A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age.

BACKGROUND: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health. METHODS: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. FINDINGS: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. INTERPRETATION: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. FUNDING: The specific funding of this article is provided in the acknowledgements section.

Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning.

Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigated at state scales, but a regional model to predict locations of new infections can guide increasingly efficient surveillance efforts. We predicted CWD incidence by county using CWD surveillance data depicting white-tailed deer (Odocoileus virginianus) in 16 eastern and midwestern US states. We predicted the binary outcome of CWD-status using four machine learning models, utilized five-fold cross-validation and grid search to pinpoint the best model, then compared model predictions against the subsequent year of surveillance data. Cross validation revealed that the Light Boosting Gradient model was the most reliable predictor given the regional data. The predictive model could be helpful for surveillance planning. Predictions of false positives emphasize areas that warrant targeted CWD surveillance because of similar conditions with counties known to harbor CWD. However, disagreements in positives and negatives between the CWD Prediction Web App predictions and the on-the-ground surveillance data one year later underscore the need for state wildlife agency professionals to use a layered modeling approach to ensure robust surveillance planning. The CWD Prediction Web App is at https://cwd-predict.streamlit.app/ .

Excess Risk of Injury in Individuals With Type 1 or Type 2 Diabetes Compared With the General Population.

OBJECTIVE: To estimate the relative risk (RR) and excess hospitalization rate for injury in individuals with diabetes compared with the general population. RESEARCH DESIGN AND METHODS: Data were obtained from the Australian National Diabetes Services Scheme, hospitalization data sets, the Australian Pharmaceutical Benefits Scheme, the National Death Index, and the census spanning from 2011 to 2017. Hospitalizations for injury were coded as head and neck, lower-extremity, upper-extremity, or abdominal and thoracic injury; burns; or other injury. Poisson regression was used to estimate the age- and sex-adjusted RR of hospitalization for injury. RESULTS: The total number of hospitalizations for any injury was 117,705 in people with diabetes and 3,463,173 in the general population. Compared with that in the general population, an elevated adjusted risk of admission was observed for any injury (RR 1.22; 95% CI 1.21, 1.22), head and neck (1.28; 1.26, 1.30), lower extremity (1.24; 1.23, 1.26), abdominal and thoracic (1.29; 1.27, 1.30), upper extremity (1.03; 1.02, 1.05), burns (1.52; 1.44, 1.61), and other injury (1.37; 1.33, 1.40). The adjusted RR of any injury was 1.62 (1.58, 1.66) in individuals with type 1 diabetes, 1.65 (1.63, 1.66) in those with type 2 diabetes who were taking insulin, and 1.07 (1.06, 1.08) in individuals with type 2 diabetes not using insulin. Falls were the primary cause of injury in individuals with diabetes. CONCLUSIONS: Individuals with diabetes, especially those using insulin, had a higher risk of hospitalization for injury compared with the general population.

Development and validation of a plasmalogen score as an independent modifiable marker of metabolic health: population based observational studies and a placebo-controlled cross-over study.

BACKGROUND: Decreased levels of circulating ethanolamine plasmalogens [PE(P)], and a concurrent increase in phosphatidylethanolamine (PE) are consistently reported in various cardiometabolic conditions. Here we devised, a plasmalogen score (Pls Score) that mirrors a metabolic signal that encompasses the levels of PE(P) and PE and captures the natural variation in circulating plasmalogens and perturbations in their metabolism associated with disease, diet, and lifestyle. METHODS: We utilised, plasma lipidomes from the Australian Obesity, Diabetes and Lifestyle study (AusDiab; n = 10,339, 55% women) a nationwide cohort, to devise the Pls Score and validated this in the Busselton Health Study (BHS; n = 4,492, 56% women, serum lipidome) and in a placebo-controlled crossover trial involving Shark Liver Oil (SLO) supplementation (n = 10, 100% men). We examined the association of the Pls Score with cardiometabolic risk factors, type 2 diabetes mellitus (T2DM), cardiovascular disease and all-cause mortality (over 17 years). FINDINGS: In a model, adjusted for age, sex and BMI, individuals in the top quintile of the Pls Score (Q5) relative to Q1 had an OR of 0.31 (95% CI 0.21-0.43), 0.39 (95% CI 0.25-0.61) and 0.42 (95% CI 0.30-0.57) for prevalent T2DM, incident T2DM and prevalent cardiovascular disease respectively, and a 34% lower mortality risk (HR = 0.66; 95% CI 0.56-0.78). Significant associations between diet and lifestyle habits and Pls Score exist and these were validated through dietary supplementation of SLO that resulted in a marked change in the Pls Score. INTERPRETATION: The Pls Score as a measure that captures the natural variation in circulating plasmalogens, was not only inversely related to cardiometabolic risk and all-cause mortality but also associate with diet and lifestyle. Our results support the potential utility of the Pls Score as a biomarker for metabolic health and its responsiveness to dietary interventions. Further research is warranted to explore the underlying mechanisms and optimise the practical implementation of the Pls Score in clinical and population settings. FUNDING: National Health and Medical Research Council (NHMRC grant 233200), National Health and Medical Research Council of Australia (Project grant APP1101320), Health Promotion Foundation of Western Australia, and National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095).

Evaluating the incidence of complications among people with diabetes according to age of onset: Findings from the UK Biobank.

AIMS: To examine the impact of current age, age at diagnosis, and duration of diabetes on the incidence rate of complications among people with type 2 diabetes. METHODS: Baseline data from 19,327 individuals with type 2 diabetes in the UK Biobank were analysed. Poisson regression was used to model incidence rates by current age, age at diagnosis, and duration of diabetes for the following outcomes: myocardial infarction (MI), heart failure (HF), stroke, end-stage kidney diseases (ESKD), chronic kidney diseases (CKD), liver diseases, depression, and anxiety. RESULTS: The mean age at baseline was 60.2 years, and median follow-up was 13.9 years. Diabetes duration was significantly longer among those with younger-onset type 2 diabetes (diagnosed at <40 years) compared to later-onset type 2 diabetes (diagnosed at ≥40 years), 16.2 and 5.3 years, respectively. Incidence rates of MI, HF, stroke, and CKD had strong positive associations with age and duration of diabetes, whereas incidence rates of ESKD liver diseases, and anxiety mainly depended on duration of diabetes. The incidence rates of depression showed minor variation by age and duration of diabetes and were highest among those diagnosed at earlier ages. No clear evidence of an effect of age of onset of diabetes on risk of complications was apparent after accounting for current age and duration of diabetes. CONCLUSIONS: Our study indicates age at diagnosis of diabetes does not significantly impact the incidence of complications, independently of the duration of diabetes. Instead, complications are primarily influenced by current age and diabetes duration.

Associations of vegetable and potato intakes with markers of type 2 diabetes risk in the AusDiab cohort.

CONTEXT: The associations of vegetable and potato intakes with type 2 diabetes (T2D) appear to be nuanced, depending on vegetable types and preparation method, respectively. OBJECTIVE: We investigated the associations of total vegetable, vegetable subgroup, and potato intakes with 1) markers of T2D at baseline and 2) incident T2D cumulative over a 12-year follow-up period in Australian adults. METHODS: Using data from the Australian Diabetes, Obesity and Lifestyle Study, intakes of vegetables and potatoes were assessed via a food frequency questionnaire at baseline. Associations between vegetable intake and 1) fasting plasma glucose (FPG), 2-hour post load plasma glucose (PLG), updated homeostasis model assessment of ß-cell function (HOMA2-%ß), HOMA2 of insulin sensitivity (HOMA2-%S), and fasting insulin levels at baseline and 2) cumulative incident T2D at the end of 12-year follow-up were examined using generalized linear and Cox proportional hazards models, respectively. RESULTS: In total, 8,009 participants were included having median age of 52 years, and vegetable intake of 132 g/day. Higher intake of total vegetable, green leafy, yellow/orange/red, and moderate intakes of cruciferous vegetables was associated with lower PLG. Additionally, higher green leafy vegetable intake was associated with lower HOMA2-%ß and serum insulin. Conversely, higher potato fries/chips intakes were associated with higher FPG, HOMA2-%ß, serum insulin, and lower HOMA2-%S. Participants with moderate cruciferous vegetables intake had a 25% lower risk of T2D at the end of 12 years follow-up. CONCLUSIONS: A higher intake of vegetables, particularly green leafy vegetables, may improve while consuming potato fries/chips, but not potatoes prepared in a healthy way, may worsen glucose tolerance and insulin sensitivity. Our findings suggest a nuanced relationship between vegetable subgroups and their impact on glucose tolerance.

Kidney trajectory charts improve GP management of patients with reduced kidney function: a randomised controlled vignette study.

