Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers

BACKGROUND

Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care.

METHODS

Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data.

RESULTS

Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups.

CONCLUSIONS

Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients.

Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomized controlled trial in England

Aims

The aim of the PULsE-AI trial was to assess the effectiveness of a machine learning risk-prediction algorithm in conjunction with diagnostic testing for identifying undiagnosed atrial fibrillation (AF) in primary care in England.

Methods and results

Eligible participants (aged ≥30 years without AF diagnosis; n = 23 745) from six general practices in England were randomized into intervention and control arms. Intervention arm participants, identified by the algorithm as high risk of undiagnosed AF (n = 944), were invited for diagnostic testing (n = 256 consented); those who did not accept the invitation, and all control arm participants, were managed routinely. The primary endpoint was the proportion of AF, atrial flutter, and fast atrial tachycardia diagnoses during the trial (June 2019-February 2021) in high-risk participants. Atrial fibrillation and related arrhythmias were diagnosed in 5.63% and 4.93% of high-risk participants in intervention and control arms, respectively {odds ratio (OR) [95% confidence interval (CI)]: 1.15 (0.77-1.73), P = 0.486}. Among intervention arm participants who underwent diagnostic testing (28.1%), 9.41% received AF and related arrhythmia diagnoses [vs. 4.93% (control); OR (95% CI): 2.24 (1.31-3.73), P = 0.003].

Conclusion

The AF risk-prediction algorithm accurately identified high-risk participants in both arms. While the proportions of AF and related arrhythmia diagnoses were not significantly different between high-risk arms, intervention arm participants who underwent diagnostic testing were twice as likely to receive arrhythmia diagnoses compared with routine care. The algorithm could be a valuable tool to select primary care groups at high risk of undiagnosed AF who may benefit from diagnostic testing.

Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients

AIMS

We investigated whether the use of an atrial fibrillation (AF) risk prediction algorithm could improve AF detection compared with opportunistic screening in primary care and assessed the associated budget impact.

METHODS AND RESULTS

Eligible patients were registered with a general practice in UK, aged 65 years or older in 2018/19, and had complete data for weight, height, body mass index, and systolic and diastolic blood pressure recorded within 1 year. Three screening scenarios were assessed: (i) opportunistic screening and diagnosis (standard care); (ii) standard care replaced by the use of the algorithm; and (iii) combined use of standard care and the algorithm. The analysis considered a 3-year time horizon, and the budget impact for the National Health Service (NHS) costs alone or with personal social services (PSS) costs. Scenario 1 would identify 79 410 new AF cases (detection gap reduced by 22%). Scenario 2 would identify 70 916 (gap reduced by 19%) and Scenario 3 would identify 99 267 new cases (gap reduction 27%). These rates translate into 2639 strokes being prevented in Scenario 1, 2357 in Scenario 2, and 3299 in Scenario 3. The 3-year NHS budget impact of Scenario 1 would be £45.3 million, £3.6 million (difference ‒92.0%) with Scenario 2, and £46.3 million (difference 2.2%) in Scenario 3, but for NHS plus PSS would be ‒£48.8 million, ‒£80.4 million (64.8%), and ‒£71.3 million (46.1%), respectively.

CONCLUSION

Implementation of an AF risk prediction algorithm alongside standard opportunistic screening could close the AF detection gap and prevent strokes while substantially reducing NHS and PSS combined care costs.

Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England

OBJECTIVE

The PULsE-AI trial sought to determine the effectiveness of a screening strategy that included a machine learning risk prediction algorithm in conjunction with diagnostic testing for identification of undiagnosed atrial fibrillation (AF) in primary care. This study aimed to evaluate the cost-effectiveness of implementing the screening strategy in a real-world setting.

METHODS

Data from the PULsE-AI trial - a prospective, randomized, controlled trial conducted across six general practices in England from June 2019 to February 2021 - were used to inform a cost-effectiveness analysis that included a hybrid screening decision tree and Markov AF disease progression model. Model outcomes were reported at both individual- and population-level (estimated UK population ≥30 years of age at high-risk of undiagnosed AF) and included number of patients screened, number of AF cases identified, mean total and incremental costs (screening, events, treatment), quality-adjusted-life-years (QALYs), and incremental cost-effectiveness ratio (ICER).

RESULTS

The screening strategy was estimated to result in 45,493 new diagnoses of AF across the high-risk population in the UK (3.3 million), and an estimated additional 14,004 lifetime diagnoses compared with routine care only. Per-patient costs for high-risk individuals who underwent the screening strategy were estimated at £1,985 (vs £1,888 for individuals receiving routine care only). At a population-level, the screening strategy was associated with a cost increase of approximately £322 million and an increase of 81,000 QALYs. The screening strategy demonstrated cost-effectiveness versus routine care only at an accepted ICER threshold of £20,000 per QALY-gained, with an ICER of £3,994/QALY.

CONCLUSIONS

Compared with routine care only, it is cost-effective to target individuals at high risk of undiagnosed AF, through an AF risk prediction algorithm, who should then undergo diagnostic testing. This AF risk prediction algorithm can reduce the number of patients needed to be screened to identify undiagnosed AF, thus alleviating primary care burden.

Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial

Atrial fibrillation (AF) is associated with an increased risk of stroke, enhanced stroke severity, and other comorbidities. However, AF is often asymptomatic, and frequently remains undiagnosed until complications occur. Current screening approaches for AF lack either cost-effectiveness or diagnostic sensitivity; thus, there is interest in tools that could be used for population screening. An AF risk prediction algorithm, developed using machine learning from a UK dataset of 2,994,837 patients, was found to be more effective than existing models at identifying patients at risk of AF. Therefore, the aim of the trial is to assess the effectiveness of this risk prediction algorithm combined with diagnostic testing for the identification of AF in a real-world primary care setting. Eligible participants (aged ≥30 years and without an existing AF diagnosis) registered at participating UK general practices will be randomised into intervention and control arms. Intervention arm participants identified at highest risk of developing AF (algorithm risk score ≥ 7.4%) will be invited for a 12‑lead electrocardiogram (ECG) followed by two-weeks of home-based ECG monitoring with a KardiaMobile device. Control arm participants will be used for comparison and will be managed routinely. The primary outcome is the number of AF diagnoses in the intervention arm compared with the control arm during the research window. If the trial is successful, there is potential for the risk prediction algorithm to be implemented throughout primary care for narrowing the population considered at highest risk for AF who could benefit from more intensive screening for AF. Trial Registration: NCT04045639.

Updated Software for Automated Assessment of Glucose Variability and Quality of Glycemic Control in Diabetes

Background: Glycemic variability is an important factor to consider in diabetes management. It can be assessed with multiple glycemic variability metrics and quality of control indices based on continuous glucose monitoring (CGM) recordings. For this, a robust repeatable calculation is important. A widely used tool for automated assessment is the EasyGV software. The aim of this work is to implement new methods of glycemic variability assessment in EasyGV and to validate implementation of each glucose metric in EasyGV against a reference implementation of the calculations. Methods: Validation data used came from the JDRF CGM study. Validation of the implementation of metrics that are available in EasyGV software v9 was carried out and the following new methods were added and validated: personal glycemic state, index of glycemic control, times in ranges, and glycemic variability percentage. Reference values considered gold standard calculations were derived from MATLAB implementation of each metric. Results: The Pearson correlation coefficient was above 0.98 for all metrics, except for mean amplitude of glycemic excursion (r = 0.87) as EasyGV implements a fuzzy logic approach to assessment of variability. Bland-Altman plots demonstrated validation of the new software. Conclusions: The new freely available EasyGV software v10 (www.phc.ox.ac.uk/research/technology-outputs/easygv) is a validated robust tool for analyzing different glycemic variabilities and control metrics.

Assessment of Glucose Control Metrics by Discriminant Ratio

Objective: Increasing use of continuous glucose monitoring (CGM) data has created an array of glucose metrics for glucose variability, temporal patterns, and times in ranges. However, a gold standard metric has not been defined. We assess the performance of multiple glucose metrics to determine their ability to detect intra- and interperson variability to determine a set of recommended metrics. Methods: The Juvenile Diabetes Research Foundation data set, a randomized controlled study of CGM and self-monitored blood glucose conducted in children and adults with type 1 diabetes (T1D), was used. To determine the ability of the evaluated glycemic metrics to discriminate between different subjects and attenuate the effect of within-subject variation, the discriminant ratio was calculated and compared for each metric. Then, the findings were confirmed using data from two other recent randomized clinical trials. Results: Mean absolute glucose (MAG) has the highest discriminant ratio value (2.98 [95% confidence interval {CI} 1.64-3.67]). In addition, low blood glucose index and index of glycemic control performed well (1.93 [95% CI 1.15-3.44] and 1.92 [95% CI 1.27-2.93], respectively). For percentage times in glucose target ranges, the optimal discriminator was percentage time in glucose target 70-180 mg/dL. Conclusions: MAG is the optimal index to differentiate glucose variability in people with T1D, and may be a complementary therapeutic monitoring tool in addition to glycated hemoglobin and a measure of hypoglycemia. Percentage time in glucose target 70-180 mg/dL is the optimal percentage time in range to report.

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study

AIMS

To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care.

METHODS

A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years. Algorithm performance metrics were sensitivity, specificity, positive predictive value, negative predictive value (NPV) and number needed to screen (NNS). Subgroup analysis of patients aged ≥65 years was also performed.

RESULTS

Of 2,542,732 patients in DISCOVER, the algorithm identified 604,135 patients suitable for risk assessment. Of these, 3.0% (17,880 patients) had a diagnosis of atrial fibrillation recorded before study end. The area under the curve of the receiver operating characteristic was 0.87, compared with 0.83 in algorithm development. The NNS was nine patients, matching the CPRD cohort. In patients aged ≥30 years, the algorithm correctly identified 99.1% of patients who did not have atrial fibrillation (NPV) and 75.0% of true atrial fibrillation cases (sensitivity). Among patients aged ≥65 years (n = 117,965), the NPV was 96.7% with 91.8% sensitivity.

CONCLUSIONS

This atrial fibrillation risk prediction algorithm, based on machine learning methods, identified patients at highest risk of atrial fibrillation. It performed comparably in a large, real-world population-based cohort and the developmental registry cohort. If implemented in primary care, the algorithm could be an effective tool for narrowing the population who would benefit from atrial fibrillation screening in the United Kingdom.

A Systematic Review of Network Meta-Analyses and Real-World Evidence Comparing Apixaban and Rivaroxaban in Nonvalvular Atrial Fibrillation

There is no direct evidence comparing the 2 most commonly prescribed direct oral anticoagulants, apixaban and rivaroxaban, used for stroke prevention in nonvalvular atrial fibrillation (NVAF). A number of network meta-analyses (NMAs) of randomized control trials and real-world evidence (RWE) studies comparing the efficacy, effectiveness, and safety of apixaban and rivaroxaban have been published; however, a comprehensive evidence review across the available body of evidence is lacking. In this study, we aimed to systematically review and evaluate the clinical outcomes of apixaban and rivaroxaban using a combination of data gleaned from both NMAs and RWE studies. The review identified 21 NMAs and 5 RWE studies. The data demonstrated that apixaban was associated with fewer major bleeding events compared to rivaroxaban. There was no difference in the efficacy/effectiveness profiles between these treatments. Bleeding is a serious complication of anticoagulation therapy for the management of NVAF, and is associated with increased rates of hospitalization, morbidity, mortality, and health-care expenditure. The majority of studies in this comprehensive evidence review suggests that apixaban has a lower risk of major bleeding events compared to rivaroxaban in patients with NVAF.

Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm

Aims: As many cases of atrial fibrillation (AF) are asymptomatic, patients often remain undiagnosed until complications (e.g. stroke) manifest. Risk-prediction algorithms may help to efficiently identify people with undiagnosed AF. However, the cost-effectiveness of targeted screening remains uncertain. This study aimed to assess the cost-effectiveness of targeted screening, informed by a machine learning (ML) risk prediction algorithm, to identify patients with AF.Methods: Cost-effectiveness analyses were undertaken utilizing a hybrid screening decision tree and Markov disease progression model. Costs and outcomes associated with the detection of AF compared traditional systematic and opportunistic AF screening strategies to targeted screening informed by a ML risk prediction algorithm. Model analyses were based on adults ≥50 years and adopted the UK NHS perspective.Results: Targeted screening using the ML risk prediction algorithm required fewer patients to be screened (61 per 1,000 patients, compared to 534 and 687 patients in the systematic and opportunistic strategies) and detected more AF cases (11 per 1,000 patients, compared to 6 and 8 AF cases in the systematic and opportunistic screening strategies). The targeted approach demonstrated cost-effectiveness under base case settings (cost per QALY gained of £4,847 and £5,544 against systematic and opportunistic screening respectively). The targeted screening strategy was predicted to provide an additional 3.40 and 2.05 QALYs per 1,000 patients screened versus systematic and opportunistic strategies. The targeted screening strategy remained cost-effective in all scenarios evaluated.Limitations: The analysis relied on assumptions that include the extended period of patient life span and the lack of consideration for treatment discontinuations/switching, as well as the assumption that the ML risk-prediction algorithm will identify asymptomatic AF.Conclusions: Targeted screening using a ML risk prediction algorithm has the potential to enhance the clinical and cost-effectiveness of AF screening, improving health outcomes through efficient use of limited healthcare resources.

An observational study of international normalized ratio control according to NICE criteria in patients with non-valvular atrial fibrillation: the SAIL Warfarin Out of Range Descriptors Study (SWORDS)

AIMS 

In patients with non-valvular atrial fibrillation prescribed warfarin, the UK National Institute of Health and Care Excellence (NICE) defines poor anticoagulation as a time in therapeutic range (TTR) of <65%, any two international normalized ratios (INRs) within a 6-month period of ≤1.5 ('low'), two INRs ≥5 within 6 months, or any INR ≥8 ('high'). Our objectives were to (i) quantify the number of patients with poor INR control and (ii) describe the demographic and clinical characteristics associated with poor INR control.

METHOD AND RESULTS

Linked anonymized health record data for Wales, UK (2006-2017) was used to evaluate patients prescribed warfarin who had at least 6 months of INR data. 32 380 patients were included. In total, 13 913 (43.0%) patients had at least one of the NICE markers of poor INR control. Importantly, in the 24 123 (74.6%) of the cohort with an acceptable TTR (≥65%), 5676 (23.5%) had either low or high INR readings at some point in their history. In a multivariable regression female gender, age (≥75 years), excess alcohol, diabetes heart failure, ischaemic heart disease, and respiratory disease were independently associated with all markers of poor INR control.

CONCLUSION 

Acceptable INR control according to NICE standards is poor. Of those with an acceptable TTR (>65%), one-quarter still had unacceptably low or high INR levels according to NICE criteria. Thus, only using TTR to assess effectiveness with warfarin has the potential to miss a large number of patients with non-therapeutic INRs who are likely to be at increased risk.

Evolution of the burden of active hepatitis C virus infection in England from September 2015 to September 2016: a repeated cross-sectional analysis

OBJECTIVE

To evaluate the impact of treatment with new direct-acting antivirals (DAAs) on the prevalent hepatitis C virus (HCV) population in England.

DESIGN

A repeated cross-sectional analysis.

SETTING

Four secondary care hospitals in England.

PARTICIPANTS

Patients who, in 2015 and/or 2016, had chronic HCV infection and were alive were eligible, regardless of the type of HCV intervention received.

OUTCOME MEASURES

Data including intravenous drug use (IVDU) status, HCV genotype, cirrhosis status, HCV treatment history, vital status and treatment outcomes were collected at two time points in 2015 and 2016 using electronic case report forms.

RESULTS

There were 1605 and 1355 patients with active chronic HCV in 2015 and 2016, respectively. Between 2015 and 2016, the proportion of patients with current IVDU increased (10.3% vs 14.5%, respectively), while that of patients with cirrhosis (28.2% vs 22.4%) and treatment-experienced patients (31.2% vs 27.1%) decreased. Among patients whose treatment outcome was known by 2016, high cure rates were observed, with an overall sustained virological response rate of 93.2%. From 2015 to 2016, there was a progressive increase in the proportion of treated patients who were non-cirrhotic, with current IVDU and non-liver transplant recipients.

CONCLUSIONS

The characteristics of patients with HCV remaining in contact with specialised care evolved with a changing landscape of treatment and related health policy. With increasing access to DAAs in UK, high cure rates were achieved in the study cohort.

RIPK3-deficient mice were not protected from nephrotoxic nephritis

Background

Necrotizing glomerular lesions are a feature of severe glomerulonephritis. Unlike apoptosis, cellular necrosis has the potential to release damage-associated proteins into the microenvironment, thereby potentiating inflammation. Until recently necrosis was thought to be an unregulated cellular response to injury. However, recent evidence suggests that under certain circumstances receptor mediated necrosis occurs in response to death ligand signalling, one form of which is termed necroptosis. RIPK3, a receptor interacting protein, is a limiting step in the intracellular signalling pathway of necroptosis. A non-redundant role for RIPK3 has been implicated in mouse models of renal ischaemia reperfusion injury and toxic renal injury. The aim of this study was to investigate the role of RIPK3 in nephrotoxic nephritis (NTN), a model of immune complex glomerulonephritis in mice.

Methods

We induced NTN in RIPK3−/− and WT mice, comparing histology and renal function in both groups.

Results

There was no improvement in urinary albumin creatinine ratio, serum urea, glomerular thrombosis or glomerular macrophage infiltration in the RIPK3−/− mice compared to WT. There was also no difference in number of apoptotic cells in glomeruli as measured by TUNEL staining between the RIPK3−/− and WT mice.

Conclusion

The data suggests that RIPK3 is not on a critical pathway in the pathogenesis of nephrotoxic nephritis.

Effectiveness of current and future regimens for treating genotype 3 hepatitis C virus infection: a large-scale systematic review

BACKGROUND

Six distinct genetic variants (genotypes 1 - 6) of hepatitis C virus (HCV) exist globally. Certain genotypes are more prevalent in particular countries or regions than in others but, globally, genotype 3 (GT3) is the second most common. Patients infected with HCV GT1, 2, 4, 5 or 6 recover to a greater extent, as measured by sustained virological response (SVR), following treatment with regimens based on direct-acting antivirals (DAAs) than after treatment with older regimens based on pegylated interferon (Peg-IFN). GT3, however, is regarded as being more difficult to treat as it is a relatively aggressive genotype, associated with greater liver damage and cancer risk; some subgroups of patients with GT3 infection are less responsive to current licensed DAA treatments. Newer DAAs have become available or are in development.

METHODS

According to PRISMA guidance, we conducted a systematic review (and descriptive statistical analysis) of data in the public domain from relevant clinical trial or observational (real-world) study publications within a 5-year period (February 2011 to May 2016) identified by PubMed, Medline In-Process, and Embase searches. This was supplemented with a search of five non-indexed literature sources, comprising annual conferences of the AASLD, APASL, CROI, EASL, and WHO, restricted to a 1-year period (April 2015 to May 2016).

RESULTS

Of the all-oral regimens, the efficacy (SVR12 ≥ 90%) of sofosbuvir plus daclatasvir- and velpatasvir-based regimens in clinical trials supports and reinforces their recommendation by guidelines. Other promising regimens comprise grazoprevir + elbasvir + sofosbuvir, and ombitasvir + paritaprevir/ribavirin + sofosbuvir. Newer regimens incorporating pibrentasvir + glecaprevir or grazoprevir + ruzasvir + MK-3682 (uprifosbuvir), offer all-oral, ribavirin-free SVR12 rates consistently greater than 95%. Observational studies report slightly lower overall SVR rates but reflect corresponding clinical trial data in terms of treatments most likely to achieve good responses.

CONCLUSIONS

On the basis of SVR12, we established that for treating GT3 infections (i) regimens incorporating newer DAAs are more effective than those comprising older DAAs, and (ii) ribavirin may be of less benefit in newer DAA regimens than in older DAA regimens. The analysis provides evidence that DAA regimens can replace Peg-IFN-based regimens for GT3 infection.

