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PurposeThe Scottish Diabetes Research Network (SDRN)-diabetes research platform was established to combine disparate electronic health record data into research-ready linked datasets for diabetes research in Scotland. The resultant cohort, ‘The SDRN-National Diabetes Dataset (SDRN-NDS)’, has many uses, for example, understanding healthcare burden and socioeconomic trends in disease incidence and prevalence, observational pharmacoepidemiology studies and building prediction tools to support clinical decision making.ParticipantsWe estimate that >99% of those diagnosed with diabetes nationwide are captured into the research platform. Between 2006 and mid-2020, the cohort comprised 472 648 people alive with diabetes at any point in whom there were 4 million person-years of follow-up. Of the cohort, 88.1% had type 2 diabetes, 8.8% type 1 diabetes and 3.1% had other types (eg, secondary diabetes). Data are captured from all key clinical encounters for diabetes-related care, including diabetes clinic, primary care and podiatry and comprise clinical history and measurements with linkage to blood results, microbiology, prescribed and dispensed drug and devices, retinopathy screening, outpatient, day case and inpatient episodes, birth outcomes, cancer registry, renal registry and causes of death.Findings to dateThere have been >50 publications using the SDRN-NDS. Examples of recent key findings include analysis of the incidence and relative risks for COVID-19 infection, drug safety of insulin glargine and SGLT2 inhibitors, life expectancy estimates, evaluation of the impact of flash monitors on glycaemic control and diabetic ketoacidosis and time trend analysis showing that diabetic ketoacidosis (DKA) remains a major cause of death under age 50 years. The findings have been used to guide national diabetes strategy and influence national and international guidelines.Future plansThe comprehensive SDRN-NDS will continue to be used in future studies of diabetes epidemiology in the Scottish population. It will continue to be updated at least annually, with new data sources linked as they become available.

Aims/hypothesis The aim of this work was to map the number of prescribed drugs over age, sex and area-based socioeconomic deprivation, and to examine the association between the number of drugs and particular high-risk drug classes with adverse health outcomes among a national cohort of individuals with type 1 diabetes. Methods Utilising linked healthcare records from the population-based diabetes register of Scotland, we identified 28,245 individuals with a diagnosis of type 1 diabetes on 1 January 2017. For this population, we obtained information on health status, predominantly reflecting diabetes-related complications, and information on the total number of drugs and particular high-risk drug classes prescribed. We then studied the association of these baseline-level features with hospital admissions for falls, diabetic ketoacidosis (DKA), and hypoglycaemia or death within the subsequent year using multivariate Cox proportional hazards models. Results Not considering insulin and treatment for hypoglycaemia, the mean number of prescribed drugs was 4.00 (SD 4.35). The proportion of individuals being prescribed five or more drugs at baseline consistently increased with age (proportion [95% CI]: 0–19 years 2.04% [1.60, 2.49]; 40–49 years 28.50% [27.08, 29.93]; 80+ years 76.04% [67.73, 84.84]). Controlling for age, sex, area-based socioeconomic deprivation and health status, each additional drug at baseline was associated with an increase in the hazard for hospitalisation for falls, hypoglycaemia and death but not for DKA admissions (HR [95% CI]: falls 1.03 [1.01, 1.06]; DKA 1.01 [1.00, 1.03]; hypoglycaemia 1.05 [1.02, 1.07]; death 1.04 [1.02, 1.06]). We found a number of drug classes to be associated with an increased hazard of one or more of these adverse health outcomes, including antithrombotic/anticoagulant agents, corticosteroids, opioids, antiepileptics, antipsychotics, hypnotics and sedatives, and antidepressants. Conclusions Polypharmacy is common among the Scottish population with type 1 diabetes and is strongly patterned by sociodemographic factors. The number of prescribed drugs and the prescription of particular high-risk drug classes are strong markers of an increased risk of adverse health outcomes, including acute complications of diabetes. Graphical abstract

