The paradoxical influence of the COVID-19 lockdown period on different types of preterm births in Alberta: a provincial study.

Objectives: The objective of this study was to determine if the COVID-19 pandemic impacted different types of preterm birth rates in Alberta, Canada. Methods: A population-based, retrospective, cohort study was conducted from March 15, 2015 to December 31, 2020 using provincial data. The primary exposure was the COVID-19 lockdown period, and the primary outcome was the incidence of preterm birth (<37 weeks gestational age). Multivariable analyses in the complete lockdown and overall lockdown (partial and complete lockdown) periods were performed to test the association between the year of birth and preterm birth status and were adjusted for various independent variables. Preterm birth status was adjusted for various confounding factors. Results: Following the analysis of n = 41,187 mothers and their singleton infants, we found that the lockdown due to COVID-19 had no impact in reducing the overall preterm birth rate. However, a paradoxical influence was observed with an increase of extremely low preterm births in the overall lockdown period, and a decrease in moderate preterm births during the complete lockdown period. Conclusions: The results of this study demonstrated that there was a decrease in moderate and increase in extremely low preterm birth rates as a result of the COVID-19 lockdown. However, the COVID-19 lockdown did not impact the very preterm and late preterm birth rate in Alberta.

Average Lifespan Shortened due to Stroke in Canada: A Nationwide Descriptive Study From 1990 to 2015.

BACKGROUND AND PURPOSE: There are challenges in comparability when using existing life lost measures to examine long-term trends in premature mortality. To address this important issue, we have developed a novel measure termed average lifespan shortened (ALSS). In the present study, we used the ALSS measure to describe temporal changes in premature mortality due to stroke in the Canadian population from 1990 to 2015. METHODS: Mortality data for stroke were obtained from the World Health Organization mortality database. Years of life lost was calculated using Canadian life tables. ALSS was calculated as the ratio of years of life lost in relation to the expected lifespan. RESULTS: Over a 25-year timeframe, the age-standardized rates adjusted to the World Standard Population for deaths from all strokes and stroke types substantially decreased in both sexes. The ALSS measure indicated that men who died of stroke lost 12.1% of their lifespan in 1990 and 11.4% in 2015, whereas these values among women were 11.1% and 10.0%, respectively. Patients with subarachnoid hemorrhagic stroke lost the largest portion whereby both sexes lost about one-third of their lifespan in 1990 and one-fourth in 2015. Men with intracerebral hemorrhagic stroke lost around 18% of their lifespan in 1990 and 14% in 2015 as compared to women who lost about 16% and 12% over the same timeframe. The loss of lifespan for patients with ischemic stroke and other stroke types combined was relatively stable at about 10% throughout the study period. CONCLUSIONS: Our study demonstrated a modest improvement in lifespan among patients with stroke in Canada between 1990 and 2015. Our novel ALSS measure provides intuitive interpretation of temporal changes in lifespan among patients with stroke and helps to enhance our understanding of the burden of strokes in the Canadian population.

Premature Mortality Due to Malignancies of the Central Nervous System in Canada, 1980-2010.

BACKGROUND: In this study, we investigated whether there has been an improvement in premature mortality due to central nervous system (CNS) cancers among the Canadian population from 1980 through 2010. METHODS: Mortality data for CNS cancers were obtained from World Health Organization mortality database. Years of life lost (YLL) was estimated using Canadian life tables. Average lifespan shortened (ALSS) was calculated and defined as the ratio of YLL relative to the expected lifespan. RESULTS: Over this study period, we observed decreases in age standardized rates to the World Standard Population for mortality due to CNS cancers from 5.3 to 4.1 per 100,000 men, and from 3.6 to 2.9 per 100,000 women. Average YLL decreased from 23.6 to 21.5 years of life among men, and from 27.0 to 23.1 years among women in 1980 and 2010, respectively. The ALSS showed that men with CNS cancers lost 30.1% of their life span and women lost 32.5% in 1980, whereas they lost 25.8 and 26.6% in 2010, respectively. CONCLUSION: Our study shows that -Canadian people with CNS cancers have had their lives prolonged at the end of the study period.

Premature mortality due to breast cancer among Canadian women: an analysis of a 30-year period from 1980 through 2010.

Background: Breast cancer is the most commonly diagnosed cancer and the second most common cause of cancer deaths for women. In the present study, we examined the trend of premature mortality due to breast cancer among Canadian women from 1980 through 2010 and proposed a new measure of lifespan shortening. Methods: Mortality data for female breast cancer was obtained from the World Health Organization mortality database. Years of life lost (YLL) was estimated using Canadian life tables. Average lifespan shortened (ALSS) that is calculated and expressed by a ratio of YLL relative to expected lifespan. Results: Over this study period, age-standardized rates of breast cancer mortality adjusted to World Standard Population decreased by 40% from 23.2 to 14.2 per 100 000 women. The adjusted YLL rates fell from 5.3 years per 1000 women to 3.3 years. On average women with breast cancer died 20.8 years prior to expected death in 1980 and 18.3 years early in 2010. A novel measure of lifespan shortening, the ALSS decreased from one-fourth of the lifespan in 1980 to one-fifth in 2010. Conclusions: Our study reports that among Canadian women with breast cancer, a smaller proportion of life was lost on average at the end of the study period. The 'life lost' measures presented in this study would be useful tools to monitor the pattern of premature mortality for chronic conditions. These measures gauge the effectiveness of the health system with respect to early detection and treatment.

Factors associated with mode of colorectal cancer detection and time to diagnosis: a population level study.

BACKGROUND: Although it is well-known that early detection of colorectal cancer (CRC) is important for optimal patient survival, the relationship of patient and health system factors with delayed diagnosis are unclear. The purpose of this study was to identify the demographic, clinical and healthcare factors related to mode of CRC detection and length of the diagnostic interval. METHODS: All residents of Alberta, Canada diagnosed with first-ever incident CRC in years 2004-2010 were identified from the Alberta Cancer Registry. Population-based administrative health datasets, including hospital discharge abstract, ambulatory care classification system and physician billing data, were used to identify healthcare services related to CRC diagnosis. The time to diagnosis was defined as the time from the first CRC-related healthcare visit to the date of CRC diagnosis. Mode of CRC detection was classified into three groups: urgent, screen-detected and symptomatic. Quantile regression was performed to assess factors associated with time to diagnosis. RESULTS: 9626 patients were included in the study; 25% of patients presented as urgent, 32% were screen-detected and 43% were symptomatic. The median time to diagnosis for urgent, screen-detected and symptomatic patients were 6 days (interquartile range (IQR) 2-14 days), 74 days (IQR 36-183 days), 84 days (IQR 39-223 days), respectively. Time to diagnosis was greater than 6 months for 27% of non-urgent patients. Healthcare factors had the largest impact on time to diagnosis: 3 or more visits to a GP increased the median by 140 days whereas 2 or more visits to a GI-specialist increased it by 108 days compared to 0-1 visits to a GP or GI-specialist, respectively. CONCLUSION: A large proportion of CRC patients required urgent work-up or had to wait more than 6 months for diagnosis. Actions are needed to reduce the frequency of urgent presentation as well as improve the timeliness of diagnosis. Findings suggest a need to improve coordination of care across multiple providers.

Real-world evidence of sotrovimab effectiveness for preventing severe outcomes in patients with COVID-19: A quality improvement propensity matched retrospective cohort study of a pan-provincial program in Alberta, Canada.

OBJECTIVE: Post-marketing surveillance of sotrovimab's effect during implementation in the Canadian population is limited. METHODS: The study used a propensity score matched retrospective cohort design. Follow-up began between the periods of December 15, 2021 to April 30 2022. The study assessed any severe outcome defined as all-cause hospital admission, or mortality within 30 days of a confirmed COVID-19 positive test. Covariate adjusted odds ratios between sotrovimab treatment and the severe outcome was conducted using logistic regression. RESULTS: There were 22,289 individuals meeting treatment criteria for sotrovimab. There were 1,603 treated and 6,299 untreated individuals included in the analysis. Outcome occurrence in the study was 5.49% (treated) and 4.21% (untreated), with a median time from diagnosis to treatment of 1.00 days (IQR = 2.00 days). In the propensity-matched cohort, sotrovimab was not associated with a lower odds of a severe outcome (OR = 1.20; 95% CI: 0.91, 1.58), adjusting for confounding variables. CONCLUSION: After adjusting for confounding variables, sotrovimab treatment was not associated with lower odds of a severe outcome within 30-days of COVID-19 positive date.

