Major cardiovascular events and subsequent risk of kidney failure with replacement therapy: a CKD Prognosis Consortium study.

AIMS: Chronic kidney disease (CKD) increases risk of cardiovascular disease (CVD). Less is known about how CVD associates with future risk of kidney failure with replacement therapy (KFRT). METHODS AND RESULTS: The study included 25 903 761 individuals from the CKD Prognosis Consortium with known baseline estimated glomerular filtration rate (eGFR) and evaluated the impact of prevalent and incident coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) events as time-varying exposures on KFRT outcomes. Mean age was 53 (standard deviation 17) years and mean eGFR was 89 mL/min/1.73 m2, 15% had diabetes and 8.4% had urinary albumin-to-creatinine ratio (ACR) available (median 13 mg/g); 9.5% had prevalent CHD, 3.2% prior stroke, 3.3% HF, and 4.4% prior AF. During follow-up, there were 269 142 CHD, 311 021 stroke, 712 556 HF, and 605 596 AF incident events and 101 044 (0.4%) patients experienced KFRT. Both prevalent and incident CVD were associated with subsequent KFRT with adjusted hazard ratios (HRs) of 3.1 [95% confidence interval (CI): 2.9-3.3], 2.0 (1.9-2.1), 4.5 (4.2-4.9), 2.8 (2.7-3.1) after incident CHD, stroke, HF and AF, respectively. HRs were highest in first 3 months post-CVD incidence declining to baseline after 3 years. Incident HF hospitalizations showed the strongest association with KFRT [HR 46 (95% CI: 43-50) within 3 months] after adjustment for other CVD subtype incidence. CONCLUSION: Incident CVD events strongly and independently associate with future KFRT risk, most notably after HF, then CHD, stroke, and AF. Optimal strategies for addressing the dramatic risk of KFRT following CVD events are needed.

Cost-effectiveness and value of information analysis of multiple frequency bioimpedance devices for fluid management in people with chronic kidney disease having dialysis.

BACKGROUND: Among people with chronic kidney disease (CKD) on dialysis, sub-optimal fluid management has been linked with hospitalisation, cardiovascular complications and death. This study assessed the cost-effectiveness using multiple-frequency bioimpedance guided fluid management versus standard fluid management based on clinical judgment. METHODS: A Markov model was developed to compare expected costs, outcomes and quality adjusted life years of the alternative management strategies. The relative effectiveness of the bioimpedance guided approach was informed by a systematic review of clinical trials, and focussed reviews were conducted to identify baseline event rates, costs and health state utility values for application in the model. The model was analysed probabilistically and a value of information (VOI) analysis was conducted to inform the value of conducting further research to reduce current uncertainties in the evidence base. RESULTS: For the base-case analysis, the incremental cost-effectiveness ratio (ICER) for bioimpedance guided fluid management versus standard management was £16,536 per QALY gained. There was a 59% chance of the ICER being below £20,000 per QALY. Form the VOI analysis, the theoretical upper bound on the value of further research was £53 million. The value of further research was highest for parameters relating to the relative effectiveness of bioimpedance guided management on final health outcomes. CONCLUSIONS: Multiple frequency bioimpedance testing may offer a cost-effective approach to improve fluid management in patients with CKD on dialysis, but further research would be of value to reduce the current uncertainties.

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.

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 (

Measuring multimorbidity in hospitalised patients using linked hospital episode data: comparison of two measures.

