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Kristian Hveem

Publications and source records attributed to Kristian Hveem.

2 recordsLinked to original sources

Ketoacidosis with SGLT2 inhibitors in routine clinical practice of type 2 diabetes: Scandinavian cohort and nested case-control study.

BACKGROUND: SGLT2 inhibitors increase the risk of ketoacidosis, but data from routine clinical practice are scarce. We used nationwide registers with the aim of assessing the incidence, risk factors, and prognosis of ketoacidosis during SGLT2 inhibitor treatment in patients with type 2 diabetes. METHODS: In this cohort and nested case-control study we used data from three Scandinavian countries. In a cohort of SGLT2 inhibitor-treatment episodes among patients with type 2 diabetes aged at least 18 years in Sweden, Denmark, and Norway, we estimated ketoacidosis incidence. Using a nested case-control design (matched on age, sex, region of birth, calendar time, and time since treatment initiation), we assessed risk factors and precipitating or co-occurring events. Changes in diabetes medications were evaluated. FINDINGS: The study period was Jan 1, 2013, to Dec 31, 2021, in Denmark and Sweden, and Jan 1, 2013, to Dec 31, 2022, in Norway. We included 322&#x2008;597 treatment episodes among 282&#x2008;282 patients with type 2 diabetes (mean age 63 years, 116&#x2008;521 [36&#xb7;1%] of 322&#x2008;597 women). During a median (IQR) follow-up of 1&#xb7;3 (0&#xb7;7-2&#xb7;8) years, 1452 ketoacidosis events occurred (incidence 2&#xb7;43 per 1000 person-years). Although highest shortly after initiation, risk persisted throughout follow-up. Strong risk factors included high HbA1c (&#x2265;83 vs &#x2264;52 mmol/mol: odds ratio [OR] 15&#xb7;37 [95% CI 11&#xb7;50-20&#xb7;53]), malnutrition (OR 10&#xb7;54 [7&#xb7;32-15&#xb7;18]), previous ketoacidosis (OR 10&#xb7;40 [7&#xb7;09-15&#xb7;24]), low BMI (<20 kg/m2vs 20 to <25 kg/m2: OR 9&#xb7;98 [5&#xb7;68-17&#xb7;53]), and recent hypoglycaemia (OR 5&#xb7;22 [2&#xb7;60-10&#xb7;49]). Infection was the most common precipitating or co-occurring event (454 [31&#xb7;8%] of 1428 vs 862 [6&#xb7;1%] of 14&#x2008;233 for ketoacidosis cases vs controls; OR 7&#xb7;60 [6&#xb7;62-8&#xb7;71]). The strongest associations were observed for alcohol intoxication, acute renal events, acute abdomen, stroke, and major surgery, although associations for some transient exposures, particularly milder conditions, might have been overestimated because of under-registration among controls. Exploratory analyses suggested that the observed associations were largely general to patients with type 2 diabetes rather than specific to SGLT2 inhibitor use. At 1 year after ketoacidosis, 211 (25&#xb7;1%) of 842 remained on SGLT2 inhibitors and insulin use increased from 269 (31&#xb7;9%) of 842 to 615 (73&#xb7;0%) of 842. INTERPRETATION: Ketoacidosis risk with SGLT2 inhibitors varies greatly by patient characteristics and is not confined to early in treatment. Risk should be assessed throughout treatment, and patients should be instructed to pause treatment during acute illness and stress. FUNDING: Region Stockholm, Swedish Society of Medicine, Karolinska Institutet.

Journal Article

A narrative review of what cohorts have taught us and how they have laid the foundation for much of our understanding of type 2 diabetes.

This narrative review provides a historical perspective on how observational research on type 2 diabetes has been developed and consolidated over the last 50 years and how well-designed cohort studies will provide us with knowledge for research and practice in the future and aid guideline development. We have included data from a large number of cohorts from every continent that have been used to study the development and/or progression of type 2 diabetes, including cohorts that are general population-based, disease-based, intervention-based and registry-based. We have structured the results from the past 50 years based on the following themes: diagnosis and screening, complications, risk factors and pathophysiology. We also discuss the strengths and weaknesses of observational research when compared with other research designs. Finally, we discuss the emerging and future directions for type 2 diabetes research using cohorts, which include novel developments, such as artificial intelligence, precision health and the exposome. We conclude that cohort research has significantly advanced our understanding of type 2 diabetes and aided guideline development, and complements experimental work, such as human randomised controlled trials and animal studies. Both approaches are essential and complementary in our pursuit to provide a more comprehensive understanding of the development and progression of type 2 diabetes, and to change dogma, practice and policies for better outcomes.

Humans