, the results emphasize a need for more high-quality population-based cancer registries - either regional or, where practical and feasible, national registries - to describe cancer patterns and trends for planning cancer control priorities.
Notes
Cites: Int J Cancer. 2015 Mar 1;136(5):E359-8625220842
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PubMed ID
26966328 View in PubMed
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An IDEA for short term outbreak projection: nearcasting using the basic reproduction number.

https://arctichealth.org/en/permalink/ahliterature105416
Source
PLoS One. 2013;8(12):e83622
Publication Type
Article
Date
2013
Author
David N Fisman
Tanya S Hauck
Ashleigh R Tuite
Amy L Greer
Author Affiliation
The Dalla Lana School of Public Health, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada ; Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada ; The Decision Centre for Infectious Disease Epidemiology (DeCIDE), Toronto, Ontario, Canada.
Source
PLoS One. 2013;8(12):e83622
Date
2013
Language
English
Publication Type
Article
Keywords
Basic Reproduction Number - statistics & numerical data
Communicable Diseases - epidemiology
Disease Outbreaks - statistics & numerical data
Forecasting - methods
Humans
Incidence
Influenza A Virus, H1N1 Subtype
Influenza, Human - epidemiology
Models, Statistical
Nunavut - epidemiology
Abstract
Communicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth.
The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R0, along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts).
Compared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R0 is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1(th) serial interval using data from the i(th) serial interval within an average of 20% of actual incidence.
This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists.
Notes
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PubMed ID
24391797 View in PubMed
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Association of automated data collection and data completeness with outcomes of intensive care. A new customised model for outcome prediction.

https://arctichealth.org/en/permalink/ahliterature126503
Source
Acta Anaesthesiol Scand. 2012 Oct;56(9):1114-22
Publication Type
Article
Date
Oct-2012
Author
M. Reinikainen
P. Mussalo
S. Hovilehto
A. Uusaro
T. Varpula
A. Kari
V. Pettilä
Author Affiliation
Department of Intensive Care, North Karelia Central Hospital, Joensuu, Finland. matti.reinikainen@pkssk.?
Source
Acta Anaesthesiol Scand. 2012 Oct;56(9):1114-22
Date
Oct-2012
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Age Factors
Aged
Aged, 80 and over
Algorithms
Automatic Data Processing - methods
Benchmarking
Child
Data Collection - methods
Data Interpretation, Statistical
Female
Finland - epidemiology
Forecasting - methods
Health Facility Size
Hospital Mortality
Humans
Intensive Care - statistics & numerical data
Male
Middle Aged
Models, Statistical
Patient Discharge
Probability
Prospective Studies
Quality Improvement
Severity of Illness Index
Treatment Outcome
Young Adult
Abstract
The Finnish Intensive Care Consortium coordinates a national intensive care benchmarking programme. Clinical information systems (CISs) that collect data automatically are widely used. The aim of this study was to explore whether the severity of illness-adjusted hospital mortality of Finnish intensive care unit (ICU) patients has changed in recent years and whether the changes reflect genuine improvements in the quality of care or are explained by changes in measuring severity of illness.
We retrospectively analysed data collected prospectively to the database of the Consortium. During the years 2001-2008, there were 116,065 admissions to the participating ICUs. We excluded readmissions, cardiac surgery patients, patients under 18 years of age and those discharged from an ICU to another hospital's ICU. The study population comprised 85,547 patients. The Simplified Acute Physiology Score II (SAPS II) was used to measure severity of illness and to calculate standardised mortality ratios (SMRs, the number of observed deaths divided by the number of expected deaths).
The overall hospital mortality rate was 18.4%. The SAPS II-based SMRs were 0.74 in 2001-2004 and 0.64 in 2005-2008. The severity of illness-adjusted odds of death were 24% lower in 2005-2008 than in 2001-2004. One fifth of this computational difference could be explained by differences in data completeness and the automation of data collection with a CIS.
The use of a CIS and improving data completeness do decrease severity-adjusted mortality rates. However, this explains only one fifth of the improvement in measured outcomes of intensive care in Finland.
PubMed ID
22384799 View in PubMed
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Changes in all-cause and cardiovascular disease mortality in three different Finnish population cohorts with and without diabetes.