Global Prevalence of Chronic Kidney Disease - A Systematic Review and Meta-Analysis

Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and is an independent risk factor for cardiovascular disease (CVD). All stages of CKD are associated with increased risks of cardiovascular morbidity, premature mortality, and/or decreased quality of life. CKD is usually asymptomatic until later stages and accurate prevalence data are lacking. Thus we sought to determine the prevalence of CKD globally, by stage, geographical location, gender and age. A systematic review and meta-analysis of observational studies estimating CKD prevalence in general populations was conducted through literature searches in 8 databases. We assessed pooled data using a random effects model. Of 5,842 potential articles, 100 studies of diverse quality were included, comprising 6,908,440 patients. Global mean(95%CI) CKD prevalence of 5 stages 13·4%(11·7-15·1%), and stages 3-5 was 10·6%(9·2-12·2%). Weighting by study quality did not affect prevalence estimates. CKD prevalence by stage was Stage-1 (eGFR>90+ACR>30): 3·5% (2·8-4·2%); Stage-2 (eGFR 60-89+ACR>30): 3·9% (2·7-5·3%); Stage-3 (eGFR 30-59): 7·6% (6·4-8·9%); Stage-4 = (eGFR 29-15): 0·4% (0·3-0·5%); and Stage-5 (eGFR<15): 0·1% (0·1-0·1%). CKD has a high global prevalence with a consistent estimated global CKD prevalence of between 11 to 13% with the majority stage 3. Future research should evaluate intervention strategies deliverable at scale to delay the progression of CKD and improve CVD outcomes.

A 24-Hour Study of the Hypothalamo-Pituitary Axes in Huntington's Disease

Background

Huntington’s disease is an inherited neurodegenerative disorder characterised by motor, cognitive and psychiatric disturbances. Patients exhibit other symptoms including sleep and mood disturbances, muscle atrophy and weight loss which may be linked to hypothalamic pathology and dysfunction of hypothalamo-pituitary axes.

Methods

We studied neuroendocrine profiles of corticotropic, somatotropic and gonadotropic hypothalamo-pituitary axes hormones over a 24-hour period in controlled environment in 15 healthy controls, 14 premanifest and 13 stage II/III Huntington’s disease subjects. We also quantified fasting levels of vasopressin, oestradiol, testosterone, dehydroepiandrosterone sulphate, thyroid stimulating hormone, free triiodothyronine, free total thyroxine, prolactin, adrenaline and noradrenaline. Somatotropic axis hormones, growth hormone releasing hormone, insulin-like growth factor-1 and insulin-like factor binding protein-3 were quantified at 06:00 (fasting), 15:00 and 23:00. A battery of clinical tests, including neurological rating and function scales were performed.

Results

24-hour concentrations of adrenocorticotropic hormone, cortisol, luteinizing hormone and follicle-stimulating hormone did not differ significantly between the Huntington’s disease group and controls. Daytime growth hormone secretion was similar in control and Huntington’s disease subjects. Stage II/III Huntington’s disease subjects had lower concentration of post-sleep growth hormone pulse and higher insulin-like growth factor-1:growth hormone ratio which did not reach significance. In Huntington’s disease subjects, baseline levels of hypothalamo-pituitary axis hormones measured did not significantly differ from those of healthy controls.

Conclusions

The relatively small subject group means that the study may not detect subtle perturbations in hormone concentrations. A targeted study of the somatotropic axis in larger cohorts may be warranted. However, the lack of significant results despite many variables being tested does imply that the majority of them do not differ substantially between HD and controls.

CD14 expression is increased on monocytes in patients with anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis and correlates with the expression of ANCA autoantigens

Monocyte subsets with differing functional properties have been defined by their expression of CD14 and CD16. We investigated these subsets in anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) and determined their surface expression of ANCA autoantigens. Flow cytometry was performed on blood from 14 patients with active AAV, 46 patients with AAV in remission and 21 controls. The proportion of classical (CD14(high) CD16(neg/low)), intermediate (CD14(high) CD16(high)) and non-classical (CD14(low) CD16(high)) monocytes and surface expression levels of CD14 and CD16 were determined, as well as surface expression of proteinase 3 (PR3) and myeloperoxidase (MPO) on monocyte subsets. There was no change in the proportion of monocytes in each subset in patients with AAV compared with healthy controls. The expression of CD14 on monocytes from patients with active AAV was increased, compared with patients in remission and healthy controls (P < 0.01). Patients with PR3-ANCA disease in remission also had increased monocyte expression of CD14 compared with controls (P < 0.01); however, levels in patients with MPO-ANCA disease in remission were lower than active MPO-ANCA patients, and not significantly different from controls. There was a correlation between CD14 and both PR3 and MPO expression on classical monocytes in AAV patients (r = 0.79, P < 0.0001 and r = 0.42, P < 0.005, respectively). In conclusion, there was an increase in monocyte CD14 expression in active AAV and PR3-ANCA disease in remission. The correlation of CD14 expression with ANCA autoantigen expression in AAV may reflect cell activation, and warrants further investigation into the potential for increased CD14 expression to trigger disease induction or relapse.

Investigating the sustainability of careers in academic primary care: a UK survey

Background

The UK National Health Service (NHS) is undergoing institutional reorganisation due to the Health and Social Care Act-2012 with a continued restriction on funding within the NHS and clinically focused academic institutions. The UK Society for Academic Primary Care (SAPC) is examining the sustainability of academic primary care careers within this climate and preliminary qualitative work has highlighted individual and organisational barriers. This study seeks to quantify the current situation for academics within primary care.

Methods

A survey of academic primary care staff was undertaken. Fifty-three academic primary care departments were selected. Members were invited to complete a survey which contained questions about an individual’s career, clarity of career pathways, organisational culture, and general experience of working within the area. Data were analysed descriptively with cross-tabulations between survey responses and career position (early, mid-level, senior), disciplinary background (medical, scientist), and gender. Pearson chi-square test was used to determine likelihood that any observed difference between the sets arose by chance.

Results

Responses were received from 217 people. Career pathways were unclear for the majority of people (64%) and 43% of the workforce felt that the next step in their career was unclear. This was higher in women (52% vs. men 25%; χ²(3) = 14.76; p = 0.002) and higher in those in early career (50% vs. senior career, 25%) and mid-career(45%; vs. senior career; χ²(6) = 29.19, p < 0.001). The workforce appeared geographically static but unstable with only 50% of people having their contract renewed or extended. The majority of people (59%) have never been promoted by their institution. There were perceptions of gender equality even in the context of females being underrepresented in senior positions (19% vs. males 39%; χ²(3) = 8.43, p = 0.015). Despite these findings, the majority of the workforce reported positive organisational and cultural experiences.

Conclusions

Sustainability of a academic primary care career is undermined by unclear pathways and a lack of promotion. If the discipline is to thrive, there is a need to support early and mid-career individuals via greater transparency of career pathways. Despite these findings staff remained positive about their careers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12875-014-0205-6) contains supplementary material, which is available to authorized users.