Aims/hypothesis We aimed to examine whether crude mortality and mortality relative to the general population below 50 years of age have improved in recent years in those with type 1 diabetes. Methods Individuals with type 1 diabetes aged below 50 and at least 1 year old at any time between 2004 and 2017 in Scotland were identified using the national register. Death data were obtained by linkage to Scottish national death registrations. Indirect age standardisation was used to calculate sex-specific standardised mortality ratios (SMRs). Poisson regression was used to test for calendar-time effects as incidence rate ratios (IRRs). Results There were 1138 deaths in 251,143 person-years among 27,935 people with type 1 diabetes. There was a significant decline in mortality rate over time (IRR for calendar year 0.983 [95% CI 0.967, 0.998], p = 0.03), but the SMR remained approximately stable at 3.1 and 3.6 in men and 4.09 and 4.16 in women for 2004 and 2017, respectively. Diabetic ketoacidosis or coma (DKAoC) accounted for 22% of deaths and the rate did not decline significantly (IRR 0.975 [95% CI 0.94, 1.011], p = 0.168); 79.3% of DKAoC deaths occurred out of hospital. Circulatory diseases accounted for 27% of deaths and did decline significantly (IRR 0.946 [95% CI 0.914, 0.979], p = 0.002). Conclusions/interpretation Absolute mortality has fallen, but the relative impact of type 1 diabetes on mortality below 50 years has not improved. There is scope to improve prevention of premature circulatory diseases and DKAoC and to develop more effective strategies for enabling people with type 1 diabetes to avoid clinically significant hyper- or hypoglycaemia.

Background: Acetaminophen is widely used as first-line therapy for chronic pain because of its perceived safety and the assumption that, unlike nonsteroidal anti-inflammatory drugs, it has little or no effect on blood pressure (BP). Although observational studies suggest that acetaminophen may increase BP, clinical trials are lacking. We, therefore, studied the effects of regular acetaminophen dosing on BP in individuals with hypertension. Methods: In this double-blind, placebo-controlled, crossover study, 110 individuals were randomized to receive 1 g acetaminophen 4× daily or matched placebo for 2 weeks followed by a 2-week washout period before crossing over to the alternate treatment. At the beginning and end of each treatment period, 24-hour ambulatory BPs were measured. The primary outcome was a comparison of the change in mean daytime systolic BP from baseline to end of treatment between the placebo and acetaminophen arms. Results: One-hundred three patients completed both arms of the study. Regular acetaminophen, compared with placebo, resulted in a significant increase in mean daytime systolic BP (132.8±10.5 to 136.5±10.1 mm Hg [acetaminophen] vs 133.9±10.3 to 132.5±9.9 mm Hg [placebo]; P P =0.005) with a placebo-corrected increase of 1.6 mm Hg (95% CI, 0.5–2.7). Similar findings were seen for 24-hour ambulatory and clinic BPs. Conclusions: Regular daily intake of 4 g acetaminophen increases systolic BP in individuals with hypertension by ≈5 mm Hg when compared with placebo; this increases cardiovascular risk and calls into question the safety of regular acetaminophen use in this situation. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01997112. URL: https://www.clinicaltrialsregister.eu ; Unique identifier: 2013-003204-40.

