The productivity of temperate grassland is limited by the response of plants to low temperature, affecting winter persistence and seasonal growth rates. During the winter, the growth of perennial ...grasses is restricted by a combination of low temperature and the lack of available light, but during early spring low ground temperature is the main limiting factor. Once temperature increases, growth is stimulated, resulting in a peak in growth in spring before growth rates decline later in the season. Growth is not primarily limited by the ability to photosynthesize, but controlled by active regulatory processes that, e.g., enable plants to restrict growth and conserve resources for cold acclimation and winter survival. An insufficient ability to cold acclimate can affect winter persistence, thereby also reducing grassland productivity. While some mechanistic knowledge is available that explains how low temperature limits plant growth, the seasonal mechanisms that promote growth in response to increasing spring temperatures but restrict growth later in the season are only partially understood. Here, we assess the available knowledge of the physiological and signaling processes that determine growth, including hormonal effects, on cellular growth and on carbohydrate metabolism. Using data for grass growth in Ireland, we identify environmental factors that limit growth at different times of the year. Ideas are proposed how developmental factors, e.g., epigenetic changes, can lead to seasonality of the growth response to temperature. We also discuss perspectives for modeling grass growth and breeding to improve grassland productivity in a changing climate.
Behaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by ...developing, validating, and applying a multivariable predictive model for risk of all-cause death.
A predictive algorithm for 5 y risk of death-the Mortality Population Risk Tool (MPoRT)-was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model.
The MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 95% CI: 0.867-0.881; females 0.875 0.868-0.882) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation).
Multivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population.
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Risk adjustment and mortality prediction in studies of critical care are usually performed using acuity of illness scores, such as Acute Physiology and Chronic Health Evaluation II (APACHE II), which ...emphasize physiological derangement. Common risk adjustment systems used in administrative datasets, like the Charlson index, are entirely based on the presence of co-morbid illnesses. The purpose of this study was to compare the discriminative ability of the Charlson index to the APACHE II in predicting hospital mortality in adult multisystem ICU patients.
This was a population-based cohort design. The study sample consisted of adult (>17 years of age) residents of the Calgary Health Region admitted to a multisystem ICU between April 2002 and March 2004. Clinical data were collected prospectively and linked to hospital outcome data. Multiple regression analyses were used to compare the performance of APACHE II and the Charlson index.
The Charlson index was a poor predictor of mortality (C = 0.626). There was minimal difference between a baseline model containing age, sex and acute physiology score (C = 0.74) and models containing either chronic health points (C = 0.76) or Charlson index variations (C = 0.75, 0.76, 0.77). No important improvement in prediction occurred when the Charlson index was added to the full APACHE II model (C = 0.808 to C = 0.813).
The Charlson index does not perform as well as the APACHE II in predicting hospital mortality in ICU patients. However, when acuity of illness scores are unavailable or are not recorded in a standard way, the Charlson index might be considered as an alternative method of risk adjustment and therefore facilitate comparisons between intensive care units.
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The objective of this study was to examine the impact of increasing proportions of grazed pasture in the diet on the composition, quality, and functionality of bovine milk across a full lactation. ...Fifty-four spring-calving cows were randomly assigned to 1 of 3 groups (n = 18), blocked on the basis of mean calving date (February 15, 2020 ± 0.8 d), pre-experimental daily milk yield (24.70 ± 3.70 kg), milk solids yield (2.30 ± 0.27 kg), lactation number (3.10 ± 0.13), and economic breeding index (182 ± 19). Raw milk samples were obtained weekly from each group between March and November 2020. Group 1 (GRS) consumed perennial ryegrass and was supplemented with 5% concentrates (dry matter basis); group 2 was maintained indoors and consumed a total mixed ration (TMR) diet consisting of maize silage, grass silage, and concentrates; and group 3 consumed a partial mixed ration diet (PMR), rotating between perennial ryegrass during the day and indoor TMR feeding at night. Raw milk samples consisted of a pooled morning and evening milking and were analyzed for gross composition, free amino acids, fatty acid composition, heat coagulation time, color, fat globule size, and pH. The TMR milks had a significantly higher total solids, lactose, protein, and whey protein as a proportion of protein content compared with both GRS and PMR milks. The GRS milks demonstrated a significantly lower somatic cell count (SCC), but a significantly higher pH and