15 research outputs found
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Smooth Risk Functions for Self-Controlled Case Series Models
The self-controlled case series (SCCS) method is commonly used to investigate associations between vaccine exposures and adverse events (side effects). It is an alternative to cohort and case control study designs. It requires information only on cases, individuals who have experienced the adverse event at least once, and automatically controls all fixed confounders that could modify the true association between exposure and adverse event. However, time-varying confounders (age, season) are not automatically controlled.
The SCCS method has parametric and semi-parametric versions in terms of controlling the age effect. The parametric method uses piecewise constant functions with a priori chosen age groups and the semi-parametric method leaves the age effect unspecified. Mis-specification of age groups in the parametric version may lead to biased estimates of the exposure effect, and the semi-parametric approach runs into computational problems when the sample size is moderately large. Moreover, both versions of SCCS represent the time-varying exposures using step functions with pre-determined cut-points. A less prescriptive approach may be beneficial when the shape of the relative risk function associated with exposure is not known a priori, especially when exposure effects can be long-lasting.
This thesis focuses on extending the SCCS method to avoid the aforementioned limitations by modelling the age and exposure effects using flexible smooth functions. Specifically, we used penalised regression splines based on cubic M-splines, which are piecewise polynomials of degree 3. We developed three new extensions: a method that represents only the age effect with splines, a method that uses splines to model only the exposure effect and a non-parametric SCCS method that represents both effects by splines. Simulation studies showed that these new methods outperformed the parametric and semi-parametric methods. The new methods are illustrated using large data sets.
Review of SCCS vaccine studies and directions on how to use the method are also given
Self-controlled case series with multiple event types
Self-controlled case series methods for events that may be classified as one of several types are described. When the event is non-recurrent, the different types correspond to competing risks. It is shown that, under circumstances that are likely to arise in practical applications, the SCCS multi-type likelihood reduces to the product of the type-specific likelihoods. For recurrent events, this applies whether or not the marginal type-specific counts are dependent. As for the standard SCCS method, a rare disease assumption is required for non-recurrent events. Several forms of this assumption are investigated by simulation. The methods are applied to data on MMR vaccine and convulsions (febrile and non-febrile), and to data on thiazolidinediones and fractures (at different sites)
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Effectiveness of pre-pregnancy lifestyle in preventing gestational diabetes mellitusâa systematic review and meta-analysis of 257,876 pregnancies
Background: Gestational Diabetes Mellitus (GDM) is hyperglycaemia first detected during pregnancy. Globally, GDM affects around 1 in 6 live births (up to 1 in 4 in low- and middle-income countries- LMICs), thus, urgent measures are needed to prevent this public health threat. Objective: To determine the effectiveness of pre-pregnancy lifestyle in preventing GDM. Methods: We searched MEDLINE, Web of science, Embase and Cochrane central register of controlled trials. Randomized control trials (RCTs), case-control studies, and cohort studies that assessed the effect of pre-pregnancy lifestyle (diet and/or physical activity based) in preventing GDM were included. Random effects model was used to calculate odds ratio (OR) with 95% confidence interval. The Cochrane ROB-2 and the Newcastle-Ottawa Scale were used for assessing the risk of bias. The protocol was registered in PROSPERO (ID: CRD42020189574) Results: Database search identified 7935 studies, of which 30 studies with 257,876 pregnancies were included. Meta-analysis of the RCTs (N = 5; n = 2471) in women who received pre-pregnancy lifestyle intervention showed non-significant reduction of the risk of developing GDM (OR 0.76, 95% CI: 0.50â1.17, p = 0.21). Meta-analysis of cohort studies showed that women who were physically active pre-pregnancy (N = 4; n = 23263), those who followed a low carbohydrate/low sugar