BACKGROUND: The stages of chronic kidney disease (CKD) and estimated glomerular filtration rate (eGFR) reference ranges are currently determined without considering age. AIM: To determine whether a chart that graphs age with eGFR helps GPs make better decisions about managing patients with declining eGFR. DESIGN & SETTING: A randomised controlled vignette study among Australian GPs using a percentile chart plotting the trajectory of eGFR by age. METHOD: Three hundred and seventy-three GPs received two case studies of patients with declining renal function. They were randomised to receive the cases with the chart or without the chart, and asked a series of questions about how they would manage the cases. RESULTS: In an older female patient with stable but reduced kidney function, use of the chart was associated with GPs in the study recommending a longer follow-up period, and longer time until repeat pathology testing. In a younger male First Nations patient with normal but decreasing kidney function, use of the chart was associated with GPs in the study recommending a shorter follow-up period, shorter time to repeat pathology testing, increased management of blood pressure and lifestyle, and avoidance of nephrotoxic medications. This represents more appropriate care in both cases. CONCLUSION: Having access to a chart of percentile eGFR by age was associated with more appropriate management review periods of patients with reduced kidney function, either by greater compliance with current guidelines or greater awareness of a clinically relevant kidney problem.

The association between sodium glucose cotransporter-2 inhibitors vs dipeptidyl peptidase-4 inhibitors and renal outcomes in people discharged from hospital with type 2 diabetes: A population-based cohort study.

BACKGROUND: We investigated the association between post-hospital discharge use of sodium glucose cotransporter-2 inhibitors (SGLT-2is) compared to dipeptidyl peptidase-4 inhibitors (DPP-4is) and the incidence of hospitalization for acute renal failure (ARF) and chronic kidney disease (CKD) in people with type 2 diabetes. METHODS: We conducted a retrospective cohort study using linked hospital and prescription data. Our cohort included people aged ≥30 years with type 2 diabetes discharged from a hospital in Victoria, Australia, from December 2013 to June 2018. We compared new users of SGLT-2is with new users of DPP-4is following discharge. People were followed from first dispensing of a SGLT-2i or DPP-4i to a subsequent hospital admission for ARF or CKD. We used competing risk models with inverse probability of treatment weighting (IPTW) to estimate subhazard ratios. RESULTS: In total, 9620 people initiated SGLT-2is and 9962 initiated DPP-4is. The incidence rate of ARF was 12.3 per 1000 person-years (median years of follow-up [interquartile range [IQR] 1.4 [0.7-2.2]) among SGLT-2i initiators and 18.9 per 1000 person-years (median years of follow-up [IQR] 1.7 [0.8-2.6]) among DPP-4i initiators (adjusted subhazard ratio with IPTW 0.78; 95% confidence interval [CI] 0.70-0.86). The incidence rate of CKD was 6.0 per 1000 person-years (median years of follow-up [IQR] 1.4 [0.7-2.2]) among SGLT-2i initiators and 8.9 per 1000 person-years (median years of follow-up [IQR] 1.7 [0.8-2.6]) among DPP-4i initiators (adjusted subhazard ratio with IPTW 0.83; 95% CI 0.73-0.94). CONCLUSIONS: Real-world data support using SGLT-2is over DPP-4is for preventing acute and chronic renal events in people with type 2 diabetes.

Temperature and CO2 interactively drive shifts in the compositional and functional structure of peatland protist communities.

Microbes affect the global carbon cycle that influences climate change and are in turn influenced by environmental change. Here, we use data from a long-term whole-ecosystem warming experiment at a boreal peatland to answer how temperature and CO2 jointly influence communities of abundant, diverse, yet poorly understood, non-fungi microbial Eukaryotes (protists). These microbes influence ecosystem function directly through photosynthesis and respiration, and indirectly, through predation on decomposers (bacteria and fungi). Using a combination of high-throughput fluid imaging and 18S amplicon sequencing, we report large climate-induced, community-wide shifts in the community functional composition of these microbes (size, shape, and metabolism) that could alter overall function in peatlands. Importantly, we demonstrate a taxonomic convergence but a functional divergence in response to warming and elevated CO2 with most environmental responses being contingent on organismal size: warming effects on functional composition are reversed by elevated CO2 and amplified in larger microbes but not smaller ones. These findings show how the interactive effects of warming and rising CO2 levels could alter the structure and function of peatland microbial food webs-a fragile ecosystem that stores upwards of 25% of all terrestrial carbon and is increasingly threatened by human exploitation.

Codesigning enhanced models of care for Northern Australian Aboriginal and Torres Strait Islander youth with type 2 diabetes: study protocol.

