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65 result(s) for "Bishop, Jen"
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Rapid Epidemiological Analysis of Comorbidities and Treatments as risk factors for COVID-19 in Scotland (REACT-SCOT): A population-based case-control study
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. 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. 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.
Relation of severe COVID-19 to polypharmacy and prescribing of psychotropic drugs: the REACT-SCOT case-control study
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
Recruiting and retaining healthcare workers in Scotland to a longitudinal COVID-19 study: a descriptive analysis
Background Rapid timescales for the design and delivery of research were common during the COVID-19 pandemic. The recruitment and retention of healthcare workers (HCWs) as participants in research studies are notoriously challenging, but this was exacerbated during the pandemic by the unprecedented demand placed on the workforce. The SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN study) is a prospective multicentre cohort study following HCWs in the UK. This paper discusses the strategies and challenges associated with recruitment and retention of HCW participants in Scotland. Methods There were 44,546 HCWs recruited to the SIREN study, of whom 6,285 were recruited by research teams at ten different research sites in Scotland between October 2020 and March 2021. Information on target and actual sample size, availability of resource, recruitment rate, and recruitment and engagement strategies by site was collated from SIREN study documentation and discussions with local key SIREN site staff. Individual-level data from 6,153 HCW participants with ongoing consent for all data usage were also collated, including socio-demographic data and information on withdrawal (in first year) and opt-in to a study extension after one year. Factors associated with these outcomes were explored in logistic regression analyses. Results Different recruitment strategies were used in each site according to local agreements, protocol and staff capacity, with the recruitment period ranging from 13 to 160 days. The locally-agreed recruitment target was met in four sites. The proportion of participants who withdrew in the first year ranged from 3.1 to 24.8% by site, while subsequent opt-in to a 12-month study extension ranged from 28.6 to 74.8%. The sites with the highest proportions of withdrawals were the same four sites with lowest proportions of opt-in. On an individual level, there was a lower level of retention among younger participants, and those from lower socio-economic backgrounds and minority ethnic groups. Conclusions Site-specific factors including research-readiness likely had a significant influence on recruitment and retention, more so than the specific recruitment or retention strategies employed. Independent of site factors, individual-level variables influenced recruitment and retention, suggesting targeted strategies may be needed to promote research engagement among particular socio-demographic groups.
Relation of severe COVID-19 in Scotland to transmission-related factors and risk conditions eligible for shielding support: REACT-SCOT case-control study
Background Clinically vulnerable individuals have been advised to shield themselves during the COVID-19 epidemic. The objectives of this study were to investigate (1) the rate ratio of severe COVID-19 associated with eligibility for the shielding programme in Scotland across the first and second waves of the epidemic and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population. Methods In a matched case-control design, all 178,578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 18 February 2021 were matched for age, sex and primary care practice to 1,744,283 controls from the general population. This dataset (REACT-SCOT) was linked to the list of 212,702 individuals identified as eligible for shielding. Severe COVID-19 was defined as cases that entered critical care or were fatal. Rate ratios were estimated by conditional logistic regression. Results With those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020. Conclusions The effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. Mitigating the impact of the epidemic requires control of nosocomial transmission.
Association of cerebral venous thrombosis with recent COVID-19 vaccination: case-crossover study using ascertainment through neuroimaging in Scotland
Background To investigate the association of primary acute cerebral venous thrombosis (CVT) with COVID-19 vaccination through complete ascertainment of all diagnosed CVT in the population of Scotland. Methods Case-crossover study comparing cases of CVT recently exposed to vaccination (1–14 days after vaccination) with cases less recently exposed. Cases in Scotland from 1 December 2020 were ascertained through neuroimaging studies up to 17 May 2021 and diagnostic coding of hospital discharges up to 28 April 2021, linked to national vaccination records. The main outcome measure was primary acute CVT. Results Of 50 primary acute CVT cases, 29 were ascertained only from neuroimaging studies, 2 were ascertained only from hospital discharges, and 19 were ascertained from both sources. Of these 50 cases, 14 had received the Astra-Zeneca ChAdOx1 vaccine and 3 the Pfizer BNT162b2 vaccine. The incidence of CVT per million doses in the first 14 days after vaccination was 2.2 (95% credible interval 0.9 to 4.1) for ChAdOx1 and 1 (95% credible interval 0.1 to 2.9) for BNT162b2. The rate ratio for CVT associated with exposure to ChAdOx1 in the first 14 days compared with exposure 15-84 days after vaccination was 3.2 (95% credible interval 1.1 to 9.5). Conclusions These findings support a causal association between CVT and the AstraZeneca vaccine. The absolute risk of post-vaccination CVT in this population-wide study in Scotland was lower than has been reported for populations in Scandinavia and Germany; the explanation for this is not clear.
