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Background: Laboratories should be aware of the stability of the analytes they are testing in order to avoid incorrect reporting and patient management. Stability studies are difficult to interpret and reproduce, with little guidance on how to determine appropriate clinical cut off values. Here we describe a standardised approach to determining stability for routine haematinics tests using published EFLM guidelines. Methods: The haematinics panel at UHNM contains vitamin B12, folate, ferritin, iron and transferrin. Blood tubes included were serum separator tubes, gel-free serum and lithium-heparin plasma. Conditions tested were room temperature, 2–8°C and −20°C. For each condition and tube, three samples were analysed in duplicate at 0, 24, 48, 72, 96 and 120 h using the Siemens Atellica platform. Results: The percentage difference was calculated for each respective blood tube and storage condition, in addition to individual analyte maximum permissible instability scores. The majority of analytes for all blood tubes were stable for 5 days or more when stored at 4–8°C and −20°C. Ferritin (excluding gel-free), iron and transferrin further showed stability >5 days when stored at room temperature. However, vitamin B12 and folate demonstrated poor stability data for all tube types tested. Conclusions: Here we describe a stability study for the haematinics panel on the Siemens Atellica platform using the standardised EFLM Checklist for Reporting Stability Studies (CRESS). The checklist was used in order to promote a standardised and transferable scientific approach to what has previously been lacking in the literature when performing stability experiments. [ABSTRACT FROM AUTHOR]

Introduction: Blood test monitoring is essential for the management of lithium treatment and National Institute for Health and Care Excellence guidance recommends 6‐monthly serum testing of thyroid function. We examined conformity to these guidelines and the impact of monitoring outside these intervals. Methods: We extracted serum lithium and thyroid hormone results at one centre between January 2009 and December 2020. We identified 266 patients who started lithium during this period with no history of thyroid abnormality within the previous 2 years and were at risk of developing thyroid abnormalities. We examined the interval between tests, time between onset of lithium testing and first thyroid‐stimulating hormone (TSH) outside the laboratory reference range and assessed impact of testing outside recommended 6‐monthly intervals. Results: The most common testing frequency was 3 months (±1 month), accounting for 17.3% of test intervals. Kaplan‐Meier analysis showed that most thyroid dysfunction manifests within 3 years (proportion with abnormal TSH at 3 years = 91.4%, 19.9% of total patients). In the first 3 months after commencing lithium therapy, eight patients developed subclinical hypothyroidism and had clinical follow‐up data available. Of these, half spontaneously normalized without clinical intervention. In the remaining patients, thyroxine replacement was only initiated after multiple occasions of subclinical hypothyroidism (median = 2 years after initiating lithium, range: 6 months to 3 years). Conclusion: The peak interval at 3 months suggests that thyroid function is frequently checked at the same time as serum lithium, indicating too frequent testing. Our data support the recommended 6‐monthly testing interval and highlight poor adherence to it. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s13300-023-01482-6.Correction to: Diabetes Therhttps://doi.org/10.1007/s13300-023-01482-6In this article, the author name Christopher J. Duff was incorrectly written as Christof J. Duff.The original article has been corrected.By David Holland; Anthony A. Fryer; Mike Stedman; Fahmy W. F. Hanna; Christopher J. Duff; Lewis Green; Jonathan Scargill; Ian Halsall; Neil Gaskell; Jonathon D. Howe; Adrian H. Heald and Pensee WuReported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

Background: Finger prick blood glucose (BG) monitoring remains a mainstay of management in people with type 2 diabetes (T2DM) who take sulphonylurea (SU) drugs or insulin. We recently examined patient experience of BG monitoring in people with type 1 diabetes (T1DM). There has not been any recent comprehensive assessment of the performance of BG monitoring strips or the patient experience of BG strips in people with T2DM in the UK. Methods: An online self‐reported questionnaire containing 44 questions, prepared following consultation with clinicians and patients, was circulated to people with T2DM. 186 responders provided completed responses (25.5% return rate). Fixed responses were coded numerically (eg not confident = 0 fairly confident = 1). Results: Of responders, 84% were treated with insulin in addition to other agents. 75% reported having had an HbA1c check in the previous 6 months. For those with reported HbA1c ≥ 65 mmol/mol, a majority of people (70%) were concerned or really concerned about the shorter term consequences of running a high HbA1c This contrasted with those who did not know their recent HbA1c, of whom only 33% were concerned/really concerned and those with HbA1c <65 mmol/mol of whom 35% were concerned. Regarding BG monitoring/insulin adjustment, only 25% of responders reported having sufficient information with 13% believing that the accuracy and precision of their BG metre was being independently checked. Only 9% recalled discussing BG metre accuracy when their latest metre was provided and only 7% were aware of the International Standardisation Organisation (ISO) standards for BG metres. 77% did not recall discussing BG metre performance with a healthcare professional. Conclusion: The group surveyed comprised engaged people with T2DM but even within this group there was significant variation in (a) awareness of shorter term risks, (b) confidence in their ability to implement appropriate insulin dosage (c) awareness of the limitations of BG monitoring technology. There is clearly an area where changes in education/support would benefit many. [ABSTRACT FROM AUTHOR]

Context Adrenal incidentalomas (AIs) are increasingly being identified during unrelated imaging. Unlike AI clinical management, data on referral patterns in routine practice are lacking. Objective This work aimed to identify factors associated with AI referral. Methods We linked data from imaging reports and outpatient bookings from a large UK teaching hospital. We examined (i) AI prevalence and (ii) pattern of referral to endocrinology, stratified by age, imaging modality, scan anatomical site, requesting clinical specialty, and temporal trends. Using key radiology phrases to identify scans reporting potential AI, we identified 4097 individuals from 479 945 scan reports (2015-2019). Main outcome measures included prevalence of AI and referral rates. Results Overall, AI lesions were identified in 1.2% of scans. They were more prevalent in abdomen computed tomography and magnetic resonance imaging scans (3.0% and 0.6%, respectively). Scans performed increased 7.7% year-on-year from 2015 to 2019, with a more pronounced increase in the number with AI lesions (14.7% per year). Only 394 of 4097 patients (9.6%) had a documented endocrinology referral code within 90 days, with medical (11.8%) more likely to refer than surgical (7.2%) specialties (P  < .001). Despite prevalence increasing with age, older patients were less likely to be referred (P  < .001). Conclusion While overall AI prevalence appeared low, scan numbers are large and rising; the number with identified AI are increasing still further. The poor AI referral rates, even in centers such as ours where dedicated AI multidisciplinary team meetings and digital management systems are used, highlights the need for new streamlined, clinically effective systems and processes to appropriately manage the AI workload. [ABSTRACT FROM AUTHOR]

The joint consensus panel of the European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) recently addressed present and future challenges in the laboratory diagnostics of atherogenic lipoproteins. Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), LDL cholesterol (LDLC), and calculated non-HDLC (=total – HDLC) constitute the primary lipid panel for estimating risk of atherosclerotic cardiovascular disease (ASCVD) and can be measured in the nonfasting state. LDLC is the primary target of lipid-lowering therapies. For on-treatment follow-up, LDLC shall be measured or calculated by the same method to attenuate errors in treatment decisions due to marked between-method variations. Lipoprotein(a) [Lp(a)]-cholesterol is part of measured or calculated LDLC and should be estimated at least once in all patients at risk of ASCVD, especially in those whose LDLC declines poorly upon statin treatment. Residual risk of ASCVD even under optimal LDL-lowering treatment should be also assessed by non-HDLC or apolipoprotein B (apoB), especially in patients with mild-to-moderate hypertriglyceridemia (2–10 mmol/L). Non-HDLC includes the assessment of remnant lipoprotein cholesterol and shall be reported in all standard lipid panels. Additional apoB measurement can detect elevated LDL particle (LDLP) numbers often unidentified on the basis of LDLC alone. Reference intervals of lipids, lipoproteins, and apolipoproteins are reported for European men and women aged 20–100 years. However, laboratories shall flag abnormal lipid values with reference to therapeutic decision thresholds. [ABSTRACT FROM AUTHOR]