b*-value than both TMR and PMR milks. The PMR milks exhibited significantly lower total solids and fat content, but also demonstrated significantly higher SCC and total free amino acid content compared with GRS and TMR. Partial least squares discriminant analysis of fatty acid profiles displayed a distinct separation between GRS and TMR samples, while PMR displayed an overlap between both GRS and TMR groupings. Variable importance in projection analysis identified conjugated linoleic acid cis-9,trans-11, C18:2n-6 cis, C18:3n-3, C11:0, and C18:2n-6 trans as the largest contributors to the variation between the diets. Milk fats derived from GRS diets exhibited the highest proportion of unsaturated fats and higher unsaturation, health-promoting, and desaturase indices. The lowest proportions of saturated fats and the lowest atherogenic index were also exhibited by GRS-derived milk fats. This work highlights the positive influence of grass-fed milk for human consumption through its more nutritionally beneficial fatty acid profile, despite the highest milk solid percentages derived from TMR feeding systems. Furthermore, this study demonstrates the proportional response of previously highlighted biomarkers of pasture feeding to the proportion of pasture in the cow's diet.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Milk is a highly nutritious food that contains an array of macro and micro components, scientifically proven to be beneficial to human health. While the composition of milk is influenced by a variety ...of factors, such as genetics, health, lactation stage etc., the animal's diet remains a key mechanism by which its nutrition and processing characteristics can be altered. Pasture feeding has been demonstrated to have a positive impact on the nutrient profile of milk, increasing the content of some beneficial nutrients such as Omega-3 polyunsaturated fatty acids, vaccenic acid, and conjugated linoleic acid (CLA), while reducing the levels of Omega-6 fatty acids and palmitic acid. These resultant alterations to the nutritional profile of "Grass-Fed" milk resonate with consumers that desire healthy, "natural", and sustainable dairy products. This review provides a comprehensive comparison of the impact that pasture and non-pasture feeding systems have on bovine milk composition from a nutritional and functional (processability) perspective, highlighting factors that will be of interest to dairy farmers, processors, and consumers.
ABSTRACT BACKGROUND Routinely collected data from large population health surveys linked to chronic disease outcomes create an opportunity to develop more complex risk-prediction algorithms. We ...developed a predictive algorithm to estimate 5-year risk of incident cardiovascular disease in the community setting. METHODS We derived the Cardiovascular Disease Population Risk Tool (CVDPoRT) using prospectively collected data from Ontario respondents of the Canadian Community Health Surveys, representing 98% of the Ontario population (survey years 2001 to 2007; follow-up from 2001 to 2012) linked to hospital admission and vital statistics databases. Predictors included body mass index, hypertension, diabetes, and multiple behavioural, demographic and general health risk factors. The primary outcome was the first major cardiovascular event resulting in hospital admission or death. Death from a noncardiovascular cause was considered a competing risk. RESULTS We included 104 219 respondents aged 20 to 105 years. There were 3709 cardiovascular events and 818 478 person-years follow-up in the combined derivation and validation cohorts (5-year cumulative incidence function, men: 0.026, 95% confidence interval CI 0.025–0.028; women: 0.018, 95% 0.017–0.019). The final CVDPoRT algorithm contained 12 variables, was discriminating (men: C statistic 0.82, 95% CI 0.81–0.83; women: 0.86, 95% CI 0.85–0.87) and was well-calibrated in the overall population (5-year observed cumulative incidence function v. predicted risk, men: 0.28%; women: 0.38%) and in nearly all predefined policy-relevant subgroups (206 of 208 groups). INTERPRETATION The CVDPoRT algorithm can accurately discriminate cardiovascular disease risk for a wide range of health profiles without the aid of clinical measures. Such algorithms hold potential to support precision medicine for individual or population uses. Study registration: ClinicalTrials.gov, no. NCT02267447
The purpose of this study was to assess whether or not the change in coding classification had an impact on diagnosis and comorbidity coding in hospital discharge data across Canadian provinces.
This ...study examined eight years (fiscal years 1998 to 2005) of hospital records from the Hospital Person-Oriented Information database (HPOI) derived from the Canadian national Discharge Abstract Database. The average number of coded diagnoses per hospital visit was examined from 1998 to 2005 for provinces that switched from International Classifications of Disease 9(th) version (ICD-9-CM) to ICD-10-CA during this period. The average numbers of type 2 and 3 diagnoses were also described. The prevalence of the Charlson comorbidities and distribution of the Charlson score one year before and one year after ICD-10 implementation for each of the 9 provinces was examined. The prevalence of at least one of the seventeen Charlson comorbidities one year before and one year after ICD-10 implementation were described by hospital characteristics (teaching/non-teaching, urban/rural, volume of patients).