SARS-CoV-2 vaccine uptake and risks of severe COVID-19 disease among people prescribed opioid agonist therapy in Scotland
BackgroundThere is limited evidence quantifying the risk of severe COVID-19 disease among people with opioid dependence. We examined vaccine uptake and severe disease (admission to critical care or death with COVID-19) among individuals prescribed opioid agonist therapy (OAT).MethodA case–control design was used to examine vaccine uptake in those prescribed OAT compared with the general population, and the association between severe disease and OAT. In both analyses, 10 controls from the general population were matched (to each OAT recipient and COVID-19 case, respectively) according to socio-demographic factors. Conditional logistic regression was used to estimate rate ratios (RR) for severe disease.ResultsVaccine uptake was markedly lower in the OAT cohort (dose 1: 67%, dose 2: 53% and dose 3: 31%) compared with matched controls (76%, 72% and 57%, respectively). Those prescribed OAT within the last 5 years, compared with those not prescribed, had increased risk of severe COVID-19 (RR 3.38, 95% CI 2.75 to 4.15), particularly in the fourth wave (RR 6.58, 95% CI 4.20 to 10.32); adjustment for comorbidity and vaccine status attenuated this risk (adjusted RR (aRR) 2.43, 95% CI 1.95 to 3.02; wave 4 aRR 3.78, 95% CI 2.30 to 6.20). Increased risk was also observed for those prescribed OAT previously (>3 months ago) compared with recently (aRR 1.74, 95% CI 1.11 to 2.71).ConclusionsThe widening gap in vaccine coverage for those prescribed OAT, compared with the general population, is likely to have exacerbated the risk of severe COVID-19 in this population over the pandemic. However, continued OAT use may have provided protection from severe COVID-19 among those with opioid dependence.
Risk of hospital admission with covid-19 among teachers compared with healthcare workers and other adults of working age in Scotland, March 2020 to July 2021: population based case-control study
AbstractObjectiveTo determine the risk of hospital admission with covid-19 and severe covid-19 among teachers and their household members, overall and compared with healthcare workers and adults of working age in the general population.DesignPopulation based nested case-control study.SettingScotland, March 2020 to July 2021, during defined periods of school closures and full openings in response to covid-19.ParticipantsAll cases of covid-19 in adults aged 21 to 65 (n=132 420) and a random sample of controls matched on age, sex, and general practice (n=1 306 566). Adults were identified as actively teaching in a Scottish school by the General Teaching Council for Scotland, and their household members were identified through the unique property reference number. The comparator groups were adults identified as healthcare workers in Scotland, their household members, and the remaining general population of working age.Main outcome measuresThe primary outcome was hospital admission with covid-19, defined as having a positive test result for SARS-CoV-2 during hospital admission, being admitted to hospital within 28 days of a positive test result, or receiving a diagnosis of covid-19 on discharge from hospital. Severe covid-19 was defined as being admitted to intensive care or dying within 28 days of a positive test result or assigned covid-19 as a cause of death.ResultsMost teachers were young (mean age 42), were women (80%), and had no comorbidities (84%). The risk (cumulative incidence) of hospital admission with covid-19 was <1% for all adults of working age in the general population. Over the study period, in conditional logistic regression models adjusted for age, sex, general practice, race/ethnicity, deprivation, number of comorbidities, and number of adults in the household, teachers showed a lower risk of hospital admission with covid-19 (rate ratio 0.77, 95% confidence interval 0.64 to 0.92) and of severe covid-19 (0.56, 0.33 to 0.97) than the general population. In the first period when schools in Scotland reopened, in autumn 2020, the rate ratio for hospital admission in teachers was 1.20 (0.89 to 1.61) and for severe covid-19 was 0.45 (0.13 to 1.55). The corresponding findings for household members of teachers were 0.91 (0.67 to 1.23) and 0.73 (0.37 to 1.44), and for patient facing healthcare workers were 2.08 (1.73 to 2.50) and 2.26 (1.43 to 3.59). Similar risks were seen for teachers in the second period, when schools reopened in summer 2021. These values were higher than those seen in spring/summer 2020, when schools were mostly closed.ConclusionCompared with adults of working age who are otherwise similar, teachers and their household members were not found to be at increased risk of hospital admission with covid-19 and were found to be at lower risk of severe covid-19. These findings should reassure those who are engaged in face-to-face teaching.
