Long-term monitoring in primary care for chronic kidney disease and chronic heart failure: a multi-method research programme

Background: Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: chronic kidney disease and chronic heart failure. Objectives: The research questions were as follows: does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage individuals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers? Design: Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation. Setting: This study was set in UK primary care. Data sources: Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature. Participant: The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals. Interventions: The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure). Main outcome measures: The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring. Results: Chronic kidney disease: serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are ≈ 2% for people with normal urine albumin, 3–5% for people with microalbuminuria (3–30 mg/mmol) and 3–12% for people with macroalbuminuria (> 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12–15% of tests in primary care. Glycaemic-control and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as ‘kidney damage’ or ‘kidney failure’ as frightening, and the term ‘chronic’ was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use ‘chronic kidney disease’ when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for individuals with an estimated glomerular filtration rate of 60–90 ml/minute/1.73 m2, aged < 70 years and without cardiovascular disease, where monitoring every 3–4 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99; specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95; specificity, 0.57). Within-person variation estimates for B-type natriuretic peptide and weight were as follows: coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For individuals, monitoring provided reassurance; future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings. Limitations: No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear. Conclusions: It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome

Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes

Abstract: Purpose: This review of sediment source fingerprinting assesses the current state-of-the-art, remaining challenges and emerging themes. It combines inputs from international scientists either with track records in the approach or with expertise relevant to progressing the science. Methods: Web of Science and Google Scholar were used to review published papers spanning the period 2013–2019, inclusive, to confirm publication trends in quantities of papers by study area country and the types of tracers used. The most recent (2018–2019, inclusive) papers were also benchmarked using a methodological decision-tree published in 2017. Scope: Areas requiring further research and international consensus on methodological detail are reviewed, and these comprise spatial variability in tracers and corresponding sampling implications for end-members, temporal variability in tracers and sampling implications for end-members and target sediment, tracer conservation and knowledge-based pre-selection, the physico-chemical basis for source discrimination and dissemination of fingerprinting results to stakeholders. Emerging themes are also discussed: novel tracers, concentration-dependence for biomarkers, combining sediment fingerprinting and age-dating, applications to sediment-bound pollutants, incorporation of supportive spatial information to augment discrimination and modelling, aeolian sediment source fingerprinting, integration with process-based models and development of open-access software tools for data processing. Conclusions: The popularity of sediment source fingerprinting continues on an upward trend globally, but with this growth comes issues surrounding lack of standardisation and procedural diversity. Nonetheless, the last 2 years have also evidenced growing uptake of critical requirements for robust applications and this review is intended to signpost investigators, both old and new, towards these benchmarks and remaining research challenges for, and emerging options for different applications of, the fingerprinting approach

The analysis and reporting of cardiovascular and neoplastic event data in type 2 diabetic populations with diabetic nephropathy: a systematic review

Background: Type 2 (T2) diabetes and diabetic nephropathy are risk factors for a range of vascular and neoplastic outcomes. The competing nature of these outcomes means that the use of standard survival analysis techniques (like Kaplan-Meier (KM) curves and Cox proportional hazards (PH) regression) could introduce bias in risk estimates. The literature was reviewed to determine whether authors accounted for competing risks (CRs) when reporting time-to-event analyses in populations with T2 diabetes and nephropathy. Methods: Medline, EMBASE and CINAHL databases were searched for studies with ≥5 years follow up reporting vascular or neoplastic outcomes in patients with T2 diabetes and nephropathy. Results: The search returned 3,886 abstracts. Of these, 179 studies were eligible for full-text review, with 29 papers eligible for data extraction. No study accounted for CRs. Analyses liable to incorporate bias through ignoring competing outcomes were present in 21 studies, of which: all studies used Cox-PH regression, 6 studies used KM curves and 2 studies produced cumulative incidence estimates from Cox-PH analysis. The remaining 8 studies did not use time-to-event analyses. Conclusions: Studies investigating cardiovascular or neoplastic outcomes in populations with DN fail to account for CRs in their analyses. Using standard analyses when populations are at increased risk of multiple outcomes is liable to introduce an unknown level of bias in risk estimates. Absolute risk estimates from KM and Cox-PH regression are well known to be susceptible to this, while many have identified relative risk measured from Cox-PH regression as also being susceptible

Differential analysis and reporting of longitudinal event data in type 2 diabetic nephropathic study populations: a systematic review