INTRODUCTION: Multimorbidity is a complex and growing health challenge. There is no accepted "gold standard" multimorbidity measure for hospital resource planning, and few studies have compared measures in hospitalised patients. AIM: To evaluate operationalisation of two multimorbidity measures in routine hospital episode data in NHS Grampian, Scotland. METHODS: Linked hospital episode data (Scottish Morbidity Record (SMR)) for the years 2009-2016 were used. Adults admitted to hospital as a general/acute inpatient during 2014 were included. Conditions (ICD-10) were identified from general/acute (SMR01) and psychiatric (SMR04) admissions during the five years prior to first admission in 2014. Two count-based multimorbidity measures were used (Charlson Comorbidity Index and Tonelli et al.), and multimorbidity was defined as ≥2 conditions. Kappa statistics assessed agreement. The association between multimorbidity and length of stay, readmission and mortality was assessed using logistic and negative binomial regression as appropriate. RESULTS: In 41,545 adults (median age 62 years, 52.6% female), multimorbidity prevalence was 15.1% (95% CI 14.8%, 15.5%) using Charlson and 27.4% (27.0%, 27.8%) using Tonelli - agreement 85.1% (Kappa 0.57). Multimorbidity prevalence, using both measures, increased with age. Multimorbidity was higher in males (16.5%) than females (13.9%) using the Charlson measure, but similar across genders when measured with Tonelli. After adjusting for covariates, multimorbidity remained associated with longer length of stay (Charlson IRR 1.1 (1.0, 1.2); Tonelli IRR 1.1 (1.0, 1.2)) and readmission (Charlson OR 2.1 (1.9, 2.2); Tonelli OR 2.1 (2.0, 2.2)). Multimorbidity had a stronger association with mortality when measured using Charlson (OR 2.7 (2.5, 2.9)), than using Tonelli (OR 1.8 (1.7, 2.0)). CONCLUSIONS: Multimorbidity measures operationalised in hospital episode data identified those at risk of poor outcomes and such operationalised tools will be useful for future multimorbidity research and use in secondary care data systems. Multimorbidity measures are not interchangeable, and the choice of measure should depend on the purpose. HIGHLIGHTS: Operationalisation of two count-based multimorbidity measures using linked electronic hospital episode data was evaluated (Charlson and Tonelli).First study to compare the Tonelli measure with another measure for investigating multimorbidity in hospitalised patients.Multimorbidity prevalence differed depending on measure used, but both multimorbidity measures identified those at risk of poor outcomes.Operationalised multimorbidity tools have uses for future multimorbidity research and use in secondary care data systems.Multimorbidity measures are not interchangeable, and choice of measure should depend on purpose.

Acute kidney injury in the UK: a replication cohort study of the variation across three regional populations.

OBJECTIVES: A rapid growth in the reported rates of acute kidney injury (AKI) has led to calls for greater attention and greater resources for improving care. However, the reported incidence of AKI also varies more than tenfold between previous studies. Some of this variation is likely to stem from methodological heterogeneity. This study explores the extent of cross-population variation in AKI incidence after minimising heterogeneity. DESIGN: Population-based cohort study analysing data from electronic health records from three regions in the UK through shared analysis code and harmonised methodology. SETTING: Three populations from Scotland, Wales and England covering three time periods: Grampian 2003, 2007 and 2012; Swansea 2007; and Salford 2012. PARTICIPANTS: All residents in each region, aged 15 years or older. MAIN OUTCOME MEASURES: Population incidence of AKI and AKI phenotype (severity, recovery, recurrence). Determined using shared biochemistry-based AKI episode code and standardised by age and sex. RESULTS: Respectively, crude AKI rates (per 10 000/year) were 131, 138, 139, 151 and 124 (p=0.095), and after standardisation for age and sex: 147, 151, 146, 146 and 142 (p=0.257) for Grampian 2003, 2007 and 2012; Swansea 2007; and Salford 2012. The pattern of variation in crude rates was robust to any modifications of the AKI definition. Across all populations and time periods, AKI rates increased substantially with age from ~20 to ~550 per 10 000/year among those aged <40 and ≥70 years. CONCLUSION: When harmonised methods are used and age and sex differences are accounted for, a similar high burden of AKI is consistently observed across different populations and time periods (~150 per 10 000/year). There are particularly high rates of AKI among older people. Policy-makers should be careful not draw simplistic assumptions about variation in AKI rates based on comparisons that are not rigorous in methodological terms.

Hip fracture incidence and mortality in chronic kidney disease: the GLOMMS-II record linkage cohort study.

