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Aim: The transition to the ICD-10-CM coding system has reduced the utility of hypoglycaemia algorithms based on ICD-9-CM diagnosis codes in real-world studies of antidiabetic drugs. We mapped a validated ICD-9-CM hypoglycaemia algorithm to ICD-10-CM codes to create an ICD-10-CM hypoglycaemia algorithm and assessed its performance in identifying severe hypoglycaemia.
Materials And Methods: We assembled a cohort of Medicare patients with DM and linked electronic health record (EHR) data to the University of North Carolina Health System and identified candidate severe hypoglycaemia events from their Medicare claims using the ICD-10-CM hypoglycaemia algorithm. We confirmed severe hypoglycaemia by EHR review and computed a positive predictive value (PPV) of the algorithm to assess its performance. We refined the algorithm by removing poor performing codes (PPV ≤0.5) and computed a Cohen's statistic to evaluate the agreement of the EHR reviews.
Results: The algorithm identified 642 candidate severe hypoglycaemia events, and we confirmed 455 as true severe hypoglycaemia events, PPV of 0.709 (95% confidence interval: 0.672, 0.744). When we refined the algorithm, the PPV increased to 0.893 (0.862, 0.918) and missed <2.42% (<11) true severe hypoglycaemia events. Agreement between reviewers was high, = 0.93 (0.89, 0.97).
Conclusions: We translated an ICD-9-CM hypoglycaemia algorithm to an ICD-10-CM version and found its performance was modest. The performance of the algorithm improved by removing poor performing codes at the trade-off of missing very few severe hypoglycaemia events. The algorithm has the potential to be used to identify severe hypoglycaemia in real-world studies of antidiabetic drugs.
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http://dx.doi.org/10.1111/dom.15428 | DOI Listing |
Diabetologia
September 2025
Centre Universitaire de Diabétologie et de ses Complications, AP-HP, Hôpital Lariboisière, Paris, France.
Aims/hypothesis: Severe hypoglycaemia events (SHE) remain frequent in people with type 1 diabetes despite advanced diabetes technologies. We examined whether time below range (TBR) 3.9 mmol/l (70 mg/dl; TBR70) or 3.
View Article and Find Full Text PDFG Ital Nefrol
August 2025
Infermiere Professionale SSD Nefrologia e Dialisi P.O. Soverato, ASP CZ.
Management of diabetes mellitus in hemodialysis is highly complex due to increased glycemic variability and hypoglycemic risk. The use of technologies applied to diabetes has been shown to improve glycemic control, however data in dialysis patients are limited. To describe the efficacy and safety of the minimed 780G AHCL system in a stable hemodialysis patient and during hospitalization in the Intensive Care Unit (ICU).
View Article and Find Full Text PDFDiabetes Obes Metab
September 2025
Centre for Pancreatic Diseases and Mech-Sense, Department of Gastroenterology and Hepatology, Aalborg University Hospital, Aalborg, Denmark.
Aims: Population-based studies have consistently shown that individuals with diabetes secondary to chronic pancreatitis (pancreatic diabetes) have a high risk of hypoglycaemia. We aimed to investigate whether this risk has declined over recent years following the introduction of modern glucose-lowering medications.
Materials And Methods: In this Danish nationwide population-based cohort study, we included all adults with new-onset diabetes between 1998 and 2022 and classified them as having pancreatic diabetes, type 1, or type 2 diabetes.
Cureus
August 2025
Internal Medicine, Dr. Samir Abbas Hospital, Jeddah, SAU.
Type 2 diabetes (T2D) requires rigorous glycemic control to prevent complications, but traditional self-monitoring of blood glucose (SMBG) offers limited insights. Real-time continuous glucose monitoring (RT-CGM) provides dynamic data to optimize management, although its efficacy in T2D remains debated. This systematic review synthesizes evidence from randomized controlled trials (RCTs) to evaluate RT-CGM's impact on glycemic outcomes in adults with T2D.
View Article and Find Full Text PDFJ Diabetes Metab Disord
December 2025
Evidence Based Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Non-islet cell tumor hypoglycemia (NICTH) is a rare paraneoplastic syndrome resulting from excessive secretion of pro-insulin-like growth factor 2 (proIGF-2). This leads to hypoinsulinemic hypoglycemia and, in some cases, acromegaly. We report the case of a 52-year-old woman with NICTH syndrome who had decreased levels of insulin-like growth factor 1 (IGF1), insulin, C-peptide, and growth hormone (GH).
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