https://arctichealth.org/en/permalink/ahliterature107914
Source
Int J Cardiol. 2013 Oct 12;168(5):4734-8
Publication Type
Article
Date
Oct-12-2013
Author
Noël C Barengo
Riitta Antikainen
Markku Peltonen
Jaakko Tuomilehto
Author Affiliation
Institute of Clinical Medicine/Internal Medicine, University of Oulu, Oulu, Finland; Universidad del Tolima, Ibagué, Colombia. Electronic address: noel.barengo@gmail.com.
Source
Int J Cardiol. 2013 Oct 12;168(5):4734-8
Date
Oct-12-2013
Language
English
Publication Type
Article
Keywords
Adult
Cardiovascular Diseases - mortality
Cause of Death - trends
Cross-Sectional Studies
Diabetes Mellitus - mortality
Female
Finland - epidemiology
Follow-Up Studies
Forecasting - methods
Humans
Male
Middle Aged
Population Surveillance - methods
Retrospective Studies
Risk factors
Survival Rate - trends
Abstract
We aimed to assess changes in cardiovascular (CVD) and all-cause mortality among diabetic and non-diabetic individuals between three large study cohorts with baseline assessments of 10 years apart and followed up for 10 years.
Six population surveys were carried out in 1972, 1977, 1982, 1987, 1992 and 1997 in Finland. For the analyses we combined the 1972 and 1977 cohorts (cohort 1), the 1982 and 1987 cohorts (cohort 2) and similarly also the 1992 and 1997 cohorts (cohort 3).
Age-adjusted hazard ratio (HR) of all-cause mortality and CVD in men without diabetes showed that both had a statistically significant decreased risk of all-cause mortality compared to the first cohort. No statistically significant changes in all-cause mortality were observed in men and women with diabetes between the latter two cohorts compared with the first after controlling for several covariates. In both men and women without diabetes, cohort 2 (men, HR=0.65; 95% CI 0.51-0.82; women, HR=0.54; 95% CI 0.32-0.89) and cohort 3 (men, HR=0.32; 95% CI 0.22-0.47; women, HR=0.31; 95% CI 0.14-0.68) showed a statistically significant decreased risk of CVD mortality compared to cohort 1. Age-adjusted HRs in regard to CVD mortality in men (HR=0.22; 95% CI 0.07-0.69) and women (HR=0.22; 95% CI 0.05-0.99) with diabetes of cohort 3 were statistically significantly lower than in cohort 1.
There seems to be a decrease in CVD mortality in people with diabetes indicating that treatment of diabetes and cardiovascular risk factors in diabetes patients may have improved during the last decade.
PubMed ID
23962774 View in PubMed
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Children's school readiness: implications for eliminating future disparities in health and education.

https://arctichealth.org/en/permalink/ahliterature115985
Source
Health Educ Behav. 2014 Feb;41(1):25-33
Publication Type
Article
Date
Feb-2014
Author
Linda S Pagani
Caroline Fitzpatrick
Author Affiliation
1Université de Montréal, Montreal, Quebec, Canada.
Source
Health Educ Behav. 2014 Feb;41(1):25-33
Date
Feb-2014
Language
English
Publication Type
Article
Keywords
Adult
Attention
Child
Child Development
Child, Preschool
Cognition
Educational Measurement - methods
Educational Status
Executive Function
Female
Forecasting - methods
Health Behavior
Health Status Disparities
Humans
Longitudinal Studies
Male
Mathematical Concepts
Quebec
Regression Analysis
Schools
Vocabulary
Abstract
School-entry characteristics predict adult educational attainment, which forecasts dispositions toward disease prevention. Health and education risks can also be transmitted from one generation to the next. As such, school readiness forecasts a set of intertwined biopsychosocial trajectories that can influence the developmental antecedents to health and disease prevalence in society.
To predict children's health behaviors and academic adjustment at the end of fourth grade from their kindergarten entry math, vocabulary, and attention skills.
We use a subsample of 614 girls and 541 boys from the Quebec Longitudinal Study of Child Development (Canada). Children were individually assessed for cognitive skills and teachers rated their classroom attention skills at 65 months. Outcome measures include health behaviors, psychosocial, and academic outcomes at 122 months. Multiple regression analyses were used.
Receptive vocabulary in kindergarten exclusively predicted fourth-grade dietary habits. Unstandardized coefficients predicted decreases in sweet snack intake (ß = -.009, 95% confidence interval [CI] = -.011 to -.006) and dairy product intake (ß = .009, 95% CI = .005 to .013). Conversely, higher kindergarten math skills predicted increases in activities requiring physical effort (ß = .030, 95% CI = .011 to .056). Although vocabulary and attention skills were found important, kindergarten math skills were stronger and more consistent predictors of later academic outcomes.
From a population-health perspective, the skills children bring to the kindergarten classroom might reduce a host of lifestyle risks from childhood through adulthood. Early promotion of such skills also offers possibilities for ultimately reducing later disparities in health and education.
PubMed ID
23445605 View in PubMed
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Climate modelling: Northern Hemisphere circulation.

