Assessment of glycaemic status in adult hospital patients for the detection of undiagnosed diabetes mellitus: A systematic review.

AIM: In-hospital blood glucose testing is commonplace, particularly in acute care. In-hospital screening for hyperglycaemia may present a valuable opportunity for early diabetes diagnosis by identifying at-risk individuals. This systematic review investigates the extent to which random blood glucose testing in acute and inpatient hospital settings predicts undiagnosed diabetes. METHODS: Two databases were systematically searched for studies in which adult patients received an in-hospital random blood glucose test, followed by a diagnostic HbA1c test. The primary outcome was the proportion of hyperglycaemic individuals diagnosed with diabetes by HbA1c. RESULTS: A total of 3245 unique citations were identified, and 12 were eligible for inclusion. Ten different blood glucose thresholds, ranging from 5.5 to 11.1 mmol/L, were used to detect hyperglycaemia, indicating that there is no consistent clinical definition for hyperglycaemia. The proportion of participants with hyperglycaemia in each study ranged from 3.3% to 62.1%, with a median (Q1 , Q3 ) of 34.5% (5.95%, 61.1%). The proportion of hyperglycaemic participants found to have a diabetes-range HbA1c varied from 4.1% to 90%, with a median (Q1 , Q3 ) of 18.9% (11.5%, 61.1%). Meta-analysis was not possible due to substantial heterogeneity between study protocols. CONCLUSIONS: All studies consistently identified a proportion of hyperglycaemic hospital patients as having a diabetes-range HbA1c, showing that in-hospital blood glucose screening can facilitate diabetes diagnosis. The proportion of hyperglycaemic participants with undiagnosed diabetes varied substantially, indicating a need for further research and consistency in defining in-hospital hyperglycaemia. This may aid the development of a standardised screening protocol to identify people with possible undiagnosed diabetes.

The potential for utilising in-hospital glucose measurements to detect individuals at high risk of previously undiagnosed diabetes: Retrospective cohort study.

BACKGROUND: Many people with undiagnosed diabetes have hyperglycaemia when admitted to hospital. Inpatient hyperglycaemia can be an indication of diabetes mellitus but can also indicate a stress response. This study reports the extent to which an in-hospital maximum observed random glucose measurement is an indicator of the need for in-hospital (or subsequent) HbA1c measurement to look for undiagnosed diabetes. METHODS: Blood glucose, HbA1c, age and sex were collected for all adults following admission to a UK NHS trust hospital from 1 January 2019 to 31 December 2020. We restricted the analysis to those participants who were registered with a GP practice that uses the trust laboratory and who had at least some tests requested by those practices since 2008. We stratified individuals according to their maximum in-hospital glucose measurement and report the number of these with HbA1c measurement ≥48 mmol/mol (6.5%) prior to the index admission, and during and after admission. We calculated an estimated proportion of individuals in each blood glucose stratum without a follow-up HbA1c who could have undiagnosed diabetes. RESULTS: In toal, 764,241 glucose measurements were recorded for 81,763 individuals who were admitted to the Oxford University Hospitals Trust. The median (Q1, Q3) age was 70 (56, 81) years, and 53% were males. Of the population, 70.7% of individuals declared themselves to be of White ethnicity, 3.1% of Asian background, and 1.1% of Black background, with 23.1% unstated. Of those individuals, 22,375 (27.4%) had no previous HbA1c measurement recorded. A total of 1689 individuals had a diabetes-range HbA1c during or after their hospital admission (2.5%) while we estimate an additional 1496 (2.2%) may have undiagnosed diabetes, with the greatest proportion of these having an in-hospital glucose of ≥15 mmol/L. We estimate that the number needed to detect a possible new case of diabetes falls from 16 (in-hospital glucose 8 mmol/L to <9 mmol/L) to 4 (14 mmol/L to <15 mmol/L). CONCLUSION: The number of people who need to be tested to identify an individual who may have diabetes decreases as a testing threshold based on maximum in-hospital glucose concentration increases. Among those with hyperglycaemia and no previous HbA1c measurement in the diabetes range, there appears to be a lack of subsequent HbA1c measurement. This work identifies the potential for integrating the testing and follow-up of people, with apparently unrecognised hospital hyperglycaemia across primary and secondary care.

Understanding acceptability in the context of text messages to encourage medication adherence in people with type 2 diabetes.

