Background/Aims: The risk factors for pituitary hormone dysfunction (PHD) in children with optic nerve hypoplasia (ONH) are not well understood. This study identified the type, timing, and predictors of PHD in children with ONH. Methods: ONH patient charts were reviewed retrospectively. The incidence rate of PHD was calculated assuming a Poisson distribution. Predictors of PHD were identified through a multivariable Cox proportional hazards model. Results: Among 144 subjects with ONH, 49.3% (n = 71) developed PHD over 614.7 person-years of follow-up. The incidence was 11.55 (95% confidence interval [CI]: 9.02–14.57/100 person-years). The median time to first PHD was 2.88 (interquartile range: 0.02–18.72) months. Eighty-two percent developed their first PHD by their 5th and 90% by their 10th birthday, and 89% within 5 years of ONH diagnosis. Prematurity (adjusted hazard ratio [aHR]: 0.33; 95% CI: 0.1–1.07), blindness (aHR: 1.72; 95% CI: 1.03–2.86), maternal substance abuse (aHR: 1.51; 95% CI: 0.91–2.48), abnormal posterior pituitary (aHR: 3.8; 95% CI: 2.01–7.18), and hypoplastic/absent anterior pituitary (aHR: 2.52; 95% CI: 1.29–4.91) were significant predictors of PHD. Conclusions:The clinical predictors of PHD included blindness, pituitary gland abnormalities, and maternal substance abuse. These predictors help clinical decision-making related to the need for and frequency of hormone testing in pediatric patients with ONH.
People remain at risk of reinfection with hepatitis C virus (HCV), even after clearance of the primary infection. We identified factors associated with HCV reinfection risk in a large population-based cohort study in British Columbia, Canada, and examined the association of opioid substitution therapy and mental health counselling with reinfection.
We obtained data from the British Columbia Hepatitis Testers Cohort, which includes all individuals tested for HCV or HIV at the British Columbia Centre for Disease Control Public Health Laboratory during 1990–2013 (when data were available). We defined cases of HCV reinfection as individuals with a positive HCV PCR test after either spontaneous clearance (two consecutive negative HCV PCR tests spaced ≥28 days apart without treatment) or a sustained virological response (SVR; two consecutive negative HCV PCR tests spaced ≥28 days apart 12 weeks after completing interferon-based treatment). We calculated incidence rates of HCV reinfection (per 100 person-years of follow-up) and corresponding 95% CIs assuming a Poisson distribution, and used a multivariable Cox proportional hazards model to examine reinfection risk factors (age, birth cohort, sex, year of HCV diagnosis, HCV clearance type, HIV co-infection, number of mental health counselling visits, levels of material and social deprivation, and alcohol and injection drug use), and the association of opioid substitution therapy and mental health counselling with HCV reinfection among people who inject drugs (PWID).
5915 individuals with HCV were included in this study after clearance (3690 after spontaneous clearance and 2225 after SVR). 452 (8%) patients developed reinfection; 402 (11%) after spontaneous clearance and 50 (2%) who had achieved SVR. Individuals were followed up for a median of 5·4 years (IQR 2·9–8·7), and the median time to reinfection was 3·0 years (1·5–5·4). The overall incidence rate of reinfection was 1·27 (95% CI 1·15–1·39) per 100 person-years of follow-up over a total of 35 672 person-years, with significantly higher rates in the spontaneous clearance group (1·59, 1·44–1·76) than in the SVR group (0·48, 0·36–0·63). With the adjusted Cox proportional hazards model, we noted higher reinfection risks in the spontaneous clearance group (adjusted hazard ratio [HR] 2·71, 95% CI 2·00–3·68), individuals co-infected with HIV (2·25, 1·78–2·85), and PWID (1·53, 1·21–1·92) than with other reinfection risk factors. Among the 1604 PWID with a current history of injection drug use, opioid substitution therapy was significantly associated with a lower risk of reinfection (adjusted HR 0·73, 95% CI 0·54–0·98), as was engagement with mental health counselling services (0·71, 0·54–0·92).
The incidence of HCV reinfection was higher among HIV co-infected individuals, those who spontaneously cleared HCV infection, and PWID. HCV treatment complemented with opioid substitution therapy and mental health counselling could reduce HCV reinfection risk among PWID. These findings support policies of post-clearance follow-up of PWID, and provision of harm-reduction services to minimise HCV reinfection and transmission.
Summary Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries—Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NCDs) comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22·7% (21·5–23·9), representing an additional 7·61 million (7·20–8·01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7·9% (7·0–8·8). The number of deaths for CMNN causes decreased by 22·2% (20·0–24·0) and the death rate by 31·8% (30·1–33·3). Total deaths from injuries increased by 2·3% (0·5–4·0) between 2007 and 2017, and the death rate from injuries decreased by 13·7% (12·2–15·1) to 57·9 deaths (55·9–59·2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000–289 000) globally in 2007 to 352 000 (334 000–363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118·0% (88·8–148·6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36·4% (32·2–40·6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33·6% (31·2–36·1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respiratory infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990—neonatal disorders, lower respiratory infections, and diarrhoeal diseases—were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Funding Bill & Melinda Gates Foundation.
Direct-acting antiviral therapies (DAA) are an important tool for hepatitis C virus (HCV) elimination. However, reinfection among people who inject drugs (PWID) may hamper elimination targets. We therefore estimated HCV reinfection rates among DAA-treated individuals, including PWIDs.
We analyzed data from the BC Hepatitis Testers Cohort which included ∼1.7 million individuals screened for HCV in British Columbia, Canada. We followed HCV-infected individuals treated with DAAs who achieved a sustained virologic response (SVR) and had ≥1 subsequent HCV RNA measurement to April 22nd, 2018. Reinfection was defined as a positive RNA measurement after SVR. PWIDs were identified using a validated algorithm and classified based on recent (<3 years) or former (≥3 years before SVR) use. Crude reinfection rates per 100 person-years (PYs) were calculated. Poisson regression was used to model adjusted incidence rate ratios (IRRs) and 95% confidence intervals (CI).
Of 4,114 individuals who met inclusion, most were male (n=2,692, 65%), born before 1965 (n=3,411, 83%) and were either recent (n=875, 21%) or former PWIDs (n=1,793, 44%). Opioid-agonist therapy (OAT) was observed in 19% of PWIDs. We identified 40 reinfections during 2,767 PYs. Reinfection rates were higher among recent (3.1/100 PYs; IRR: 6.7, 95% CI: 1.9, 23.5) and former PWIDs (1.4/100 PYs; IRR: 3.7, 95% CI: 1.1, 12.9) than non-PWIDs (0.3/100 PYs). Among recent PWIDs, reinfection rates were higher among individuals born after 1975 (10.2/100 PYs) and those with co-infected with HIV (5.7/100 PYs). Only one PWID receiving daily OAT developed reinfection.
Population-level reinfection rates remain elevated after DAA therapy among PWIDs because of ongoing exposure risk. Engagement of PWIDs in harm-reduction and support services is needed to prevent reinfections.
We estimated HCV reinfection rates after successful treatment with direct-acting antiviral therapies. Our findings showed that the risk of reinfection was highest among people with recent injection drug use. Among people who inject drugs, daily use of opioid-agonist therapy was associated with a lower risk of reinfection.
To access care, pediatric type 1 diabetes (T1D) patients living in British Columbia (BC), Canada, travel to the sole tertiary pediatric hospital (BC Children's Hospital; BCCH), or they receive community care from pediatric endocrinologists and/or pediatricians. We sought to determine whether HbA1C and patient reported outcomes were associated with (i) distance to clinic and (ii) tertiary vs. community care.
Patients were recruited from T1D clinics across BC. Clinical chart review and patient surveys were completed, including the Diabetes Treatment Satisfaction Questionnaire (DTSQ). Clinic type was categorized as tertiary (BCCH) or community, and travel time to BCCH was categorized as <1 hour (h), 1-2h, or >2h.