Long-term health care use and diagnosis after hospitalization for COVID-19: a retrospective matched cohort study.

BACKGROUND: Knowledge pertaining to the health and health care utilization of patients after recovery from acute COVID-19 is limited. We sought to assess the frequency of new diagnoses of disease and health care use after hospitalization with COVID-19. METHODS: We included all patients hospitalized with COVID-19 in Alberta between Mar. 5 and Dec. 31, 2020. Additionally, 2 matched controls (SARS-CoV-2 negative) per case were included and followed up until Apr. 30, 2021. New diagnoses and health care use were identified from linked administrative health data. Repeated measures were made for the periods 1-30 days, 31-60 days, 61-90 days, 91-180 days, and 180 and more days from the index date. We used multivariable regression analysis to evaluate the association of COVID-19-related hospitalization with the number of physician visits during follow-up. RESULTS: The study sample included 3397 cases and 6658 controls. Within the first 30 days of follow-up, the case group had 37.12% (95% confidence interval [CI] 35.44% to 38.80%) more patients with physician visits, 11.12% (95% CI 9.77% to 12.46%) more patients with emergency department visits and 2.92% (95% CI 2.08% to 3.76%) more patients with hospital admissions than the control group. New diagnoses involving multiple organ systems were more common in the case group. Regression results indicated that recovering from COVID-19-related hospitalization, admission to an intensive care unit, older age, greater number of comorbidities and more prior health care use were associated with increased physician visits. INTERPRETATION: Patients recovered from the acute phase of COVID-19 continued to have greater health care use up to 6 months after hospital discharge. Research is required to further explore the effect of post-COVID-19 conditions, pre-existing health conditions and health-seeking behaviours on health care use.

A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population.

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta's Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy.

Adverse drug reactions in elderly hospitalized patients: a 12-year population-based retrospective cohort study.

BACKGROUND: Although research has identified some risk factors for first-time adverse drug reactions (ADRs), little is known about the risks associated with the number of ADRs. Modeling ADR counts is relatively complex because of the rarity of the events, requiring careful consideration of appropriate models that best present the observed data. OBJECTIVE: To determine the incidence of ADRs among elderly hospitalized patients, assess patient-related risk factors for the number of ADRs, and review drug classes commonly responsible for ADRs. METHODS: This retrospective cohort study used a population-based large administrative database on hospital separations from all acute care hospitals in the Canadian province of Newfoundland and Labrador. Patients aged 65 years or older with at least 1 hospital admission from April 1, 1995, to March 31, 2007, were included. Comorbidities, Charlson Comorbidity Index (CCI), and sociodemographic factors were assessed as predictors of ADR counts. A zero-inflated negative binomial regression model was used for analysis. RESULTS: The study cohort contained 64,446 patients. The incidence of ADRs was 15.2 per 1000 person-years (95% CI 14.8 to 15.7). Of those having an ADR, 15.4% had recurrent ADRs. The most common drug category implicated in ADRs was cardiovascular agents (17.7%). A dose-response relationship was found between CCI and ADR counts (rate ratio [RR] 1.67, 95% CI 1.41 to 1.98 for CCI 2-3; RR 2.38, 95% CI 1.98 to 2.87 for CCI 4-5; and RR 3.83, 95% CI 3.21-4.57 for CCI ≥6). Comorbid conditions including congestive heart failure (RR 1.58, 95% CI 1.33 to 1.89), diabetes (RR 2.42, 95% CI 1.64 to 3.56), and cancer (RR 3.12, 95% CI 2.58 to 3.76) were strong predictors. Rural areas (RR 1.22, 95% CI 1.01 to 1.46) were associated with increased risk for ADRs, whereas age and sex had no effect. CONCLUSIONS: Comorbidity from chronic diseases and severity of illness, rather than individual characteristics (advancing age and sex), increased the likelihood of ADRs. Changes in the delivery of care focusing on the monitoring of prescribed drugs in elderly patients with comorbidities could mitigate ADRs.

Predicting the Risk Factors Associated With Severe Outcomes Among COVID-19 Patients-Decision Tree Modeling Approach.

