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BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Context Hyperglycemia in hospital inpatients without pre-existing diabetes is associated with increased mortality. However, the independent contribution of hyperglycemia to health care–associated infection (HAI), acute kidney injury (AKI), and stroke is unclear. Objective To investigate the relationship between hyperglycemia and adverse clinical outcomes in hospital for patients with and without diabetes. Methods Diabetes IN-hospital: Glucose and Outcomes (DINGO) was a 26-week (October 2019-March 2020) prospective cohort study. Clinical and glucose data were collected up to the 14th day of admission. Primary stratification was by hyperglycemia, defined as ≥2 random capillary blood glucose (BG) measurements ≥11.1 mmol/L (≥200 mg/dL). Propensity weighting for 9 clinical characteristics was performed to allow interrogation of causality. To maintain the positivity assumption, patients with HbA1c >12.0% were excluded and prehospital treatment not adjusted for. The setting was the Royal Melbourne Hospital, a quaternary referral hospital in Melbourne, Australia. Admissions with at least 2 capillary glucose values and length of stay >24 hours were eligible, with half randomly sampled. Outcome measures were HAI, AKI, stroke, and mortality. Results Of 2558 included admissions, 1147 (45%) experienced hyperglycemia in hospital. Following propensity-weighting and adjustment, hyperglycemia in hospital was found to, independently of 9 covariables, contribute an increased risk of in-hospital HAI (130 [11.3%] vs 100 [7.1%], adjusted odds ratio [aOR] 1.03, 95% CI 1.01-1.05, P =.003), AKI (120 [10.5%] vs 59 [4.2%], aOR 1.07, 95% CI 1.05-1.09, P <.001), and stroke (10 [0.9%] vs 1 [0.1%], aOR 1.05, 95% CI 1.04-1.06, P <.001). Conclusion In hospital inpatients (HbA1c ≤12.0%), irrespective of diabetes status and prehospital glycemia, hyperglycemia increases the risk of in-hospital HAI, AKI, and stroke compared with those not experiencing hyperglycemia. [ABSTRACT FROM AUTHOR]

Objective: Several national and international guidelines recommend lipidocolloid technology with a nano-oligosaccharide factor (TLC-NOSF) dressings (UrgoStart dressing range, Laboratoires Urgo, France) for treating patients with chronic wounds. However, these dressings are still often reported as second-line options, potentially leading to loss of opportunity for patients and additional costs for payers. This review aimed to explore the reported wound healing and patient outcomes as well as the related costs when the dressings were used as first-line treatment in patients with different types of chronic wounds. Method: A systematic review of the literature was conducted. Databases (MEDLINE, Embase, Emcare, and Google Scholar) were searched up to 1 February 2024, without any language or time period limitations. Studies were eligible if the evaluated dressings had been used as a first-line treatment for chronic wounds, that is, as an integral part of the standard of care (SoC) at the patient's first presentation and/or in recent wounds. The main evaluation criteria included: wound healing rate; time to reach wound closure; change in patients' quality of life (QoL); and associated costs. The quality of evidence of the included studies was appraised using well-recognised risk-of-bias tools suitable for different study designs. A narrative synthesis describes the findings in three sections depending on the type of comparison. This report followed the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: A total of 17 studies published between 2017 and 2024 met the eligibility criteria. A comparative analysis between TLC-NOSF dressings and standard dressings, both of which were used as first-line treatment, was reported in nine studies. A comparative analysis between the use of TLC-NOSF dressings as first-line and second-line treatments was reported in eight studies, and five studies reported a systematic use of the TLC-NOSF dressing as first-line treatment without a control group. Overall, the included studies had a relatively low risk of bias for the respective types of evidence. Data of 10,191 patients of both sexes and different age groups with a total of 10,203 wounds (diabetic foot ulcers, leg ulcers, pressure injuries, and other types of chronic wounds) were included in the analysis: 7775 treated with the evaluated dressing and 2428 treated with a comparator dressing. The data suggested that using TLC-NOSF as a first-line treatment for chronic wounds consistently resulted in significantly higher healing rates, shorter healing times, and cost savings compared with standard dressings used under similar conditions. Real-life evidence confirmed the results obtained in clinical trials and economic models, within similar ranges, regardless of the settings involved or of the characteristics of the patients and wounds treated. The wound healing rates ranged around 70-80% by week 20/24 and time-to-heal was reported on average around seven weeks, with slightly longer times reported in wounds with a more severe prognosis. Furthermore, the dressings were shown to improve patient QoL, and were well tolerated and accepted, supporting a wider adoption approach. Conclusion: The results of this review are aligned with the current guidelines recommending the use of TLC-NOSF dressings in the treatment of patients with chronic wounds. They support its wider implementation as a first-line treatment and as an integral part of SoC for these wounds in the daily practice of all centres involved in their management. [ABSTRACT FROM AUTHOR]

Aims: The FLASH‐UK trial showed lower HbA1c with intermittently scanned continuous glucose monitoring (isCGM), as compared with self monitoring of blood glucose (SMBG), in adults with type 1 diabetes and HbA1c ≥58 mmol/mol (≥7.5%). Here, we present results from the pre‐specified subgroup analysis for the 24‐week HbA1c (primary outcome) and selected sensor‐based secondary outcomes. Methods: This was a multi‐centre, parallel‐design, randomised controlled trial. The difference in treatment effect between subgroups (baseline HbA1c [≤75 vs. >75 mmol/mol] [≤9.0 vs >9.0%], treatment modality [pump vs injections], prior participation in structured education, age, educational level, impaired awareness of hypoglycaemia, deprivation index quintile sex, ethnic group and Patient Health Questionnaire‐9 [PHQ‐9] detected depression category) were evaluated. Results: One hundred fifty‐six participants (females 44%, mean [SD] baseline HbA1c 71 [9] mmol/mol 8.6 [0.8%], age 44 [15]) were randomly assigned, in a 1:1 ratio to isCGM (n = 78) or SMBG (n = 78). The mean (SD) baseline HbA1c (%) was 8.7 (0.9) in the isCGM group and 8.5 (0.8) in the SMBG group, lowering to 7.9 (0.8) versus 8.3 (0.9), respectively, at 24 weeks (adjusted mean difference −0.5, 95% confidence interval [CI] −0.7 to −0.3; p < 0.001]. For HbA1c, there was no impact of treatment modality, prior participation in structured education, deprivation index quintile, sex or baseline depression category. The between‐group difference in HbA1c was larger for younger people (a reduction of 2.7 [95% CI 0.3–5.0; p = 0.028] mmol/mol for every additional 15 years of age). Those with HbA1c 76–97 mmol/mol (>9.0%–11.0%) had a marginally non‐significant higher reduction in HbA1c of 8.4 mmol/mol (3.3–13.5) compared to 3.1 (0.3–6.0) in those with HbA1c 58–75 mmol/mol (p = 0.08). For 'Time in range' (% 3.9–10 mmol/L), the difference was larger for those with at least a bachelor's degree. For 'Time below range' (% <3.9 mmol/L), the difference was larger for those using injections, older people and those with less than bachelor's degree. Conclusions: Intermittently scanned continuous glucose monitoring is generally effective across a range of baseline characteristics. [ABSTRACT FROM AUTHOR]

Objective: We previously showed that intermittently scanned continuous glucose monitoring (isCGM) reduces HbA1c at 24 weeks compared with self‐monitoring of blood glucose with finger pricking (SMBG) in adults with type 1 diabetes and high HbA1c levels (58–97 mmol/mol [7.5%–11%]). We aim to assess the economic impact of isCGM compared with SMBG. Methods: Participant‐level baseline and follow‐up health status (EQ‐5D‐5L) and within‐trial healthcare resource‐use data were collected. Quality‐adjusted life‐years (QALYs) were derived at 24 weeks, adjusting for baseline EQ‐5D‐5L. Participant‐level costs were generated. Using the IQVIA CORE Diabetes Model, economic analysis was performed from the National Health Service perspective over a lifetime horizon, discounted at 3.5%. Results: Within‐trial EQ‐5D‐5L showed non‐significant adjusted incremental QALY gain of 0.006 (95% CI: −0.007 to 0.019) for isCGM compared with SMBG and an adjusted cost increase of £548 (95% CI: 381–714) per participant. The lifetime projected incremental cost (95% CI) of isCGM was £1954 (−5108 to 8904) with an incremental QALY (95% CI) gain of 0.436 (0.195–0.652) resulting in an incremental cost‐per‐QALY of £4477. In all subgroups, isCGM had an incremental cost‐per‐QALY better than £20,000 compared with SMBG; for people with baseline HbA1c >75 mmol/mol (9.0%), it was cost‐saving. Sensitivity analysis suggested that isCGM remains cost‐effective if its effectiveness lasts for at least 7 years. Conclusion: While isCGM is associated with increased short‐term costs, compared with SMBG, its benefits in lowering HbA1c will lead to sufficient long‐term health‐gains and cost‐savings to justify costs, so long as the effect lasts into the medium term. [ABSTRACT FROM AUTHOR]

The article discusses the challenges faced by people with diabetes who undergo surgical interventions, including increased risks of complications and mortality. It emphasizes the importance of implementing effective systems for perioperative diabetes care, such as using national guidelines, setting glycemic target ranges, and employing networked blood glucose meters with alert systems. The article highlights the need for consistent adherence to guidelines and the potential benefits of proactive diabetes teams. It also discusses different models of care, including the integration of electronic medical records and networked blood glucose meters, as well as a patient journey approach. The article concludes by suggesting future directions for improving inpatient diabetes care, including the use of artificial intelligence and wearable sensors. Overall, the article provides evidence that investment in various aspects of inpatient diabetes care can lead to improved outcomes and patient experience. [Extracted from the article]