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Background: In Australia, diabetes is the fastest growing chronic condition, with prevalence trebling over the past three decades. Despite reported sex differences in diabetes outcomes, disparities in management and health targets remain unclear. This population-based retrospective study used MedicineInsight primary healthcare data to investigate sex differences in diabetes prevalence, incidence, management, and achievement of health targets., Methods: Adults (aged ≥ 18 years) attending 39 general practices in Western Australia were included. Diabetes incidence and prevalence were estimated by age category. Health targets assessed included body mass index (BMI), blood pressure, blood lipids, and glycated haemoglobin (HbA 1c ) levels. Medical management of diabetes-associated conditions was also investigated. Time-to-incident diabetes was modelled using a Weibull regression. A multilevel mixed-effects logistic regression model investigated risk-adjusted sex differences in achieving the HbA 1c health target (HbA 1c  ≤ 7.0% (≤ 53 mmol/mol))., Results: Records of 668,891 individuals (53.4% women) were analysed. Diabetes prevalence ranged from 1.3% (95% confidence interval (CI) 1.2%-1.3%) in those aged < 50 years to 7.2% (95% CI 7.1%-7.3%) in those aged ≥ 50 years and was overall higher in men. In patients younger than 30 years, incidence was higher in women, with this reversing after the age of 50. Among patients with diabetes, BMI ≥ 35 kg/m 2 was more prevalent in women, whereas current and past smoking were more common in men. Women were less likely than men to achieve lipid health targets and less likely to receive prescriptions for lipid, blood pressure, or glucose-lowering agents. Men with incident diabetes were 21% less likely than women to meet the HbA1 c target. Similarly, ever recorded retinopathy, nephropathy, neuropathy, hypertension, dyslipidaemia, coronary heart disease, heart failure, peripheral vascular disease and peripheral artery disease were higher in men than women., Conclusions: This research underscores variations in diabetes epidemiology and management based on sex. Tailoring diabetes management should consider the patient's sex., (© 2024. The Author(s).)

Background: There is a deficiency in the evidence from rural and regional centres in Australia on the weekend effect following presentation with acute stroke., Objective: To estimate the association between admission over a weekend/holiday and all-cause mortality 3-day, 7-day, 14-day, 1-month, 3-month, 6-month, and 12-month following acute stroke., Methods: The records of stroke patients admitted to a main regional hospital in Australia from 2010 to 2020 were linked with the National Death Index. Time to death following ischaemic, haemorrhagic, and total stroke at different time points was modelled using Weibull, Exponential, or Gompertz regression based on best model fit determined by Akaike's information criterion., Results: Of 1669 patients, 1273 (76.3%) were admitted on a weekday, and 396 (23.7%) on a weekend/ or holiday. After adjusting for age, sex, and Charlson Comorbidity Index, stroke type and country of birth, admissions over a weekend/holiday following total stroke were significantly associated with an increased risk of dying within three days from admission [hazard ratio (HR): 1.59, 95% confidence interval: 1.01-2.50]. In haemorrhagic stroke, increased risk of death was significantly higher at three days (HR: 2.19, 95% confidence interval: 1.17-4.08), 14 days (HR: 1.73, 95% confidence interval: 1.02-2.93), and 1 month (HR: 1.82, 95% confidence interval: 1.09-3.03) following admission on the weekend/ or holiday compared to those admitted during the weekdays., Conclusions: This study reports a short-term adverse weekend/holiday effect following admission for haemorrhagic stroke or total stroke. No significant weekend/holiday effect was found in ischaemic stroke., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: The optimal Early Warning System (EWS) scores for identifying patients at risk of clinical deterioration among those transported by ambulance services remain uncertain. This retrospective study compared the performance of 21 EWS scores to predict clinical deterioration using vital signs (VS) measured in the prehospital or emergency department (ED) setting., Methods: Adult patients transported to a single ED by ambulances and subsequently admitted to the hospital between 1 January 2019 and 18 April 2019 were eligible for inclusion. The primary outcome was 30-day mortality; secondary outcomes included 3-day mortality, admission to intensive care or coronary care units, length of hospital stay and emergency call activations. The discriminative ability of the EWS scores was assessed using the area under the receiver operating characteristic curve (AUROC). Subanalyses compared the performance of EWS scores between surgical and medical patient types., Results: Of 1414 patients, 995 (70.4%) (53.1% male, mean age 68.7±17.5 years) were included. In the ED setting, 30-day mortality was best predicted by VitalPAC EWS (AUROC 0.71, 95% CI (0.65 to 0.77)) and National Early Warning Score (0.709 (0.65 to 0.77)). All EWS scores calculated in the prehospital setting had AUROC <0.70. Rapid Emergency Medicine Score (0.83 (0.73 to 0.92)) and New Zealand EWS (0.88 (0.81 to 0.95)) best predicted 3-day mortality in the prehospital and ED settings, respectively. EWS scores calculated using either prehospital or ED VS were more effective in predicting 3-day mortality in surgical patients, whereas 30-day mortality was best predicted in medical patients. Among the EWS scores that achieved AUROC ≥0.70, no statistically significant differences were detected in their discriminatory abilities to identify patients at risk of clinical deterioration., Conclusions: EWS scores better predict 3-day as opposed to 30-day mortality and are more accurate when estimated using VS measured in the ED. The discriminatory performance of EWS scores in identifying patients at higher risk of clinical deterioration may vary by patient type., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

24-h shift (24 hS) exposed emergency physicians to a higher stress level than 14-h night shift (14 hS), with an impact spreading on several days. Catecholamines are supposed to be chronic stress biomarker. However, no study has used catecholamines to assess short-term residual stress or measured them over multiple shifts. A shift-randomized trial was conducted to study urinary catecholamines levels of 17 emergency physicians during a control day (clerical work on return from leave) and two working day (14 hS and 24 hS). The Wilcoxon matched-pairs test was utilized to compare the mean catecholamine levels. Additionally, a multivariable generalized estimating equations model was employed to further analyze the independent relationships between key factors such as shifts (compared to control day), perceived stress, and age with catecholamine levels. Dopamine levels were lower during 24 hS than 14 hS and the control day. Norepinephrine levels increased two-fold during both night shifts. Epinephrine levels were higher during the day period of both shifts than on the control day. Despite having a rest day, the dopamine levels did not return to their normal values by the end of the third day after the 24 hS. The generalized estimating equations model confirmed relationships of catecholamines with workload and fatigue. To conclude, urinary catecholamine biomarkers are a convenient and non-invasive strong measure of stress during night shifts, both acutely and over time. Dopamine levels are the strongest biomarker with a prolonged alteration of its circadian rhythm. Due to the relation between increased catecholamine levels and both adverse psychological effects and cardiovascular disease, we suggest that emergency physicians restrict their exposure to 24 hS to mitigate these risks., (© 2024. The Author(s).)