Background: The COVID-19 pandemic has seen a large surge in case numbers over several waves, and has critically strained the health care system, with a significant number of cases requiring hospitalization and ICU admission. This study used a decision tree modeling approach to identify the most important predictors of severe outcomes among COVID-19 patients. Methods: We identified a retrospective population-based cohort (n = 140,182) of adults who tested positive for COVID-19 between 5th March 2020 and 31st May 2021. Demographic information, symptoms and co-morbidities were extracted from a communicable disease and outbreak management information system and electronic medical records. Decision tree modeling involving conditional inference tree and random forest models were used to analyze and identify the key factors(s) associated with severe outcomes (hospitalization, ICU admission and death) following COVID-19 infection. Results: In the study cohort, nearly 6.37% were hospitalized, 1.39% were admitted to ICU and 1.57% died due to COVID-19. Older age (>71Y) and breathing difficulties were the top two factors associated with a poor prognosis, predicting about 50% of severe outcomes in both models. Neurological conditions, diabetes, cardiovascular disease, hypertension, and renal disease were the top five pre-existing conditions that altogether predicted 29% of outcomes. 79% of the cases with poor prognosis were predicted based on the combination of variables. Age stratified models revealed that among younger adults (18-40 Y), obesity was among the top risk factors associated with adverse outcomes. Conclusion: Decision tree modeling has identified key factors associated with a significant proportion of severe outcomes in COVID-19. Knowledge about these variables will aid in identifying high-risk groups and allocating health care resources.

Development and validation of a hypertension risk prediction model and construction of a risk score in a Canadian population.

Identifying high-risk individuals for targeted intervention may prevent or delay hypertension onset. We developed a hypertension risk prediction model and subsequent risk sore among the Canadian population using measures readily available in a primary care setting. A Canadian cohort of 18,322 participants aged 35-69 years without hypertension at baseline was followed for hypertension incidence, and 625 new hypertension cases were reported. At a 2:1 ratio, the sample was randomly divided into derivation and validation sets. In the derivation sample, a Cox proportional hazard model was used to develop the model, and the model's performance was evaluated in the validation sample. Finally, a risk score table was created incorporating regression coefficients from the model. The multivariable Cox model identified age, body mass index, systolic blood pressure, diabetes, total physical activity time, and cardiovascular disease as significant risk factors (p < 0.05) of hypertension incidence. The variable sex was forced to enter the final model. Some interaction terms were identified as significant but were excluded due to their lack of incremental predictive capacity. Our model showed good discrimination (Harrel's C-statistic 0.77) and calibration (Grønnesby and Borgan test, [Formula: see text] statistic = 8.75, p = 0.07; calibration slope 1.006). A point-based score for the risks of developing hypertension was presented after 2-, 3-, 5-, and 6 years of observation. This simple, practical prediction score can reliably identify Canadian adults at high risk of developing incident hypertension in the primary care setting and facilitate discussions on modifying this risk most effectively.

Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis.

OBJECTIVE: We aimed to identify existing hypertension risk prediction models developed using traditional regression-based or machine learning approaches and compare their predictive performance. METHODS: We systematically searched MEDLINE, EMBASE, Web of Science, Scopus, and the grey literature for studies predicting the risk of hypertension among the general adult population. Summary statistics from the individual studies were the C-statistic, and a random-effects meta-analysis was used to obtain pooled estimates. The predictive performance of pooled estimates was compared between traditional regression-based models and machine learning-based models. The potential sources of heterogeneity were assessed using meta-regression, and study quality was assessed using the PROBAST (Prediction model Risk Of Bias ASsessment Tool) checklist. RESULTS: Of 14,778 articles, 52 articles were selected for systematic review and 32 for meta-analysis. The overall pooled C-statistics was 0.75 [0.73-0.77] for the traditional regression-based models and 0.76 [0.72-0.79] for the machine learning-based models. High heterogeneity in C-statistic was observed. The age (p = 0.011), and sex (p = 0.044) of the participants and the number of risk factors considered in the model (p = 0.001) were identified as a source of heterogeneity in traditional regression-based models. CONCLUSION: We attempted to provide a comprehensive evaluation of hypertension risk prediction models. Many models with acceptable-to-good predictive performance were identified. Only a few models were externally validated, and the risk of bias and applicability was a concern in many studies. Overall discrimination was similar between models derived from traditional regression analysis and machine learning methods. More external validation and impact studies to implement the hypertension risk prediction model in clinical practice are required.