Plasma melatonin is reduced in Huntington's disease

This study was undertaken to determine whether the production of melatonin, a hormone regulating sleep in relation to the light/dark cycle, is altered in Huntington's disease. We analyzed the circadian rhythm of melatonin in a 24-hour study of cohorts of control, premanifest, and stage II/III Huntington's disease subjects. The mean and acrophase melatonin concentrations were significantly reduced in stage II/III Huntington's disease subjects compared with controls. We also observed a nonsignificant trend toward reduced mean and acrophase melatonin in premanifest Huntington's disease subjects. Onset of melatonin rise was significantly more temporally spread in both premanifest and stage II/III Huntington's disease subjects compared with controls. A nonsignificant trend also was seen for reduced pulsatile secretion of melatonin. Melatonin concentrations are reduced in Huntington's disease. Altered melatonin patterns may provide an explanation for disrupted sleep and circadian behavior in Huntington's disease, and represent a biomarker for disease state. Melatonin therapy may help the sleep disorders seen in Huntington's disease.

Low circulating levels of IGF-1 in healthy adults are associated with reduced β-cell function, increased intramyocellular lipid, and enhanced fat utilization during fasting

CONTEXT

Low serum IGF-1 levels have been linked to increased risk for development of type 2 diabetes. However, the physiological role of IGF-1 in glucose metabolism is not well characterized.

OBJECTIVE

Our objective was to explore glucose and lipid metabolism associated with variations in serum IGF-1 levels.

DESIGN, SETTING AND PARTICIPANTS

IGF-1 levels were measured in healthy, nonobese male volunteers aged 18 to 50 years from a biobank (n = 275) to select 24 subjects (age 34.8 ± 8.9 years), 12 each in the lowest (low-IGF) and highest (high-IGF) quartiles of age-specific IGF-1 SD scores. Evaluations were undertaken after a 24-hour fast and included glucose and glycerol turnover rates using tracers, iv glucose tolerance test to estimate peripheral insulin sensitivity (IS) and acute insulin and C-peptide responses (indices of insulin secretion), magnetic resonance spectroscopy to measure intramyocellular lipids (IMCLs), calorimetry, and gene expression studies in a muscle biopsy.

MAIN OUTCOME MEASURES

Acute insulin and C-peptide responses, IS, and glucose and glycerol rate of appearance (Ra) were evaluated.

RESULTS

Fasting insulin and C-peptide levels and glucose Ra were reduced (all P < .05) in low-IGF compared with high-IGF subjects, indicating increased hepatic IS. Acute insulin and C-peptide responses were lower (both P < .05), but similar peripheral IS resulted in reduced insulin secretion adjusted for IS in low-IGF subjects (P = 0.044). Low-IGF subjects had higher overnight levels of free fatty acids (P = .028) and β-hydroxybutyrate (P = .014), increased accumulation of IMCLs in tibialis anterior muscle (P = .008), and a tendency for elevated fat oxidation rates (P = .058); however, glycerol Ra values were similar. Gene expression of the fatty acid metabolism pathway (P = .0014) was upregulated, whereas the GLUT1 gene was downregulated (P = .005) in the skeletal muscle in low-IGF subjects.

CONCLUSIONS

These data suggest that serum IGF-1 levels could be an important marker of β-cell function and glucose as well as lipid metabolic responses during fasting.

Benefits of Aldosterone Receptor Antagonism in Chronic Kidney Disease (BARACK D) trial-a multi-centre, prospective, randomised, open, blinded end-point, 36-month study of 2,616 patients within primary care with stage 3b chronic kidney disease to compare the efficacy of spironolactone 25 mg once daily in addition to routine care on mortality and cardiovascular outcomes versus routine care alone: study protocol for a randomized controlled trial

BACKGROUND

Chronic kidney disease (CKD) is common and increasing in prevalence. Cardiovascular disease (CVD) is a major cause of morbidity and death in CKD, though of a different phenotype to the general CVD population. Few therapies have proved effective in modifying the increased CVD risk or rate of renal decline in CKD. There are accumulating data that aldosterone receptor antagonists (ARA) may offer cardio-protection and delay renal impairment in patients with the CV phenotype in CKD. The use of ARA in CKD has therefore been increasingly advocated. However, no large study of ARA with renal or CVD outcomes is underway.

METHODS

The study is a prospective randomised open blinded endpoint (PROBE) trial set in primary care where patients will mainly be identified by their GPs or from existing CKD lists. They will be invited if they have been formally diagnosed with CKD stage 3b or there is evidence of stage 3b CKD from blood results (eGFR 30-44 mL/min/1.73 m2) and fulfil the other inclusion/exclusion criteria. Patients will be randomised to either spironolactone 25 mg once daily in addition to routine care or routine care alone and followed-up for 36 months.

DISCUSSION

BARACK D is a PROBE trial to determine the effect of ARA on mortality and cardiovascular outcomes (onset or progression of CVD) in patients with stage 3b CKD.

TRIAL REGISTRATION

EudraCT: 2012-002672-13ISRTN: ISRCTN44522369.

The Oxford Renal (OxRen) cross-sectional study of chronic kidney disease in the UK

INTRODUCTION

Chronic kidney disease (CKD) diagnosed with objective measures of kidney damage and function has been recognised as a major public health burden. Independent of age, sex, ethnicity and comorbidity, strong associations exist between cardiovascular disease, mortality, morbidity and CKD, defined by reduced glomerular filtration rate and increased urinary albumin excretion. Detection of CKD within the population is therefore a priority for health systems.

METHODS AND ANALYSIS

15 000 patients aged 60 years or over meeting the inclusion criteria will be invited to the study. Recruitment will be stratified to represent the distribution of socioeconomic position in the UK general population. Patients will be excluded if terminally ill (expected survival <1 year), or if they have received a solid organ transplant. Patients will attend up to two screening visits, to determine if they have CKD, followed by an assessment visit where demographic and physiological parameters will be recorded alongside questionnaires on exercise, diet, cognitive assessment and quality of life. Blood and urine specimens will be taken for immediate routine assays as well as for freezing pending peptide and genetic studies. Patients will have office and home blood pressure measurements as well as pulse wave velocity assessment. Healthcare costs of screening and subsequent monitoring will be calculated.

ETHICS AND DISSEMINATION

The protocol and related documents have been approved by NRES Committee South Central-Oxford B-Reference 13/SC/0020.

Expansion of the homeostasis model assessment of β-cell function and insulin resistance to enable clinical trial outcome modeling through the interactive adjustment of physiology and treatment effects: iHOMA2

OBJECTIVE

To describe and make available an interactive, 24-variable homeostasis model assessment (iHOMA2) that extends the HOMA2 model, enabling the modeling of physiology and treatment effects, to present equations of the HOMA2 and iHOMA2 models, and to exemplify iHOMA2 in two widely differing scenarios: changes in insulin sensitivity with thiazolidinediones and changes in renal threshold with sodium glucose transporter 2 (SGLT2) inhibition.