INTRODUCTION: Premature onset of type 2 diabetes and excess mortality are critical issues internationally, particularly in Indigenous populations. There is an urgent need for developmentally appropriate and culturally safe models of care. We describe the methods for the codesign, implementation and evaluation of enhanced models of care with Aboriginal and Torres Strait Islander youth living with type 2 diabetes across Northern Australia. METHODS AND ANALYSIS: Our mixed-methods approach is informed by the principles of codesign. Across eight sites in four regions, the project brings together the lived experience of Aboriginal and Torres Strait Islander young people (aged 10-25) with type 2 diabetes, their families and communities, and health professionals providing diabetes care through a structured yet flexible codesign process. Participants will help identify and collaborate in the development of a range of multifaceted improvements to current models of care. These may include addressing needs identified in our formative work such as the development of screening and management guidelines, referral pathways, peer support networks, diabetes information resources and training for health professionals in youth type 2 diabetes management. The codesign process will adopt a range of methods including qualitative interviews, focus group discussions, art-based methods and healthcare systems assessments. A developmental evaluation approach will be used to create and refine the components and principles of enhanced models of care. We anticipate that this codesign study will produce new theoretical insights and practice frameworks, resources and approaches for age-appropriate, culturally safe models of care. ETHICS AND DISSEMINATION: The study design was developed in collaboration with Aboriginal and Torres Strait Islander and non-Indigenous researchers, health professionals and health service managers and has received ethical approval across all sites. A range of outputs will be produced to disseminate findings to participants, other stakeholders and the scholarly community using creative and traditional formats.

Urine Albumin-Creatinine Ratio Variability in People With Type 2 Diabetes: Clinical and Research Implications.

RATIONALE & OBJECTIVE: Evidence has demonstrated that albuminuria is a key diagnostic and prognostic marker of diabetic chronic kidney disease, but the impact of its day-to-day variability has not been adequately considered. This study quantified within-individual variability of albuminuria in people with type 2 diabetes to inform clinical albuminuria monitoring. STUDY DESIGN: Descriptive cross-sectional analysis. SETTING & PARTICIPANTS: People with type 2 diabetes (n=826, 67.1 [IQR, 60.3-72.4] years, 64.9% male) participating in the Progression of Diabetic Complications (PREDICT) cohort study. EXPOSURE: Four spot urine collections for measurement of urinary albumin-creatinine ratio (UACR) within 4 weeks. OUTCOME: Variability of UACR. ANALYTICAL APPROACH: We characterized within-individual variability (coefficient of variation [CV], 95% limits of random variation, intraclass correlation coefficient), developed a calculator displaying probabilities that any observed difference between a pair of UACR values truly exceeded a 30% difference, and estimated the ranges of diagnostic uncertainty to inform a need for additional UACR collections to exclude or confirm albuminuria. Multiple linear regression examined factors influencing UACR variability. RESULTS: We observed high within-individual variability (CV 48.8%; 95% limits of random variation showed a repeated UACR to be as high/low as 3.78/0.26 times the first). If a single-collection UACR increased from 2 to 5mg/mmol, the probability that UACR actually increased by at least 30% was only 50%, rising to 97% when 2 collections were obtained at each time point. The ranges of diagnostic uncertainty were 2.0-4.0mg/mmol after an initial UACR test, narrowing to 2.4-3.2 and 2.7-2.9mg/mmol for the mean of 2 and 3 collections, respectively. Some factors correlated with higher (female sex; moderately increased albuminuria) or lower (reduced estimated glomerular filtration rate and sodium-glucose cotransporter 2 inhibitor/angiotensin-converting enzyme inhibitor/angiotensin receptor blocker treatment) within-individual UACR variability. LIMITATIONS: Reliance on the mean of 4 UACR collections as the reference standard for albuminuria. CONCLUSIONS: UACR demonstrates a high degree of within-individual variability among individuals with type 2 diabetes. Multiple urine collections for UACR may improve capacity to monitor changes over time in clinical and research settings but may not be necessary for the diagnosis of albuminuria. PLAIN-LANGUAGE SUMMARY: Albuminuria (albumin in urine) is a diagnostic and prognostic marker of diabetic chronic kidney disease. However, albuminuria can vary within an individual from day to day. We compared 4 random spot urinary albumin-creatinine ratio (UACR) samples from 826 participants. We found that a second UACR collection may be as small as a fourth or as large as almost 4 times the first sample's UACR level. This high degree of variability presents a challenge to our ability to interpret changes in albuminuria. Multiple collections have been suggested as a solution. We have constructed tools that may aid clinicians in deciding how many urine collections are required to monitor and diagnose albuminuria. Multiple urine collections may be required for individual monitoring but not necessarily for diagnosis.