Aims/hypothesis We assessed the real-world effect of flash monitor (FM) usage on HbA1c levels and diabetic ketoacidosis (DKA) and severe hospitalised hypoglycaemia (SHH) rates among people with type 1 diabetes in Scotland and across sociodemographic strata within this population. Methods This study was retrospective, observational and registry based. Using the national diabetes registry, 14,682 individuals using an FM at any point between 2014 and mid-2020 were identified. Within-person change from baseline in HbA1c following FM initiation was modelled using linear mixed models accounting for within-person pre-exposure trajectory. DKA and SHH events were captured through linkage to hospital admission and mortality data. The difference in DKA and SHH rates between FM-exposed and -unexposed person-time was assessed among users, using generalised linear mixed models with a Poisson likelihood. In a sensitivity analysis, we tested whether changes in these outcomes were seen in an age-, sex- and baseline HbA1c-matched sample of non-users over the same time period. Results Prevalence of ever-FM use was 45.9% by mid-2020, with large variations by age and socioeconomic status: 64.3% among children aged ≥65 years; and 54.4% vs 36.2% in the least-deprived vs most-deprived quintile. Overall, the median (IQR) within-person change in HbA1c in the year following FM initiation was −2.5 (−9.0, 2.5) mmol/mol (−0.2 [−0.8, 0.2]%). The change varied widely by pre-usage HbA1c: −15.5 (−31.0, −4.0) mmol/mol (−1.4 [−2.8, −0.4]%) in those with HbA1c > 84 mmol/mol [9.8%] and 1.0 (−2.0, 5.5) mmol/mol (0.1 [−0.2, 0.5]%) in those with HbA1c 1c were found in all age bands, sexes and socioeconomic strata, and regardless of prior/current pump use, completion of a diabetes education programme or early FM adoption. Variation between the strata of these factors beyond that driven by differing HbA1c at baseline was slight. No change in HbA1c in matched non-users was observed in the same time period (median [IQR] within-person change = 0.5 [−5.0, 5.5] mmol/mol [0.0 (−0.5, 0.5)%]). DKA rates decreased after FM initiation overall and in all strata apart from the adolescents. Estimated overall reduction in DKA event rates (rate ratio) was 0.59 [95% credible interval (CrI) 0.53, 0.64]) after FM vs before FM initiation, accounting for pre-exposure trend. Finally, among those at higher risk for SHH, estimated reduction in event rates was rate ratio 0.25 (95%CrI 0.20, 0.32) after FM vs before FM initiation. Conclusions/interpretation FM initiation is associated with clinically important reductions in HbA1c and striking reduction in DKA rate. Increasing uptake among the socioeconomically disadvantaged offers considerable potential for tightening the current socioeconomic disparities in glycaemia-related outcomes. Graphical abstract

OBJECTIVE Whether advances in the management of type 1 diabetes are reducing rates of diabetic ketoacidosis (DKA) is unclear. We investigated time trends in DKA rates in a national cohort of individuals with type 1 diabetes monitored for 14 years, overall and by socioeconomic characteristics. RESEARCH DESIGN AND METHODS All individuals in Scotland with type 1 diabetes who were alive and at least 1 year old between 1 January 2004 and 31 December 2018 were identified using the national register (N = 37,939). DKA deaths and hospital admissions were obtained through linkage to Scottish national death and morbidity records. Bayesian regression was used to test for DKA time trends and association with risk markers, including socioeconomic deprivation. RESULTS There were 30,427 DKA admissions and 472 DKA deaths observed over 393,223 person-years at risk. DKA event rates increased over the study period (incidence rate ratio [IRR] per year 1.058 [95% credibility interval 1.054–1.061]). Males had lower rates than females (IRR male-to-female 0.814 [0.776–0.855]). DKA incidence rose in all age-groups other than 10- to 19-year-olds, in whom rates were the highest, but fell over the study. There was a large socioeconomic differential (IRR least-to-most deprived quintile 0.446 [0.406–0.490]), which increased during follow-up. Insulin pump use or completion of structured education were associated with lower DKA rates, and antidepressant and methadone prescription were associated with higher DKA rates. CONCLUSIONS DKA incidence has risen since 2004, except in 10- to 19-year-olds. Of particular concern are the strong and widening socioeconomic disparities in DKA outcomes. Efforts to prevent DKA, especially in vulnerable groups, require strengthening.

