Recovery of kidney function after acute kidney disease-a multi-cohort analysis.

BACKGROUND: There are no consensus definitions for evaluating kidney function recovery after acute kidney injury (AKI) and acute kidney disease (AKD), nor is it clear how recovery varies across populations and clinical subsets. We present a federated analysis of four population-based cohorts from Canada, Denmark and Scotland, 2011-18. METHODS: We identified incident AKD defined by serum creatinine changes within 48 h, 7 days and 90 days based on KDIGO AKI and AKD criteria. Separately, we applied changes up to 365 days to address widely used e-alert implementations that extend beyond the KDIGO AKI and AKD timeframes. Kidney recovery was based on resolution of AKD and a subsequent creatinine measurement below 1.2× baseline. We evaluated transitions between non-recovery, recovery and death up to 1 year; within age, sex and comorbidity subgroups; between subset AKD definitions; and across cohorts. RESULTS: There were 464 868 incident cases, median age 67-75 years. At 1 year, results were consistent across cohorts, with pooled mortalities for creatinine changes within 48 h, 7 days, 90 days and 365 days (and 95% confidence interval) of 40% (34%-45%), 40% (34%-46%), 37% (31%-42%) and 22% (16%-29%) respectively, and non-recovery of kidney function of 19% (15%-23%), 30% (24%-35%), 25% (21%-29%) and 37% (30%-43%), respectively. Recovery by 14 and 90 days was frequently not sustained at 1 year. Older males and those with heart failure or cancer were more likely to die than to experience sustained non-recovery, whereas the converse was true for younger females and those with diabetes. CONCLUSION: Consistently across multiple cohorts, based on 1-year mortality and non-recovery, KDIGO AKD (up to 90 days) is at least prognostically similar to KDIGO AKI (7 days), and covers more people. Outcomes associated with AKD vary by age, sex and comorbidities such that older males are more likely to die, and younger females are less likely to recover.

True prevalence of long-COVID in a nationwide, population cohort study.

Long-COVID prevalence estimates vary widely and should take account of symptoms that would have occurred anyway. Here we determine the prevalence of symptoms attributable to SARS-CoV-2 infection, taking account of background rates and confounding, in a nationwide population cohort study of 198,096 Scottish adults. 98,666 (49.8%) had symptomatic laboratory-confirmed SARS-CoV-2 infections and 99,430 (50.2%) were age-, sex-, and socioeconomically-matched and never-infected. While 41,775 (64.5%) reported at least one symptom 6 months following SARS-CoV-2 infection, this was also true of 34,600 (50.8%) of those never-infected. The crude prevalence of one or more symptom attributable to SARS-CoV-2 infection was 13.8% (13.2%,14.3%), 12.8% (11.9%,13.6%), and 16.3% (14.4%,18.2%) at 6, 12, and 18 months respectively. Following adjustment for potential confounders, these figures were 6.6% (6.3%, 6.9%), 6.5% (6.0%, 6.9%) and 10.4% (9.1%, 11.6%) respectively. Long-COVID is characterised by a wide range of symptoms that, apart from altered taste and smell, are non-specific. Care should be taken in attributing symptoms to previous SARS-CoV-2 infection.

Natural history of long-COVID in a nationwide, population cohort study.

Previous studies on the natural history of long-COVID have been few and selective. Without comparison groups, disease progression cannot be differentiated from symptoms originating from other causes. The Long-COVID in Scotland Study (Long-CISS) is a Scotland-wide, general population cohort of adults who had laboratory-confirmed SARS-CoV-2 infection matched to PCR-negative adults. Serial, self-completed, online questionnaires collected information on pre-existing health conditions and current health six, 12 and 18 months after index test. Of those with previous symptomatic infection, 35% reported persistent incomplete/no recovery, 12% improvement and 12% deterioration. At six and 12 months, one or more symptom was reported by 71.5% and 70.7% respectively of those previously infected, compared with 53.5% and 56.5% of those never infected. Altered taste, smell and confusion improved over time compared to the never infected group and adjusted for confounders. Conversely, late onset dry and productive cough, and hearing problems were more likely following SARS-CoV-2 infection.

Inequalities in children's mental health care: analysis of routinely collected data on prescribing and referrals to secondary care.