BACKGROUND: Individuals on renal replacement therapy (RRT) have increased fracture risk, but risk in less advanced chronic kidney disease (CKD) is unclear. OBJECTIVE: To investigate CKD associations with hip fracture incidence and mortality. DESIGN: Record linkage cohort study Grampian Laboratory Outcomes Mortality and Morbidity Study II. SETTING: Single health region in Scotland. PARTICIPANTS: All individuals (≥15 years) with sustained CKD stages 3-5 and those on RRT, and a 20% random sample of those with normal renal function, in the resident population in 2003. OUTCOME MEASURES: Outcomes were (1) incident hip fracture measured with (A) admissions or (B) deaths, with at least 5.5 years follow-up and (2) post-hip fracture mortality. Unadjusted and adjusted, incident rate ratios (IRRs) and mortality rate ratios were calculated using Poisson regression. RESULTS: Of 39 630 individuals identified in 2003 (41% males, mean age 63.3 years), 19 537 had CKD stages 3-5, 345 were on RRT and 19 748 had normal estimated glomerular filtration rate (eGFR). Hip fracture incidence, measured by admissions, was increased in CKD stages 3-5 (compared with normal eGFR), both overall (adjusted IRR 1.49 (95% CI 1.24 to 1.79)) and for individual CKD stages 3a, 3b and 4. Hip fracture incidence, measured using deaths, was increased in those with CKD stages 3b and 4. Post-hip fracture mortality was only increased in CKD stage 4. There was only a small number of individuals and events for CKD stage 5, resulting in insufficient statistical power. CONCLUSION: Hip fracture incidence was higher in CKD stages 3-5 compared with normal eGFR. Post-hip fracture mortality was only increased in CKD stage 4. Reducing hip fracture incidence in CKD through regular fall and fracture risk review should reduce overall deaths after hip fracture in the population.

Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate.

Patients with chronic kidney disease and severely decreased glomerular filtration rate (GFR) are at high risk for kidney failure, cardiovascular disease (CVD) and death. Accurate estimates of risk and timing of these clinical outcomes could guide patient counseling and therapy. Therefore, we developed models using data of 264,296 individuals in 30 countries participating in the international Chronic Kidney Disease Prognosis Consortium with estimated GFR (eGFR)s under 30 ml/min/1.73m2. Median participant eGFR and urine albumin-to-creatinine ratio were 24 ml/min/1.73m2 and 168 mg/g, respectively. Using competing-risk regression, random-effect meta-analysis, and Markov processes with Monte Carlo simulations, we developed two- and four-year models of the probability and timing of kidney failure requiring kidney replacement therapy (KRT), a non-fatal CVD event, and death according to age, sex, race, eGFR, albumin-to-creatinine ratio, systolic blood pressure, smoking status, diabetes mellitus, and history of CVD. Hypothetically applied to a 60-year-old white male with a history of CVD, a systolic blood pressure of 140 mmHg, an eGFR of 25 ml/min/1.73m2 and a urine albumin-to-creatinine ratio of 1000 mg/g, the four-year model predicted a 17% chance of survival after KRT, a 17% chance of survival after a CVD event, a 4% chance of survival after both, and a 28% chance of death (9% as a first event, and 19% after another CVD event or KRT). Risk predictions for KRT showed good overall agreement with the published kidney failure risk equation, and both models were well calibrated with observed risk. Thus, commonly-measured clinical characteristics can predict the timing and occurrence of clinical outcomes in patients with severely decreased GFR.

Multiple-frequency bioimpedance devices for fluid management in people with chronic kidney disease receiving dialysis: a systematic review and economic evaluation.

BACKGROUND: Chronic kidney disease (CKD) is a long-term condition requiring treatment such as conservative management, kidney transplantation or dialysis. To optimise the volume of fluid removed during dialysis (to avoid underhydration or overhydration), people are assigned a 'target weight', which is commonly assessed using clinical methods, such as weight gain between dialysis sessions, pre- and post-dialysis blood pressure and patient-reported symptoms. However, these methods are not precise, and measurement devices based on bioimpedance technology are increasingly used in dialysis centres. Current evidence on the role of bioimpedance devices for fluid management in people with CKD receiving dialysis is limited. OBJECTIVES: To evaluate the clinical effectiveness and cost-effectiveness of multiple-frequency bioimpedance devices versus standard clinical assessment for fluid management in people with CKD receiving dialysis. DATA SOURCES: We searched major electronic databases [e.g. MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Science Citation Index and Cochrane Central Register of Controlled Trials (CENTRAL)] conference abstracts and ongoing studies. There were no date restrictions. Searches were undertaken between June and October 2016. REVIEW METHODS: Evidence was considered from randomised controlled trials (RCTs) comparing fluid management by multiple-frequency bioimpedance devices and standard clinical assessment in people receiving dialysis, and non-randomised studies evaluating the use of the devices for fluid management in people receiving dialysis. One reviewer extracted data and assessed the risk of bias of included studies. A second reviewer cross-checked the extracted data. Standard meta-analyses techniques were used to combine results from included studies. A Markov model was developed to assess the cost-effectiveness of the interventions. RESULTS: Five RCTs (with 904 adult participants) and eight non-randomised studies (with 4915 adult participants) assessing the use of the Body Composition Monitor [(BCM) Fresenius Medical Care, Bad Homburg vor der Höhe, Germany] were included. Both absolute overhydration and relative overhydration were significantly lower in patients evaluated using BCM measurements than for those evaluated using standard clinical methods [weighted mean difference -0.44, 95% confidence interval (CI) -0.72 to -0.15, p = 0.003, I2 = 49%; and weighted mean difference -1.84, 95% CI -3.65 to -0.03; p = 0.05, I2 = 52%, respectively]. Pooled effects of bioimpedance monitoring on systolic blood pressure (SBP) (mean difference -2.46 mmHg, 95% CI -5.07 to 0.15 mmHg; p = 0.06, I2 = 0%), arterial stiffness (mean difference -1.18, 95% CI -3.14 to 0.78; p = 0.24, I2 = 92%) and mortality (hazard ratio = 0.689, 95% CI 0.23 to 2.08; p = 0.51) were not statistically significant. The economic evaluation showed that, when dialysis costs were included in the model, the probability of bioimpedance monitoring being cost-effective ranged from 13% to 26% at a willingness-to-pay threshold of £20,000 per quality-adjusted life-year gained. With dialysis costs excluded, the corresponding probabilities of cost-effectiveness ranged from 61% to 67%. LIMITATIONS: Lack of evidence on clinically relevant outcomes, children receiving dialysis, and any multifrequency bioimpedance devices, other than the BCM. CONCLUSIONS: BCM used in addition to clinical assessment may lower overhydration and potentially improve intermediate outcomes, such as SBP, but effects on mortality have not been demonstrated. If dialysis costs are not considered, the incremental cost-effectiveness ratio falls below £20,000, with modest effects on mortality and/or hospitalisation rates. The current findings are not generalisable to paediatric populations nor across other multifrequency bioimpedance devices. FUTURE WORK: Services that routinely use the BCM should report clinically relevant intermediate and long-term outcomes before and after introduction of the device to extend the current evidence base. STUDY REGISTRATION: This study is registered as PROSPERO CRD42016041785. FUNDING: The National Institute for Health Research Health Technology Assessment programme.

Models of care for chronic kidney disease: A systematic review.

AIM: Chronic kidney disease (CKD) is common and presents an increasing burden to patients and health services. However, the optimal model of care for patients with CKD is unclear. We systematically reviewed the clinical effectiveness of different models of care for the management of CKD. METHODS: A comprehensive search of eight databases was undertaken for articles published from 1992 to 2016. We included randomized controlled trials that assessed any model of care in the management of adults with pre-dialysis CKD, reporting renal, cardiovascular, mortality and other outcomes. Data extraction and quality assessment was carried out independently by two authors. RESULTS: Results were summarized narratively. Nine articles (seven studies) were included. Four models of care were identified: nurse-led, multidisciplinary specialist team, pharmacist-led and self-management. Nurse and pharmacist-led care reported improved rates of prescribing of drugs relevant to CKD. Heterogeneity was high between studies and all studies were at high risk of bias. Nurse-led care and multidisciplinary specialist care were associated with small improvements in blood pressure control. CONCLUSION: Evidence of long term improvements in renal, cardiovascular or mortality endpoints was limited by short follow up. We found little published evidence about the effectiveness of different models of care to guide best practice for service design, although there was some evidence that models of care where health professionals deliver care according to a structured protocol or guideline may improve adherence to treatment targets.

Post-discharge kidney function is associated with subsequent ten-year renal progression risk among survivors of acute kidney injury.