diet (N = 4; n = 25739) and those women with higher quality diet scores were 29%, 14% and 28% less likely to develop GDM respectively (OR 0.71, 95% CI: 0.57, 0.88, p = 0.002, OR 0.86, 95% CI: 0.68, 1.09, p = 0.22 and OR 0.72, 95% CI 0.60â0.87, p = 0.0006). Conclusion: This study highlights that some components of pre-pregnancy lifestyle interventions/exposures such as diet/physical activity-based preparation/counseling, intake of vegetables, fruits, low carbohydrate/low sugar diet, higher quality diet scores and high physical activity can reduce the risk of developing gestational diabetes. Evidence from RCTs globally and the number of studies in LMICs are limited, highlighting the need for carefully designed RCTs that combine the different aspects of the lifestyle and are personalized to achieve better clinical and cost effectiveness
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Machine learning prediction of non-attendance to postpartum glucose screening and subsequent risk of type 2 diabetes following gestational diabetes
Objective The aim of the present study was to identify the factors associated with non-attendance of immediate postpartum glucose test using a machine learning algorithm following gestational diabetes mellitus (GDM) pregnancy. Method: A retrospective cohort study of all GDM women (n = 607) for postpartum glucose test due between January 2016 and December 2019 at the George Eliot Hospital NHS Trust, UK. Results Sixty-five percent of women attended postpartum glucose test. Type 2 diabetes was diagnosed in 2.8% and 21.6% had persistent dysglycaemia at 6â13 weeks post-delivery. Those who did not attend postpartum glucose test seem to be younger, multiparous, obese, and continued to smoke during pregnancy. They also had higher fasting glucose at antenatal oral glucose tolerance test. Our machine learning algorithm predicted postpartum glucose non-attendance with an area under the receiver operating characteristic curve of 0.72. The model could achieve a sensitivity of 70% with 66% specificity at a risk score threshold of 0.46. A total of 233 (38.4%) women attended subsequent glucose test at least once within the first two years of delivery and 24% had dysglycaemia. Compared to women who attended postpartum glucose test, those who did not attend had higher conversion rate to type 2 diabetes (2.5% vs 11.4%; p = 0.005). Conclusion Postpartum screening following GDM is still poor. Women who did not attend postpartum screening appear to have higher metabolic risk and higher conversion to type 2 diabetes by two years post-delivery. Machine learning model can predict women who are unlikely to attend postpartum glucose test using simple antenatal factors. Enhanced, personalised education of these women may improve postpartum glucose screening
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Prevalence of prediabetes and type 2 diabetes mellitus in south and southeast Asian women with history of gestational diabetes mellitus: Systematic review and meta-analysis
Background The burden of Gestational Diabetes Mellitus (GDM) is very high in south Asia (SA) and southeast Asia (SEA). Thus, there is a need to understand the prevalence and risk factors for developing prediabetes and type 2 diabetes mellitus (T2DM) postpartum, in this high-risk population. Aim To conduct a systematic review and meta-analysis to estimate the prevalence of prediabetes and T2DM among the women with history of GDM in SA and SEA. Methods A comprehensive literature search was performed in the following databases: Medline, EMBASE, Web of Knowledge and CINHAL till December 2021. Studies that had reported greater than six weeks of postpartum follow-up were included. The pooled prevalence of diabetes and prediabetes were estimated by random effects meta-analysis model and I2 statistic was used to assess heterogeneity. Results Meta-analysis of 13 studies revealed that the prevalence of prediabetes and T2DM in post-GDM women were 25.9% (95%CI 18.94 to 33.51) and 29.9% (95%CI 17.02 to 44.57) respectively. Women with history of GDM from SA and SEA seem to have higher risk of developing T2DM than women without GDM (RR 13.2, 95%CI 9.52 to 18.29, p Conclusion The conversion to T2DM and prediabetes is very high among women with history of GDM in SA and SEA. This highlights the need for follow-up of GDM women for early identification of dysglycemia and to plan interventions to prevent/delay the progression to T2DM
Cardiovascular outcomes associated with use of clarithromycin: population based study
Study question
What is the association between clarithromycin use and cardiovascular outcomes?
Methods
In this population based study the authors compared cardiovascular outcomes in adults aged 18 or more receiving oral clarithromycin or amoxicillin during 2005-09 in Hong Kong. Based on age within five years, sex, and calendar year at use, each clarithromycin user was matched to one or two amoxicillin users. The cohort analysis included patients who received clarithromycin (n=108â988) or amoxicillin (n=217â793). The self controlled case series and case crossover analysis included those who received Helicobacter pylori eradication treatment containing clarithromycin. The primary outcome was myocardial infarction. Secondary outcomes were all cause, cardiac, or non-cardiac mortality, arrhythmia, and stroke.
Study answer and limitations
The propensity score adjusted rate ratio of myocardial infarction 14 days after the start of antibiotic treatment was 3.66 (95% confidence interval 2.82 to 4.76) comparing clarithromycin use (132 events, rate 44.4 per 1000 person years) with amoxicillin use (149 events, 19.2 per 1000 person years), but no long term increased risk was observed. Similarly, rate ratios of secondary outcomes increased significantly only with current use of clarithromycin versus amoxicillin, except for stroke. In the self controlled case analysis, there was an association between current use of H pylori eradication treatment containing clarithromycin and cardiovascular events. The risk returned to baseline after treatment had ended. The case crossover analysis also showed an increased risk of cardiovascular events during current use of H pylori eradication treatment containing clarithromycin. The adjusted absolute risk difference for current use of clarithromycin versus amoxicillin was 1.90 excess myocardial infarction events (95% confidence interval 1.30 to 2.68) per 1000 patients.
What this study adds
Current use of clarithromycin was associated with an increased risk of myocardial infarction, arrhythmia, and cardiac mortality short term but no association with long term cardiovascular risks among the Hong Kong population
Evaluation of the risk of cardiovascular events with clarithromycin using both propensity score and self-controlled study designs
Aim:
Some previous studies suggest a long term association between clarithromycin use and cardiovascular events. This study investigates this association for clarithromycin given as part of Helicobacter pylori treatment (HPT).
Methods:
Our source population was the Clinical Practice Research Datalink (CPRD), a UK primary care database. We conducted a self-controlled case series (SCCS), a caseâtimeâcontrol study (CTC) and a propensity score adjusted cohort study comparing the rate of cardiovascular events in the 3 years after exposure to HPT containing clarithromycin with exposure to clarithromycin free HPT.
Outcomes were first incident diagnosis of myocardial infarction (MI), arrhythmia and stroke. For the cohort analysis we included secondary outcomes all cause and cardiovascular mortality.
Results:
Twenty-eight thousand five hundred and fifty-two patients were included in the cohort. The incidence rate ratio of first MI within 1 year of exposure to HPT containing clarithromycin was 1.07 (95% CI 0.85, 1.34, P = 0.58) and within 90 days was 1.43 (95% CI 0.99, 2.09 P = 0.057) in the SCCS analysis. CTC and cohort results were consistent with these findings.
Conclusions
There was some evidence for a short term association for first MI but none for a long term association for any outcome
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A modified selfâcontrolled case series method for eventâdependent exposures and high eventârelated mortality, with application to COVIDâ19 vaccine safety
We propose a modified selfâcontrolled case series (SCCS) method to handle both eventâdependent exposures and high eventârelated mortality. This development is motivated by an epidemiological study undertaken in France to quantify potential risks of cardiovascular events associated with COVIDâ19 vaccines. Eventâdependence of vaccinations, and high eventârelated mortality, are likely to arise in other SCCS studies of COVIDâ19 vaccine safety. Using this case study and simulations to broaden its scope, we explore these features and the biases they may generate, implement the modified SCCS model, illustrate some of the properties of this model, and develop a new test for presence of a dose effect. The model we propose has wider application, notably when the event of interest is death
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Serum bile acid measurements in women of European and South Asian ethnicity with or without gestational diabetes mellitus: A cohort study
Objective
Investigation of serum bile acid profiles in pregnancies complicated by gestational diabetes mellitus (GDM) in a multiâethnic cohort of women who are lean or obese.
Design
Prospective cohort study.
Setting
UK multicentre study.
Population
Fasting serum from participants of European or South Asian selfâreported ethnicity from the PRiDE study, between 23 and 31 weeks of gestation.
Methods
Bile acids were measured using ultraâperformance liquid chromatographyâtandem mass spectrometry. Logâtransformed data were analysed using linear regression in STATA/IC 15.0.
Main outcome measures
Total bile acids (TBAs), C4, fasting glucose and insulin.
Results
The TBAs were 1.327âfold (1.105â1.594) increased with GDM in European women ( P = 0.003). Women with GDM had 1.162âfold (1.002â1.347) increased levels of the BA synthesis marker C4 ( P = 0.047). In South Asian women, obesity (but not GDM) increased TBAs 1.522âfold (1.193â1.942, P = 0.001). Obesity was associated with 1.420âfold (1.185â1.702) increased primary/secondary BA ratio ( P
Conclusions
Serum BA homeostasis in late gestation depends on body mass index and GDM in ethnicityâspecific ways. This suggests ethnicityâspecific aetiologies may contribute to metabolic risk in European and South Asian women, with the relationship between BAs and insulin resistance of greater importance in European women. Further studies into ethnicityâspecific precision medicine for GDM are required
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Early pregnancy HbA1c as the first screening test for gestational diabetes: results from three prospective cohorts
Background More than 90% of gestational diabetes cases are estimated to occur in low-income and middle-income countries (LMICs). Most current guidelines recommend an oral glucose tolerance test (OGTT) at 24â28 weeks of gestation. The OGTT is burdensome, especially in LMICs, resulting in a high proportion of women not being screened. We aimed to develop a simple and effective screening strategy for gestational diabetes.
Methods STRiDE, a prospective cohort study, was set up in seven centres in south India and seven centres in western Kenya, and included pregnant women aged 18â50 years of age and at less than 16 weeks of gestation (1c (venous and capillary point-of-care), either alone or as part of a composite risk score with age, BMI, and family history of diabetes, in predicting gestational diabetes at 24â28 weeks of gestation, in two LMICs (India and Kenya) and in a UK multi-ethnic population from the PRiDE study. A key secondary outcome was to assess whether an early pregnancy composite risk score can reduce the need for OGTTs. Gestational diabetes was diagnosed using current WHO criteria.
Findings Between Feb 15, 2016, Dec 13, 2019, we enrolled 3070 participants in India and 4104 in Kenya. 4320 participants were included from the PRiDE cohort. Gestational diabetes prevalence by OGTT at 24â28 weeks was 19·2% in India, 3·0% in Kenya, and 14·5% in the UK. Early pregnancy HbA1c was independently associated with incidence of gestational diabetes at 24â28 weeks of gestation. Adjusted risk ratios were 1·60 (95% CI 1·19â2·16) in India, 3·49 (2·8â4·34) in Kenya, and 4·72 (3·82â5·82) in the UK. Composite risk score models that combined venous or point-of-care HbA1c with age, BMI, and family history of diabetes best predicted testing positive for gestational diabetes. A population-specific, two-threshold screening strategy of rule-in and rule-out gestational diabetes using early pregnancy composite risk score could reduce the requirement of OGTTs by 50â64%. For the HbA1c-alone model, the thresholds were 5·4% (rule in) and 4·9% (rule out) in India, 6·0% (rule in) and 5·2% (rule out) in Kenya, and 5·6% (rule in) and 5·2% (rule out) in the UK.
Interpretation Early pregnancy HbA1c offers a simple screening test for gestational diabetes, allowing those at highestrisk to receive early intervention and greatly reduce the need for OGTTs. This can also be carried out using point-of-care HbA1c in LMIC