RESEARCH DESIGN AND METHODS

iHOMA2 enables a user of the available software to examine and modify the mathematical functions describing the organs and tissues involved in the glucose and hormonal compartments. We exemplify this with SGLT2 inhibition modeling (by changing the renal threshold parameters) using published data of renal effect, showing that the modeled effect is concordant with the effects on fasting glucose from independent data.

RESULTS

iHOMA2 modeling of thiazolidinediones effect suggested that changes in insulin sensitivity in the fasting state are predominantly hepatic. SGLT2 inhibition modeled by iHOMA2 resulted in a decrease in mean glucose of 1.1 mmol/L. Observed data showed a decrease in glucose of 0.9 mmol/L. There was no significant difference between the model and the independent data. Manipulation of iHOMA2's renal excretion threshold variable suggested that a decrease of 17% was required to obtain a 0.9 mmol/L decrease in mean glucose.

CONCLUSIONS

iHOMA2 is an extended mathematical model for the assessment of insulin resistance and β-cell function. The model can be used to evaluate therapeutic agents and predict effects on fasting glucose and insulin and on β-cell function and insulin sensitivity.

Methodology for quantifying fasting glucose homeostasis in type 2 diabetes: observed variability and lability

BACKGROUND

Increased glycemic variability is associated with an increase risk of adverse clinical outcomes in diabetes. Central to the understanding of diabetes is glucose homeostasis. "Good" homeostasis is equated to low glycemic variability, and "poor" homeostasis is linked to greater glycemic variability. We have, therefore, developed a method with the aim to objectively quantify the domain of glucose-insulin homeostasis. We have termed this method as Observed Variability And Lability (OVAL).

METHOD

Blood samples for the measurement of glucose and insulin concentrations were acquired every 2 min for 120 min from 12 patients with type 2 diabetes mellitus [T2DM; median (range) age 35 (25-47) years and duration of diabetes 7 (2-9) years receiving oral hypoglycemic treatment] and 27 controls [aged 38(30-53) years] with an equal split of genders and equal distribution of body mass indexes. The insulin-glucose time variant data form the boundaries of OVAL, defined as the ellipse enclosing the 95% confidence intervals of the insulin and glucose concentrations plotted on an x-y scatter graph and normalized to ensure equal weighting of insulin and glucose.

RESULTS

Less precise OVAL homeostasis was observed in subjects with T2DM, by a factor of 4, in comparison with controls [OVAL, T2DM 7.8(3.8) versus controls 1.9(1.0); p = .0003]. The assessment remained statistically robust (p < .001) with increased sampling intervals up to 8 min.

CONCLUSION

The OVAL model is a robust method for measuring glucose-insulin homeostasis in controls and T2DM subjects (available online at http://www.oval-calc.co.uk). Deranged glucose-insulin homeostasis is the hallmark of diabetes and OVAL has the capacity to quantify in the fasting state.

Maternal hyperinsulinism and glycaemic status in the first trimester of pregnancy are associated with the development of pregnancy-induced hypertension and gestational diabetes

OBJECTIVE

To evaluate the relationships across a range of glucose and insulin measures at 12 weeks of gestation with the development of pregnancy-induced hypertension (PIH), gestational diabetes mellitus (GDM) and birth size.

MATERIALS AND METHODS

Prospective study of pregnant women booking before 15th week of gestation. At the first antenatal visit, standard measures of height, weight, blood pressure (BP) and social status were recorded, and blood sample was drawn for measurements of fasting glucose and plasma insulin. Oral glucose tolerance test with 75  g glucose load was performed after overnight fast. Odds ratios (ORs) with 95% CI were calculated to determine the risk of developing PIH or GDM depending on quartiles of blood glucose or tertiles of plasma insulin levels.

RESULTS

One thousand six hundred and fifty pregnant women were included in the study. Of them, 1484 delivered a live infant of whom 70 were preterm, 166 did not complete the study, 155 mothers developed PIH (10.4%), 18 were diagnosed with GDM (1.2%) and four had both PIH and GDM. At 12 weeks of gestation, women who became hypertensive were heavier (P<0.001), with higher BMI (P<0.001) than controls. Both systolic (P<0.001) and diastolic BPs (P<0.001) were already higher in women who developed PIH. Fasting insulin concentrations were higher in PIH group (P<0.002). Fasting glucose level >6.8 mmol/l was associated with the likelihood of delivering a macrosomic baby (OR 3.1 (95% CI: 1.21-8.0); P=0.02); the effect was heightened in multiparous mothers (OR 4.0 (95% CI: 1.4-11.1); P=0.01). Fasting plasma insulin had, however, no effect on size at birth in this study.

CONCLUSIONS

Our data suggest that women who develop PIH may be metabolically challenged at early stages of pregnancy with hyperinsulinism, insulin insensitivity and slightly higher BP.

Proliferation rates of multiple endocrine neoplasia type 1 (MEN1)-associated tumors

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterized by the combined occurrence of parathyroid and adrenocortical tumors, and neuroendocrine tumors (NETs) of the pancreas and pituitary. The pancreatic NETs are predominantly gastrinomas and insulinomas, and the pituitary NETs are mostly prolactinomas and somatotrophinomas. We postulated that the different types of pancreatic and pituitary NETs may be partly due to differences in their proliferation rates, and we therefore assessed these in MEN1-associated tumors and gonadal tumors that developed in mice deleted for an Men1 allele (Men1(+/-)). To label proliferating cells in vivo, Men1(+/-) and wild-type (Men1(+/+)) mice were given 5-bromo-2-deoxyuridine (BrdU) in drinking water from 1-12 wk, and tissue sections were immunostained using anti-BrdU and hormone-specific antibodies. Proliferation in the tumors of Men1(+/-) mice was significantly (P < 0.001) increased when compared with the corresponding normal Men1(+/+) tissues. Pancreatic, pituitary and adrenocortical proliferation fitted first- and second-order regression lines in Men1(+/+) tissues and Men1(+/-) tumors, respectively, R(2) = 0.999. Apoptosis was similar in Men1(+/-) pancreatic, pituitary, and parathyroid tumors when compared with corresponding normal tissues, decreased in Men1(+/-) adrenocortical tumors, but increased in Men1(+/-) gonadal tumors. Mathematical modeling of NET growth rates (proliferation minus apoptosis rates) predicted that in Men1(+/-) mice, only pancreatic β-cells, pituitary lactotrophs and somatotrophs could develop into tumors within a murine lifespan. Thus, our studies demonstrate that Men1(+/-) tumors have low proliferation rates (<2%), second-order kinetics, and the higher occurrence of insulinomas, prolactinomas, and somatotrophinomas in MEN1 is consistent with a mathematical model for NET proliferation.

Normal reference range for mean tissue glucose and glycemic variability derived from continuous glucose monitoring for subjects without diabetes in different ethnic groups

BACKGROUND

Glycemic variability has been proposed as a contributing factor in the development of diabetes complications. Multiple measures exist to calculate the magnitude of glycemic variability, but normative ranges for subjects without diabetes have not been described. For treatment targets and clinical research we present normative ranges for published measures of glycemic variability.

