Does exercise improve glycaemic control in type 1 diabetes? A systematic review and meta-analysis.

This is the final published version. Available from PLoS via the DOI in this record.OBJECTIVE: Whilst regular exercise is advocated for people with type 1 diabetes, the benefits of this therapy are poorly delineated. Our objective was to review the evidence for a glycaemic benefit of exercise in type 1 diabetes. RESEARCH DESIGN AND METHODS: Electronic database searches were carried out in MEDLINE, Embase, Cochrane's Controlled Trials Register and SPORTDiscus. In addition, we searched for as yet unpublished but completed trials. Glycaemic benefit was defined as an improvement in glycosylated haemoglobin (HbA1c). Both randomised and non-randomised controlled trials were included. RESULTS: Thirteen studies were identified in the systematic review. Meta-analysis of twelve of these (including 452 patients) demonstrated an HbA1c reduction but this was not statistically significant (standardised mean difference (SMD) -0.25; 95% CI, -0.59 to 0.09). CONCLUSIONS: This meta-analysis does not reveal evidence for a glycaemic benefit of exercise as measured by HbA1c. Reasons for this finding could include increased calorie intake, insulin dose reductions around the time of exercise or lack of power. We also suggest that HbA1c may not be a sensitive indicator of glycaemic control, and that improvement in glycaemic variability may not be reflected in this measure. Exercise does however have other proven benefits in type 1 diabetes, and remains an important part of its management

Gestational dyslipidaemia and adverse birthweight outcomes : a systematic review and meta-analysis

Background Low and high birthweight is known to increase the risk of acute and longer‐term adverse outcomes, such as stillbirth, infant mortality, obesity, type 2 diabetes and cardiovascular diseases. Gestational dyslipidaemia is associated with a numbers of adverse birth outcomes, but evidence regarding birthweight is still inconsistent to reliably inform clinical practice and treatment recommendations. Objective The aim of this study was to explore the relationship between maternal gestational dyslipidaemia and neonatal health outcomes, namely, birthweight, metabolic factors and inflammatory parameters. Methods We searched systematically Embase, MEDLINE, PubMed, CINAHL Plus and Cochrane Library up to 1 August 2016 (with an updated search in MEDLINE at the end of July 2017) for longitudinal studies that assessed the association of maternal lipid levels during pregnancy with neonatal birthweight, or metabolic and inflammatory parameters up to 3 years old. Results Data from 46 publications including 31,402 pregnancies suggest that maternal high triglycerides and low high‐density‐lipoprotein cholesterol levels throughout pregnancy are associated with increased birthweight, higher risk of large for gestational age and macrosomia and lower risk of small‐for‐gestational age. The findings were consistent across the studied populations, but stronger associations were observed in women who were overweight or obese prior to pregnancy. Conclusions This meta‐analysis suggested that the potential under‐recognized adverse effects of intrauterine exposure to maternal dyslipidaemia may warrant further investigation into the relationship between maternal dyslipidaemia and birthweight in large prospective cohorts or in randomized trials

Long Covid symptoms and diagnosis in primary care: A cohort study using structured and unstructured data in The Health Improvement Network primary care database

BACKGROUND: Long Covid is a widely recognised consequence of COVID-19 infection, but little is known about the burden of symptoms that patients present with in primary care, as these are typically recorded only in free text clinical notes. AIMS: To compare symptoms in patients with and without a history of COVID-19, and investigate symptoms associated with a Long Covid diagnosis. METHODS: We used primary care electronic health record data until the end of December 2020 from The Health Improvement Network (THIN), a Cegedim database. We included adults registered with participating practices in England, Scotland or Wales. We extracted information about 89 symptoms and 'Long Covid' diagnoses from free text using natural language processing. We calculated hazard ratios (adjusted for age, sex, baseline medical conditions and prior symptoms) for each symptom from 12 weeks after the COVID-19 diagnosis. RESULTS: We compared 11,015 patients with confirmed COVID-19 and 18,098 unexposed controls. Only 20% of symptom records were coded, with 80% in free text. A wide range of symptoms were associated with COVID-19 at least 12 weeks post-infection, with strongest associations for fatigue (adjusted hazard ratio (aHR) 3.46, 95% confidence interval (CI) 2.87, 4.17), shortness of breath (aHR 2.89, 95% CI 2.48, 3.36), palpitations (aHR 2.59, 95% CI 1.86, 3.60), and phlegm (aHR 2.43, 95% CI 1.65, 3.59). However, a limited subset of symptoms were recorded within 7 days prior to a Long Covid diagnosis in more than 20% of cases: shortness of breath, chest pain, pain, fatigue, cough, and anxiety / depression. CONCLUSIONS: Numerous symptoms are reported to primary care at least 12 weeks after COVID-19 infection, but only a subset are commonly associated with a GP diagnosis of Long Covid

Increased risk of cardiovascular and renal disease, and diabetes for all women diagnosed with gestational diabetes mellitus in New Zealand:A national retrospective cohort study

