Push or pull? Digital notification platform implementation reduces dysglycaemia.

Pushing selected information to clinicians, as opposed to the traditional method of clinicians pulling information from an electronic medical record, has the potential to improve care. A digital notification platform was designed by clinicians and implemented in a tertiary hospital to flag dysglycaemia. There were 112 patients included in the study, and the post-implementation group demonstrated lower rates of dysglycaemia (2.5% vs 1.1%, P = 0.038). These findings raise considerations for information delivery methods for multiple domains in contemporary healthcare.

ARTIFICIAL INTELLIGENCE AGE PREDICTION USING ELECTROCARDIOGRAM DATA: EXPLORING BIOLOGICAL AGE DIFFERENCES.

BACKGROUND: Biological age can be predicted using artificial intelligence (AI) trained on electrocardiograms (ECGs), which is prognostic for mortality and cardiovascular events. OBJECTIVE: We developed an AI model to predict age from ECG and compared baseline characteristics to identify determinants of advanced biological age. METHODS: An AI model was trained on ECGs from cardiology inpatients aged 20-90 years. AI analysis used a convolutional neural network with data divided in an 80:20 ratio (development:internal validation), with external validation undertaken using data from the UK Biobank. Performance and subgroup comparison measures included correlation, difference and mean absolute difference. RESULTS: 63,246 patients with 353,704 total ECGs were included. In internal validation, the correlation coefficient was 0.72, with a mean absolute difference between chronological and AI-predicted age of 9.1 years. The same model performed similarly in external validation. In patients aged 20-29, AI-ECG biological age was older than chronological age by a mean 14.3±0.2 yrs. In patients aged 80-89 years, biological age was younger by a mean 10.5±0.1 yrs. Women were biologically younger than men by a mean of 10.7 months (P=0.023) and patients with a single ECG were biologically 1.0 years younger than those with multiple ECGs (P<0.0001). CONCLUSION: There are significant between-group differences in AI-ECG biological age for patient subgroups. Biological age was greater than chronological age in young, hospitalized patient, and less than chronological age in the older hospitalized patient. Women and patients with a single ECG recorded were biologically younger than men and patients with multiple recorded ECGs.

A Retrospective Analysis of Characteristics Favouring In-Hospital Resuscitation Plan Completion, Their Timing, and Associated Outcomes.

Background: Comprehensive resuscitation plans document treatment recommendations, such as 'Not for cardiopulmonary resuscitation'. When created early in admission as a shared decision-making process, these plans support patient autonomy and guide future treatment. The characteristics of patients who have resuscitation plans documented, their timing, and associations with clinical outcomes remain unclear. Objectives: To characterise factors associated with resuscitation plan completion, early completion, and differences in mortality rates and Intensive Care Unit (ICU) admissions based on resuscitation plan status. Methods: This retrospective study analysed non-elective admissions to an Australian tertiary centre from January to June 2021, examining plan completion timing (early < 48 h, late > 48 h) and associations with mortality and ICU admission. Results: Of 13,718 admissions, 5745 (42%) had a resuscitation plan recorded. Most plans (89%) were completed early. Furthermore, 9% of patients died during admission, and 8.2% were admitted to the ICU. For those without resuscitation plans, 0.5% died (p < 0.001), and 9.7% were admitted to the ICU (p = 0.002). Factors associated with plan completion included a medical unit, in-hours admission, older age, female gender, limited English proficiency, and non-Indigenous status. Plans completed late (>48 h) correlated with a higher mortality (14% vs. 9%; p < 0.001) and more ICU admissions (25% vs. 6%; p < 0.001). Aboriginal and/or Torres Strait Islander patients were often overlooked for resuscitation documentation before death. No resuscitation plans were documented for 62% of ICU admissions. Conclusions: Important disparities exist in resuscitation plan completion rates across highly relevant inpatient and demographic groups.

Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).

Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have previously been derived to predict which patients are nearing discharge based upon ward round notes. In this implementation study, such an artificial intelligence algorithm was coupled with a multidisciplinary discharge facilitation team on weekend shifts. This approach was implemented in a tertiary hospital, and then compared to a historical cohort from the same time the previous year. There were 3990 patients included in the study. There was a significant increase in the proportion of inpatients who received weekend discharges in the intervention group compared to the control group (median 18%, IQR 18-20%, vs median 14%, IQR 12% to 17%, P = 0.031). There was a corresponding higher absolute number of weekend discharges during the intervention period compared to the control period (P = 0.025). The studied intervention was associated with an increase in weekend discharges and economic analyses support this approach as being cost-effective. Further studies are required to examine the generalizability of this approach to other centers.

Risk factors for MEK-associated retinopathy in patients with advanced melanoma treated with combination BRAF and MEK inhibitor therapy.

BACKGROUND: Retinopathy is a common adverse event with mitogen-activated extracellular signal-regulated kinase (MEK) inhibitors. Little is known about the pathophysiology of MEK inhibitor-associated retinopathy (MEKAR). Since MEKAR has many similarities to central serous chorioretinopathy (CSCR), they may share common risk factors. The aim of this study was to evaluate the association between baseline characteristics and MEKAR in melanoma patients initiating MEK inhibitor treatment. METHODS: Data from patients treated with cobimetinib and vemurafenib for advanced melanoma in the coBRIM trial were subjected to secondary analysis. Consistent with CSCR risk factors, assessed baseline characteristics included: age, gender, past ocular disease, weight, hypertension, diabetes, dyslipidemia, glomerular filtration rate (eGFR) and corticosteroid use. Associations between characteristics and retinopathy events (any grade and symptomatic) were evaluated using univariate logistic regression and represented as odds ratios (OR). RESULTS: A total of 247 patients were treated with cobimetinib and vemurafenib, of whom 72 (29%) had retinopathy of any grade and 33 (13%) had symptomatic retinopathy. Patients with a history of ocular disease were at significantly higher risk of retinopathy (any grade, 44%; symptomatic, 22%) than those with no ocular disease history (any grade, 22%; symptomatic, 10%). Individuals with a history of ocular inflammation or infection were at highest risk: 4 of 5 developed symptomatic retinopathy during MEK inhibitor therapy. Increased age was associated with a higher risk of any grade retinopathy {decade increase OR [95% confidence interval (CI)] = 1.03 (1.01-1.05); p = 0.009}, while increasing eGFR was significantly associated with a decreased risk of any grade retinopathy [0.98 (0.96-0.99); p = 0.004]; the associations were not statistically significant with symptomatic retinopathy. Other assessed CSCR risk factors were not significantly associated with MEKAR. CONCLUSION: Age, glomerular filtration rate and history of ocular disease (particularly inflammatory eye disease) were associated with a risk of MEK inhibitor induced retinopathy. Patients who are at increased risk of MEKAR may benefit from more regular ophthalmologic assessment during treatment.