BACKGROUND: One in eight children in the United Kingdom are estimated to have a mental health condition, and many do not receive support or treatment. The COVID-19 pandemic has negatively impacted mental health and disrupted the delivery of care. Prevalence of poor mental health is not evenly distributed across age groups, by sex or socioeconomic groups. Equity in access to mental health care is a policy priority but detailed socio-demographic trends are relatively under-researched. METHODS: We analysed records for all mental health prescriptions and referrals to specialist mental health outpatient care between the years of 2015 and 2021 for children aged 2 to 17 years in a single NHS Scotland health board region. We analysed trends in prescribing, referrals, and acceptance to out-patient treatment over time, and measured differences in treatment and service use rates by age, sex, and area deprivation. RESULTS: We identified 18,732 children with 178,657 mental health prescriptions and 21,874 referrals to specialist outpatient care. Prescriptions increased by 59% over the study period. Boys received double the prescriptions of girls and the rate of prescribing in the most deprived areas was double that in the least deprived. Mean age at first mental health prescription was almost 1 year younger in the most deprived areas than in the least. Referrals increased 9% overall. Initially, boys and girls both had an annual referral rate of 2.7 per 1000, but this fell 6% for boys and rose 25% for girls. Referral rate for the youngest decreased 67% but increased 21% for the oldest. The proportion of rejected referrals increased steeply since 2020 from 17 to 30%. The proportion of accepted referrals that were for girls rose to 62% and the mean age increased 1.5 years. CONCLUSIONS: The large increase in mental health prescribing and changes in referrals to specialist outpatient care aligns with emerging evidence of increasing poor mental health, particularly since the start of the COVID-19 pandemic. The static size of the population accepted for specialist treatment amid greater demand, and the changing demographics of those accepted, indicate clinical prioritisation and unmet need. Persistent inequities in mental health prescribing and referrals require urgent action.

Care processes and outcomes of deprivation across the clinical course of kidney disease: findings from a high-income country with universal healthcare.

BACKGROUND: No single study contrasts the extent and consequences of inequity of kidney care across the clinical course of kidney disease. METHODS: This population study of Grampian (UK) followed incident presentations of acute kidney injury (AKI) and incident estimated glomerular filtration rate (eGFR) thresholds of <60, <45 and <30 mL/min/1.73 m2 in separate cohorts (2011-2021). The key exposure was area-level deprivation (lowest quintile of the Scottish Index of Multiple Deprivation). Outcomes were care processes (monitoring, prescribing, appointments, unscheduled care), long-term mortality and kidney failure. Modelling involved multivariable logistic regression, negative binomial regression and cause-specific Cox models with and without adjustment of comorbidities. RESULTS: There were 41 313, 51 190, 32 171 and 17 781 new presentations of AKI and eGFR thresholds <60, <45 and <30  mL/min/1.73 m2. A total of 6.1-7.8% of the population was from deprived areas and (versus all others) presented on average 5 years younger, with more diabetes and pulmonary and liver disease. Those from deprived areas were more likely to present initially in hospital, less likely to receive community monitoring, less likely to attend appointments and more likely to have an unplanned emergency department or hospital admission episode. Deprivation had the greatest association with long-term kidney failure at the eGFR <60 mL/min/1.73 m2 threshold {adjusted hazard ratio [HR] 1.48 [95% confidence interval (CI) 1.17-1.87]} and this association decreased with advancing disease severity [HR 1.09 (95% CI 0.93-1.28) at eGFR <30 mL/min/1.73 m2), with a similar pattern for mortality. Across all analyses the most detrimental associations of deprivation were an eGFR threshold <60 mL/min/1.73 m2, AKI, males and those <65 years of age. CONCLUSIONS: Even in a high-income country with universal healthcare, serious and consistent inequities in kidney care exist. The poorer care and outcomes with area-level deprivation were greater earlier in the disease course.

Outcomes among confirmed cases and a matched comparison group in the Long-COVID in Scotland study.