The extent to which renal progression after acute kidney injury (AKI) arises from an initial step drop in kidney function (incomplete recovery), or from a long-term trajectory of subsequent decline, is unclear. This makes it challenging to plan or time post-discharge follow-up. This study of 14651 hospital survivors in 2003 (1966 with AKI, 12685 no AKI) separates incomplete recovery from subsequent renal decline by using the post-discharge estimated glomerular filtration rate (eGFR) rather than the pre-admission as a new reference point for determining subsequent renal outcomes. Outcomes were sustained 30% renal decline and de novo CKD stage 4, followed from 2003-2013. Death was a competing risk. Overall, death was more common than subsequent renal decline (37.5% vs 11.3%) and CKD stage 4 (4.5%). Overall, 25.7% of AKI patients had non-recovery. Subsequent renal decline was greater after AKI (vs no AKI) (14.8% vs 10.8%). Renal decline after AKI (vs no AKI) was greatest among those with higher post-discharge eGFRs with multivariable hazard ratios of 2.29 (1.88-2.78); 1.50 (1.13-2.00); 0.94 (0.68-1.32) and 0.95 (0.64-1.41) at eGFRs of 60 or more; 45-59; 30-44 and under 30, respectively. The excess risk after AKI persisted over ten years of study, irrespective of AKI severity, or post-episode proteinuria. Thus, even if post-discharge kidney function returns to normal, hospital admission with AKI is associated with increased renal progression that persists for up to ten years. Follow-up plans should avoid false reassurance when eGFR after AKI returns to normal.

Acute kidney injury as an independent risk factor for unplanned 90-day hospital readmissions.

BACKGROUND: Reducing readmissions is an international priority in healthcare. Acute kidney injury (AKI) is common, serious and also a global concern. This analysis evaluates AKI as a candidate risk factor for unplanned readmissions and determines the reasons for readmissions. METHODS: GLOMMS-II is a large population cohort from one health authority in Scotland, combining hospital episode data and complete serial biochemistry results through data-linkage. 16453 people (2623 with AKI and 13830 without AKI) from GLOMMS-II who survived an index hospital admission in 2003 were used to identify the causes of and predict readmissions. The main outcome was "unplanned readmission or death" within 90 days of discharge. In a secondary analysis, the outcome was limited to readmissions with acute pulmonary oedema. 26 candidate predictors during the index admission included AKI (defined and staged 1-3 using an automated e-alert algorithm), prior AKI episodes, baseline kidney function, index admission circumstances and comorbidities. Prediction models were developed and assessed using multivariable logistic regression (stepwise variable selection), C statistics, bootstrap validation and decision curve analysis. RESULTS: Three thousand sixty-five (18.6%) patients had the main outcome (2702 readmitted, 363 died without readmission). The outcome was strongly predicted by AKI. Multivariable odds ratios for AKI stage 3; 2 and 1 (vs no AKI) were 2.80 (2.22-3.53); 2.23 (1.85-2.68) and 1.50 (1.33-1.70). Acute pulmonary oedema was the reason for readmission in 26.6% with AKI and eGFR < 60; and 4.0% with no AKI and eGFR ≥ 60. The best stepwise model from all candidate predictors had a C statistic of 0.698 for the main outcome. In a secondary analysis, a model for readmission with acute pulmonary oedema had a C statistic of 0.853. In decision curve analysis, AKI improved clinical utility when added to any model, although the incremental benefit was small when predicting the main outcome. CONCLUSIONS: AKI is a strong, consistent and independent risk factor for unplanned readmissions - particularly readmissions with acute pulmonary oedema. Pre-emptive planning at discharge should be considered to minimise avoidable readmissions in this high risk group.

Intermediate and Long-term Outcomes of Survivors of Acute Kidney Injury Episodes: A Large Population-Based Cohort Study.