Epidemiology of SARS-CoV-2 during the first three waves in Scotland: a national record linkage study
BackgroundThe early COVID-19 pandemic in Scotland—defined as the era before widespread access to vaccination and monoclonal antibody treatment—can be characterised into three distinct waves: March–July 2020, July 2020–April 2021 and May–August 2021. Each wave was met with various societal restrictions in an effort to reduce disease transmission and associated morbidity and mortality. Understanding the epidemiology of infections during these waves can provide valuable insights into future pandemic planning.MethodsScottish RT-PCR testing data reported up until 8 August 2021, the day prior to most restrictions being lifted in Scotland, were included. Demographic characteristics including age, sex and social deprivation associated with transmission, morbidity and mortality were compared across waves. A case–control analysis for each wave was then modelled to further compare risk factors associated with death over time.ResultsOf the 349 904 reported cases, there were 18 099, 197 251 and 134 554 in waves 1, 2 and 3, respectively. Hospitalisations, intensive care unit admissions and deaths appeared highest in wave 2, though risk factors associated with COVID-19 death remained similar across the waves. Higher deprivation and certain comorbidities were associated with higher deaths in all waves.ConclusionsDespite the higher number of cases reported in waves 2 and 3, case fatality rates were lower: likely a combination of improved detection of infections in younger age groups, introduction of social measures and vaccination. Higher social deprivation and comorbidities resulted in higher deaths for all waves.
Comparing Predicted Probability of Hepatocellular Carcinoma in Patients With Cirrhosis With the General Population: An Opportunity to Improve Risk Communication?
INTRODUCTION:Risk scores estimating a patient's probability of a hepatocellular carcinoma (HCC) diagnosis are abundant but are difficult to interpret in isolation. We compared the predicted HCC probability for individuals with cirrhosis and cured hepatitis C with the general population (GP).METHODS:All patients with cirrhosis achieving sustained viral response (SVR) in Scotland by April 2018 were included (N = 1,803). The predicted 3-year probability of HCC at time of SVR achievement was determined using the aMAP prognostic model. GP data on the total number of incident HCCs in Scotland, stratified by demographics, were obtained from Public Health Scotland. Predicted HCC risk of cirrhosis SVR patients was compared with GP incidence using 2 metrics: (i) incidence ratio: i.e., 3-year predicted probability for a given patient divided by the 3-year probability in GP for the equivalent demographic group and (ii) absolute risk difference: the 3-year predicted probability minus the 3-year probability in the GP.RESULTS:The mean predicted 3-year HCC probability among cirrhosis SVR patients was 3.64% (range: 0.012%-36.12%). Conversely, the 3-year HCC probability in the GP was much lower, ranging from <0.0001% to 0.25% depending on demographics. The mean incidence ratio was 410, ranging from 5 to >10,000. The mean absolute risk difference was 3.61%, ranging from 0.012% to 35.9%. An online HCC-GP comparison calculator for use by patients/clinicians is available at https://thrive-svr.shinyapps.io/RShiny/.DISCUSSION:Comparing a patient's predicted HCC probability with the GP is feasible and may help clinicians communicate risk information and encourage screening uptake.
Comparing Predicted Probability of Hepatocellular Carcinoma in Patients With Cirrhosis With the General Population: An Opportunity to Improve Risk Communication?
Risk scores estimating a patient's probability of a hepatocellular carcinoma (HCC) diagnosis are abundant but are difficult to interpret in isolation. We compared the predicted HCC probability for individuals with cirrhosis and cured hepatitis C with the general population (GP). All patients with cirrhosis achieving sustained viral response (SVR) in Scotland by April 2018 were included (N = 1,803). The predicted 3-year probability of HCC at time of SVR achievement was determined using the aMAP prognostic model. GP data on the total number of incident HCCs in Scotland, stratified by demographics, were obtained from Public Health Scotland. Predicted HCC risk of cirrhosis SVR patients was compared with GP incidence using 2 metrics: (i) incidence ratio: i.e., 3-year predicted probability for a given patient divided by the 3-year probability in GP for the equivalent demographic group and (ii) absolute risk difference: the 3-year predicted probability minus the 3-year probability in the GP. The mean predicted 3-year HCC probability among cirrhosis SVR patients was 3.64% (range: 0.012%-36.12%). Conversely, the 3-year HCC probability in the GP was much lower, ranging from <0.0001% to 0.25% depending on demographics. The mean incidence ratio was 410, ranging from 5 to >10,000. The mean absolute risk difference was 3.61%, ranging from 0.012% to 35.9%. An online HCC-GP comparison calculator for use by patients/clinicians is available at https://thrive-svr.shinyapps.io/RShiny/ . Comparing a patient's predicted HCC probability with the GP is feasible and may help clinicians communicate risk information and encourage screening uptake.