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.
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.
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Cites: Public Health Genomics. 2010;13(7-8):514-2320484876
Cites: Am J Obstet Gynecol. 2005 Apr;192(4):1023-715846175
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.
Cites: Int J Cancer. 2015 Mar 1;136(5):E359-8625220842
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.
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.
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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.
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.
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.
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.
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.