Incidence of Pregnancy-Associated Cancer in Two Canadian Provinces: A Population-Based Study.

Pregnancy-associated cancer-that is diagnosed in pregnancy or within 365 days after delivery-is increasingly common as cancer therapy evolves and survivorship increases. This study assessed the incidence and temporal trends of pregnancy-associated cancer in Alberta and Ontario-together accounting for 50% of Canada's entire population. Linked data from the two provincial cancer registries and health administrative data were used to ascertain new diagnoses of cancer, livebirths, stillbirths and induced abortions among women aged 18-50 years, from 2003 to 2015. The annual crude incidence rate (IR) was calculated as the number of women with a pregnancy-associated cancer per 100,000 deliveries. A nonparametric test for trend assessed for any temporal trends. In Alberta, the crude IR of pregnancy-associated cancer was 156.2 per 100,000 deliveries (95% CI 145.8-166.7), and in Ontario, the IR was 149.4 per 100,000 deliveries (95% CI 143.3-155.4). While no statistically significant temporal trend in the IR of pregnancy-associated cancer was seen in Alberta, there was a rise in Ontario (p = 0.01). Pregnancy-associated cancer is common enough to warrant more detailed research on maternal, pregnancy and child outcomes, especially as cancer therapies continue to evolve.

Adverse drug events in adult patients leading to emergency department visits.

BACKGROUND: Adverse drug events (ADEs) occurring in the community and treated in emergency departments (EDs) have not been well studied. OBJECTIVE: To determine the prevalence, severity, and preventability of ADEs in patients presenting at EDs in 2 university-affiliated tertiary care hospitals in the Canadian province of Newfoundland and Labrador. METHODS: A retrospective chart review was conducted on a stratified random sample (n = 1458) of adults (> or =18 y) who presented to EDs from January 1 to December 31, 2005. Prior to the chart review, the sample frame was developed by first eliminating visits that were clearly not the result of an ADE. The ED summary of each patient was initially reviewed by 2 trained reviewers in order to identify probable ADEs. All eligible charts were subsequently reviewed by a clinical team, consisting of 2 pharmacists and 2 ED physicians, to identify ADEs and determine their severity and preventability. RESULTS: Of the 1458 patients presenting to the 2 EDs, 55 were determined to have an ADE or a possible ADE (PADE). After a sample-weight adjustment, the prevalence of ADEs/PADEs was found to be 2.4%. Prevalence increased with age (0.7%, 18-44 y; 1.9%, 45-64 y; 7.8%, > or =65 y) and the mean age for patients with ADEs was higher than for those with no ADEs (69.9 vs 63.8 y; p < 0.01). A higher number of comorbidities and medications was associated with drug-related visits. Approximately 29% of the ADEs/PADEs identified were considered to be preventable, with 42% requiring hospitalization. Cardiovascular agents (37.4%) were the most common drug class associated with ADEs/PADEs. CONCLUSIONS: Adult ADE-related ED visits are frequent in Newfoundland and Labrador, and in many cases are preventable. Further efforts are needed to reduce the occurrence of preventable ADEs leading to ED visits.

Adverse drug events among children presenting to a hospital emergency department in Newfoundland and Labrador, Canada.