Background: Type 2 (T2) diabetes and diabetic nephropathy (DN) are risk factors for multiple vascular and cancerous outcomes. The competing nature of these outcomes mean that the use of standard survival analysis techniques can result in bias and overestimation of the risk; particularly in cases where follow-up is long or the competing outcome is common. I reviewed the literature to determine whether authors account for competing risks (CRs) in reporting time-to-event risk measures of outcomes in individuals with T2-DN. Methods: Medline, EMBASE and CINAHL databases were searched for trial and cohort studies reporting occurrences of vascular or neoplasm events in T2 diabetic nephropathic populations. Articles were excluded if median follow-up was &lt;5yrs or &lt;1,000 subjects with T2-DN were present at baseline. Articles published &lt;1980 or not available in English were also excluded from the analysis. Results: From 3,886 abstracts identified, 179 studies were eligible for full-text review. Of 16 papers currently identified for data extraction: only 1 implemented a true CRs model, 14 used single outcome models or composite end-points and 1 study provided only general incidence statistics. More results will be available. Conclusions: Preliminary results suggest most studies fail to account for CRs in their analyses. The use of both composite end points and serial single-outcome models can produce bias through either assuming the same hazard for several outcomes or failing to accurately define the population at risk, respectively. Simulation work is currently underway to explore these biases and their potential effect on the risk measures generated

Standard and competing risk analysis of the effect of albuminuria on cardiovascular and cancer mortality in patients with type 2 diabetes mellitus

Background Competing risks occur when populations may experience outcomes that either preclude or alter the probability of experiencing the main study outcome(s). Many standard survival analysis methods do not account for competing risks. We used mortality risk in people with diabetes with and without albuminuria as a case study to investigate the impact of competing risks on measures of absolute and relative risk. Methods A population with type 2 diabetes was identified in Clinical Practice Research Datalink as part of a historical cohort study. Patients were followed for up to 9 years. To quantify differences in absolute risk estimates of cardiovascular and cancer, mortality standard (Kaplan-Meier) estimates were compared to competing-risks-adjusted (cumulative incidence competing risk) estimates. To quantify differences in measures of association, regression coefficients for the effect of albuminuria on the relative hazard of each outcome were compared between standard cause-specific hazard (CSH) models (Cox proportional hazards regression) and two competing risk models: the unstratified Lunn-McNeil model, which estimates CSH, and the Fine-Gray model, which estimates subdistribution hazard (SDH). Results In patients with normoalbuminuria, standard and competing-risks-adjusted estimates for cardiovascular mortality were 11.1% (95% confidence interval (CI) 10.8–11.5%) and 10.2% (95% CI 9.9–10.5%), respectively. For cancer mortality, these figures were 8.0% (95% CI 7.7–8.3%) and 7.2% (95% CI 6.9–7.5%). In patients with albuminuria, standard and competing-risks-adjusted estimates for cardiovascular mortality were 21.8% (95% CI 20.9–22.7%) and 18.5% (95% CI 17.8–19.3%), respectively. For cancer mortality, these figures were 10.7% (95% CI 10.0–11.5%) and 8.6% (8.1–9.2%). For the effect of albuminuria on cardiovascular mortality, regression coefficient values from multivariable standard CSH, competing risks CSH, and competing risks SDH models were 0.557 (95% CI 0.491–0.623), 0.561 (95% CI 0.494–0.628), and 0.456 (95% CI 0.389–0.523), respectively. For the effect of albuminuria on cancer mortality, these values were 0.237 (95% CI 0.148–0.326), 0.244 (95% CI 0.154–0.333), and 0.102 (95% CI 0.012–0.192), respectively. Conclusions Studies of absolute risk should use methods that adjust for competing risks to avoid over-stating risk, such as the CICR estimator. Studies of relative risk should consider carefully which measure of association is most appropriate for the research question

Quantifying the effects of diuretics and β-adrenoceptor blockers on glycaemic control in diabetes mellitus - a systematic review and meta-analysis

Although there are reports that β-adrenoceptor antagonists (beta-blockers) and diuretics can affect glycaemic control in people with diabetes mellitus, there is no clear information on how blood glucose concentrations may change and by how much. We report results from a systematic review to quantify the effects of these antihypertensive drugs on glycaemic control in adults with established diabetes.We systematically reviewed the literature to identify randomized controlled trials in which glycaemic control was studied in adults with diabetes taking either beta-blockers or diuretics. We combined data on HbA1c and fasting blood glucose using fixed effects meta-analysis.From 3864 papers retrieved, we found 10 studies of beta-blockers and 12 studies of diuretics to include in the meta-analysis. One study included both comparisons, totalling 21 included reports. Beta-blockers increased fasting blood glucose concentrations by 0.64 mmol l(-1) (95% CI 0.24, 1.03) and diuretics by 0.77 mmol l(-1) (95% CI 0.14, 1.39) compared with placebo. Effect sizes were largest in trials of non-selective beta-blockers (1.33, 95% CI 0.72, 1.95) and thiazide diuretics (1.69, 95% CI 0.60, 2.69). Beta-blockers increased HbA1c concentrations by 0.75% (95% CI 0.30, 1.20) and diuretics by 0.24% (95% CI -0.17, 0.65) compared with placebo. There was no significant difference in the number of hypoglycaemic events between beta-blockers and placebo in three trials.Randomized trials suggest that thiazide diuretics and non-selective beta-blockers increase fasting blood glucose and HbA1c concentrations in patients with diabetes by moderate amounts. These data will inform prescribing and monitoring of beta-blockers and diuretics in patients with diabetes