https://arctichealth.org/en/permalink/ahliterature83246
Source
Nature. 2005 Sep 22;437(7058):496
Publication Type
Article
Date
Sep-22-2005
Author
Gillett Nathan P
Author Affiliation
Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK. n.gillett@uea.ac.uk
Source
Nature. 2005 Sep 22;437(7058):496
Date
Sep-22-2005
Language
English
Publication Type
Article
Keywords
Air Movements
Arctic Regions
Climate
Computer simulation
Europe
Forecasting - methods
Greenhouse Effect
Human Activities
Models, Theoretical
Pressure
Rain
Reproducibility of Results
Abstract
Air pressure at sea level during winter has decreased over the Arctic and increased in the Northern Hemisphere subtropics in recent decades, a change that has been associated with 50% of the Eurasian winter warming observed over the past 30 years, with 60% of the rainfall increase in Scotland and with 60% of the rainfall decrease in Spain. This trend is inconsistent with the simulated response to greenhouse-gas and sulphate-aerosol changes, but it has been proposed that other climate influences--such as ozone depletion--could account for the discrepancy. Here I compare observed Northern Hemisphere sea-level pressure trends with those simulated in response to all the major human and natural climate influences in nine state-of-the-art coupled climate models over the past 50 years. I find that these models all underestimate the circulation trend. This inconsistency suggests that we cannot yet simulate changes in this important property of the climate system or accurately predict regional climate changes.
PubMed ID
16177779 View in PubMed
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A comparison of methods for forecasting emergency department visits for respiratory illness using telehealth Ontario calls.

https://arctichealth.org/en/permalink/ahliterature136543
Source
Can J Public Health. 2010 Nov-Dec;101(6):464-9
Publication Type
Article
Author
Alexander G Perry
Kieran M Moore
Linda E Levesque
C William L Pickett
Michael J Korenberg
Author Affiliation
Kingston, Frontenac and Lennox & Addington Public Health, Kingston, ON. alexander.perry@queensu.ca
Source
Can J Public Health. 2010 Nov-Dec;101(6):464-9
Language
English
Publication Type
Article
Keywords
Emergency Service, Hospital - utilization
Forecasting - methods
Humans
Ontario - epidemiology
Respiratory Tract Diseases - epidemiology - therapy
Surge Capacity - organization & administration
Telemedicine - methods - statistics & numerical data
Abstract
Anticipating increases in hospital emergency department (ED) visits for respiratory illness could help time interventions such as opening flu clinics to reduce surges in ED visits. Five different methods for estimating ED visits for respiratory illness from Telehealth Ontario calls are compared, including two non-linear modeling methods. Daily visit estimates up to 14 days in advance were made at the health unit level for all 36 Ontario health units.
Telehealth calls from June 1, 2004 to March 14, 2006 were included. Estimates generated by regression, Exponentially Weighted Moving Average (EWMA), Numerical Methods for Subspace State Space Identification (N4SID), Fast Orthogonal Search (FOS), and Parallel Cascade Identification (PCI) were compared to the actual number of ED visits for respiratory illness identified from the National Ambulatory Care Reporting System (NACRS) database. Model predictor variables included Telehealth Ontario calls and upcoming holidays/weekends. Models were fit using the first 304 days of data and prediction accuracy was measured over the remaining 348 days.
Forecast accuracy was significantly better (p
PubMed ID
21370782 View in PubMed
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52 records – page 1 of 6.