There were 189 participants. Age and duration of T1D were similar across groups. Mean number of visits/year for BCCH groups were 2.23, 2.24 and 2.05 for the <1h, 1-2h and >2h groups, respectively, vs. 3.26 for the community group. Adjusted mean difference in HbA1C was +0.65% (95% CI 0.15, 1.15) and +0.52% (95% CI 0.02, 1.02) for the BCCH >2h group compared to BCCH <1h group and community group, respectively. Child DTSQ scores were significantly lower in the BCCH >2h group compared to the BCCH <1h and community groups.
Children travelling >2h to T1D clinic at BCCH had significantly higher HbA1C values and lower satisfaction with care versus those travelling <1h to BCCH and those receiving community care. Access to care closer to home may benefit glycemic control in children with T1D and improve treatment satisfaction. Future research should determine whether these findings can be replicated in other regions. This article is protected by copyright. All rights reserved.
Introduction Behavioural and cognitive behavioural programmes are commonly used to assist with weight management, but there is considerable scope to improve their effectiveness, particularly in the longer term. Third-wave cognitive behaviour therapies (CBTs) have this potential and are increasingly used. This systematic review will assess the effect of third-wave CBTs for weight management on weight, psychological and physical health outcomes in adults with overweight or obesity.Methods and analysis The systematic review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidance. We will include studies of any third-wave CBTs focusing on weight loss or weight maintenance for adults with a body mass index (BMI) >=25kg/m2. Eligible study designs will be randomised control trials, non-randomised trials, prospective cohort and case series. Outcomes of interest will be body weight/BMI, psychological and physical health, and adherence. We will search the following databases from inception to 16 January 2018: MEDLINE, CINAHL, Embase, Cochrane database (CENTRAL), PsycINFO, AMED, ASSIA and Web of Science. The search strategy will be based on the concepts: (1) third-wave CBTs and (2) overweight, obesity or weight management. No restrictions will be applied. We will search reference lists of relevant reviews and included articles. Two independent reviewers will screen articles for eligibility using a two-stage process. Two independent reviewers will extract data, assess risk of bias using Risk of Bias 2.0, Risk of Bias in Non-randomised studies of Interventions or Risk of Bias in Non-randomised Studies of Exposures checklist and assess quality using the Grading of Recommendations Assessment, Development and Evaluation tool. A random-effects network meta-analysis of outcomes, and sub-group analyses and meta-regression will be conducted, where data permit. If not appropriate, a narrative synthesis will be undertaken.Ethics and dissemination Ethical approval is not required as no primary data will be collected. The completed systematic review will be disseminated in a peer-reviewed journal, presented at conferences and used to inform the development of a weight management programme.PROSPERO registration number CRD42018088255.
Large linked healthcare administrative datasets could be used to monitor programs providing prevention and treatment services to people who inject drugs (PWID). However, diagnostic codes in administrative datasets do not differentiate non-injection from injection drug use (IDU). We validated algorithms based on diagnostic codes and prescription records representing IDU in administrative datasets against interview-based IDU data.
The British Columbia Hepatitis Testers Cohort (BC-HTC) includes ∼1.7 million individuals tested for HCV/HIV or reported HBV/HCV/HIV/tuberculosis cases in BC from 1990 to 2015, linked to administrative datasets including physician visit, hospitalization and prescription drug records. IDU, assessed through interviews as part of enhanced surveillance at the time of HIV or HCV/HBV diagnosis from a subset of cases included in the BC-HTC (n = 6559), was used as the gold standard. ICD-9/ICD-10 codes for IDU and injecting-related infections (IRI) were grouped with records of opioid substitution therapy (OST) into multiple IDU algorithms in administrative datasets. We assessed the performance of IDU algorithms through calculation of sensitivity, specificity, positive predictive, and negative predictive values.
Sensitivity was highest (90–94%), and specificity was lowest (42–73%) for algorithms based either on IDU or IRI and drug misuse codes. Algorithms requiring both drug misuse and IRI had lower sensitivity (57–60%) and higher specificity (90–92%). An optimal sensitivity and specificity combination was found with two medical visits or a single hospitalization for injectable drugs with (83%/82%) and without OST (78%/83%), respectively. Based on algorithms that included two medical visits, a single hospitalization or OST records, there were 41,358 (1.2% of 11–65 years individuals in BC) recent PWID in BC based on health encounters during 3- year period (2013–2015).