With increasing numbers infected by SARS-CoV-2, understanding long-COVID is essential to inform health and social care support. A Scottish population cohort of 33,281 laboratory-confirmed SARS-CoV-2 infections and 62,957 never-infected individuals were followed-up via 6, 12 and 18-month questionnaires and linkage to hospitalization and death records. Of the 31,486 symptomatic infections,1,856 (6%) had not recovered and 13,350 (42%) only partially. No recovery was associated with hospitalized infection, age, female sex, deprivation, respiratory disease, depression and multimorbidity. Previous symptomatic infection was associated with poorer quality of life, impairment across all daily activities and 24 persistent symptoms including breathlessness (OR 3.43, 95% CI 3.29-3.58), palpitations (OR 2.51, OR 2.36-2.66), chest pain (OR 2.09, 95% CI 1.96-2.23), and confusion (OR 2.92, 95% CI 2.78-3.07). Asymptomatic infection was not associated with adverse outcomes. Vaccination was associated with reduced risk of seven symptoms. Here we describe the nature of long-COVID and the factors associated with it.

Harmonization of epidemiology of acute kidney injury and acute kidney disease produces comparable findings across four geographic populations.

There is substantial variability in the reported incidence and outcomes of acute kidney injury (AKI). The extent to which this is attributable to differences in source populations versus methodological differences between studies is uncertain. We used 4 population-based datasets from Canada, Denmark, and the United Kingdom to measure the annual incidence and prognosis of AKI and acute kidney disease (AKD), using a homogenous analytical approach that incorporated KDIGO creatinine-based definitions and subsets of the AKI/AKD criteria. The cohorts included 7 million adults ≥18 years of age between 2011 and 2014; median age 59-68 years, 51.9-54.4% female sex. Age- and sex-standardised incidence rates for AKI or AKD were similar between regions and years; range 134.3-162.4 events/10,000 person years. Among patients who met either KDIGO 48-hour or 7-day AKI creatinine criteria, the standardised 1-year mortality was similar (30.4%-38.5%) across the cohorts, which was comparable to standardised 1-year mortality among patients who met AKI/AKD criteria using a baseline creatinine within 8-90 days prior (32.0%-37.4%). Standardised 1-year mortality was lower (21.0%-25.5% across cohorts) among patients with AKI/AKD ascertained using a baseline creatinine >90 days prior. These findings illustrate that the incidence and prognosis of AKI and AKD based on KDIGO criteria are consistent across 3 high-income countries when capture of laboratory tests is complete, creatinine-based definitions are implemented consistently within but not beyond a 90-day period, and adjustment is made for population age and sex. These approaches should be consistently applied to improve the generalizability and comparability of AKI research and clinical reporting.

Identifying multimorbidity clusters in an unselected population of hospitalised patients.

Multimorbidity (multiple coexisting chronic health conditions) is common and increasing worldwide, and makes care challenging for both patients and healthcare systems. To ensure care is patient-centred rather than specialty-centred, it is important to know which conditions commonly occur together and identify the corresponding patient profile. To date, no studies have described multimorbidity clusters within an unselected hospital population. Our aim was to identify and characterise multimorbidity clusters, in a large, unselected hospitalised patient population. Linked inpatient hospital episode data were used to identify adults admitted to hospital in Grampian, Scotland in 2014 who had ≥ 2 of 30 chronic conditions diagnosed in the 5 years prior. Cluster analysis (Gower distance and Partitioning around Medoids) was used to identify groups of patients with similar conditions. Clusters of conditions were defined based on clinical review and assessment of prevalence within patient groups and labelled according to the most prevalent condition. Patient profiles for each group were described by age, sex, admission type, deprivation and urban-rural area of residence. 11,389 of 41,545 hospitalised patients (27%) had ≥ 2 conditions. Ten clusters of conditions were identified: hypertension; asthma; alcohol misuse; chronic kidney disease and diabetes; chronic kidney disease; chronic pain; cancer; chronic heart failure; diabetes; hypothyroidism. Age ranged from 51 (alcohol misuse) to 79 (chronic heart failure). Women were a higher proportion in the chronic pain and hypothyroidism clusters. The proportion of patients from the most deprived quintile of the population ranged from 6% (hypertension) to 14% (alcohol misuse). Identifying clusters of conditions in hospital patients is a first step towards identifying opportunities to target patient-centred care towards people with unmet needs, leading to improved outcomes and increased efficiency. Here we have demonstrated the face validity of cluster analysis as an exploratory method for identifying clusters of conditions in hospitalised patients with multimorbidity.

Examining variation in the measurement of multimorbidity in research: a systematic review of 566 studies.