Background: Gestational diabetes mellitus increases the risk of developing type 2 diabetes. The aim of this study is to compare cardiometabolic and renal outcomes for all women in New Zealand with gestational diabetes (2001–2010) with women without diabetes, 10–20 years following delivery. Methods: A retrospective cohort study, utilizing a national dataset providing information for all women who gave birth between 1 January 2001 and 31 December 2010 (n = 604 398). Adolescent girls <15 years, women ≥50 years and women with prepregnancy diabetes were excluded. In total 11 459 women were diagnosed with gestational diabetes and 11 447 were matched (for age and year of delivery) with 57 235 unexposed (control) women. A national hospital dataset was used to compare primary outcomes until 31 May 2021.Results: After controlling for ethnicity, women with gestational diabetes were significantly more likely than control women to develop diabetes—adjusted hazard ratio (HR) 20.06 and 95% confidence interval (CI) 18.46–21.79; a first cardiovascular event 2.19 (1.86–2.58); renal disease 6.34 (5.35–7.51) and all-cause mortality 1.55 (1.31–1.83), all p values <.0001. The HR and 95% CI remained similar after controlling for significant covariates: diabetes 18.89 (17.36–20.56), cardiovascular events 1.79 (1.52–2.12), renal disease 5.42 (4.55–6.45), and all-cause mortality 1.44 (1.21–1.70). When time-dependent diabetes was added to the model, significance remained for cardiovascular events 1.33 (1.10–1.61), p = .003 and renal disease 2.33 (1.88–2.88), p < .0001 but not all-cause mortality.Conclusions: Women diagnosed with gestational diabetes have an increased risk of adverse cardiometabolic and renal outcomes. Findings highlight the importance of follow-up screening for diabetes, cardiovascular risk factors, and renal disease

Bayesian blockwise inference for joint models of longitudinal and multistate data with application to longitudinal multimorbidity analysis

Multistate models provide a useful framework for modelling complex event history data in clinical settings and have recently been extended to the joint modelling framework to appropriately handle endogenous longitudinal covariates, such as repeatedly measured biomarkers, which are informative about health status and disease progression. However, the practical application of such joint models faces considerable computational challenges. Motivated by a longitudinal multimorbidity analysis of large-scale UK health records, we introduce novel Bayesian inference approaches for these models that are capable of handling complex multistate processes and large datasets with straightforward implementation. These approaches decompose the original estimation task into smaller inference blocks, leveraging parallel computing and facilitating flexible model specification and comparison. Using extensive simulation studies, we show that the proposed approaches achieve satisfactory estimation accuracy, with notable gains in computational efficiency compared to the standard Bayesian estimation strategy. We illustrate our approaches by analysing the coevolution of routinely measured systolic blood pressure and the progression of three important chronic conditions, using a large dataset from the Clinical Practice Research Datalink Aurum database. Our analysis reveals distinct and previously lesser-known association structures between systolic blood pressure and different disease transitions

Association of sildenafil use with age-related macular degeneration:a retrospective cohort study

Objective: Despite significant advances in clinical care and understanding of the underlying pathophysiology, age-related macular degeneration (AMD)—a major cause of global blindness—lacks effective treatment to prevent the irreversible degeneration of photoreceptors leading to central vision loss. Limited studies suggest phosphodiesterase type 5 (PDE5) inhibitors, such as sildenafil, may prevent AMD by increasing retinal blood flow. This study explores the potential association between sildenafil use and AMD risk in men with erectile dysfunction using UK data. Methods and analysis: Using the UK’s IQVIA Medical Research Data, the study analysed 31 575 men prescribed sildenafil for erectile dysfunction and no AMD history from 2007 to 2015, matched with a comparator group of 62 155 non-sildenafil users in a 1:2 ratio, over a median follow-up of approximately three years. Results: The primary outcome was the incidence of AMD in the two groups. The study found no significant difference in AMD incidence between the sildenafil users and the non-users, with an adjusted hazard ratio (HR) of 0.99 (95% CI 0.84 to 1.16), after accounting for confounders such as age, ethnicity, Townsend deprivation quintile, body mass index category, and diagnosis of hypertension and type 2 diabetes. Conclusion: The study results indicated no significant association between sildenafil use and AMD prevention in UK men with erectile dysfunction, suggesting sildenafil’s protective effect on AMD is likely insignificant

Association of maternal lipid levels with birth weight and cord blood insulin: A Bayesian network analysis

Objective To assess the independent association of maternal lipid levels with birth weight and cord blood insulin (CBI) level. Setting The Born in Guangzhou Cohort Study, Guangzhou, China. Participants Women who delivered between January 2015 and June 2016 and with umbilical cord blood retained were eligible for this study. Those with prepregnancy health conditions, without an available fasting blood sample in the second trimester, or without demographic and glycaemic information were excluded. After random selection, data from 1522 mother-child pairs were used in this study. Exposures and outcome measures Additive Bayesian network analysis was used to investigate the interdependency of lipid profiles with other metabolic risk factors (prepregnancy body mass index (BMI), fasting glucose and early gestational weight gain) in association with birth weight and CBI, along with multivariable linear regression models. Results In multivariable linear regressions, maternal triglyceride was associated with increased birth weight (adjusted β=67.46, 95% CI 41.85 to 93.06 g per mmol/L) and CBI (adjusted β=0.89, 95% CI 0.06 to 1.72 μU/mL per mmol/L increase), while high-density lipoprotein cholesterol was associated with decreased birth weight (adjusted β=-45.29, 95% CI -85.49 to -5.09 g per mmol/L). After considering the interdependency of maternal metabolic risk factors in the Network analysis, none of the maternal lipid profiles was independently associated with birth weight and CBI. Instead, prepregnancy BMI was the global strongest factor for birth weight and CBI directly and indirectly. Conclusions Gestational dyslipidaemia appears to be secondary to metabolic dysfunction with no clear association with metabolic adverse outcomes in neonates. Maternal prepregnancy overweight/obesity appears the most influential upstream metabolic risk factor for both maternal and neonatal metabolic health; these data imply weight management may need to be addressed from the preconception period and during early pregnancy

Sociodemographic characteristics and longitudinal progression of multimorbidity:A multistate modelling analysis of a large primary care records dataset in England

BackgroundMultimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions.Methods and findingsWe utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p ConclusionsOur results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity