Publications by authors named "P E Wandell"

Background: Middle Eastern (ME) immigrants to Europe have a heavy burden of metabolic disorders including a higher prevalence of insulin resistance, T2D and obesity as compared to native-born Europeans. Vitamin D insufficiency and deficiency are prevalent conditions in people originating from the ME.

Aims: To study the differences in the levels of 25(OH)D and parathyroid hormone (PTH) across ME and European ethnicity, and the effect of 25(OH)D and PTH on insulin action and secretion.

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Background: Higher circulating levels of tumor necrosis factor (TNF) alpha receptors 1 (TNFR1) and 2 (TNFR2) are associated with increased long-term mortality and impaired kidney function.

Aim: To study associations between levels of TNFR1 and TNFR2 and all-cause mortality as well as estimated glomerular filtration rate (eGFR) decline.

Population And Methods: Patients with chronic kidney disease (CKD) stages 3-5 in the Salford Kidney Study were included.

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In this study we examined the effect of simultaneously elevated levels of parathyroid hormone (PTH) (≥ 65 ng/mL) and high levels of insulin-like growth factor-binding protein 1 (IGFBP-1) on the 10-year risk of all-cause mortality and hip fractures. Blood tests for levels of PTH and IGFBP-1 was collected at baseline in 338 community-dwelling women in Stockholm aged between 69 and 79 years. Data on hip fractures and all-cause mortality over the next 10 years were retrieved from healthcare registers.

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The aim was to study if nurse-managed hypertension care was associated with differences in pharmacotherapy, lifestyle counseling, and prevalence of comorbid cardiometabolic diseases among patients receiving care at primary health care centers. To assess the extent of nurses' involvement in the hypertension care, a questionnaire was distributed to all primary health care centers in Region Stockholm. Age-adjusted logistic regression models were used to analyze the results, odds ratios with 99% confidence intervals.

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Aims: We aimed to create a predictive model utilizing machine learning (ML) to identify new cases of congestive heart failure (CHF) in individuals with diabetes in primary health care (PHC) through the analysis of diagnostic data.

Methods: We used a sex- and age-matched case-control design. Cases of new CHF were identified across all outpatient care settings 2015-2022 (n = 9098).

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