Algorithms for identifying PWID using diagnostic codes in linked administrative data could be used for tracking the progress of programing aimed at PWID. With population-based datasets, this tool can be used to inform much needed estimates of PWID population size.
Youth-onset type 2 diabetes is an emerging disease. We estimated incidence and prevalence trends of youth-onset type 2 diabetes between 2002 and 2013 in the Canadian province of British Columbia.
This population-based cohort study used a validated diabetes case-finding definition and algorithm to differentiate type 2 from type 1 diabetes to identify youth <20 years with type 2 diabetes within linked population-based administrative data. Age-standardized incidence and prevalence were calculated. JoinPoint regression and double exponential smooth modeling were used.
From 2002/2003 to 2012/2013, the incidence of youth-onset type 2 diabetes increased from 3.45 (95% confidence interval, CI: 2.43, 4.80) to 5.16 (95% CI: 3.86, 6.78)/100 000. The annual percent change (APC) in incidence was 3.74 (95% CI: 1.61, 5.92; P = 0.003) overall, while it was 5.94 (95% CI: 1.84, 10.20; P = 0.009) and 0.53 (95% CI: -5.04, 6.43; P = 0.837) in females and males, respectively. The prevalence increased from 0.009% (95% CI: 0.007, 0.011) in 2002/2003 to 0.021% (95% CI: 0.018, 0.024) in 2012/2013 with an APC of 7.89 (95% CI: 6.41, 9.40; P < 0.0001). In females, it increased from 0.012% (95% CI: 0.009, 0.015) to 0.027% (95% CI: 0.023, 0.032) and in males from 0.007% (95% CI: 0.005, 0.009) to 0.015% (95% CI: 0.012, 0.019). By 2030, we forecast a prevalence of 0.046% (95% CI: 0.043, 0.048).
Youth-onset type 2 diabetes is increasing with higher rates in females vs males. If these rates continue, in 2030, the number of cases will increase by 5-fold. These data are needed to set priorities for diabetes prevention in youth.
Incidence rates of type 1 diabetes have long been on the rise across the globe, however, there is emerging evidence that the rate of rise may be slowing. The objective of this study was to describe trends in the incidence and prevalence of type 1 diabetes in a sample of Canadian children and youth.
Cases were extracted using linked administrative datasets and a validated diabetes case-finding definition. Incidence and prevalence trends were analyzed using the JoinPoint regression analysis program.
A small increase in the incidence of type 1 diabetes was observed over the 11-year period from 2002-2003 to 2012-2013. Total incident cases per year ranged from 201 (2005-2006) to 250 (2007-2008). Total prevalent cases per year ranged from 1790 (2002-2003) to 2264 (2012-2013). Incidence was highest among children aged 5 to 14 years, and lowest in the youngest (1-4 years) and oldest (15-19 years) age brackets. The most significant increase in incidence was in children aged 10 to 14 years. Age-standardized prevalence increased significantly throughout the study period.
These results are similar to data from the United States but differ from European data with respect to the annual percent change for incidence as well as age-specific incidence trends. In keeping with the low mortality rates associated with type 1 diabetes, the prevalence continues to rise.
Background: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. Methods We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0.5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Sociodemographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. Findings: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86.9 years (95% UI 86.7-87.2), and for men in Singapore, at 81.3 years (78.8-83.7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap between male and female life expectancy increased with progression to higher levels of SDI. Some countries with exceptional health performance in 1990 in terms of the difference in observed to expected life expectancy at birth had slower progress on the same measure in 2016. Interpretation Globally, mortality rates have decreased across all age groups over the past five decades, with the largest improvements occurring among children younger than 5 years. However, at the national level, considerable heterogeneity remains in terms of both level and rate of changes in age-specific mortality; increases in mortality for certain age groups occurred in some locations. We found evidence that the absolute gap between countries in age-specific death rates has declined, although the relative gap for some age-sex groups increased. Countries that now lead in terms of having higher observed life expectancy than that expected on the basis of development alone, or locations that have either increased this advantage or rapidly decreased the deficit from expected levels, could provide insight into the means to accelerate progress in nations where progress has stalled. Copyright (C) The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.