BACKGROUND: The long-term prognosis after acute kidney injury (AKI) is variable. It is unclear how the prognosis of AKI and its relationship to prognostic factors (baseline kidney function, AKI severity, prior AKI episodes, and recovery of kidney function) change as follow-up progresses. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: The Grampian Laboratory Outcomes Morbidity and Mortality Study II (GLOMMS-II) is a large regional population cohort with complete serial biochemistry and outcome data capture through data linkage. From GLOMMS-II, we followed up 17,630 patients hospitalized in 2003 through to 2013. PREDICTORS: AKI identified using KDIGO (Kidney Disease: Improving Global Outcomes) serum creatinine criteria, characterized by baseline kidney function (estimated glomerular filtration rate [eGFR] ≥ 60, 45-59, 30-44, and <30mL/min/1.73m2), AKI severity (KDIGO stage), 90-day recovery of kidney function, and prior AKI episodes. OUTCOMES: Intermediate- (30-364 days) and long-term (1-10 years) mortality and long-term renal replacement therapy. MEASUREMENTS: Poisson regression in time discrete intervals. Multivariable Cox regression for those at risk in the intermediate and long term, adjusted for age, sex, baseline comorbid conditions, and acute admission circumstances. RESULTS: Of 17,630 patients followed up for a median of 9.0 years, 9,251 died. Estimated incidences of hospital AKI were 8.4% and 17.6% for baseline eGFRs≥60 and <60mL/min/1.73m2, respectively. Intermediate-term (30-364 days) adjusted mortality HRs for AKI versus no AKI were 2.48 (95% CI, 2.15-2.88), 2.50 (95% CI, 2.04-3.06), 1.90 (95% CI, 1.51-2.39), and 1.63 (95% CI, 1.20-2.22) for eGFRs≥60, 45 to 59, 30 to 44, and <30mL/min/1.73m2, respectively. Among 1-year survivors, long-term HRs were attenuated: 1.44 (95% CI, 1.31-1.58), 1.25 (95% CI, 1.09-1.43), 1.21 (95% CI, 1.03-1.42), and 1.08 (95% CI, 0.85-1.36), respectively. The excess long-term hazards in AKI were lower for lower baseline eGFRs (P for interaction = 0.01). LIMITATIONS: Nonprotocolized observational data. No adjustment for albuminuria. CONCLUSIONS: The prognostic importance of a discrete AKI episode lessens over time. Baseline kidney function is of greater long-term importance.

KDIGO-based acute kidney injury criteria operate differently in hospitals and the community-findings from a large population cohort.

BACKGROUND: Early recognition of acute kidney injury (AKI) is important. It frequently develops first in the community. KDIGO-based AKI e-alert criteria may help clinicians recognize AKI in hospitals, but their suitability for application in the community is unknown. METHODS: In a large renal cohort (n = 50 835) in one UK health authority, we applied the NHS England AKI 'e-alert' criteria to identify and follow three AKI groups: hospital-acquired AKI (HA-AKI), community-acquired AKI admitted to hospital within 7 days (CAA-AKI) and community-acquired AKI not admitted within 7 days (CANA-AKI). We assessed how AKI criteria operated in each group, based on prior blood tests (number and time lag). We compared 30-day, 1- and 5-year mortality, 90-day renal recovery and chronic renal replacement therapy (RRT). RESULTS: In total, 4550 patients met AKI e-alert criteria, 61.1% (2779/4550) with HA-AKI, 22.9% (1042/4550) with CAA-AKI and 16.0% (729/4550) with CANA-AKI. The median number of days since last blood test differed between groups (1, 52 and 69 days, respectively). Thirty-day mortality was similar for HA-AKI and CAA-AKI, but significantly lower for CANA-AKI (24.2, 20.2 and 2.6%, respectively). Five-year mortality was high in all groups, but followed a similar pattern (67.1, 64.7 and 46.2%). Differences in 5-year mortality among those not admitted could be explained by adjusting for comorbidities and restricting to 30-day survivors (hazard ratio 0.91, 95% confidence interval 0.80-1.04, versus hospital AKI). Those with CANA-AKI (versus CAA-AKI) had greater non-recovery at 90 days (11.8 versus 3.5%, P < 0.001) and chronic RRT at 5 years (3.7 versus 1.2%, P < 0.001). CONCLUSIONS: KDIGO-based AKI criteria operate differently in hospitals and in the community. Some patients may not require immediate admission but are at substantial risk of a poor long-term outcome.

Multinational Assessment of Accuracy of Equations for Predicting Risk of Kidney Failure: A Meta-analysis.