Background The objective of this study was to investigate the relation of severe COVID-19 to prior drug prescribing. Methods Severe cases were defined by entry to critical care or fatal outcome. For this matched case-control study (REACT-SCOT), all 4251 cases of severe COVID-19 in Scotland since the start of the epidemic were matched for age, sex and primary care practice to 36,738 controls from the population register. Records were linked to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. Results Severe COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in a care home, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.8, 13.3), and in those without any of the conditions designated as conferring increased risk of COVID-19. Of 17 drug classes postulated at the start of the epidemic to be “medications compromising COVID”, all were associated with increased risk of severe COVID-19 and these associations were present in those without any of the designated risk conditions. The fraction of cases in the population attributable to exposure to these drug classes was 38%. The largest effect was for antipsychotic agents: rate ratio 4.18 (3.42, 5.11). Other drug classes with large effects included proton pump inhibitors (rate ratio 2.20 (1.72, 2.83) for = 2 defined daily doses/day), opioids (3.66 (2.68, 5.01) for = 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates and were stronger with recent than with non-recent exposure. Conclusions Severe COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression, or dyskinesia; have anticholinergic effects; or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Measures to reduce the burden of mortality and morbidity from COVID-19 should include reinforcing existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy. Registration ENCEPP number https://EUPAS35558

SHu reports grants from Health Protection Scotland during the conduct of the study. TMC reports grants from Diabetes UK (18/0005786). CR reports grants from Public Health Scotland and UK Research and Innovation. Background We aimed to ascertain the cumulative risk of fatal or critical care unit-treated COVID-19 in people with diabetes and compare it with that of people without diabetes, and to investigate risk factors for and build a cross-validated predictive model of fatal or critical care unit-treated COVID-19 among people with diabetes. Methods In this cohort study, we captured the data encompassing the first wave of the pandemic in Scotland, from March 1, 2020, when the first case was identified, to July 31, 2020, when infection rates had dropped sufficiently that shielding measures were officially terminated. The participants were the total population of Scotland, including all people with diabetes who were alive 3 weeks before the start of the pandemic in Scotland (estimated Feb 7, 2020). We ascertained how many people developed fatal or critical care unit-treated COVID-19 in this period from the Electronic Communication of Surveillance in Scotland database (on virology), the RAPID database of daily hospitalisations, the Scottish Morbidity Records-01 of hospital discharges, the National Records of Scotland death registrations data, and the Scottish Intensive Care Society and Audit Group database (on critical care). Among people with fatal or critical care unit-treated COVID-19, diabetes status was ascertained by linkage to the national diabetes register, Scottish Care Information Diabetes. We compared the cumulative incidence of fatal or critical care unit-treated COVID-19 in people with and without diabetes using logistic regression. For people with diabetes, we obtained data on potential risk factors for fatal or critical care unit-treated COVID-19 from the national diabetes register and other linked health administrative databases. We tested the association of these factors with fatal or critical care unit-treated COVID-19 in people with diabetes, and constructed a prediction model using stepwise regression and 20-fold cross-validation. Findings Of the total Scottish population on March 1, 2020 (n=5 463 300), the population with diabetes was 319 349 (5·8%), 1082 (0·3%) of whom developed fatal or critical care unit-treated COVID-19 by July 31, 2020, of whom 972 (89·8%) were aged 60 years or older. In the population without diabetes, 4081 (0·1%) of 5 143 951 people developed fatal or critical care unit-treated COVID-19. As of July 31, the overall odds ratio (OR) for diabetes, adjusted for age and sex, was 1·395 (95% CI 1·304–1·494; p

