What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Endocrinology
- Diabetes mellitus
Hans Lithell focuses on Internal medicine, Endocrinology, Insulin, Insulin resistance and Diabetes mellitus.
His work carried out in the field of Internal medicine brings together such families of science as Surgery and Cardiology.
His Insulin research includes themes of Obesity and Lipoprotein lipase.
His studies in Insulin resistance integrate themes in fields like Adipose tissue, Lipid profile, Very low-density lipoprotein and Metabolic syndrome.
His Diabetes mellitus research includes elements of Hemodynamics and Atenolol.
His work in the fields of Blood pressure, such as Candesartan, Angiotensin II and Complications of hypertension, intersects with other areas such as Cognition.
His most cited work include:
- Hypertension and Associated Metabolic Abnormalities — The Role of Insulin Resistance and the Sympathoadrenal System (1276 citations)
- Glucose tolerance and mortality: comparison of WHO and American Diabetes Association diagnostic criteria (1270 citations)
- The Study on Cognition and Prognosis in the Elderly (SCOPE): principal results of a randomized double-blind intervention trial. (1226 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Internal medicine, Endocrinology, Insulin, Blood pressure and Insulin resistance.
Hans Lithell has researched Internal medicine in several fields, including Diabetes mellitus and Cardiology.
The concepts of his Diabetes mellitus study are interwoven with issues in Captopril and Pharmacology.
His Insulin study frequently involves adjacent topics like Carbohydrate metabolism.
His research investigates the link between Blood pressure and topics such as Body mass index that cross with problems in Obesity.
The various areas that Hans Lithell examines in his Risk factor study include Prospective cohort study, Surgery, Myocardial infarction and Cohort.
He most often published in these fields:
- Internal medicine (83.88%)
- Endocrinology (68.06%)
- Insulin (29.25%)
What were the highlights of his more recent work (between 2000-2016)?
- Internal medicine (83.88%)
- Endocrinology (68.06%)
- Blood pressure (25.67%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Internal medicine, Endocrinology, Blood pressure, Insulin and Cardiology.
His studies deal with areas such as Diabetes mellitus and Surgery as well as Internal medicine.
His work in Insulin resistance, Lipoprotein, Vasodilation, Type 2 diabetes and Hyperinsulinemia is related to Endocrinology.
His Blood pressure research is multidisciplinary, relying on both Ambulatory and Anesthesia.
Insulin is often connected to Heart rate in his work.
Hans Lithell has included themes like Predictive value of tests, Left ventricular hypertrophy and Diastolic function in his Cardiology study.
Between 2000 and 2016, his most popular works were:
- The Study on Cognition and Prognosis in the Elderly (SCOPE): principal results of a randomized double-blind intervention trial. (1226 citations)
- Clinical value of the metabolic syndrome for long term prediction of total and cardiovascular mortality: prospective, population based cohort study (317 citations)
- Isolated Ambulatory Hypertension Predicts Cardiovascular Morbidity in Elderly Men (300 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Endocrinology
- Diabetes mellitus
His primary areas of study are Internal medicine, Cohort study, Risk factor, Endocrinology and Blood pressure.
His Internal medicine study combines topics from a wide range of disciplines, such as Surgery and Cardiology.
His Cohort study study combines topics in areas such as Rate ratio, Confidence interval and Cohort.
His Risk factor research incorporates elements of Body mass index and Cancer.
The Endocrinology study combines topics in areas such as Odds ratio and Physiology.
His Insulin resistance research is multidisciplinary, incorporating elements of Offspring and Polymorphism.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