METHODS

Seventy-eight subjects without diabetes having a fasting plasma glucose of <120 mg/dL (6.7 mmol/L) underwent up to 72 h of continuous glucose monitoring (CGM) with a Medtronic Minimed (Northridge, CA) CGMS(®) Gold device. Glycemic variability was calculated using EasyGV(©) software (available free for non-commercial use at www.easygv.co.uk ), a custom program that calculates the SD, M-value, mean amplitude of glycemic excursions (MAGE), average daily risk ratio (ADRR), Lability Index (LI), J-Index, Low Blood Glucose Index (LBGI), High Blood Glucose Index (HBGI), continuous overlapping net glycemic action (CONGA), mean of daily differences (MODD), Glycemic Risk Assessment in Diabetes Equation (GRADE), and mean absolute glucose (MAG).

RESULTS

Eight CGM traces were excluded because there were inadequate data. From the remaining 70 traces, normative reference ranges (mean±2 SD) for glycemic variability were calculated: SD, 0-3.0; CONGA, 3.6-5.5; LI, 0.0-4.7; J-Index, 4.7-23.6; LBGI, 0.0-6.9; HBGI, 0.0-7.7; GRADE, 0.0-4.7; MODD, 0.0-3.5; MAGE-CGM, 0.0-2.8; ADDR, 0.0-8.7; M-value, 0.0-12.5; and MAG, 0.5-2.2.

CONCLUSIONS

We present normative ranges for measures of glycemic variability in adult subjects without diabetes for use in clinical care and academic research.

Normal reference range for mean tissue glucose and glycemic variability derived from continuous glucose monitoring for subjects without diabetes in different ethnic groups

BACKGROUND

Glycemic variability has been proposed as a contributing factor in the development of diabetes complications. Multiple measures exist to calculate the magnitude of glycemic variability, but normative ranges for subjects without diabetes have not been described. For treatment targets and clinical research we present normative ranges for published measures of glycemic variability.

METHODS

Seventy-eight subjects without diabetes having a fasting plasma glucose of <120 mg/dL (6.7 mmol/L) underwent up to 72 h of continuous glucose monitoring (CGM) with a Medtronic Minimed (Northridge, CA) CGMS(®) Gold device. Glycemic variability was calculated using EasyGV(©) software (available free for non-commercial use at www.easygv.co.uk ), a custom program that calculates the SD, M-value, mean amplitude of glycemic excursions (MAGE), average daily risk ratio (ADRR), Lability Index (LI), J-Index, Low Blood Glucose Index (LBGI), High Blood Glucose Index (HBGI), continuous overlapping net glycemic action (CONGA), mean of daily differences (MODD), Glycemic Risk Assessment in Diabetes Equation (GRADE), and mean absolute glucose (MAG).

RESULTS

Eight CGM traces were excluded because there were inadequate data. From the remaining 70 traces, normative reference ranges (mean±2 SD) for glycemic variability were calculated: SD, 0-3.0; CONGA, 3.6-5.5; LI, 0.0-4.7; J-Index, 4.7-23.6; LBGI, 0.0-6.9; HBGI, 0.0-7.7; GRADE, 0.0-4.7; MODD, 0.0-3.5; MAGE-CGM, 0.0-2.8; ADDR, 0.0-8.7; M-value, 0.0-12.5; and MAG, 0.5-2.2.

CONCLUSIONS

We present normative ranges for measures of glycemic variability in adult subjects without diabetes for use in clinical care and academic research.

Sleep apnea predicts distinct alterations in glucose homeostasis and biomarkers in obese adults with normal and impaired glucose metabolism

BACKGROUND

Notwithstanding previous studies supporting independent associations between obstructive sleep apnea (OSA) and prevalence of diabetes, the underlying pathogenesis of impaired glucose regulation in OSA remains unclear. We explored mechanisms linking OSA with prediabetes/diabetes and associated biomarker profiles. We hypothesized that OSA is associated with distinct alterations in glucose homeostasis and biomarker profiles in subjects with normal (NGM) and impaired glucose metabolism (IGM).

METHODS

Forty-five severely obese adults (36 women) without certain comorbidities/medications underwent anthropometric measurements, polysomnography, and blood tests. We measured fasting serum glucose, insulin, selected cytokines, and calculated homeostasis model assessment estimates of insulin sensitivity (HOMA-IS) and pancreatic beta-cell function (HOMA-B).

RESULTS

Both increases in apnea-hypopnea index (AHI) and the presence of prediabetes/diabetes were associated with reductions in HOMA-IS in the entire cohort even after adjustment for sex, race, age, and BMI (P = 0.003). In subjects with NGM (n = 30), OSA severity was associated with significantly increased HOMA-B (a trend towards decreased HOMA-IS) independent of sex and adiposity. OSA-related oxyhemoglobin desaturations correlated with TNF-α (r=-0.76; P = 0.001) in women with NGM and with IL-6 (rho=-0.55; P = 0.035) in women with IGM (n = 15) matched individually for age, adiposity, and AHI.

CONCLUSIONS

OSA is independently associated with altered glucose homeostasis and increased basal beta-cell function in severely obese adults with NGM. The findings suggest that moderate to severe OSA imposes an excessive functional demand on pancreatic beta-cells, which may lead to their exhaustion and impaired secretory capacity over time. The two distinct biomarker profiles linking sleep apnea with NGM and IGM via TNF-α and IL-6 have been discerned in our study to suggest that sleep apnea and particularly nocturnal oxyhemoglobin desaturations are associated with chronic metabolic fluxes and specific cytokine stressors that reflect links between sleep apnea and glucose metabolism. The study may help illuminate potential mechanisms for glucose dysregulation in OSA, and resolve some controversy over the associations of OSA with TNF-α and IL-6 in previous studies.

Glycaemic risk assessment in children and young people with Type 1 diabetes mellitus

AIM

To ascertain if those with diabetes (and their carers) ascribe a similar level of risk to blood glucose control as healthcare professionals.

METHODS

We used a structured questionnaire to ask fifty healthcare professionals how 'dangerous' a given blood glucose value was. Their answers were modelled to produce an algorithm of assessed risk. To examine if patients (and their carers) would apportion a similar level of risk to that of healthcare professionals, the same questionnaire was issued to fifty children and adolescents with Type 1 diabetes. For patients under 8 years old the carers completed the questionnaires (n = 23). Both patient and carers together completed the questionnaire for those aged 8-11 years (n = 15) and patients over the age of 11 years completed the questionnaire themselves (n = 12). The median results and interquartile range of the assessed level of risk, as determined by the two groups, were compared using a generalized linear model.

RESULTS

A significant difference (P < 0.0001) was identified between the median risk assessments of the two groups. The zero level of assessed risk was upward shifted in the patient group by 0.8 mmol/l and indicated the patients' view of risk increased.