Nine Canadian provinces switched from ICD-9-CM to ICD-I0-CA over a 6 year period starting in 2001. The average number of diagnoses coded per hospital visit for all code types over the study period was 2.58. After implementation of ICD-10-CA a decrease in the number of diagnoses coded was found in four provinces whereas the number of diagnoses coded in the other five provinces remained similar. The prevalence of at least one of the seventeen Charlson conditions remained relatively stable after ICD-10 was implemented, as did the distribution of the Charlson score. When stratified by hospital characteristics, the prevalence of at least one Charlson condition decreased after ICD-10-CA implementation, particularly for low volume hospitals.
In conclusion, implementation of ICD-10-CA in Canadian provinces did not substantially change coding practices, but there was some coding variation in the average number of diagnoses per hospital visit across provinces.
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Physician chart documentation can facilitate patient care decisions, reduce treatment errors, and inform health system planning and resource allocation activities. Although accurate and complete ...patient chart data supports quality and continuity of patient care, physician documentation often varies in terms of timeliness, legibility, clarity and completeness. While many educational and other approaches have been implemented in hospital settings, the extent to which these interventions can improve the quality of documentation in emergency departments (EDs) is unknown.
We conducted a systematic review to assess the effectiveness of approaches to improve ED physician documentation. Peer reviewed electronic databases, grey literature sources, and reference lists of included studies were searched to March 2015. Studies were included if they reported on outcomes associated with interventions designed to enhance the quality of physician documentation.
Nineteen studies were identified that report on the effectiveness of interventions to improve physician documentation in EDs. Interventions included audit/feedback, dictation, education, facilitation, reminders, templates, and multi-interventions. While ten studies found that audit/feedback, dictation, pharmacist facilitation, reminders, templates, and multi-pronged approaches did improve the quality of physician documentation across multiple outcome measures, the remaining nine studies reported mixed results.
Promising approaches to improving physician documentation in emergency department settings include audit/feedback, reminders, templates, and multi-pronged education interventions. Future research should focus on exploring the impact of implementing these interventions in EDs with and without emergency medical record systems (EMRs), and investigating the potential of emerging technologies, including EMR-based machine-learning, to promote improvements in the quality of ED documentation.
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The increasing availability of large electronic population-based databases offers unique opportunities to conduct cardiovascular health surveillance traditionally done using surveys. We aimed to ...examine cardiovascular risk-factor burden, preventive care, and disease incidence among adults in Ontario, Canada—using routinely collected data—and compare estimates with health survey data.
In the Cardiovascular Health in Ambulatory Care Research Team (CANHEART) initiative, multiple health administrative databases were linked to create a population-based cohort of 10.3 million adults without histories of cardiovascular disease. We examined cardiovascular risk-factor burden and screening and outcomes between 2016 and 2020. Risk- factor burden was also compared with cycles 3 to 5 (2012 to 2017) of the Canadian Health Measures Survey (CMHS), which included 9473 participants across Canada.
Mean age of our study cohort was 47.9 ± 17.0 years, and 52.0% were women. Lipid and diabetes assessment rates among individuals 40 to 79 years were 76.6% and 78.2%, respectively, and lowest among men 40 to 49 years of age. Total cholesterol levels and diabetes and hypertension rates among men and women 20 to 79 years were similar to Canadian Health Measures Survey (CHMS) findings (total cholesterol: 4.80/4.98 vs 4.94/5.25 mmol/L; diabetes: 8.2%/7.1% vs 8.1%/6.0%; hypertension: 21.4%/21.6% vs 23.9%/23.1%, respectively); however, patients in the CANHEART study had slightly higher mean glucose (men: 5.79 vs 5.44; women: 5.39 vs 5.09 mmol/L) and systolic blood pressures (men: 126.2 vs 118.3; women: 120.6 vs 115.7 mm Hg).
Cardiovascular health surveillance is possible through linkage of routinely collected electronic population-based datasets. However, further investigation is needed to understand differences between health administrative and survey measures cross-sectionally and over time.