IMPORTANCE: Identifying patients at risk of chronic kidney disease (CKD) progression may facilitate more optimal nephrology care. Kidney failure risk equations, including such factors as age, sex, estimated glomerular filtration rate, and calcium and phosphate concentrations, were previously developed and validated in 2 Canadian cohorts. Validation in other regions and in CKD populations not under the care of a nephrologist is needed. OBJECTIVE: To evaluate the accuracy of the risk equations across different geographic regions and patient populations through individual participant data meta-analysis. DATA SOURCES: Thirty-one cohorts, including 721,357 participants with CKD stages 3 to 5 in more than 30 countries spanning 4 continents, were studied. These cohorts collected data from 1982 through 2014. STUDY SELECTION: Cohorts participating in the CKD Prognosis Consortium with data on end-stage renal disease. DATA EXTRACTION AND SYNTHESIS: Data were obtained and statistical analyses were performed between July 2012 and June 2015. Using the risk factors from the original risk equations, cohort-specific hazard ratios were estimated and combined using random-effects meta-analysis to form new pooled kidney failure risk equations. Original and pooled kidney failure risk equation performance was compared, and the need for regional calibration factors was assessed. MAIN OUTCOMES AND MEASURES: Kidney failure (treatment by dialysis or kidney transplant). RESULTS: During a median follow-up of 4 years of 721,357 participants with CKD, 23,829 cases kidney failure were observed. The original risk equations achieved excellent discrimination (ability to differentiate those who developed kidney failure from those who did not) across all cohorts (overall C statistic, 0.90; 95% CI, 0.89-0.92 at 2 years; C statistic at 5 years, 0.88; 95% CI, 0.86-0.90); discrimination in subgroups by age, race, and diabetes status was similar. There was no improvement with the pooled equations. Calibration (the difference between observed and predicted risk) was adequate in North American cohorts, but the original risk equations overestimated risk in some non-North American cohorts. Addition of a calibration factor that lowered the baseline risk by 32.9% at 2 years and 16.5% at 5 years improved the calibration in 12 of 15 and 10 of 13 non-North American cohorts at 2 and 5 years, respectively (P = .04 and P = .02). CONCLUSIONS AND RELEVANCE: Kidney failure risk equations developed in a Canadian population showed high discrimination and adequate calibration when validated in 31 multinational cohorts. However, in some regions the addition of a calibration factor may be necessary.

Is routine hospital episode data sufficient for identifying individuals with chronic kidney disease? A comparison study with laboratory data.

Internationally, investment in the availability of routine health care data for improving health, health surveillance and health care is increasing. We assessed the validity of hospital episode data for identifying individuals with chronic kidney disease compared to biochemistry data in a large population-based cohort, the Grampian Laboratory Outcomes, Morbidity and Mortality Study-II (n = 70,435). Grampian Laboratory Outcomes, Morbidity and Mortality Study-II links hospital episode data to biochemistry data for all adults in a health region with impaired kidney function and random samples of individuals with normal and unmeasured kidney function in 2003. We compared identification of individuals with chronic kidney disease by hospital episode data (based on International Classification of Diseases-10 codes) to the reference standard of biochemistry data (at least two estimated glomerular filtration rates <60 mL/min/1.73 m(2) at least 90 days apart). Hospital episode data, compared to biochemistry data, identified a lower prevalence of chronic kidney disease and had low sensitivity (<10%) but high specificity (>97%). Using routine health care data from multiple sources offers the best opportunity to identify individuals with chronic kidney disease.

Maximising Acute Kidney Injury Alerts--A Cross-Sectional Comparison with the Clinical Diagnosis.

BACKGROUND: Acute kidney injury (AKI) is serious and widespread across healthcare (1 in 7 hospital admissions) but recognition is often delayed causing avoidable harm. Nationwide automated biochemistry alerts for AKI stages 1-3 have been introduced in England to improve recognition. We explored how these alerts compared with clinical diagnosis in different hospital settings. METHODS: We used a large population cohort of 4464 patients with renal impairment. Each patient had case-note review by a nephrologist, using RIFLE criteria to diagnose AKI and chronic kidney disease (CKD). We identified and staged AKI alerts using the new national NHS England AKI algorithm and compared this with nephrologist diagnosis across hospital settings. RESULTS: Of 4464 patients, 525 had RIFLE AKI, 449 had mild AKI, 2185 had CKD (without AKI) and 1305 were of uncertain chronicity. NHS AKI algorithm criteria alerted for 90.5% of RIFLE AKI, 72.4% of mild AKI, 34.1% of uncertain cases and 14.0% of patients who actually had CKD.The algorithm identified AKI particularly well in intensive care (95.5%) and nephrology (94.6%), but less well on surgical wards (86.4%). Restricting the algorithm to stage 2 and 3 alerts reduced the over-diagnosis of AKI in CKD patients from 14.0% to 2.1%, but missed or delayed alerts in two-thirds of RIFLE AKI patients. CONCLUSION: Automated AKI detection performed well across hospital settings, but was less sensitive on surgical wards. Clinicians should be mindful that restricting alerts to stages 2-3 may identify fewer CKD patients, but including stage 1 provides more sensitive and timely alerting.