BACKGROUND: A systematic understanding of how multimorbidity has been constructed and measured is unavailable. This review aimed to examine the definition and measurement of multimorbidity in peer-reviewed studies internationally. METHODS: We systematically reviewed studies on multimorbidity, via a search of nine bibliographic databases (Ovid [PsycINFO, Embase, Global Health, and MEDLINE], Web of Science, the Cochrane Library, CINAHL Plus, Scopus, and ProQuest Dissertations & Theses Global), from inception to Jan 21, 2020. Reference lists and tracked citations of retrieved articles were hand-searched. Eligible studies were full-text articles measuring multimorbidity for any purpose in community, primary care, care home, or hospital populations receiving a non-specialist service. Abstracts, qualitative research, and case series were excluded. Two reviewers independently reviewed the retrieved studies with conflicts resolved by discussion or a third reviewer, and a single researcher extracted data from published papers. To assess our objectives of how multimorbidity has been measured and examine variation in the chronic conditions included (in terms of number and type), we used descriptive analysis (frequencies, cross-tabulation, and negative binomial regression) to summarise the characteristics of multimorbidity studies and measures (study setting, source of morbidity data, study population, primary study purpose, and multimorbidity measure type). This systematic review is registered with PROSPERO, CRD420201724090. FINDINGS: 566 studies were included in our review, of which 206 (36·4%) did not report a reference definition for multimorbidity and 73 (12·9%) did not report the conditions their measure included. The number of conditions included in measures ranged from two to 285 (median 17 [IQR 11-23). 452 (79·9%) studies reported types of condition within a single multimorbidity measure; most included at least one cardiovascular condition (441 [97·6%] of 452 studies), metabolic and endocrine condition (440 [97·3%]), respiratory condition (422 [93·4%]), musculoskeletal condition (396 [87·6%]), or mental health condition (355 [78·5%]) in their measure of multimorbidity. Chronic infections (123 [27·2%]), haematological conditions (110 [24·3%]), ear, nose, and throat conditions (107 [23·7%]), skin conditions (70 [15·5%]), oral conditions (19 [4·2%]), and congenital conditions (14 [3·1%]) were uncommonly included. Only eight individual conditions were included by more than half of studies in the multimorbidity measure used (diabetes, stroke, cancer, chronic obstructive pulmonary disease, hypertension, coronary heart disease, chronic kidney disease, and heart failure), with individual mental health conditions under-represented. Of the 566 studies, 419 were rated to be of moderate risk of bias, 107 of high risk of bias, and 40 of low risk of bias according to the Effective Public Health Practice Project quality assessment tool. INTERPRETATION: Measurement of multimorbidity is poorly reported and highly variable. Consistent reporting of measure definitions should be required by journals, and consensus studies are needed to define core and study-dependent conditions to include in measures of multimorbidity. FUNDING: Health Data Research UK.

Validation of Risk Prediction Models to Inform Clinical Decisions After Acute Kidney Injury.

RATIONALE & OBJECTIVE: There is limited evidence to guide follow-up after acute kidney injury (AKI). Knowledge gaps include which patients to prioritize, at what time point, and for mitigation of which outcomes. In this study, we sought to compare the net benefit of risk model-based clinical decisions following AKI. STUDY DESIGN: External validation of 2 risk models of AKI outcomes: the Grampian -Aberdeen (United Kingdom) AKI readmissions model and the Alberta (Canada) kidney disease risk model of chronic kidney disease (CKD) glomerular (G) filtration rate categories 4 and 5 (CKD G4 and G5). Process mining to delineate existing care pathways. SETTING & PARTICIPANTS: Validation was based on data from adult hospital survivors of AKI from Grampian, 2011-2013. PREDICTORS: KDIGO-based measures of AKI severity and comorbidities specified in the original models. OUTCOMES: Death or readmission within 90 days for all hospital survivors. Progression to new CKD G4-G5 for patients surviving at least 90 days after AKI. ANALYTICAL APPROACH: Decision curve analysis to assess the "net benefit" of use of risk models to guide clinical care compared to alternative approaches (eg, prioritizing all AKI, severe AKI, or only those without kidney recovery). RESULTS: 26,575 of 105,461 hospital survivors in Grampian (mean age, 60.9 ± 19.8 [SD] years) were included for validation of the death or readmission model, and 9,382 patients (mean age, 60.9 ± 19.8 years) for the CKD G4-G5 model. Both models discriminated well (area under the curve [AUC], 0.77 and 0.86, respectively). Decision curve analysis showed greater net benefit for follow up of all AKI than only severe AKI in most cases. Both original and refitted models provided net benefit superior to any other decision strategy. In process mining of all hospital discharges, 41% of readmissions and deaths occurred among people recovering after AKI. 1,464 of 3,776 people (39%) readmitted after AKI had received no intervening monitoring. LIMITATIONS: Both original models overstated risks, indicating a need for regular updating. CONCLUSIONS: Follow up after AKI has potential net benefit for preempting readmissions, death, and subsequent CKD progression. Decisions could be improved by using risk models and by focusing on AKI across a full spectrum of severity. The current lack of monitoring among many with poor outcomes indicates possible opportunities for implementation of decision support.