Background The objectives of this study were to identify risk factors for severe coronavirus disease 2019 (COVID-19) and to lay the basis for risk stratification based on demographic data and health records. Methods and findings The design was a matched case-control study. Severe COVID-19 was defined as either a positive nucleic acid test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the national database followed by entry to a critical care unit or death within 28 days or a death certificate with COVID-19 as underlying cause. Up to 10 controls per case matched for sex, age, and primary care practice were selected from the national population register. For this analysis—based on ascertainment of positive test results up to 6 June 2020, entry to critical care up to 14 June 2020, and deaths registered up to 14 June 2020—there were 36,948 controls and 4,272 cases, of which 1,894 (44%) were care home residents. All diagnostic codes from the past 5 years of hospitalisation records and all drug codes from prescriptions dispensed during the past 240 days were extracted. Rate ratios for severe COVID-19 were estimated by conditional logistic regression. In a logistic regression using the age-sex distribution of the national population, the odds ratios for severe disease were 2.87 for a 10-year increase in age and 1.63 for male sex. In the case-control analysis, the strongest risk factor was residence in a care home, with rate ratio 21.4 (95% CI 19.1–23.9, p = 8 × 10−644). Univariate rate ratios for conditions listed by public health agencies as conferring high risk were 2.75 (95% CI 1.96–3.88, p = 6 × 10−9) for type 1 diabetes, 1.60 (95% CI 1.48–1.74, p = 8 × 10−30) for type 2 diabetes, 1.49 (95% CI 1.37–1.61, p = 3 × 10−21) for ischemic heart disease, 2.23 (95% CI 2.08–2.39, p = 4 × 10−109) for other heart disease, 1.96 (95% CI 1.83–2.10, p = 2 × 10−78) for chronic lower respiratory tract disease, 4.06 (95% CI 3.15–5.23, p = 3 × 10−27) for chronic kidney disease, 5.4 (95% CI 4.9–5.8, p = 1 × 10−354) for neurological disease, 3.61 (95% CI 2.60–5.00, p = 2 × 10−14) for chronic liver disease, and 2.66 (95% CI 1.86–3.79, p = 7 × 10−8) for immune deficiency or suppression. Seventy-eight percent of cases and 52% of controls had at least one listed condition (51% of cases and 11% of controls under age 40). Severe disease was associated with encashment of at least one prescription in the past 9 months and with at least one hospital admission in the past 5 years (rate ratios 3.10 [95% CI 2.59–3.71] and 2.75 [95% CI 2.53–2.99], respectively) even after adjusting for the listed conditions. In those without listed conditions, significant associations with severe disease were seen across many hospital diagnoses and drug categories. Age and sex provided 2.58 bits of information for discrimination. A model based on demographic variables, listed conditions, hospital diagnoses, and prescriptions provided an additional 1.07 bits (C-statistic 0.804). A limitation of this study is that records from primary care were not available. Conclusions We have shown that, along with older age and male sex, severe COVID-19 is strongly associated with past medical history across all age groups. Many comorbidities beyond the risk conditions designated by public health agencies contribute to this. A risk classifier that uses all the information available in health records, rather than only a limited set of conditions, will more accurately discriminate between low-risk and high-risk individuals who may require shielding until the epidemic is over., Paul McKeigue and co-workers study comorbidities and medical treatments as risk factors for severe COVID-19 in Scotland., Author summary Why was this study done? Most people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) do not become seriously ill: risk of severe or fatal disease is associated with older age, male sex, and conditions designated by public health agencies, including asthma, diabetes, and heart disease. Studies reported so far have focused on these “listed conditions” but have not examined medical records systematically to identify possible risk factors for severe coronavirus disease 2019 (COVID-19). The objectives of this study were to identify risk factors for severe COVID-19 and to lay the basis for risk stratification based on electronic health records. What did the researchers do and find? Using Scotland’s capability for linking electronic health records, we report the first systematic study of the relationship of severe or fatal COVID-19 to preexisting health conditions and other risk factors. Residents in care homes were 21 times more likely to develop severe disease than people of the same age and sex not living in care homes. The conditions associated with increased risk include not only those already designated by public health agencies—asthma, diabetes, heart disease, disabling neurological disease, kidney disease—but other diagnoses that are associated with frailty and poor health such as strokes and a history of falls. In those without any listed conditions, use of prescribed drugs acting on the digestive system or nervous system is associated with increased risk of severe COVID-19. What do these findings mean? The risk to younger individuals without any recent history of hospital admission or use of prescription drugs is very low. This study lays a basis for calculating a risk score based on electronic health records for every individual in the population and using it to advise those at high risk of severe disease to shield themselves when there is a COVID-19 epidemic in their locality.