BACKGROUND: Acceptability is recognised as a key concept in the development of health interventions, but there has been a lack of consensus about how acceptability should be conceptualised. The theoretical framework of acceptability (TFA) provides a potential tool for understanding acceptability. It has been proposed that acceptability measured before use of an intervention (anticipated acceptability) may differ from measures taken during and after use (experienced acceptability), but thus far this distinction has not been tested for a specific intervention. This paper 1) directly compares ratings of anticipated and experienced acceptability of a text message-based intervention, 2) explores the applicability of the TFA in a technology-based intervention, and 3) uses these findings to inform suggestions for measuring acceptability over the lifespan of technology-based health interventions. METHODS: Data were obtained from a quantitative online survey assessing anticipated acceptability of the proposed text messages (n = 59) and a 12-week proof-of-concept mixed methods study assessing experienced acceptability while receiving the text messages (n = 48). Both quantitative ratings by return text message, and qualitative data from participant interviews were collected during the proof-of-concept study. RESULTS: The quantitative analysis showed anticipated and experienced acceptability were significantly positively correlated (rs > .4). The qualitative analysis identified four of the seven constructs of the TFA as themes (burden, intervention coherence, affective attitude and perceived effectiveness). An additional two themes were identified as having an important impact on the TFA constructs (perceptions of appropriateness and participants' role). Three suggestions are given related to the importance of appropriateness, what may affect ratings of acceptability and what to consider when measuring acceptability. CONCLUSIONS: The high correlation between anticipated and experienced acceptability was a surprising finding and could indicate that, in some cases, acceptability of an intervention can be gauged adequately from an anticipated acceptability study, prior to an expensive pilot or feasibility study. Directly exploring perceptions of appropriateness and understanding whether the acceptability described by participants is related to the intervention or the research - and is for themselves or others - is important in interpreting the results and using them to further develop interventions and predict future use.

Identifying routine clinical predictors of non-adherence to second-line therapies in type 2 diabetes: A retrospective cohort analysis in a large primary care database.

AIMS: To investigate whether combinations of routinely available clinical features can predict which patients are likely to be non-adherent to diabetes medication. MATERIALS AND METHODS: A total of 67 882 patients with prescription records for their first and second oral glucose-lowering therapies were identified from electronic healthcare records (Clinical Practice Research Datalink). Non-adherence was defined as a medical possession ratio (MPR) ≤80%. Potential predictors were examined, including age at diagnosis, sex, body mass index, duration of diabetes, glycated haemoglobin, Charlson index and other recent prescriptions. RESULTS: Routine clinical features were poor at predicting non-adherence to the first diabetes therapy (c-statistic = 0.601 for all in combined model). Non-adherence to the second drug was better predicted for all combined factors (c-statistic =0.715) but this improvement was predominantly a result of including adherence to the first drug (c-statistic =0.695 for this alone). Patients with an MPR ≤80% for their first drug were 3.6 times (95% confidence interval 3.3,3.8) more likely to be non-adherent to their second drug (32% vs. 9%). CONCLUSIONS: Although certain clinical features were associated with poor adherence, their performance for predicting who is likely to be non-adherent, even when combined, was weak. The strongest predictor of adherence to second-line therapy was adherence to the first therapy. Examining previous prescription records could offer a practical way for clinicians to identify potentially non-adherent patients and is an area warranting further research.

Time trends in prescribing of type 2 diabetes drugs, glycaemic response and risk factors: A retrospective analysis of primary care data, 2010-2017.

AIM: To describe population-level time trends in prescribing patterns of type 2 diabetes therapy, and in short-term clinical outcomes (glycated haemoglobin [HbA1c], weight, blood pressure, hypoglycaemia and treatment discontinuation) after initiating new therapy. MATERIALS AND METHODS: We studied 81 532 people with type 2 diabetes initiating a first- to fourth-line drug in primary care between 2010 and 2017 inclusive in United Kingdom electronic health records (Clinical Practice Research Datalink). Trends in new prescriptions and subsequent 6- and 12-month adjusted changes in glycaemic response (reduction in HbA1c), weight, blood pressure and rates of hypoglycaemia and treatment discontinuation were examined. RESULTS: Use of dipeptidyl peptidase-4 inhibitors as second-line therapy near doubled (41% of new prescriptions in 2017 vs. 22% in 2010), replacing sulphonylureas as the most common second-line drug (29% in 2017 vs. 53% in 2010). Sodium-glucose co-transporter-2 inhibitors, introduced in 2013, comprised 17% of new first- to fourth-line prescriptions by 2017. First-line use of metformin remained stable (91% of new prescriptions in 2017 vs. 91% in 2010). Over the study period there was little change in average glycaemic response and in the proportion of people discontinuing treatment. There was a modest reduction in weight after initiating second- and third-line therapy (improvement in weight change 2017 vs. 2010 for second-line therapy: -1.5 kg, 95% confidence interval [CI] -1.9, -1.1; P < 0.001), and a slight reduction in systolic blood pressure after initiating first-, second- and third-line therapy (improvement in systolic blood pressure change 2017 vs. 2010 range: -1.7 to -2.1 mmHg; all P < 0.001). Hypoglycaemia rates decreased over time with second-line therapy (incidence rate ratio 0.94 per year, 95% CI 0.88, 1.00; P = 0.04), mirroring the decline in use of sulphonylureas. CONCLUSIONS: Recent changes in prescribing of therapy for people with type 2 diabetes have not led to a change in glycaemic response and have resulted in modest improvements in other population-level short-term clinical outcomes.

Identifying Brief Message Content for Interventions Delivered via Mobile Devices to Improve Medication Adherence in People With Type 2 Diabetes Mellitus: A Rapid Systematic Review.

