Continued high rates of antibiotic prescribing to adults with respiratory tract infection: survey of 568 UK general practices

OBJECTIVES: Overutilisation of antibiotics may contribute to the emergence of antimicrobial drug resistance, a growing international concern. This study aimed to analyse the performance of UK general practices with respect to antibiotic prescribing for respiratory tract infections (RTIs) among young and middle-aged adults.SETTING: Data are reported for 568 UK general practices contributing to the Clinical Practice Research Datalink.PARTICIPANTS: Participants were adults aged 18-59?years. Consultations were identified for acute upper RTIs including colds, cough, otitis-media, rhino-sinusitis and sore throat.PRIMARY AND SECONDARY OUTCOME MEASURES: For each consultation, we identified whether an antibiotic was prescribed. The proportion of RTI consultations with antibiotics prescribed was estimated.RESULTS: There were 568 general practices analysed. The median general practice prescribed antibiotics at 54% of RTI consultations. At the highest prescribing 10% of practices, antibiotics were prescribed at 69% of RTI consultations. At the lowest prescribing 10% of practices, antibiotics were prescribed at 39% RTI consultations. The median practice prescribed antibiotics at 38% of consultations for 'colds and upper RTIs', 48% for 'cough and bronchitis', 60% for 'sore throat', 60% for 'otitis-media' and 91% for 'rhino-sinusitis'. The highest prescribing 10% of practices issued antibiotic prescriptions at 72% of consultations for 'colds', 67% for 'cough', 78% for 'sore throat', 90% for 'otitis-media' and 100% for 'rhino-sinusitis'.CONCLUSIONS: Most UK general practices prescribe antibiotics to young and middle-aged adults with respiratory infections at rates that are considerably in excess of what is clinically justified. This will fuel antibiotic resistance.<br/

Incidence of type 2 diabetes after bariatric surgery: population-based matched cohort study

Background:- The effect of currently used bariatric surgical procedures on the development of diabetes in obese people is not well defined. We aimed to assess the effect of bariatric surgery on development of type 2 diabetes in a large population of obese individuals. Methods:- We did a matched cohort study of adults (age 20–100 years) identified from a UK-wide database of family practices, who were obese (BMI ≥30 kg/m2) and did not have diabetes. We enrolled 2167 patients who had undergone bariatric surgery between Jan 1, 2002, and April 30, 2014, and matched them—according to BMI, age, sex, index year, and HbA1c—with 2167 controls who had not had surgery. Procedures included laparoscopic gastric banding (n=1053), gastric bypass (795), and sleeve gastrectomy (317), with two procedures undefined. The primary outcome was development of clinical diabetes, which we extracted from electronic health records. Analyses were adjusted for matching variables, comorbidity, cardiovascular risk factors, and use of antihypertensive and lipid-lowering drugs. Findings:- During a maximum of 7 years of follow-up (median 2·8 years [IQR 1·3–4·5]), 38 new diagnoses of diabetes were made in bariatric surgery patients and 177 were made in controls. By the end of 7 years of follow-up, 4·3% (95% CI 2·9–6·5) of bariatric surgery patients and 16·2% (13·3–19·6) of matched controls had developed diabetes. The incidence of diabetes diagnosis was 28·2 (95% CI 24·4–32·7) per 1000 person-years in controls and 5·7 (4·2–7·8) per 1000 person-years in bariatric surgery patients; the adjusted hazard ratio was 0·20 (95% CI 0·13–0·30, p<0·0001). This estimate was robust after varying the comparison group in sensitivity analyses, excluding gestational diabetes, or allowing for competing mortality risk. Interpretation:- Bariatric surgery is associated with reduced incidence of clinical diabetes in obese participants without diabetes at baseline for up to 7 years after the procedure

Potential gains in life expectancy from reducing amenable mortality among people diagnosed with serious mental illness in the United Kingdom.

BACKGROUND: To estimate the potential gain in life expectancy from addressing modifiable risk factors for all-cause mortality (excluding suicide and deaths from accidents or violence) across specific serious mental illness (SMI) subgroups, namely schizophrenia, schizoaffective disorders, and bipolar disorders in a Western population. METHODS: We have used relative risks from recent meta-analyses to estimate the population attribution fraction (PAF) due to specific modifiable risk factors known to be associated with all-cause mortality within SMI. The potential gain in life expectancy at birth, age 50 and age 65 years were assessed by estimating the combined effect of modifiable risk factors from different contextual levels (behavioural, healthcare, social) and accounting for the effectiveness of existing interventions tackling these factors. Projections for annual gain in life expectancy at birth during a two-decade was estimated using the Annual Percentage Change (APC) formula. The predicted estimates were based on mortality rates for year 2014-2015. RESULTS: Based on the effectiveness of existing interventions targeting these modifiable risk factors, we estimated potential gain in life expectancy at birth of four (bipolar disorders), six (schizoaffective disorders), or seven years (schizophrenia). The gain in life expectancy at age 50 years was three (bipolar disorders) or five (schizophrenia and schizoaffective disorders) years. The projected gain in life expectancy at age 65 years was three (bipolar disorders) or four (schizophrenia and schizoaffective disorders) years. CONCLUSIONS: The implementation of existing interventions targeting modifiable risk factors could narrow the current mortality gap between the general and the SMI populations by 24% (men) to 28% (women). These projections represent ideal circumstances and without the limitation of overestimation which often comes with PAFs

Severe mental illnesses and mortality following COVID-19 infection: Data linkage study using the Clinical Practice Research Database (CPRD).

Background The association of COVID-19 infection with death in people with severe mental illnesses (SMI), and the relationship to multimorbidities/ underlying health conditions ethnicity is unclear. Health records linked to COVID-19 tests data could help to inform this knowledge gap. Objective To determine the risk of death in people with SMI following COVID-19 infection compared to reference groups and assess whether excess mortality is accounted through underlying health conditions or further elevated in minority ethnic groups. Design, setting and participants Nationally representative cohort study using primary care data from the Clinical Practice Research Database (CPRD), with participants followed from the start of the pandemic in 2020, for 1.5 years, covering England, Wales and Northern Ireland. For consenting practices, CPRD data was linked to COVID-19 data Public Health England (PHE) Second Generation Surveillance System (SGSS), PHE COVID-19 Hospitalisation in England Surveillance System (CHESS), and Intensive Care National Audit and Research Centre (ICNARC) data on COVID-10 intensive care admissions. The cohort comprised 795,836 individuals, with 7,493 individuals with SMI and a positive COVID-19 test (“SMI/COVID-19”). Comparison groups were: 2,325 individuals with SMI/ testing negative for COVID-19 (“SMI/ non COVID-19”), 657,414 individuals from a non-SMI group/ testing positive for COVID-19 (“non-SMI/ COVID-19”), and 128,604 individuals from a non-SMI group/ testing negative for COVID-19 (“non-SMI/ non-COVID-19”). Exposures SMI defined as the presence of schizophrenia, schizoaffective disorder, bipolar disorder, or affective disorders with psychosis, according to the International Classification of Mental Disorders (ICD-10). COVID-19 diagnoses identified through confirmed laboratory tests and clinical diagnoses. Outcomes All-cause mortality Results A higher proportion of SMI patients with COVID-19 were obese (37% versus 22% in the non-SMI/non-COVID-19 group), current smokers (27% versus 23% in the non-SMI/non-COVID-19 group), had underlying health conditions, and were Black Caribbean/ Black African (5% versus 1% in the non-SMI/non-COVID-19 group). Relative to the non-SMI/ non-COVID-19 group, the SMI/ COVID-19 group had an elevated risk of death (age and sex-adjusted hazard ratio (aHR) 5.03 (95%CI: 4.61-5.54)). This was elevated to a lesser extent, in the SMI/ non COVID-19 group (aHR: 1.93 (95%CI: 1.54-2.41)) and in the non-SMI/ COVID-19 group (aHR: 2.85 (95%CI: 2.72-2.98). Excess risk persisted after adjusting for tobacco use, weight and comorbidities. Mortality trends were similar across groups by ethnicity. Risk of death was highest for the SMI/ COVID-19 group during the first wave of infection in the UK, however excess mortality was still evident and substantially elevated at the second wave also. Conclusions People living with SMI are at an increased risk of death compared to population controls; this excess risk is further elevated following COVID-19 infection, with similar trends by ethnicity. Underlying health conditions only partially account for deaths following COVID-19 infection in this group

Depressive symptoms during early adulthood and the development of physical multimorbidity in the UK: an observational cohort study

Background An understanding of whether early-life depression is associated with physical multimorbidity could be instrumental for the development of preventive measures and the integrated management of depression. We therefore aimed to map out the cumulative incidence of physical multimorbidity over adulthood, and to determine the association between the presence of depressive symptoms during early adulthood and the development of physical multimorbidity in middle age. Methods In this observational cohort study, we used pooled data from the 1958 National Child Development Study (NCDS) and the 1970 British Cohort Study (BCS). Cohort waves were pooled in each decade of adult life available (when cohort members were aged 26 years in the BCS and 23 years in the NCDS [baseline]; 34 years in the BCS and 33 years in the NCDS [age 34 BCS/33 NCDS]; 42 years in the BCS and NCDS [age 42 BCS/NCDS]; and 46 years in the BCS and 50 years in the NCDS [age 46 BCS/50 NCDS]). We included participants who had completed the nine-item Malaise Inventory at baseline, and did not have a history of physical multimorbidity, any physical multimorbidity at baseline, or the presence of depressive symptoms before the development of physical multimorbidity. The presence of depressive symptoms was determined using the nine-item Malaise Inventory (cutoff score ≥4). Physical multimorbidity was defined as having at least two measures of any of the following ten self-reported groups of long-term conditions: asthma or bronchitis; backache; bladder or kidney conditions; cancer; cardiovascular conditions; convulsions or epilepsy; diabetes; hearing conditions; migraine; and stomach, bowel, or gall conditions. Cumulative incidence (with 95% CI) of physical multimorbidity was calculated for each decade considered after baseline, with physical multimorbidity being assessed as both a dichotomous and categorical variable. The association between depressive symptoms and the development of physical multimorbidity was assessed using adjusted relative risk ratios (with 95% CIs). Findings Analyses included 15 845 participants, of whom 4001 (25·25%; 95% CI 24·57–25·93) had depressive symptoms at baseline and 11 844 (74·75%; 74·07–75·42) did not. The cumulative incidence of physical multimorbidity (dichotomous) ranged over the study period from 2263 (18·44%; 95% CI 17·75–18·14) of 12 273 participants at age 34 BCS/33 NCDS, to 4496 (42·90%; 41·95–43·85) of 10 481 participants at age 46 BCS/50 NCDS, and was consistently higher in participants with depressive symptoms at baseline. The adjusted relative risk of physical multimorbidity was higher in participants with depressive symptoms than in those without and remained stable over the study period (adjusted relative rate ratio 1·67, 95% CI 1·50–1·87, at age 34 BCS/33 NCDS; 1·63, 1·48–1·79, at age 42 BCS/NCDS; and 1·58, 1·43–1·73, at age 46 BCS/50 NCDS). Interpretation The presence of depressive symptoms during early adulthood is associated with an increased risk of the development of physical multimorbidity in middle age. Although further research about the drivers of this relationship is needed, these results could help to enhance the integrated management of individuals with depressive symptoms and the development of preventive strategies to reduce the effect and burden of physical multimorbidity

Utility of electronic patient records in primary care for stroke secondary prevention trials

BACKGROUND: This study aimed to inform the design of a pragmatic trial of stroke prevention in primary care by evaluating data recorded in electronic patient records (EPRs) as potential outcome measures. The study also evaluated achievement of recommended standards of care; variation between family practices; and changes in risk factor values from before to after stroke.METHODS: Data from the UK General Practice Research Database (GPRD) were analysed for 22,730 participants with an index first stroke between 2003 and 2006 from 414 family practices. For each subject, the EPR was evaluated for the 12 months before and after stroke. Measures relevant to stroke secondary prevention were analysed including blood pressure (BP), cholesterol, smoking, alcohol use, body mass index (BMI), atrial fibrillation, utilisation of antihypertensive, antiplatelet and cholesterol lowering drugs. Intraclass correlation coefficients (ICC) were estimated by family practice. Random effects models were fitted to evaluate changes in risk factor values over time.RESULTS: In the 12 months following stroke, BP was recorded for 90%, cholesterol for 70% and body mass index (BMI) for 47%. ICCs by family practice ranged from 0.02 for BP and BMI to 0.05 for LDL and HDL cholesterol. For subjects with records available both before and after stroke, the mean reductions from before to after stroke were: mean systolic BP, 6.02 mm Hg; diastolic BP, 2.78 mm Hg; total cholesterol, 0.60 mmol/l; BMI, 0.34 Kg/m2. There was an absolute reduction in smokers of 5% and heavy drinkers of 4%. The proportion of stroke patients within the recommended guidelines varied from less than a third (29%) for systolic BP, just over half for BMI (54%), and over 90% (92%) on alcohol consumption.CONCLUSIONS: Electronic patient records have potential for evaluation of outcomes in pragmatic trials of stroke secondary prevention. Stroke prevention interventions in primary care remain suboptimal but important reductions in vascular risk factor values were observed following stroke. Better recording of lifestyle factors in the GPRD has the potential to expand the scope of the GPRD for health care research and practice

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK