Enhancing Glycemic Risk Assessment in Long‐Term Care: Suggestions for Future Research

We read with great interest the study by Wondimkun et al., which leveraged the Registry of Senior Australians to quantify 12-month hospitalizations for acute glycemic events after entry to long-term care facilities (LTCFs) [1]. While the authors should be commended for analyzing a national cohort of ≥ 55,000 residents, we believe three methodological issues merit attention to maximize the translational value of their findings. First, the true incidence may be higher than reported. When the analysis relied only on principal public-hospital diagnosis codes, 12-month rates were 1.0% for hypoglycemia and 0.5% for hyperglycemia; adding secondary codes tripled these figures, and private-hospital data were not available. Moreover, many acute glycemic events may be misclassified at presentation—as falls, near syncope, stroke, myocardial infarction, or altered mental status—which can further obscure detection and understate the true burden. Linking emergency-department and private-hospital records or using glucose logs kept by nursing staff in LTCFs could capture events that never reach a public-hospital discharge sheet. Second, key markers of glycemic control are missing. HbA1c, glucose variability, and insulin dose—all powerful predictors of both hypo- and hyperglycemia in frail older adults—are not captured in ROSA [2], even though the 2024 ADA Standards of Care for Older Adults explicitly recommend tailoring therapeutic targets on the basis of HbA1c and day-to-day glucose swings [3]. Linking ROSA to central laboratory feeds or point-of-care testing systems inside LTCFs would make it possible to run HbA1c-stratified analyses and produce more accurate medication-safety estimates. Third, generalizability and equity deserve attention. Aboriginal and Torres Strait Islander residents were excluded, and residents whose preferred language was not English faced a higher hyperglycemia risk in the study; language barriers are known to impair diabetes control and cardiovascular risk-factor management [4]. Including Indigenous Australians and adding culture-specific variables would broaden applicability and help tailor prevention programmers for communities carrying a disproportionate diabetes burden. In conclusion, Wondimkun et al. provide a valuable snapshot of glycemic emergencies in Australian LTCFs. Addressing event capture, adding laboratory data, and broadening the sample would make the work even more useful for policymakers and bedside teams alike. Z.X. conceived the idea for the commentary, performed the literature review, and drafted the manuscript. H.Z. and F.Z. revised the manuscript critically for important intellectual content, approved the final version, and are accountable for all aspects of the work. The authors have nothing to report. The authors declare no conflicts of interest. This publication is linked to a related article by Wondimkun et al. To view this article, visit https://doi.org/0.1111/jgs.70131.