BACKGROUND: Current interventions to support medication adherence in people with type 2 diabetes are generally resource-intensive and ineffective. Brief messages, such as those delivered via short message service (SMS) systems, are increasingly used in digital health interventions to support adherence because they can be delivered on a wide scale and at low cost. The content of SMS text messages is a crucial intervention feature for promoting behavior change, but it is often unclear what the rationale is for chosen wording or any underlying mechanisms targeted for behavioral change. There is little guidance for developing and optimizing brief message content for use in mobile device-delivered interventions. OBJECTIVE: This review aimed to (1) identify theoretical constructs (ie, the targets that interventions aim to change) and behavioral strategies (ie, features of intervention content) found to be associated with medication adherence in patients with type 2 diabetes and (2) map these onto a standard taxonomy for behavior change techniques (BCTs, that is, active ingredients of interventions used to promote behavioral change, to produce an evidence-based set of approaches that have shown promise of improving adherence in previous studies and which could be further tested in digital health interventions. METHODS: A rapid systematic review of existing relevant systematic reviews was conducted. MEDLINE and PsycINFO databases were searched from inception to April 10, 2017. Inclusion criteria were (1) systematic reviews of quantitative data if the studies reviewed identified predictors of or correlates with medication adherence or evaluated medication adherence-enhancing interventions and included adult participants taking medication to manage a chronic physical health condition, and (2) systematic reviews of qualitative studies of experiences of medication adherence for adult participants with type 2 diabetes. Data were extracted on review characteristics and BCTs, theoretical constructs, or behavioral strategies associated with improved adherence. Constructs and strategies were mapped onto the BCT version 1 taxonomy. RESULTS: A total of 1701 references were identified; 25 systematic reviews (19 quantitative reviews, 3 qualitative reviews, and 3 mixed-method reviews) were included. Moreover, 20 theoretical constructs (eg, self-efficacy) and 19 behavioral strategies (eg, habit analysis) were identified in the included reviews. In total, 46 BCTs were identified as being related to medication adherence in type 2 diabetes (eg, habit formation, prompts or cues, and information about health consequences). CONCLUSIONS: We identified 46 promising BCTs related to medication adherence in type 2 diabetes on which the content of brief messages delivered through mobile devices to improve adherence could be based. By using explicit systematic review methods and linking our findings to a standardized taxonomy of BCTs, we have described a novel approach for the development of digital message content. Future brief message interventions that aim to support medication adherence could incorporate the identified BCTs.

Mobile Phone Text Messages to Support Treatment Adherence in Adults With High Blood Pressure (SMS-Text Adherence Support [StAR]): A Single-Blind, Randomized Trial.

BACKGROUND: We assessed the effect of automated treatment adherence support delivered via mobile phone short message system (SMS) text messages on blood pressure. METHODS AND RESULTS: In this pragmatic, single-blind, 3-arm, randomized trial (SMS-Text Adherence Support [StAR]) undertaken in South Africa, patients treated for high blood pressure were randomly allocated in a 1:1:1 ratio to information only, interactive SMS text messaging, or usual care. The primary outcome was change in systolic blood pressure at 12 months from baseline measured with a validated oscillometric device. All trial staff were masked to treatment allocation. Analyses were intention to treat. Between June 26, 2012, and November 23, 2012, 1372 participants were randomized to receive information-only SMS text messages (n=457), interactive SMS text messages (n=458), or usual care (n=457). Primary outcome data were available for 1256 participants (92%). At 12 months, the mean adjusted change in systolic blood pressure compared with usual care was -2.2 mm Hg (95% confidence interval, -4.4 to -0.04) with information-only SMS and -1.6 mm Hg (95% confidence interval, -3.7 to 0.6) with interactive SMS. Odds ratios for the proportion of participants with a blood pressure <140/90 mm Hg were 1.42 (95% confidence interval, 1.03-1.95) for information-only messaging and 1.41 (95% confidence interval, 1.02-1.95) for interactive messaging compared with usual care. CONCLUSIONS: In this randomized trial of an automated adherence support program delivered by SMS text message in a general outpatient population of adults with high blood pressure, we found a small reduction in systolic blood pressure control compared with usual care at 12 months. There was no evidence that an interactive intervention increased this effect. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT02019823. South African National Clinical Trials Register, number SANCTR DOH-27-1212-386; Pan Africa Trial Register, number PACTR201411000724141.

Performance of point-of-care HbA1c test devices: implications for use in clinical practice - a systematic review and meta-analysis.