CONCLUSIONS

Patients with Type 1 diabetes (and their carers) evaluate the risk from blood glucose values differently from healthcare professionals. The euglycaemic state (zero ascribed risk) that patients chose was 0.8 mmol/l greater than that of healthcare professionals, indicating, perhaps, hypoglycaemia avoidance, a more pragmatic approach or less exposure to current trends in glycaemic control.

Validation of continuous glucose monitoring in children and adolescents with cystic fibrosis: a prospective cohort study

OBJECTIVE

To validate continuous glucose monitoring (CGM) in children and adolescents with cystic fibrosis.

RESEARCH DESIGN AND METHODS

Paired oral glucose tolerance tests (OGTTs) and CGM monitoring was undertaken in 102 children and adolescents with cystic fibrosis (age 9.5-19.0 years) at baseline (CGM1) and after 12 months (CGM2). CGM validity was assessed by reliability, reproducibility, and repeatability.

RESULTS

CGM was reliable with a Bland-Altman agreement between CGM and OGTT of 0.81 mmol/l (95% CI for bias +/- 2.90 mmol/l) and good correlation between the two (r = 0.74-0.9; P < 0.01). CGM was reproducible with no significant differences in the coefficient of variation of the CGM assessment between visits and repeatable with a mean difference between CGM1 and CGM2 of 0.09 mmol/l (95% CI for difference +/- 0.46 mmol/l) and a discriminant ratio of 13.0 and 15.1, respectively.

CONCLUSIONS

In this cohort of children and adolescents with cystic fibrosis, CGM performed on two occasions over a 12-month period was reliable, reproducible, and repeatable.

A method for assessing quality of control from glucose profiles

AIM

As the practice of multiple assessments of glucose concentration throughout the day increases for people with diabetes, there is a need for an assessment of glycaemic control weighted for the clinical risks of both hypoglycaemia and hyperglycaemia.

METHODS

We have developed a methodology to report the degree of risk which a glycaemic profile represents. Fifty diabetes professionals assigned risk values to a range of 40 blood glucose concentrations. Their responses were summarised and a generic function of glycaemic risk was derived. This function was applied to patient glucose profiles to generate an integrated risk score termed the Glycaemic Risk Assessment Diabetes Equation (GRADE). The GRADE score was then reported by use of the mean value and the relative percent contribution to the weighted risk score from the hypoglycaemic, euglycaemic, hyperglycaemic range, respectively, e.g. GRADE (hypoglycaemia%, euglycaemia%, hyperglycaemia%).

RESULTS

The GRADE scores of indicative glucose profiles were as follows: continuous glucose monitoring profile non-diabetic subjects GRADE = 1.1, Type 1 diabetes continuous glucose monitoring GRADE = 8.09 (20%, 8%, 72%), Type 2 diabetes home blood glucose monitoring GRADE = 9.97 (2%, 7%, 91%).

CONCLUSIONS

The GRADE score of a glucose profile summarises the degree of risk associated with a glucose profile. Values < 5 correspond to euglycaemia. The GRADE score is simple to generate from any blood glucose profile and can be used as an adjunct to HbA1c to report the degree of risk associated with glycaemic variability.

A method for assessing quality of control from glucose profiles

AIM

As the practice of multiple assessments of glucose concentration throughout the day increases for people with diabetes, there is a need for an assessment of glycaemic control weighted for the clinical risks of both hypoglycaemia and hyperglycaemia.

METHODS

We have developed a methodology to report the degree of risk which a glycaemic profile represents. Fifty diabetes professionals assigned risk values to a range of 40 blood glucose concentrations. Their responses were summarised and a generic function of glycaemic risk was derived. This function was applied to patient glucose profiles to generate an integrated risk score termed the Glycaemic Risk Assessment Diabetes Equation (GRADE). The GRADE score was then reported by use of the mean value and the relative percent contribution to the weighted risk score from the hypoglycaemic, euglycaemic, hyperglycaemic range, respectively, e.g. GRADE (hypoglycaemia%, euglycaemia%, hyperglycaemia%).

RESULTS

The GRADE scores of indicative glucose profiles were as follows: continuous glucose monitoring profile non-diabetic subjects GRADE = 1.1, Type 1 diabetes continuous glucose monitoring GRADE = 8.09 (20%, 8%, 72%), Type 2 diabetes home blood glucose monitoring GRADE = 9.97 (2%, 7%, 91%).

CONCLUSIONS

The GRADE score of a glucose profile summarises the degree of risk associated with a glucose profile. Values < 5 correspond to euglycaemia. The GRADE score is simple to generate from any blood glucose profile and can be used as an adjunct to HbA1c to report the degree of risk associated with glycaemic variability.

Pioglitazone and metformin

Pioglitazone and metformin have both proven safe and efficacious in the treatment of type 2 diabetes. Their combination into a single tablet seems logical. This article reviews the data that are available for this combination. Because the tablets are not currently widely available, the review examines some aspects of the effects of both agents separately and in the few trials where they have been administered concurrently, though not as a single pharmaceutical preparation. Based on this evidence, the combination appears therapeutically efficacious and clinically safe. The side effects are not multiplicative and reflect those predictable from monotherapy with either agent.

A homozygous R262Q mutation in the gonadotropin-releasing hormone receptor presenting as constitutional delay of growth and puberty with subsequent borderline oligospermia

CONTEXT

The GnRH receptor plays a central role in regulating gonadotropin synthesis and release, and several mutations in the GNRHR gene have been reported in patients with idiopathic or familial forms of isolated hypogonadotropic hypogonadism (IHH).

OBJECTIVE

The objective of the study was to investigate whether partial loss-of-function mutations in the GnRH receptor might be responsible for delayed puberty phenotypes.

PATIENTS

Patients included sibling pairs with delayed puberty (n = 8) or those in whom one brother had delayed puberty and another had hypogonadotropic hypogonadism (n = 3).

METHODS

Methods included mutational analysis of the GNRHR gene.

RESULTS

A homozygous R262Q mutation in the GnRH receptor was identified in two brothers from one family. In this kindred, the proband presented at 15 yr of age with delayed puberty. After a short course of testosterone, he seemed to be progressing through puberty appropriately and was discharged from follow-up. His younger brother was also referred with delayed puberty but showed little progress after treatment. Frequent sampling revealed detectable but apulsatile LH and FSH release. His clinical progress was consistent with IHH, and he requires ongoing testosterone replacement.

CONCLUSIONS

Homozygous partial loss-of-function mutations in the GnRH receptor, such as R262Q, can present with variable phenotypes including apparent delayed puberty. Ongoing clinical vigilance might be required when patients are discharged from follow-up, especially when there is a family history of delayed puberty or IHH because oligospermia and reduced bone mineralization can occur with time.

Synthesis of colensan-1-one

Colensan-I-one (I), an isomer of the naturally occurring norditerpene, colens-14-en-2-one, has been synthesized from 2-oxomanoyl oxide (II).