Aims/hypothesis Our aim was to assess the use of continuous subcutaneous insulin infusion (CSII) in people with type 1 diabetes in Scotland and its association with glycaemic control, as measured by HbA1c levels, frequency of diabetic ketoacidosis (DKA) and severe hospitalised hypoglycaemia (SHH), overall and stratified by baseline HbA1c. Methods We included 4684 individuals with type 1 diabetes from the national Scottish register, who commenced CSII between 2004 and 2019. We presented crude within-person differences from baseline HbA1c over time since initiation, crude DKA and SHH event-rates pre-/post-CSII exposure. We then used mixed models to assess the significance of CSII exposure, taking into account: (1) the diffuse nature of the intervention (i.e. structured education often precedes initiation); (2) repeated within-person measurements; and (3) background time-trends occurring pre-intervention. Results HbA1c decreased after CSII initiation, with a median within-person change of −5.5 mmol/mol (IQR −12.0, 0.0) (−0.5% [IQR −1.1, 0.0]). Within-person changes were most substantial in those with the highest baseline HbA1c, with median −21.0 mmol/mol (−30.0, −11.0) (−1.9% [−2.7, −1.0]) change in those with a baseline >84 mmol/mol (9.8%) within a year of exposure, that was sustained: −19.0 mmol/mol (−27.6, −6.5) (−1.7% [−2.5, −0.6]) at ≥5 years. Statistical significance and magnitude of change were supported by the mixed models results. The crude DKA event-rate was significantly lower in post-CSII person-time compared with pre-CSII person-time: 49.6 events (95% CI 46.3, 53.1) per 1000 person-years vs 67.9 (64.1, 71.9); rate ratio from Bayesian mixed models adjusting for pre-exposure trend: 0.61 (95% credible interval [CrI] 0.47, 0.77; posterior probability of reduction pp = 1.00). The crude overall SHH event-rate in post-CSII vs pre-CSII person-time was also lower: 17.8 events (95% CI 15.8, 19.9) per 1000 person-years post-exposure vs 25.8 (23.5, 28.3) pre-exposure; rate ratio from Bayesian mixed models adjusting for pre-exposure trend: 0.67 (95% CrI 0.45, 1.01; pp = 0.97). Conclusions/interpretation CSII therapy was associated with marked falls in HbA1c especially in those with high baseline HbA1c. CSII was independently associated with reduced DKA and SHH rates. CSII appears to be an effective option for intensive insulin therapy in people with diabetes for improving suboptimal glycaemic control. Graphical abstract

OBJECTIVE In 2019, the European Society of Cardiology led and released new guidelines for diabetes cardiovascular risk management, reflecting recent evidence of cardiovascular disease (CVD) reduction with sodium–glucose cotransporter 2 inhibitors (SGLT-2is) and some glucagon-like peptide 1 receptor agonists (GLP-1RAs) in type 2 diabetes (T2D). A key recommendation is that all those with T2D who are (antihyperglycemic) drug naïve or on metformin monotherapy should be CVD risk stratified and an SGLT-2i or a GLP-1RA initiated in all those at high or very high risk, irrespective of glycated hemoglobin. We assessed the impact of these guidelines in Scotland were they introduced as is. RESEARCH DESIGN AND METHODS Using a nationwide diabetes register in Scotland, we did a cross-sectional analysis, using variables in our register for risk stratification at 1 January 2019. We were conservative in our definitions, assuming the absence of a risk factor where data were not available. The risk classifications were applied to people who were drug naïve or on metformin monotherapy and the anticipated prescribing change calculated. RESULTS Of the 265,774 people with T2D in Scotland, 53,194 (20.0% of those with T2D) were drug naïve, and 56,906 (21.4%) were on metformin monotherapy. Of these, 74.5% and 72.4%, respectively, were estimated as at least high risk given the guideline risk definitions. CONCLUSIONS Thus, 80,830 (30.4%) of all those with T2D (n = 265,774) would start one of these drug classes according to table 7 and figure 3 of the guideline. The sizeable impact on drug budgets, enhanced clinical monitoring, and the trade-off with reduced CVD-related health care costs will need careful consideration.