BACKGROUND: Point-of-care (POC) devices could be used to measure hemoglobin A1c (HbA1c) in the doctors' office, allowing immediate feedback of results to patients. Reports have raised concerns about the analytical performance of some of these devices. We carried out a systematic review and meta-analysis using a novel approach to compare the accuracy and precision of POC HbA1c devices. METHODS: Medline, Embase and Web of Science databases were searched in June 2015 for published reports comparing POC HbA1c devices with laboratory methods. Two reviewers screened articles and extracted data on bias, precision and diagnostic accuracy. Mean bias and variability between the POC and laboratory test were combined in a meta-analysis. Study quality was assessed using the QUADAS2 tool. RESULTS: Two researchers independently reviewed 1739 records for eligibility. Sixty-one studies were included in the meta-analysis of mean bias. Devices evaluated were A1cgear, A1cNow, Afinion, B-analyst, Clover, Cobas b101, DCA 2000/Vantage, HemoCue, Innovastar, Nycocard, Quo-Lab, Quo-Test and SDA1cCare. Nine devices had a negative mean bias which was significant for three devices. There was substantial variability in bias within devices. There was no difference in bias between clinical or laboratory operators in two devices. CONCLUSIONS: This is the first meta-analysis to directly compare performance of POC HbA1c devices. Use of a device with a mean negative bias compared to a laboratory method may lead to higher levels of glycemia and a lower risk of hypoglycaemia. The implications of this on clinical decision-making and patient outcomes now need to be tested in a randomized trial.

Large-scale community echocardiographic screening reveals a major burden of undiagnosed valvular heart disease in older people: the OxVALVE Population Cohort Study.

BACKGROUND: Valvular heart disease (VHD) is expected to become more common as the population ages. However, current estimates of its natural history and prevalence are based on historical studies with potential sources of bias. We conducted a cross-sectional analysis of the clinical and epidemiological characteristics of VHD identified at recruitment of a large cohort of older people. METHODS AND RESULTS: We enrolled 2500 individuals aged ≥65 years from a primary care population and screened for undiagnosed VHD using transthoracic echocardiography. Newly identified (predominantly mild) VHD was detected in 51% of participants. The most common abnormalities were aortic sclerosis (34%), mitral regurgitation (22%), and aortic regurgitation (15%). Aortic stenosis was present in 1.3%. The likelihood of undiagnosed VHD was two-fold higher in the two most deprived socioeconomic quintiles than in the most affluent quintile, and three-fold higher in individuals with atrial fibrillation. Clinically significant (moderate or severe) undiagnosed VHD was identified in 6.4%. In addition, 4.9% of the cohort had pre-existing VHD (a total prevalence of 11.3%). Projecting these findings using population data, we estimate that the prevalence of clinically significant VHD will double before 2050. CONCLUSIONS: Previously undetected VHD affects 1 in 2 of the elderly population and is more common in lower socioeconomic classes. These unique data demonstrate the contemporary clinical and epidemiological characteristics of VHD in a large population-based cohort of older people and confirm the scale of the emerging epidemic of VHD, with widespread implications for clinicians and healthcare resources.

Telemedicine Technologies for Diabetes in Pregnancy: A Systematic Review and Meta-Analysis.

BACKGROUND: Diabetes in pregnancy is a global problem. Technological innovations present exciting opportunities for novel approaches to improve clinical care delivery for gestational and other forms of diabetes in pregnancy. OBJECTIVE: To perform an updated and comprehensive systematic review and meta-analysis of the literature to determine whether telemedicine solutions offer any advantages compared with the standard care for women with diabetes in pregnancy. METHODS: The review was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Randomized controlled trials (RCT) in women with diabetes in pregnancy that compared telemedicine blood glucose monitoring with the standard care were identified. Searches were performed in SCOPUS and PubMed, limited to English language publications between January 2000 and January 2016. Trials that met the eligibility criteria were scored for risk of bias using the Cochrane Collaborations Risk of Bias Tool. A meta-analysis was performed using Review Manager software version 5.3 (Nordic Cochrane Centre, Cochrane Collaboration). RESULTS: A total of 7 trials were identified. Meta-analysis demonstrated a modest but statistically significant improvement in HbA1c associated with the use of a telemedicine technology. The mean HbA1c of women using telemedicine was 5.33% (SD 0.70) compared with 5.45% (SD 0.58) in the standard care group, representing a mean difference of -0.12% (95% CI -0.23% to -0.02%). When this comparison was limited to women with gestational diabetes mellitus (GDM) only, the mean HbA1c of women using telemedicine was 5.22% (SD 0.70) compared with 5.37% (SD 0.61) in the standard care group, mean difference -0.14% (95% CI -0.25% to -0.04%). There were no differences in other maternal and neonatal outcomes reported. CONCLUSIONS: There is currently insufficient evidence that telemedicine technology is superior to standard care for women with diabetes in pregnancy; however, there was no evidence of harm. No trials were identified that assessed patient satisfaction or cost of care delivery, and it may be in these areas where these technologies may be found most valuable.

Selection for tameness, a key behavioral trait of domestication, increases adult hippocampal neurogenesis in foxes.

Work on laboratory and wild rodents suggests that domestication may impact on the extent of adult hippocampal neurogenesis and its responsiveness to regulatory factors. There is, however, no model of laboratory rodents and their nondomesticated conspecifics that would allow a controlled comparison of the effect of domestication. Here, we present a controlled within-species comparison of adult hippocampal neurogenesis in farm-bred foxes (Vulpes vulpes) that differ in their genetically determined degree of tameness. Quantitative comparisons of cell proliferation (Ki67) and differentiating cells of neuronal lineage (doublecortin, DCX) in the hippocampus of foxes were performed as a proxy for neurogenesis. Higher neurogenesis was observed in tameness-selected foxes, notably in an extended subgranular zone of the middle and temporal compartments of the hippocampus. Increased neurogenesis is negatively associated with aggressive behavior. Across all animals, strong septotemporal gradients were found, with higher numbers of proliferating cells and young neurons relative to resident granule cells in the temporal than in the septal hippocampus. The opposite gradient was found for the ratio of DCX/Ki67- positive cells. When tameness-selected and unselected foxes are compared with rodents and primates, proliferation is similar, while the number of young neurons is higher. The difference may be mediated by an extended period of differentiation or higher rate of survival. On the background of this species-specific neurogenic pattern, selection of foxes for a single behavioral trait key to domestication, i.e., genetic tameness, is accompanied by global and region-specific increases in neurogenesis.

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

AIMS: Although there are reports that ß-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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Interactive telemedicine: effects on professional practice and health care outcomes.

BACKGROUND: Telemedicine (TM) is the use of telecommunication systems to deliver health care at a distance. It has the potential to improve patient health outcomes, access to health care and reduce healthcare costs. As TM applications continue to evolve it is important to understand the impact TM might have on patients, healthcare professionals and the organisation of care. OBJECTIVES: To assess the effectiveness, acceptability and costs of interactive TM as an alternative to, or in addition to, usual care (i.e. face-to-face care, or telephone consultation). SEARCH METHODS: We searched the Effective Practice and Organisation of Care (EPOC) Group's specialised register, CENTRAL, MEDLINE, EMBASE, five other databases and two trials registers to June 2013, together with reference checking, citation searching, handsearching and contact with study authors to identify additional studies. SELECTION CRITERIA: We considered randomised controlled trials of interactive TM that involved direct patient-provider interaction and was delivered in addition to, or substituting for, usual care compared with usual care alone, to participants with any clinical condition. We excluded telephone only interventions and wholly automatic self-management TM interventions. DATA COLLECTION AND ANALYSIS: For each condition, we pooled outcome data that were sufficiently homogenous using fixed effect meta-analysis. We reported risk ratios (RR) and 95% confidence intervals (CI) for dichotomous outcomes, and mean differences (MD) for continuous outcomes. MAIN RESULTS: We included 93 eligible trials (N = 22,047 participants), which evaluated the effectiveness of interactive TM delivered in addition to (32% of studies), as an alternative to (57% of studies), or partly substituted for usual care (11%) as compared to usual care alone.The included studies recruited patients with the following clinical conditions: cardiovascular disease (36), diabetes (21), respiratory conditions (9), mental health or substance abuse conditions (7), conditions requiring a specialist consultation (6), co morbidities (3), urogenital conditions (3), neurological injuries and conditions (2), gastrointestinal conditions (2), neonatal conditions requiring specialist care (2), solid organ transplantation (1), and cancer (1).Telemedicine provided remote monitoring (55 studies), or real-time video-conferencing (38 studies), which was used either alone or in combination. The main TM function varied depending on clinical condition, but fell typically into one of the following six categories, with some overlap: i) monitoring of a chronic condition to detect early signs of deterioration and prompt treatment and advice, (41); ii) provision of treatment or rehabilitation (12), for example the delivery of cognitive behavioural therapy, or incontinence training; iii) education and advice for self-management (23), for example nurses delivering education to patients with diabetes or providing support to parents of very low birth weight infants or to patients with home parenteral nutrition; iv) specialist consultations for diagnosis and treatment decisions (8), v) real-time assessment of clinical status, for example post-operative assessment after minor operation or follow-up after solid organ transplantation (8) vi), screening, for angina (1).The type of data transmitted by the patient, the frequency of data transfer, (e.g. telephone, e-mail, SMS) and frequency of interactions between patient and healthcare provider varied across studies, as did the type of healthcare provider/s and healthcare system involved in delivering the intervention.We found no difference between groups for all-cause mortality for patients with heart failure (16 studies; N = 5239; RR:0.89, 95% CI 0.76 to 1.03, P = 0.12; I(2) = 44%) (moderate to high certainty of evidence) at a median of six months follow-up. Admissions to hospital (11 studies; N = 4529) ranged from a decrease of 64% to an increase of 60% at median eight months follow-up (moderate certainty of evidence). We found some evidence of improved quality of life (five studies; N = 482; MD:-4.39, 95% CI -7.94 to -0.83; P < 0.02; I(2) = 0%) (moderate certainty of evidence) for those allocated to TM as compared with usual care at a median three months follow-up. In studies recruiting participants with diabetes (16 studies; N = 2768) we found lower glycated haemoglobin (HbA1c %) levels in those allocated to TM than in controls (MD -0.31, 95% CI -0.37 to -0.24; P < 0.00001; I(2)= 42%, P = 0.04) (high certainty of evidence) at a median of nine months follow-up. We found some evidence for a decrease in LDL (four studies, N = 1692; MD -12.45, 95% CI -14.23 to -10.68; P < 0.00001; I(2 =) 0%) (moderate certainty of evidence), and blood pressure (four studies, N = 1770: MD: SBP:-4.33, 95% CI -5.30 to -3.35, P < 0.00001; I(2) = 17%; DBP: -2.75 95% CI -3.28 to -2.22, P < 0.00001; I(2) = 45% (moderate certainty evidence), in TM as compared with usual care.Seven studies that recruited participants with different mental health and substance abuse problems, reported no differences in the effect of therapy delivered over video-conferencing, as compared to face-to-face delivery. Findings from the other studies were inconsistent; there was some evidence that monitoring via TM improved blood pressure control in participants with hypertension, and a few studies reported improved symptom scores for those with a respiratory condition. Studies recruiting participants requiring mental health services and those requiring specialist consultation for a dermatological condition reported no differences between groups. AUTHORS' CONCLUSIONS: The findings in our review indicate that the use of TM in the management of heart failure appears to lead to similar health outcomes as face-to-face or telephone delivery of care; there is evidence that TM can improve the control of blood glucose in those with diabetes. The cost to a health service, and acceptability by patients and healthcare professionals, is not clear due to limited data reported for these outcomes. The effectiveness of TM may depend on a number of different factors, including those related to the study population e.g. the severity of the condition and the disease trajectory of the participants, the function of the intervention e.g., if it is used for monitoring a chronic condition, or to provide access to diagnostic services, as well as the healthcare provider and healthcare system involved in delivering the intervention.

Remote Vital Sign Monitoring in Admission Avoidance Hospital at Home: A Systematic Review.

OBJECTIVES: To examine randomized controlled trials (RCTs) of "hospital at home" (HAH) for admission avoidance in adults presenting with acute physical illness to identify the use of vital sign monitoring approaches and evidence for their effectiveness. DESIGN: Systematic review. SETTING AND PARTICIPANTS: This review compared strategies for vital sign monitoring in admission avoidance HAH for adults presenting with acute physical illness. Vital sign monitoring can support HAH acute multidisciplinary care by contributing to safety, determining requirement of further assessment, and guiding clinical decisions. There are a wide range of systems currently available, including reliable and automated continuous remote monitoring using wearable devices. METHODS: Eligible studies were identified through updated database and trial registries searches (March 2, 2016, to February 15, 2023), and existing systematic reviews. Risk of bias was assessed using the Cochrane risk of bias 2 tool. Random effects meta-analyses were performed, and narrative summaries provided stratified by vital sign monitoring approach. RESULTS: Twenty-one eligible RCTs (3459 participants) were identified. Two approaches to vital sign monitoring were characterized: manual and automated. Reporting was insufficient in the majority of studies for classification. For HAH compared to hospital care, 6-monthly mortality risk ratio (RR) was 0.94 (95% CI 0.78-1.12), 3-monthly readmission to hospital RR 1.02 (0.77-1.35), and length of stay mean difference 1.91 days (0.71-3.12). Readmission to hospital was reduced in the automated monitoring subgroup (RR 0.30 95% CI 0.11-0.86). CONCLUSIONS AND IMPLICATIONS: This review highlights gaps in the reporting and evidence base informing remote vital sign monitoring in alternatives to admission for acute illness, despite expanding implementation in clinical practice. Although continuous vital sign monitoring using wearable devices may offer added benefit, its use in existing RCTs is limited. Recommendations for the implementation and evaluation of remote monitoring in future clinical trials are proposed.

Supporting people with type 2 diabetes in effective use of their medicine through mobile health technology integrated with clinical care (SuMMiT-D pilot): results of a feasibility randomised trial.

BACKGROUND: The purpose of this 6-month intervention pilot feasibility randomised trial was to test sending brief messages using mobile phones to promote self-management through taking medication as prescribed to people with type 2 diabetes. This was to inform the design and conduct of a future large-scale United Kingdom-based clinical trial and establish the feasibility of recruitment, the technology used, follow-up, and data collection. METHODS: A multicentre individually randomised, controlled parallel group trial in primary care, recruiting adults (≥ 35 years) with type 2 diabetes in England. Consenting participants were randomly allocated to receive short message system text messages up to four times a week, or usual care, for a period of 6 months; messages contained behavioural change techniques targeting medication use. The primary outcome was the rate of recruitment to randomisation of participants to the trial with a planned rate of 22 participants randomised per month. The study also aimed to establish the feasibility of follow-up at 6 months, with an aim of retaining more than 80% of participants. Data, including patient-reported measures, were collected at baseline and the end of the 6-month follow-up period, and a notes review was completed at 24 months. RESULTS: The trial took place between 26 November 2018 and 30 September 2019. In total 209 participants were randomly allocated to intervention (n = 103) or usual care (n = 106). The maximum rate of monthly recruitment to the trial was 60-80 participants per month. In total, 12,734 messages were sent to participants. Of these messages, 47 were identified as having failed to be sent by the service provider. Participants sent 2,864 messages to the automated messaging system. Baseline data from medical records were available for > 90% of participants with the exception of cholesterol (78.9%). At 6 months, a further HbA1c measurement was reported for 67% of participants. In total medical record data were available at 6 months for 207 (99.0%) of participants and completed self-report data were available for 177 (84.7%) of participants. CONCLUSION: The feasibility of a large-scale randomised evaluation of brief message intervention for people with type 2 diabetes appears to be high using this efficient design. Failure rate of sending messages is low, rapid recruitment was achieved among people with type 2 diabetes, clinical data is available on participants from routine medical records and self-report of economic measures was acceptable. TRIAL REGISTRATION: ISCTRN ISRCTN13404264. Registered on 10 October 2018.

Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus.

BACKGROUND: Diabetes is one of the commonest chronic medical conditions, affecting around 347 million adults worldwide. Structured patient education programmes reduce the risk of diabetes-related complications four-fold. Internet-based self-management programmes have been shown to be effective for a number of long-term conditions, but it is unclear what are the essential or effective components of such programmes. If computer-based self-management interventions improve outcomes in type 2 diabetes, they could potentially provide a cost-effective option for reducing the burdens placed on patients and healthcare systems by this long-term condition. OBJECTIVES: To assess the effects on health status and health-related quality of life of computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. SEARCH METHODS: We searched six electronic bibliographic databases for published articles and conference proceedings and three online databases for theses (all up to November 2011). Reference lists of relevant reports and reviews were also screened. SELECTION CRITERIA: Randomised controlled trials of computer-based self-management interventions for adults with type 2 diabetes, i.e. computer-based software applications that respond to user input and aim to generate tailored content to improve one or more self-management domains through feedback, tailored advice, reinforcement and rewards, patient decision support, goal setting or reminders. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the abstracts and extracted data. A taxonomy for behaviour change techniques was used to describe the active ingredients of the intervention. MAIN RESULTS: We identified 16 randomised controlled trials with 3578 participants that fitted our inclusion criteria. These studies included a wide spectrum of interventions covering clinic-based brief interventions, Internet-based interventions that could be used from home and mobile phone-based interventions. The mean age of participants was between 46 to 67 years old and mean time since diagnosis was 6 to 13 years. The duration of the interventions varied between 1 to 12 months. There were three reported deaths out of 3578 participants.Computer-based diabetes self-management interventions currently have limited effectiveness. They appear to have small benefits on glycaemic control (pooled effect on glycosylated haemoglobin A1c (HbA1c): -2.3 mmol/mol or -0.2% (95% confidence interval (CI) -0.4 to -0.1; P = 0.009; 2637 participants; 11 trials). The effect size on HbA1c was larger in the mobile phone subgroup (subgroup analysis: mean difference in HbA1c -5.5 mmol/mol or -0.5% (95% CI -0.7 to -0.3); P < 0.00001; 280 participants; three trials). Current interventions do not show adequate evidence for improving depression, health-related quality of life or weight. Four (out of 10) interventions showed beneficial effects on lipid profile.One participant withdrew because of anxiety but there were no other documented adverse effects. Two studies provided limited cost-effectiveness data - with one study suggesting costs per patient of less than $140 (in 1997) or 105 EURO and another study showed no change in health behaviour and resource utilisation. AUTHORS' CONCLUSIONS: Computer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control and the effect was larger in the mobile phone subgroup. There is no evidence to show benefits in other biological outcomes or any cognitive, behavioural or emotional outcomes.

Clustering by multiple long-term conditions and social care needs: a cross-sectional study among 10 026 older adults in England.

BACKGROUND   : People with multiple long-term conditions (MLTC) face health and social care challenges. This study aimed to classify people by MLTC and social care needs (SCN) into distinct clusters and quantify the association between derived clusters and care outcomes. METHODS : A cross-sectional study was conducted using the English Longitudinal Study of Ageing, including people with up to 10 MLTC. Self-reported SCN was assessed through 13 measures of difficulty with activities of daily living, 10 measures of mobility difficulties and whether health status was limiting earning capability. Latent class analysis was performed to identify clusters. Multivariable logistic regression quantified associations between derived MLTC/SCN clusters, all-cause mortality and nursing home admission. RESULTS: Our study included 9171 people at baseline with a mean age of 66.3 years; 44.5% were men. Nearly 70.8% had two or more MLTC, the most frequent being hypertension, arthritis and cardiovascular disease. We identified five distinct clusters classified as high SCN/MLTC through to low SCN/MLTC clusters. The high SCN/MLTC included mainly women aged 70-79 years who were white and educated to the upper secondary level. This cluster was significantly associated with higher nursing home admission (OR=8.71; 95% CI: 4.22 to 18). We found no association between clusters and all-cause mortality. CONCLUSIONS: We have highlighted those at risk of worse care outcomes, including nursing home admission. Distinct clusters of individuals with shared sociodemographic characteristics can help identify at-risk individuals with MLTC and SCN at primary care level.

Patient stratification for determining optimal second-line and third-line therapy for type 2 diabetes: the TriMaster study.

Precision medicine aims to treat an individual based on their clinical characteristics. A differential drug response, critical to using these features for therapy selection, has never been examined directly in type 2 diabetes. In this study, we tested two hypotheses: (1) individuals with body mass index (BMI) > 30 kg/m2, compared to BMI ≤ 30 kg/m2, have greater glucose lowering with thiazolidinediones than with DPP4 inhibitors, and (2) individuals with estimated glomerular filtration rate (eGFR) 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, have greater glucose lowering with DPP4 inhibitors than with SGLT2 inhibitors. The primary endpoint for both hypotheses was the achieved HbA1c difference between strata for the two drugs. In total, 525 people with type 2 diabetes participated in this UK-based randomized, double-blind, three-way crossover trial of 16 weeks of treatment with each of sitagliptin 100 mg once daily, canagliflozin 100 mg once daily and pioglitazone 30 mg once daily added to metformin alone or metformin plus sulfonylurea. Overall, the achieved HbA1c was similar for the three drugs: pioglitazone 59.6 mmol/mol, sitagliptin 60.0 mmol/mol and canagliflozin 60.6 mmol/mol (P = 0.2). Participants with BMI > 30 kg/m2, compared to BMI ≤ 30 kg/m2, had a 2.88 mmol/mol (95% confidence interval (CI): 0.98, 4.79) lower HbA1c on pioglitazone than on sitagliptin (n = 356, P = 0.003). Participants with eGFR 60-90 ml/min/1.73 m2, compared to eGFR >90 ml/min/1.73 m2, had a 2.90 mmol/mol (95% CI: 1.19, 4.61) lower HbA1c on sitagliptin than on canagliflozin (n = 342, P = 0.001). There were 2,201 adverse events reported, and 447/525 (85%) randomized participants experienced an adverse event on at least one of the study drugs. In this precision medicine trial in type 2 diabetes, our findings support the use of simple, routinely available clinical measures to identify the drug class most likely to deliver the greatest glycemic reduction for a given patient. (ClinicalTrials.gov registration: NCT02653209 ; ISRCTN registration: 12039221 .).

The impact of renin-angiotensin-aldosterone system inhibitors on Type 1 and Type 2 diabetic patients with and without early diabetic nephropathy.

Renin-angiotensin-aldosterone system inhibitors prevent the progression of kidney disease in patients with diabetic nephropathy, and we studied how that benefit varies by the type of diabetes and baseline urinary albumin. We pooled data from 49 randomized controlled trials in a meta-analysis using the ratio of endpoint urinary albumin levels in those treated compared to those untreated with renin-angiotensin-aldosterone system inhibitors in both fixed- and random-effects models. The urinary albumin excretion for treated microalbuminuric patients with Type 1 diabetes was on average 60% lower at the end of the trial compared with patients not treated with renin-angiotensin-aldosterone system inhibitors using the fixed-effects model and 67% lower using the random-effects model. There was no significant effect of treatment in patients with normal albumin excretion. For normoalbuminuric patients with Type 2 diabetes, urinary albumin excretion was on average 12% lower after treatment using the fixed-effects model compared to 21% lower using the random-effects model. For microalbuminuric patients, urinary albumin excretion was on average 23% lower using the fixed-effects model and 27% lower using the random-effects model. Thus, renin-angiotensin-aldosterone system inhibition reduced urinary albumin excretion for Type 1 diabetic patients with micro-, but not those with normoalbuminuria. Treatment reduced urinary albumin excretion for Type 2 diabetic patients with and without microalbuminuria.

Three-year efficacy of complex insulin regimens in type 2 diabetes.

BACKGROUND: Evidence supporting the addition of specific insulin regimens to oral therapy in patients with type 2 diabetes mellitus is limited. METHODS: In this 3-year open-label, multicenter trial, we evaluated 708 patients who had suboptimal glycated hemoglobin levels while taking metformin and sulfonylurea therapy. Patients were randomly assigned to receive biphasic insulin aspart twice daily, prandial insulin aspart three times daily, or basal insulin detemir once daily (twice if required). Sulfonylurea therapy was replaced by a second type of insulin if hyperglycemia became unacceptable during the first year of the study or subsequently if glycated hemoglobin levels were more than 6.5%. Outcome measures were glycated hemoglobin levels, the proportion of patients with a glycated hemoglobin level of 6.5% or less, the rate of hypoglycemia, and weight gain. RESULTS: Median glycated hemoglobin levels were similar for patients receiving biphasic (7.1%), prandial (6.8%), and basal (6.9%) insulin-based regimens (P=0.28). However, fewer patients had a level of 6.5% or less in the biphasic group (31.9%) than in the prandial group (44.7%, P=0.006) or in the basal group (43.2%, P=0.03), with 67.7%, 73.6%, and 81.6%, respectively, taking a second type of insulin (P=0.002). [corrected] Median rates of hypoglycemia per patient per year were lowest in the basal group (1.7), higher in the biphasic group (3.0), and highest in the prandial group (5.7) (P<0.001 for the overall comparison). The mean weight gain was higher in the prandial group than in either the biphasic group or the basal group. Other adverse event rates were similar in the three groups. CONCLUSIONS: Patients who added a basal or prandial insulin-based regimen to oral therapy had better glycated hemoglobin control than patients who added a biphasic insulin-based regimen. Fewer hypoglycemic episodes and less weight gain occurred in patients adding basal insulin. (Current Controlled Trials number, ISRCTN51125379.)