The Determination of Diabetes Utilities, Costs, and Effects Model: A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation.

OBJECTIVES: To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes. METHODS: The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error. RESULTS: The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios. CONCLUSIONS: The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.

Imputation of plasma lipid species to facilitate integration of lipidomic datasets.

Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less resolved lipids in the target dataset, (2) addressing discrepancies between aligned lipid species, (3) generating prediction models, (4) assessing their transferability into the targe dataset, and (5) evaluating their prediction accuracy. To demonstrate our approach, we used the AusDiab population-based cohort (747 lipid species) as the reference to impute unmeasured lipid species into the LIPID study (342 lipid species). Furthermore, we compared measured and imputed lipids in terms of parameter estimation and predictive performance, and validated imputations in an independent study. Our method for harmonising plasma lipidomic datasets will facilitate model validation and data integration efforts.

SGLT-2 Inhibitor Use and Cause-Specific Hospitalization Rates: An Outcome-Wide Study to Identify Novel Associations of SGLT-2 Inhibitors.

Sodium-glucose co-transporter 2 inhibitors (SGLT2is) have demonstrated multifaceted pharmacological effects. In addition to type 2 diabetes, they are now indicated for heart failure and chronic kidney disease. This study aimed to identify novel associations between SGLT2i use and health outcomes using real-world data. Using linked data from a nationwide diabetes registry in Australia, we compared hospitalization rates in people living with type 2 diabetes commencing treatment with SGLT2i and dipeptidyl peptidase-4 inhibitor (DPP4i) between December 1, 2013, and June 30, 2019. Cause-specific hospitalizations were categorized across three hierarchies of diagnoses (first, first three, and first four digits of International Classification of Diseases, Tenth Version, Australian Modification codes). Incidence rate ratio (IRR) and 95% confidence interval (95% CI) for each cause-specific hospitalization were estimated using negative binomial regression. In the first hierarchy, hospitalization rates were lower across most diagnosis groups among SGLT2i initiators (n = 99,569) compared with DPP4i initiators (n = 186,353). In the second and third hierarchies, there were lower hospitalization rates relating to infections, anemias, and obstructive airway diseases among SGLT2i initiators compared with DPP4i initiators. These included sepsis (IRR: 0.60, 95% CI: 0.51-0.72) anemia (IRR: 0.55, 95% CI: 0.46-0.66), and chronic obstructive pulmonary diseases (IRR: 0.52, 95% CI: 0.40-0.68), as well as for previously known associations (e.g., heart failure (IRR: 0.63, 95% CI: 0.56-0.70)). SGLT2is have previously uncharacterized associations on a range of important clinical outcomes; validation of these associations requires further study, some of which may suggest novel benefits or new indications for SGLT2is.

Evaluation of video visit appropriateness for common symptoms seen in primary care: A retrospective cohort study.

INTRODUCTION: Little is known about which conditions seen in primary care are appropriate for video visits. This study evaluated video visits compared to office visits for six conditions: abdominal pain, joint pain, back pain, headache, chest pain, and dizziness. METHODS: Six hundred charts of adult patients from our institution's same-day outpatient clinic were reviewed in this study. Charts for video visits evaluating the aforementioned chief complaints that occurred between August and October 2020 were reviewed and compared with charts for office visits that occurred from August to September 2019. Frequencies of 3-week follow-up visits, Emergency Room visits, imaging, and referrals for office and video visits were measured. Reasons for in-person evaluation for patients seen by video were determined by review of clinician notes. RESULTS: Three-week in-person follow-up was more frequent for patients presenting with chest pain (52% vs 18%, p = 0.0007) and joint pain (24% vs 8%, p = 0.05) after video evaluation, relative to an office evaluation. Three-week in-person follow-up was also more frequent for patients presenting with dizziness (38% vs 28%) and low back pain (24% vs 14%); however, this difference was not statistically significant. Patients presenting with headache and abdominal pain did not have a higher rate of follow-up. DISCUSSION: Based on the frequency of in-person follow-up, this study suggests that video visits are generally adequate for evaluating headache and abdominal pain. Patients with dizziness and chest pain have the highest frequency of in-person and Emergency Room follow-up within 3 weeks when first seen by video compared to other conditions evaluated and may be less suitable for an initial video visit. Institutions can consider these findings when scheduling and providing guidance to patients on what type of visit is most appropriate for their symptoms.