OBJECTIVES: The aim of this study was to examine epidemiologic characteristics of Adverse Drug Events (ADEs) among children and adolescents presenting to an Emergency Department (ED) in Newfoundland and Labrador (NL), Canada. MATERIALS AND METHODS: This study was conducted in three phases and included an ED chart review of visits to the Janeway Hospital in St. John's, NL, between 27th April 2006 and 26th April 2007. The first phase narrowed the sampling frame by excluding visits highly unlikely to be drug-related. In the second phase, a random sample of ED charts was selected for review by two research nurses using a Trigger Assessment Tool that classified ED visits according to their likelihood of being drug related ('high', 'moderate', 'low', 'very low', or 'no' probability). The third phase included a full chart review of all 'high', 'moderate', 'low', and 'very low' probability ADE charts, carried out independently by two ED pediatricians and two clinical pharmacists. Each ADE was also scored for severity and preventability, and consensus was reached among all four reviewers during meetings held at the end of this phase. RESULTS: In this study, 69 patients presented to the ED either due to an ADE or a possible ADE (PADE). After a sample-weight adjustment, the prevalence of ADEs/PADEs was found to be 2.1%. The number of co-morbidities was inversely associated with medication-related visits. There was no significant difference found between patients with and without medication related visits with respect to mean age of the patient and the mean number of current medications being taken. Of the 69 confirmed ADE/PADEs, none were fatal, six (8.7%) were serious/life-threatening, and 63 (91.3%) were considered significant. Antimicrobial agents (45.0%) were the most common drug classes associated with ADEs/PADEs. Approximately 20% of the 69 ADEs/PADEs identified were considered preventable. CONCLUSIONS: In St. John's NL, emergency department visits as a result of ADEs are common among the pediatric population and in many cases preventable. Age and number of current medications do not appear to be associated with ED visits related with ADE. Antimicrobial agents were found to be to the cause of most ADEs/PADEs.

Diabetes and its impact on health-related quality of life: a life table analysis.

PURPOSE: To investigate the health burden of diabetes and determine its impact on health-related quality of life (HRQOL) in a population with a high prevalence of chronic conditions. METHODS: A representative sample of the Canadian province of Newfoundland and Labrador (NL) was used to estimate prevalence of diabetes and mean health utility index (HUI), a utility-based measure of HRQOL. Diabetes-deleted life expectancy (LE) and health-adjusted life expectancy (HALE) were derived to measure HRQOL. RESULTS: Diabetic individuals comprised 6.8% of the sample and accounted for 14% of total deaths from 2001 to 2005. Life Expectancy at age 15 was 61.3 years for men and 66.7 years for women, of which 53.0 and 57.0 years, respectively, were spent with perfect health (86.4 and 85.5%). Eliminating diabetes would extend both the overall LE and HALE for men by 1.3 and 1.4 years, and women by 2.0 and 1.7 years, respectively. People with diabetes had a significantly lower HRQOL than people without diabetes (mean HUI: 0.78 vs. 0.88, P < 0.01). CONCLUSION: The burden of illness from diabetes in NL is considerable. Using cause-eliminated LE and HALE provides a robust approach for assessing HRQOL that may have important implications for diabetes surveillance, prevention, and management strategies.

Unintentional injuries among children and adolescents in Aboriginal and non-Aboriginal communities, Newfoundland and Labrador, Canada.

OBJECTIVES: To compare epidemiologic characteristics of unintentional injuries among children and adolescents in Aboriginal and non-Aboriginal communities in the Province of Newfoundland and Labrador (NL), Canada. STUDY DESIGN: A comparative population-based study of unintentional injuries among individuals 0-19 years was conducted among Aboriginal and non-Aboriginal communities in NL. METHODS: The provincial hospital discharge and mortality data were analyzed for a 6-year period, April 1995 to March 2001. Rates and rate ratios related to hospital discharge and mortality due to unintentional injuries were calculated to assess variation of rates. The 2-independent sample binomial proportion test was used to compare rates between Aboriginal and non-Aboriginal communities. RESULTS: The overall hospital discharge rates of unintentional injury in Aboriginal and non-Aboriginal communities were 1,132.0 and 614.2 per 100,000 population, respectively (p(2)<0.001). For both Aboriginal and non-Aboriginal communities, the rate among males was higher than that of females (p(2)<0.001). The mortality rate was found to be higher in Aboriginal communities than non-Aboriginal communities (84.3 vs. 10.2 per 100,000 population) (p(2)<0.001). CONCLUSIONS: The rate of unintentional injury among children and adolescents in Aboriginal communities is higher than non-Aboriginal communities. Sex (male) and place of residence (Aboriginal communities) were strong predictors of unintentional injury in NL.

Summarising and synthesising regression coefficients through systematic review and meta-analysis for improving hypertension prediction using metamodelling: protocol.

