Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence-Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study.

BACKGROUND: The clinical management of type 2 diabetes mellitus (T2DM) presents a significant challenge due to the constantly evolving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelligence (AI)-enabled clinical decision support systems (CDSSs) have proven to be effective in assisting clinicians with informed decision-making. Despite the merits of AI-driven CDSSs, a significant research gap exists concerning the early-stage implementation and adoption of AI-enabled CDSSs in T2DM management. OBJECTIVE: This study aimed to explore the perspectives of clinicians on the use and impact of the AI-enabled Prescription Advisory (APA) tool, developed using a multi-institution diabetes registry and implemented in specialist endocrinology clinics, and the challenges to its adoption and application. METHODS: We conducted focus group discussions using a semistructured interview guide with purposively selected endocrinologists from a tertiary hospital. The focus group discussions were audio-recorded and transcribed verbatim. Data were thematically analyzed. RESULTS: A total of 13 clinicians participated in 4 focus group discussions. Our findings suggest that the APA tool offered several useful features to assist clinicians in effectively managing T2DM. Specifically, clinicians viewed the AI-generated medication alterations as a good knowledge resource in supporting the clinician's decision-making on drug modifications at the point of care, particularly for patients with comorbidities. The complication risk prediction was seen as positively impacting patient care by facilitating early doctor-patient communication and initiating prompt clinical responses. However, the interpretability of the risk scores, concerns about overreliance and automation bias, and issues surrounding accountability and liability hindered the adoption of the APA tool in clinical practice. CONCLUSIONS: Although the APA tool holds great potential as a valuable resource for improving patient care, further efforts are required to address clinicians' concerns and improve the tool's acceptance and applicability in relevant contexts.

Renal Outcomes 1 Year After Metabolic Bariatric Surgery in a Multi-ethnic Asian Cohort.

PURPOSE: Obesity increases the risk of incident chronic kidney disease (CKD) and is one of the strongest risk factors for new-onset CKD even in the absence of metabolic risk factors. Weight loss has been shown to reduce renal hyperfiltration and proteinuria. Metabolic bariatric surgery (MBS) remains an effective treatment for obesity and its metabolic-related complications. However, literature on its impact on renal function remains limited. MATERIALS AND METHODS: This was an observational retrospective study in a tertiary centre in Singapore. MBS cases performed at the centre between 2008 and 2019 were included. The primary outcome measures were estimated glomerular filtration rate (eGFR), calculated using the CKD epidemiology collaboration equation, and albuminuria (defined as urine albumin-creatinine ratio (uACR) > 3.5 mg/mmol) at baseline and 1-year post-MBS. RESULTS: Five hundred fifty-seven patients were included. One-year post-MBS, median eGFR increased from 110.9 mL/min/1.73 m2 (IQR 92.4 to 121.5) to 112.6 mL/min/1.73 m2 (IQR 97.3 to 122.3), p < 0.001. Median uACR decreased from 1.00 mg/mmol (IQR 0.40 to 3.55) to 0.70 mg/mmol (IQR 0.40 to 1.80) 1-year post-MBS (p = 0.001). 12.9% of patients had improved CKD staging. The proportion of patients with albuminuria decreased from 24.8% at baseline to 1.89% 1-year post-MBS (p < 0.001). One-year post-MBS, the subgroup with reduced eGFR had significant increases in eGFR (p < 0.001), with a trend towards a reduction in uACR. CONCLUSIONS: MBS had a positive impact on renal function with modest but statistically significant improvement in eGFR and reduction in albuminuria at 1-year post-surgery. Longer-term data is required to investigate the durability of this impact.

Factors associated with prolonged length of stay in patients admitted with severe hypoglycaemia to a tertiary care hospital.

Severe hypoglycaemia carries considerable morbidity and potential mortality. We aim to elucidate the factors which were associated with a prolonged length of stay (LOS) among patients with diabetes who were admitted to the hospital with severe hypoglycaemia. Three hundred and four patients were included in the analysis, with a mean age of 70.6 ± 11.3 years, mean glycated haemoglobin of 6.9 ± 1.3% and median LOS of 3 days. Patients with a LOS >3 days had significantly higher Charlson Comorbidity Index (CCI) (4.9 ± 2.1 vs 4.1 ± 2.1, P < 0.01), a lower glomerular filtration rate (GFR) (34.6 ± 31.4 mL/min vs 44.8 ± 28.9 mL/min, P = 0.01) and a higher proportion of these patients suffered from recurrent hypoglycaemia during the admission (38.9% vs 27.7%, P = 0.04). In addition, they had higher white cell counts (11.1 ± 4.8 × 109/L vs 9.3 ± 3.2 × 109/L) and lower albumin concentrations (32.9 ± 6.6 g/L vs 36.8 ± 4.9 g/L). Bivariate analysis showed that the same factors were associated with prolonged LOS. Identification of risk factors associated with prolonged LOS provides the opportunity for intervention to reduce the LOS and improve the outcomes for these patients.

High one-year mortality following hospitalization for severe hypoglycemia among patients with diabetes mellitus: findings of a retrospective cohort study at an acute tertiary care hospital in Singapore.

OBJECTIVES: Little is known about the 1-year short-term mortality rate following hospital admissions with severe hypoglycemia. This study aimed to determine the factors associated with increased 1-year mortality rate following hospitalization in diabetes patients admitted with severe hypoglycemia to the Singapore General Hospital. METHODS: Clinical, biochemical, and 1-year mortality data from diabetes patients who were admitted with severe hypoglycemia in the year 2014 were extracted from institutional medical records. Patients who passed away during the episode of admissions with severe hypoglycemia were excluded from the analysis. The clinical and biochemical factors between patients who survived and those who did not survive within 1 year following admission were compared using logistic regression analysis. RESULTS: Three hundred and four patients (181 female and 123 male) were admitted with severe hypoglycemia in 2014, and the mean capillary blood glucose on admission was 2.3 ± 0.7 mmol/L. Sixty-three (20.7%) patients died within 1-year post-discharge from the hospital. Compared with patients who survived 1-year post-discharge from the hospital, non-survivors were older (69.3 ± 11.0 vs 75.5 ± 11.2 years, p < .001), had longer lengths of stay (LOS) (5.0 ± 7.4 vs 9.0 ± 12.8 days, p = .02), and had a higher Charlson Comorbidity Index (CCI) (4.1 ± 1.9 vs 5.9 ± 2.4, p < .001). Factors associated with increased 1-year mortality risk were age (odds ratio [OR] = 1.06; 95% confidence interval [CI] = 1.03-1.09, p < .01), LOS in hospital (OR = 1.01; 95% CI = 1.01-1.08, p < .01), and CCI (OR = 1.51; 95% CI = 1.31-1.75, p < .01), respectively. CONCLUSIONS: Older diabetes patients with more comorbidities and longer LOS were at increased risk of dying within a year of discharge after hospitalization with severe hypoglycemia. Admission with severe hypoglycemia has important prognostic implications. Healthcare professionals should address hypoglycemia and other health issues during the hospital admissions.