Aims/hypothesis:\ud \ud Dapagliflozin, a sodium–glucose cotransporter 2 (SGLT2) inhibitor, is indicated for improving glycaemic control in type 2 diabetes mellitus. Whether its effects on HbA1c and other variables, including safety outcomes, in clinical trials are obtained in real-world practice needs to be established.\ud Methods:\ud \ud We used data from the comprehensive national diabetes register, the Scottish Care Information-Diabetes (SCI-Diabetes) collaboration database, available from 2004 to mid-2016. Data within this database were linked to mortality data from the General Registrar, available from the Information Services Division (ISD) of the National Health Service in Scotland. We calculated crude within-person differences between pre- and post-drug-initiation values of HbA1c, BMI, body weight, systolic blood pressure (SBP) and eGFR. We used mixed-effects regression models to adjust for within-person time trajectories in these measures. For completeness, we evaluated safety outcomes, cardiovascular disease events, lower-limb amputation and diabetic ketoacidosis, focusing on cumulative exposure effects, using Cox proportional hazard models, though power to detect such effects was limited.\ud Results:\ud \ud Among 8566 people exposed to dapagliflozin over a median of 210 days the crude within-person change in HbA1c was −10.41 mmol/mol (−0.95%) after 3 months’ exposure. The crude change after 12 months was −12.99 mmol/mol (−1.19%) but considering the expected rise over time in HbA1c gave a dapagliflozin-exposure-effect estimate of −15.14 mmol/mol (95% CI −15.87, −14.41) (−1.39% [95% CI −1.45, −1.32]) at 12 months that was maintained thereafter. A drop in SBP of −4.32 mmHg (95% CI −4.84, −3.79) on exposure within the first 3 months was also maintained thereafter. Reductions in BMI and body weight stabilised by 6 months at −0.82 kg/m2 (95% CI −0.87, −0.77) and −2.20 kg (95% CI −2.34, −2.06) and were maintained thereafter. eGFR declined initially by −1.81 ml min−1 [1.73 m]−2 (95% CI −2.10, −1.52) at 3 months but varied thereafter. There were no significant effects of cumulative drug exposure on safety outcomes.\ud Conclusions/interpretation:\ud \ud Dapagliflozin exposure was associated with reductions in HbA1c, SBP, body weight and BMI that were at least as large as in clinical trials. Dapagliflozin also prevented the expected rise in HbA1c and SBP over the period of study.

Aconite poisoning is relatively rare but is frequently complicated by ventricular dysrhythmias, which may be fatal. Molecular basis of aconite alkaloid ventricular arrhythmogenicity: Aconite exerts its toxic effects due to the presence of an admixture of alkaloids present in all parts of the plant. The major target of these aconite alkaloids is the fast voltage-gates sodium channel, where they cause persistent activation. This blockade of the channel in the activated state promotes automaticity within the ventricular myocardium and the generation of ventricular arrhythmias. Aconitine-induced arrhythmias: Aconite alkaloids are known to cause many different types of disturbance of heart rhythm. However, this focused review specifically looks at ventricular rhythm disturbances, namely ventricular ectopy, ventricular tachycardia, torsades des pointes and ventricular fibrillation.The objective of this review was to identify the outcome of anti-dysrhythmic strategies from animal studies and case reports in humans in order to guide the management of ventricular dysrhythmias in aconite poisoning in humans.A review of the literature in English was conducted in PubMed and Google Scholar from 1966 to July 2016 using the search terms "aconite/aconitine"; "aconite/aconitine + poisoning" and "aconite/aconitine + dysrhythmia". 168 human case-reports and case-series were identified by these searches, of which 103 were rejected if exposure to aconite did not result in ventricular dysrhythmias, if it was uncertain as to whether aconite had been ingested, if other agents were co-ingested, if there was insufficient information to determine the type of treatments administered or if there was insufficient information to determine outcome. Thus, 65 case reports of probable aconite poisoning that resulted in ventricular dysrhythmias were identified. Toxicokinetic data in aconite poisoning: Data were only available in three papers; the presence of ventricular rhythm disturbances directly correlated with the concentration of aconite alkaloids in the plasma.54 of 65 cases developed ventricular tachycardia, six developed torsades des pointes, 15 patients developed ventricular fibrillation, 10 developed ventricular ectopics and one developed a broad complex tachycardia not otherwise specified; each dysrhythmia was regarded as separate and patients may have had more than one dysrhythmia. 10 patients died, giving a mortality of 15%. In total, 147 treatments were administered to 65 patients. 