Multimorbidity in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: Results From a Longitudinal, Multicenter Data Linkage Study.

OBJECTIVE: Antineutrophil cytoplasmic antibody-associated vasculitis (AAV) is considered a chronic, relapsing condition. To date, no studies have investigated multimorbidity in AAV nationally. This study was undertaken to characterize temporal trends in multimorbidity and report excess health care expenditures associated with multimorbidities in a national AAV cohort from Scotland. METHODS: Eligible patients with AAV were diagnosed between 1997 and 2017. Each patient was matched with up to 5 general population controls. Linked morbidity and health care expenditure data were retrieved from a Scottish national hospitalization repository and from published national cost data. Multimorbidity was defined as the development of ≥2 disorders. Prespecified morbidities, individually and together, were analyzed for risks and associations over time using modified Poisson regression, discrete interval analysis, and chi-square test for trend. The relationship between multimorbidities and health care expenditure was investigated using multivariate linear regression. RESULTS: In total, 543 patients with AAV (median age 58.7 years [range 48.9-68.0 years]; 53.6% male) and 2,672 general population controls (median age 58.7 years [range 48.9-68.0 years]; 53.7% male) were matched and followed up for a median of 5.1 years. AAV patients were more likely to develop individual morbidities at all time points, but especially <2 years after diagnosis. The highest proportional risk observed was for osteoporosis (adjusted incidence rate ratio 8.0, 95% confidence interval [95% CI] 4.5-14.2). After 1 year, 23.0% of AAV patients and 9.3% of controls had developed multimorbidity (P < 0.0001). After 10 years, 37.0% of AAV patients and 17.3% of controls were reported to have multimorbidity (P < 0.0001). Multimorbidity was associated with disproportionate increases in health care expenditures in AAV patients. Health care expenditure was highest for AAV patients with ≥3 morbidities (3.89-fold increase in costs, 95% CI 2.83-5.31; P < 0.001 versus no morbidities). CONCLUSION: These findings emphasize the importance of holistic care in patients with AAV, and may identify a potentially critical opportunity to consider early screening.

Using a knowledge exchange event to assess study participants' attitudes to research in a rapidly evolving research context.

Background: The UK hosts some of the world's longest-running longitudinal cohort studies, which make repeated observations of their participants and use these data to explore health outcomes. An alternative method for data collection is record linkage; the linking together of electronic health and administrative records. Applied nationally, this could provide unrivalled opportunities to follow a large number of people in perpetuity. However, public attitudes to the use of data in research are currently unclear. Here we report on an event where we collected attitudes towards recent opportunities and controversies within health data science. Methods: The event was attended by ~250 individuals (cohort members and their guests), who had been invited through the offices of their participating cohort studies. There were a series of presentations describing key research results and the audience participated in 15 multiple-choice questions using interactive voting pads. Results: Our participants showed a high level of trust in researchers (87% scoring them 4/5 or 5/5) and doctors (81%); but less trust in commercial companies (35%). They supported the idea of researchers using information from both neonatal blood spots (Guthrie spots) (97% yes) and from electronic health records (95% yes). Our respondents were willing to wear devices like a 'Fit-bit' (88% agreed) or take a brain scan that might predict later mental illness (73%). However, they were less willing to take a new drug for research purposes (45%). They were keen to encourage others to take part in research; whether that be offering the opportunity to pregnant mothers (97% agreed) or extending invitations to their own children and grandchildren (98%). Conclusions: Our participants were broadly supportive of research access to data, albeit less supportive when commercial interests were involved. Public engagement events that facilitate two-way interactions can influence and support future research and public engagement efforts.

