We commend Lee et al. (1) on their recent paper reporting on Stanford Health Care’s hospital policy supporting continued patient use of continuous glucose monitoring (CGM) during hospitalization through accuracy monitoring and electronic health record integrations. The study results, including 1,506 paired glucose values from 185 inpatient encounters (135 patients), reported preference for supported inpatient CGM use over routine finger-stick blood glucose monitoring (FSBG) use by nursing staff and patients alike as well as favorable inpatient CGM accuracy, with overall mean absolute relative difference of 9.6%.

While outpatient CGM accuracy and glycemic efficacy are well established, as Lee et al. (1) mention, there is a current lack of U.S. Food and Drug Administration (FDA) labeling for inpatient-specific CGM use. To date, studies of inpatient CGM use have largely investigated single CGM device models (2,3). While these types of studies are important, unfortunately such results offer insufficient data breadth across CGM models to guide clinical decision-making in the real world, where a range of CGM device models are in common use and patients do not all use the same device. Studies, such as that by Lee et al. (1), of real-world inpatient CGM use across the broad range of CGM device models in clinical use are therefore of crucial importance for clinicians and patients alike to understand real-world inpatient CGM accuracy across a breadth of device models.

Evaluation of inpatient CGM accuracy in people with type 1 diabetes (T1D) warrants special consideration given this patient population has the highest proportion of CGM use and are increasingly likely to be admitted to hospital while wearing a CGM device. Existing inpatient CGM studies have assessed accuracy in populations predominantly with type 2 diabetes (2,3). However, it has previously been suggested that CGM accuracy reports may be lower in people with T1D due to their greater inherent glycemic variability (5). Indeed, FDA validation criteria for integrated CGM systems (4) requires accuracy demonstration in “the intended use population,” which would naturally include people with T1D. In the study by Lee et al. (1), 27.4% of the study participants had T1D. While this proportion is greater than that of most reported studies (2,3), it is still a minority and thus the overall pooled accuracy results with mean absolute relative difference of 9.6% may not be representative of CGM accuracy among inpatients with T1D. Further studies specifically evaluating CGM accuracy in hospitalized patients with T1D are warranted.

Overall, the reported study results (1) provide important evidence for feasibility of CGM–electronic health record integration and represent an important advance in embracing diabetes technology for inpatient diabetes care. This is a change welcomed by both health care providers and patients (1). Real-world inpatient CGM accuracy studies encompassing a variety of CGM device models are important, and more inpatient studies of CGM accuracy are required imminently given the rapidly increasing uptake of CGM in people with T1D.

Funding. R.W. is supported by an Australian Commonwealth Government RTP Scholarship, ACADI PhD grant, Fred Knight Research Scholarship, Rowden White Scholarship, and Gordon P. Castles Scholarship.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Handling Editors. The journal editor responsible for overseeing the review of the manuscript was Steven E. Kahn.

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