La disponibilité croissante de vastes bases de données électroniques populationnelles offre des possibilités uniques d’effectuer une surveillance de la santé cardiovasculaire qui aurait été traditionnellement réalisée par des enquêtes. Notre objectif était d’examiner le fardeau des facteurs de risque cardiovasculaire, la prestation de soins de prévention et l’incidence des maladies cardiovasculaires chez des adultes de l’Ontario (Canada) en utilisant les données recueillies systématiquement, et de comparer ces estimations avec celles obtenues avec des données provenant d’enquêtes sur la santé.
Dans le cadre de l’initiative de la Cardiovascular Health in Ambulatory Care Research Team (CANHEART), différentes bases de données de santé de nature administrative ont été liées pour créer une cohorte populationnelle de 10,3 millions d’adultes sans antécédents de maladies cardiovasculaires. Nous avons examiné le fardeau des facteurs de risque cardiovasculaire, ainsi que le dépistage et les résultats de santé cardiovasculaire entre 2016 et 2020. Le fardeau des facteurs de risque a également été comparé aux données des cycles 3 à 5 (de 2012 à 2017) de l’Enquête canadienne sur les mesures de la santé (ECMS), menée auprès de 9 473 personnes au Canada.
L’âge moyen des personnes faisant partie de la cohorte à l’étude était de 47,9 ± 17,0 ans, et 52,0 % étaient des femmes. Les taux d’évaluation des lipides et du statut du diabète chez les personnes âgées de 40 à 79 ans étaient respectivement de 76,6 % et 78,2 %, et ces taux étaient les plus faibles chez les hommes de 40 à 49 ans. Les taux de cholestérol total, de diabète et d’hypertension chez les hommes et les femmes de 20 à 79 ans étaient comparables à ceux rapportés par l’ECMS (cholestérol total : 4,80/4,98 vs 4,94/5,25 mmol/l; diabète : 8,2 %/7,1 % vs 8,1 %/6,0 %; hypertension : 21,4 %/21,6 % vs 23,9 %/23,1 %, respectivement). Par contre, les patients de l’étude CANHEART présentaient des valeurs moyennes légèrement plus élevées pour la glycémie (hommes : 5,79 vs 5,44; femmes : 5,39 vs 5,09 mmol/l) et la pression artérielle systolique (hommes : 126,2 vs 118,3; femmes : 120,6 vs 115,7 mm Hg).
Il est possible d’effectuer une surveillance de la santé cardiovasculaire par l’association d’ensembles de données électroniques recueillies systématiquement à l’échelle des populations. Une investigation plus approfondie reste néanmoins nécessaire pour comprendre les différences entre les mesures provenant des bases de données de santé administratives et celles provenant d’enquêtes, sur le plan transversal et au fil du temps.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose
Sepsis is a considerable health system burden. Population-based epidemiological surveillance of sepsis is limited to basic data available in administrative databases. We sought to determine ...if routinely collected Census data, linked to hospitalization data, can provide a broad socio-demographic profile of patients admitted to Canadian hospitals with sepsis.
Methods
Linking the 2006 long-form Canadian Census (most recent available for linkage) to the Discharge Abstract Data from 2006/2007 to 2008/2009, we created a population-based cohort of approximately 3,433,900 Canadians. Patients admitted to hospital with sepsis were identified using the Canadian Institute for Health Information administrative data definition. Age-standardized hospital admission rates for sepsis were calculated. Multivariable modelling was used to examine the relationship between Census characteristics and hospitalization with sepsis.
Results
Of those individuals successfully linked to the 2006 long-form Canadian Census, 10,400 patients of 18 yr and older were admitted to hospital with sepsis between the fiscal years 2006/2007 and 2008/2009. These individuals represented a weighted count of approximately 49,000 Canadians from all provinces and territories, excluding Quebec. The age-standardized rate of sepsis hospitalization was 96 cases/100,000 population. Of these, 37/100,000 cases were classified as severe sepsis. The association of Census characteristics with sepsis hospitalization varied with age. In all age-specific models, male sex, never being married, visible minority status, having functional limitations, and not being in the labour force were associated with an increased odds of hospital admission.
Conclusions
Census data identified broad socio-demographic risk factors for admission to hospital with sepsis. Consideration should be given to incorporating Census data linked to administrative hospital data in population-based epidemiologic surveillance.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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