Knowledge Driven Phenotyping.

Extracting patient phenotypes from routinely collected health data (such as Electronic Health Records) requires translating clinically-sound phenotype definitions into queries/computations executable on the underlying data sources by clinical researchers. This requires significant knowledge and skills to deal with heterogeneous and often imperfect data. Translations are time-consuming, error-prone and, most importantly, hard to share and reproduce across different settings. This paper proposes a knowledge driven framework that (1) decouples the specification of phenotype semantics from underlying data sources; (2) can automatically populate and conduct phenotype computations on heterogeneous data spaces. We report preliminary results of deploying this framework on five Scottish health datasets.

The long-term health effects of attending a selective school: a natural experiment.

BACKGROUND: Education is widely associated with better physical and mental health, but isolating its causal effect is difficult because education is linked with many socioeconomic advantages. One way to isolate education's effect is to consider environments where similar students are assigned to different educational experiences based on objective criteria. Here we measure the health effects of assignment to selective schooling based on test score, a widely debated educational policy. METHODS: In 1960s Britain, children were assigned to secondary schools via a test taken at age 11. We used regression discontinuity analysis to measure health differences in 5039 people who were separated into selective and non-selective schools this way. We measured selective schooling's effect on six outcomes: mid-life self-reports of health, mental health, and life limitation due to health, as well as chronic disease burden derived from hospital records in mid-life and later life, and the likelihood of dying prematurely. The analysis plan was accepted as a registered report while we were blind to the health outcome data. RESULTS: Effect estimates for selective schooling were as follows: self-reported health, 0.1 worse on a 4-point scale (95%CI - 0.2 to 0); mental health, 0.2 worse on a 16-point scale (- 0.5 to 0.1); likelihood of life limitation due to health, 5 percentage points higher (- 1 to 10); mid-life chronic disease diagnoses, 3 fewer/100 people (- 9 to + 4); late-life chronic disease diagnoses, 9 more/100 people (- 3 to + 20); and risk of dying before age 60, no difference (- 2 to 3 percentage points). Extensive sensitivity analyses gave estimates consistent with these results. In summary, effects ranged from 0.10-0.15 standard deviations worse for self-reported health, and from 0.02 standard deviations better to 0.07 worse for records-derived health. However, they were too imprecise to allow the conclusion that selective schooling was detrimental. CONCLUSIONS: We found that people who attended selective secondary school had more advantaged economic backgrounds, higher IQs, higher likelihood of getting a university degree, and better health. However, we did not find that selective schooling itself improved health. This lack of a positive influence of selective secondary schooling on health was consistent despite varying a wide range of model assumptions.

Urban-rural and socioeconomic status: Impact on multimorbidity prevalence in hospitalized patients.

OBJECTIVE: The aim of this study was to describe multimorbidity prevalence in hospitalized adults, by urban-rural area of residence and socioeconomic status (SES). METHODS: Linked hospital episode data were used. Adults (≥18 years) admitted to hospital as an inpatient during 2014 in Grampian, Scotland, were included. Conditions were identified from admissions during the 5 years prior to the first admission in 2014. Multimorbidity was defined as ≥2 conditions and measured using Tonelli et al. based on International Classification of Diseases-10 coding (preselected list of 30 conditions). We used proportions and 95% confidence intervals (CIs) to summarize the prevalence of multimorbidity by age group, sex, urban-rural category and deprivation. The association between multimorbidity and patient characteristics was assessed using the χ 2 test. RESULTS: Forty one thousand five hundred and forty-five patients were included (median age 62, 52.6% female). Overall, 27.4% (95% CI 27.0, 27.8) of patients were multimorbid. Multimorbidity prevalence was 28.8% (95% CI 28.1, 29.5) in large urban versus 22.0% (95% CI 20.9, 23.3) in remote rural areas and 28.7% (95% CI 27.2, 30.3) in the most deprived versus 26.0% (95% CI 25.2, 26.9) in the least deprived areas. This effect was consistent in all age groups, but not statistically significant in the age group 18-29 years. Multimorbidity increased with age but was similar for males and females. CONCLUSION: Given the scarcity of research into the effect of urban-rural area and SES on multimorbidity prevalence among hospitalized patients, these findings should inform future research into new models of care, including the consideration of urban-rural area and SES.

Characterizing infection in anti-neutrophil cytoplasmic antibody-associated vasculitis: results from a longitudinal, matched-cohort data linkage study.

OBJECTIVES: Infection exerts a major burden in ANCA-associated vasculitis (AAV), however, its precise extent and nature remains unclear. In this national study we aimed to longitudinally quantify, characterize and contextualize infection risk in AAV. METHODS: We conducted a multicentre matched cohort study of AAV. Complementary data on infections were retrieved via data linkage with the population-based Scottish microbiological laboratory, hospitalization and primary care prescribing registries. RESULTS: A total of 379 AAV patients and 1859 controls were followed up for a median of 3.5 years (interquartile range 1.9-5.7). During follow-up, the proportions of AAV patients with at least one laboratory-confirmed infection, severe infection and primary care antibiotic prescription were 55.4%, 35.6% and 74.6%, respectively. The risk of infection was higher in AAV than in matched controls {laboratory-confirmed infections: incidence rate ratio [IRR] 7.3 [95% confidence interval (CI) 5.6, 9.6]; severe infections: IRR 4.4 [95% CI 3.3, 5.7]; antibiotic prescriptions: IRR 2.2 [95% CI 1.9, 2.6]}. Temporal trend analysis showed that AAV patients remained at a higher risk of infections throughout the follow-up period, especially year 1. Although the Escherichia genus was the most commonly identified pathogen (16.6% of AAV, 5.5% of controls; P < 0.0001), AAV patients had the highest risk for Herpes [IRR 12.5 (95% CI 3.7, 42.6)] and Candida [IRR 11.4 (95% CI 2.4, 55.4)]. CONCLUSION: AAV patients have up to seven times higher risk of infection than the general population and the overall risk remains significant after 8 years of follow-up. The testing of enhanced short- to medium-term prophylactic antibiotic regimes should be considered.

Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care.

BACKGROUND: Outcomes after acute kidney injury (AKI) are well described, but not for those already under nephrology clinic care. This is where discussions about kidney failure risk are commonplace. We evaluated whether the established kidney failure risk equation (KFRE) should account for previous AKI episodes when used in this setting. METHODS: This observational cohort study included 7491 people referred for nephrology clinic care in British Columbia in 2003-09 followed to 2016. Predictors were previous Kidney Disease: Improving Global Outcomes-based AKI, age, sex, proteinuria, estimated glomerular filtration rate (eGFR) and renal diagnosis. Outcomes were 5-year kidney failure and death. We developed cause-specific Cox models (AKI versus no AKI) for kidney failure and death, stratified by eGFR (

Risk factors associated with biochemically detected and hospitalised acute kidney injury in patients prescribed renin angiotensin system inhibitors.

AIMS: Therapy with angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB) is a mainstay of treatment for heart failure (HF), diabetes mellitus (DM) and chronic kidney disease (CKD). These agents have been associated with development of acute kidney injury (AKI) during intercurrent illness. Risk factors for AKI in patients prescribed ACEi/ARB therapy are not well described. METHODS: We captured the incidence of AKI in patients commencing ACEi/ARB during 2009-2015 using anonymised patient records. Hospital-coded AKI was defined from hospital episode statistics; biochemical AKI was ascertained from laboratory data. Risk factors for biochemically detected and hospitalised AKI were investigated. RESULTS: Of 61,318 patients prescribed ACEi/ARB, with 132 885 person years (py) follow-up, there were 1070 hospitalisations with AKI as a diagnosis recorded and a total of 4645 AKI events, including AKI episodes indicated by biochemical KDIGO-based creatinine change criteria. Incidence of any AKI event was 35.0 per 1000-py, hospital-coded AKI was 7.8 per 1000-py and biochemical AKI was 33.7 per 1000-py. Independent risk factors in a multivariable model for hospital-coded AKI events were age, male gender, HF, diabetes, cerebrovascular disease, lower estimated glomerular filtration rate, socioeconomic deprivation, diuretic or non-steroidal anti-inflammatory use (all P < 0.001). CONCLUSION: In patients prescribed ACEi/ARB, the highest risk of AKI is associated with conditions which are considered strong evidence-based indications for their prescription. Socio-economic status is an under-reported risk factor for AKI with these agents. Strategies targeted at prevention of AKI may be of benefit, such as enhanced awareness based on higher risk comorbidities.