Understanding the Biering-Sørensen test: Contributors to extensor endurance in young adults with and without a history of low back pain.

The Biering-Sørensen test is commonly used to assess paraspinal muscle endurance. Research using a single repetition of the test has provided conflicting evidence for the contribution of impaired paraspinal muscle endurance to low back pain (LBP). This study investigated how Sørensen test duration, muscle activation, and muscle fatigability are affected by multiple repetitions of the test and determined predictors of Sørensen test duration in young adults with and without a history of LBP. Sixty-four young individuals performed three repetitions of the Sørensen test. Amplitude of activation and median frequency slope (fatigability) were calculated for the lumbar and thoracic paraspinals and hamstrings. Duration of the test was significantly less for the 3rd repetition in individuals with LBP. In individuals without LBP, test duration was predicted by fatigability of the lumbar paraspinals. In individuals with LBP, Sørensen test duration was predicted by fatigability of the hamstrings and amplitude of activation of the thoracic and lumbar paraspinals. Our findings demonstrate that it is necessary to amplify the difficulty of the Sørensen test to reveal impairments in young, active adults with LBP. Training programs aiming to improve lumbar paraspinal performance should monitor performance of other synergist muscles during endurance exercise.

Acculturation and glycaemic control in Arab immigrants with type 2 diabetes in Australia.

AIMS/HYPOTHESIS: This study aimed to investigate acculturation's direct and mediated effects on HbA1c levels in individuals with type 2 diabetes from Arabic-speaking countries that are members of the Arab League who have emigrated to Australia. METHODS: In this multicentre cross-sectional study, we recruited 382 Arabic-speaking immigrants who were born in any of the 22 countries of the Arab League and who had type 2 diabetes from different healthcare settings in Australia. HbA1c levels were retrieved from medical records. A validated self-report questionnaire was used to assess behavioural and psychosocial outcomes. Acculturation was measured using the General Acculturation Index and the Adherence to Traditional Values tool. We used structural equation modelling to test mediation hypotheses. RESULTS: Participants had a mean HbA1c value of 63.9 mmol/mol (8.0%), a low acculturation level (mean±SD: 1.9±0.6; range: 1-5) and highly adhered to traditional values (mean General Acculturation Index value: 3.7±0.7; range: 1-5). Higher HbA1c was associated with lower acculturation levels (Pearson correlation coefficient [r] = -0.32, p<0.01) and higher adherence to traditional values (r=0.35, p<0.01). Self-efficacy, health literacy and self-care activities partially mediated the relationship between acculturation and HbA1c. CONCLUSIONS/INTERPRETATION: Among Arab immigrants in Australia with type 2 diabetes, the degree of acculturation is related to glycaemic control, suggesting possible avenues for new interventions.

A novel approach to accurately measuring the burden of hospitalisations for cardiovascular disease in people with diabetes: A pilot study.

AIM: To determine the reliability of hospital discharge codes for heart failure (HF), acute myocardial infarction (AMI) and stroke compared with adjudicated diagnosis, and to pilot a scalable approach to adjudicate records on a population-based sample. METHODS: A population-based sample of 685 people with diabetes admitted (1274 admissions) to one of three Australian hospitals during 2018-2020 were randomly selected for this study. All medical records were reviewed and adjudicated. RESULTS: Cardiovascular diseases were the most common primary reason for hospitalisation in people with diabetes, accounting for ~17% (215/1274) of all hospitalisations, with HF as the leading cause. ICD-10 codes substantially underestimated HF prevalence and had the lowest agreement with the adjudicated diagnosis of HF (Kappa = 0.81), compared with AMI and stroke (Kappa ≥ 0.91). While ICD-10 codes provided suboptimal sensitivity (72%) for HF, the performance was better for AMI (sensitivity 84%; specificity 100%) and stroke (sensitivity 85%; specificity 100%). A novel approach to screen possible HF cases only required adjudicating 8% (105/1274) of records, correctly identified 78/81 of HF admissions and yielded 96% sensitivity and 98% specificity. CONCLUSIONS: While ICD-10 codes appear reliable for AMI or stroke, a more complex diagnosis such as HF benefits from a two-stage process to screen for suspected HF cases that need adjudicating. The next step is to validate this novel approach on large multi-centre studies in diabetes.