INTRODUCTION: Hypertension is one of the most common medical conditions and represents a major risk factor for heart attack, stroke, kidney disease and mortality. The risk of progression to hypertension depends on several factors, and combining these risk factors into a multivariable model for risk stratification would help to identify high-risk individuals who should be targeted for healthy behavioural changes and/or medical treatment to prevent the development of hypertension. The risk prediction models can be further improved in terms of accuracy by using a metamodel updating technique where existing hypertension prediction models can be updated by combining information available in existing models with new data. A systematic review and meta-analysis will be performed of hypertension prediction models in order to identify known risk factors for high blood pressure and to summarise the magnitude of their association with hypertension. METHODS AND ANALYSIS: MEDLINE, Embase, Web of Science, Scopus and grey literature will be systematically searched for studies predicting the risk of hypertension among the general population. The search will be based on two key concepts: hypertension and risk prediction. The summary statistics from the individual studies will be the regression coefficients of the hypertension risk prediction models, and random-effect meta-analysis will be used to obtain pooled estimates. Heterogeneity and publication bias will be assessed, along with study quality, which will be assessed using the Prediction Model Risk of Bias Assessment Tool checklist. ETHICS AND DISSEMINATION: Ethics approval is not required for this systematic review and meta-analysis. We plan to disseminate the results of our review through journal publications and presentations at applicable platforms.

Premature deaths due to head and neck cancers in canada: A nationwide analysis from 1980 to 2010.

OBJECTIVES/HYPOTHESIS: To examine if there has been a reduction in premature mortality due to head and neck cancers and their subtypes in the Canadian population between 1980 and 2010. STUDY DESIGN: Retrospective database review. METHODS: Mortality data for head and neck cancers were obtained from the World Health Organization's mortality database. Years of life lost (YLL) was calculated according to Canadian life tables. A new measure, average lifespan shortened (ALSS), was calculated as a ratio of YLL over the expected lifespan. RESULTS: During the period of interest, decreases in age standardized rates of death adjusted to the World Standard Population were observed mainly among men. The adjusted YLL rates remained unchanged with respect to oral cancers in women, but slightly decreased for oral cancers in men and for laryngeal cancers in both sexes. Our new measure of ALSS showed that in 1980, patients with oral cancers lost an average of 20% of their lifespan, whereas in 2010, men and women still lost approximately 20% and 18%, respectively. Patients with laryngeal cancers lost 18% of their lifespan in both sexes in 1980 and 17% in 2010. The ALSS subanalysis showed that the largest gain of lifespan was observed for cancers of the hypopharynx in men and for cancers of the floor of mouth and nasopharynx in women. CONCLUSIONS: There appears to be modest improvements in premature mortality due to head and neck cancers in Canada over a 30-year period, with the exception of oral cancers in men. Changes in premature mortality varied slightly by cancer subtypes. LEVEL OF EVIDENCE: NA Laryngoscope, 130:911-917, 2020.

Hospital safety among neurologic patients: A population-based cohort study of adverse events.

OBJECTIVE: To examine the frequency and type of adverse events (AEs) experienced by neurologic patients in hospital. METHODS: This population-based, retrospective cohort study used hospital discharge abstract data for children and adults admitted to hospital from 2009 to 2015 with 1 of 9 neurologic conditions (Alzheimer disease and related dementia, brain tumor, epilepsy, motor neuron disease, multiple sclerosis, parkinsonism/Parkinson disease, spinal cord injury, traumatic brain injury, and stroke). Neurologic conditions were identified with ICD-10-CA codes. Eighteen AEs were examined with ICD-10-CA codes. The proportion of AEs was calculated, and regression analysis was used to examine factors and outcomes associated with AEs (age, sex, comorbidity, length of stay, and mortality). RESULTS: The overall proportion of admissions associated with an AE among those with a neurologic condition was 11 per 100 admissions. Those with a spinal cord injury had the highest proportion of AEs (39.4 per 100 admissions). The most common AEs were infections and respiratory complications (32.0% and 16.7%, respectively). Age and the presence of comorbidities were associated with higher odds of an AE, while readmission was associated with lower odds of an AE. Having an AE was associated with increased length of stay and higher odds of mortality. CONCLUSIONS: This study demonstrates that neurologic patients have a high proportion of AEs in hospital. The findings provide information on the quality and safety of care for people with neurologic conditions in hospital, which can help inform future quality improvement initiatives.