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 crossvalidated predictive model of fatal or critical care unit-treated COVID-19 among people with diabetes. MethodsIn 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 onMarch 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<0•0001, compared with the risk in those without diabetes. The OR was 2•396 (1•815-3•163; p<0•0001) in type 1 diabetes and 1•369 (1•276-1•468; p<0•0001) in type 2 diabetes. Among people with diabetes, adjusted for age, sex, and diabetes duration and type, those who developed fatal or critical care unit-treated COVID-19 were more likely to be male, live in residential care or a more deprived area, have a COVID-19 risk condition, retinopathy, reduced renal function, or worse glycaemic control, have had a diabetic ketoacidosis or hypoglycaemia hospitalisation in the past 5 years, be on more...

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.

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

PurposeParacetamol 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.MethodGoogle 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.ResultsAt 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.ConclusionThere 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 materialThe online version of this article (10.1007/s00228-017-2356-6) contains supplementary material, which is available to authorized users.

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.

OBJECTIVE Studies using claims databases reported that SARS-CoV-2 infection &gt;30 days earlier was associated with an increase in the incidence of type 1 diabetes. Using exact dates of diabetes diagnosis from the national register in Scotland linked to virology laboratory data, we sought to replicate this finding. RESEARCH DESIGN AND METHODS A cohort of 1,849,411 individuals aged &lt;35 years without diabetes, including all those in Scotland who subsequently tested positive for SARS-CoV-2, was followed from 1 March 2020 to 22 November 2021. Incident type 1 diabetes was ascertained from the national registry. Using Cox regression, we tested the association of time-updated infection with incident diabetes. Trends in incidence of type 1 diabetes in the population from 2015 through 2021 were also estimated in a generalized additive model. RESULTS There were 365,080 individuals who had at least one detected SARS-CoV-2 infection during follow-up and 1074 who developed type 1 diabetes. The rate ratio for incident type 1 diabetes associated with first positive test for SARS-CoV-2 (reference category: no previous infection) was 0.86 (95% CI 0.62, 1.21) for infection &gt;30 days earlier and 2.62 (95% CI 1.81, 3.78) for infection in the previous 30 days. However, negative and positive SARS-CoV-2 tests were more frequent in the days surrounding diabetes presentation. In those aged 0–14 years, incidence of type 1 diabetes during 2020–2021 was 20% higher than the 7-year average. CONCLUSIONS Type 1 diabetes incidence in children increased during the pandemic. However, the cohort analysis suggests that SARS-CoV-2 infection itself was not the cause of this increase.

Background Acetylcysteine (NAC) is effective at preventing liver injury after paracetamol overdose. The Scottish and Newcastle Anti-emetic Pre-treatment for Paracetamol Poisoning (SNAP) Study demonstrated that a 12 h NAC regimen was associated with fewer adverse drug reactions compared with the standard 21 h regimen. Here, we describe the clinical effectiveness of the SNAP NAC regimen. Methods The SNAP regimen, consisting of intravenous NAC 100 mg/kg over 2 h then 200 mg/kg over 10 h, was introduced to treat all paracetamol overdose patients at the Royal Infirmary of Edinburgh, the Royal Victoria Infirmary, Newcastle and St Thomas' Hospital, London. Patient data were prospectively and systematically collected before and after the change in treatment (total patients N = 3340, 21 h N = 1488, SNAP N = 1852). Health record linkage was used to determine patient outcome after hospital discharge. Findings There was no difference in liver injury or liver synthetic dysfunction between regimens. Hepatotoxicity (peak ALT > 1000 U/L) occurred in 64 (4.3%) and 67 (3.6%) patients, respectively, in the 21 h and SNAP groups (absolute difference − 0.7%, 95% CI − 2.1 to 0.6). Multivariable logistic regression did not identify treatment regimen as an outcome-associated factor. No patients were readmitted to hospital with, or died from, liver failure within 30 days of discharge. Anti-histamine treatment (for NAC anaphylactoid drug reactions) was prescribed for 163 (11.0%) patients with the 21 h regimen and 37 (2.0%) patients with the SNAP regimen (absolute difference 9.0% (95% CI 7.3 to 10.7)). Interpretation In clinical use the SNAP regimen has similar efficacy as standard therapy for preventing liver injury and produces fewer adverse reactions.

Aims/hypothesis Dapagliflozin, a sodium-glucose cotransporter 2 (SGLT2) inhibitor, is indicated for improving glycaemic control in type 2 diabetes mellitus. Whether its effects on HbA 1c and other variables, including safety outcomes, in clinical trials are obtained in real-world practice needs to be established. Methods 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 HbA 1c , 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. Results Among 8566 people exposed to dapagliflozin over a median of 210 days the crude within-person change in HbA 1c 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 HbA 1c 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/m 2 (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. Conclusions/interpretation Dapagliflozin exposure was associated with reductions in HbA 1c , SBP, body weight and BMI that were at least as large as in clinical trials. Dapagliflozin also prevented the expected rise in HbA 1c and SBP over the period of study.