46 of the interventions were assessed by the authors as having been associated with successful restoration of sinus rhythm. Flecainide administration was accompanied by dysrhythmia termination in six of seven cases. Mexiletine was connected with correcting dysrhythmias in 3 of 3 cases. Procainamide administration was associated with return to sinus rhythm in 2 of 2 cases. Prolonged cardio-pulmonary resuscitation was administered to 15 patients where it was associated with a return to sinus rhythm in nine of these. Amiodarone was linked to success in correcting dysrhythmias in 11 of 20 cases. Cardiopulmonary bypass use was associated with a return to sinus rhythm in four out of six cases. Epinephrine was documented as being employed on four occasions, and was associated with a restoration of sinus rhythm on two of these. Magnesium sulphate administration was accompanied by dysrhythmia termination in two of nine cases. Direct cardioversion was associated with a return of sinus rhythm in 5 of 30 cases. However, it is not certain whether the drug treatment influenced the course of the dysrhythmia.Based on the evidence available from human case reports, flecainaide or amiodarone appear to be more associated with a return to sinus rhythm than lidocaine and/or cardioversion, although it is not established whether the administration of treatment caused reversion to normal sinus rhythm. The potential beneficial effects of amiodarone were not observed in animal studies. This may be due to intra-species differences between ion channels or relate to the wider cardiovascular toxicity of aconite that extends beyond arrhythmias. Prolonged cardiopulmonary resuscitation and cardiopulmonary bypass should be considered as an integral part of good clinical care as "time-buying" strategies to allow the body to excrete the toxic alkaloids. There may also be a role for mexiletine, procainamide and magnesium sulphate.

Weighing up sources of evidence is a key skill for clinical decision-makers. Randomised controlled trials (RCTs) and observational studies each have advantages and disadvantages, and in both cases perceived weaknesses can be improved through modifications of design and analysis. In the field of pharmacoepidemiology, RCTs are the best way to determine whether an intervention modifies an outcome being studied, largely because randomisation reduces bias and confounding. Observational studies are useful to investigate whether benefits/harms of a treatment are seen in day-to-day clinical practice in a wider group of patients. Although observational studies, even in a small cohort, can provide very useful clinical evidence, they may also be misleading (as shown by subsequent RCTs), in part because of allocation bias. There is an unmet need for clinicians to become well-versed in appraising the study design and statistical analysis of observational pharmacoepidemiology (OP) studies, rather like the medical training already offered for RCT evaluation. This is because OP studies are likely to become more common with the computerisation of healthcare records and increasingly contribute to the evidence base available for clinical decision-making. However, when the results of an RCT conflict with the results of an OP study, the findings of the RCT should be preferred, especially if its findings have been repeated elsewhere. Conversely, OP studies that align with the findings of RCTs can provide rich and useful information to complement that generated by RCTs.

Purpose Paracetamol is one of the world’s most commonly used drugs. In overdose, it is well established to be hepatotoxic. The aim of this review was to identify factors that have been, or actually are, associated with the development of liver injury after paracetamol exposure in humans. Method Google Scholar and PubMed were searched on various dates between December 2016 and March 2017. Papers identified had their references analysed for further studies that might be relevant. Results At the time of writing, there was little good quality clinical evidence—from studies of paracetamol overdose or therapeutic use—to suggest that any groups of people are relatively protected from, or are at greater risk of, liver injury. The factors that were historically used to indicate higher risk in the UK have no good quality clinical evidence to support their re-introduction into clinical practice. The safe (and still effective) oral dose of paracetamol in patients weighing less than 50 kg has not been established. Conclusion There is no patient group that is unequivocally at elevated risk of paracetamol-induced liver toxicity. We propose two clinical scenarios that warrant further research. Firstly, there is a need to establish whether the dose of paracetamol should be reduced in patients with low body weight. Secondly, if or when genomic information regarding individual patients becomes readily available to inform prescribing, we propose the contribution of the genome to paracetamol toxicity should be re-investigated with robustly designed studies. Such studies could enhance the safe use of one of the most frequently taken drugs. Electronic supplementary material The online version of this article (10.1007/s00228-017-2356-6) contains supplementary material, which is available to authorized users.