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It has been argued that persons with severe mental illness (SMI) receive poorer treatment for somatic comorbidities. This study assesses the treatment rates of glucose-lowering and cardiovascular medications among persons with incident type 2 diabetes (T2D) and SMI compared to persons with T2D without SMI. We identified persons ≥30 years old with incident diabetes (HbA1c ≥ 48 mmol/mol and/or glucose ≥ 11.0 mmol/L) from 2001 through 2015 in the Copenhagen Primary Care Laboratory (CopLab) Database. The SMI group included persons with psychotic, affective, or personality disorders within five years preceding the T2D diagnosis. Using a Poisson regression model, we calculated the adjusted rate ratios (aRR) for the redemption of various glucose-lowering and cardiovascular medications up to ten years after T2D diagnosis. We identified 1,316 persons with T2D and SMI and 41,538 persons with T2D but no SMI. Despite similar glycemic control at diagnosis, persons with SMI redeemed a glucose-lowering medication more often than persons without SMI in the period 0.5–2 years after the T2D diagnosis; for example, the aRR was 1.05 (95% CI 1.00–1.11) in the period 1.5–2 years after the T2D diagnosis. This difference was mainly driven by metformin. In contrast, persons with SMI were less often treated with cardiovascular medications during the first 3 years after T2D diagnosis, e.g., in the period 1.5–2 years after T2D diagnosis, the aRR was 0.96 (95% CI 0.92–0.99). For people with SMI in addition to T2D, metformin is more likely to be used in the initial years after T2D diagnosis, while our results suggest potential room for improvement regarding the use of cardiovascular medications. [ABSTRACT FROM AUTHOR]

Current metrics for estimating a scientist’s academic performance treat the author’s publications as if these were solely attributable to the author. However, this approach ignores the substantive contributions of co-authors, leading to misjudgments about the individual’s own scientific merits and consequently to misallocation of funding resources and academic positions. This problem is becoming the more urgent in the biomedical field where the number of collaborations is growing rapidly, making it increasingly harder to support the best scientists. Therefore, here we introduce a simple harmonic weighing algorithm for correcting citations and citation-based metrics such as the h-index for co-authorships. This weighing algorithm can account for both the nvumber of co-authors and the sequence of authors on a paper. We then derive a measure called the ‘profit (p)-index’, which estimates the contribution of co-authors to the work of a given author. By using samples of researchers from a renowned Dutch University hospital, Spinoza Prize laureates (the most prestigious Dutch science award), and Nobel Prize laureates in Physiology or Medicine, we show that the contribution of co-authors to the work of a particular author is generally substantial (i.e., about 80%) and that researchers’ relative rankings change materially when adjusted for the contributions of co-authors. Interestingly, although the top University hospital researchers had the highest h-indices, this appeared to be due to their significantly higher p-indices. Importantly, the ranking completely reversed when using the profit adjusted h-indices, with the Nobel laureates having the highest, the Spinoza Prize laureates having an intermediate, and the top University hospital researchers having the lowest profit adjusted h-indices, respectively, suggesting that exceptional researchers are characterized by a relatively high degree of scientific independency/originality. The concepts and methods introduced here may thus provide a more fair impression of a scientist’s autonomous academic performance. [ABSTRACT FROM AUTHOR]

Current metrics for estimating a scientist's academic performance treat the author's publications as if these were solely attributable to the author. However, this approach ignores the substantive contributions of co-authors, leading to misjudgments about the individual's own scientific merits and consequently to misallocation of funding resources and academic positions. This problem is becoming the more urgent in the biomedical field where the number of collaborations is growing rapidly, making it increasingly harder to support the best scientists. Therefore, here we introduce a simple harmonic weighing algorithm for correcting citations and citation-based metrics such as the h-index for co-authorships. This weighing algorithm can account for both the nvumber of co-authors and the sequence of authors on a paper. We then derive a measure called the 'profit (p)-index', which estimates the contribution of co-authors to the work of a given author. By using samples of researchers from a renowned Dutch University hospital, Spinoza Prize laureates (the most prestigious Dutch science award), and Nobel Prize laureates in Physiology or Medicine, we show that the contribution of co-authors to the work of a particular author is generally substantial (i.e., about 80%) and that researchers' relative rankings change materially when adjusted for the contributions of co-authors. Interestingly, although the top University hospital researchers had the highest h-indices, this appeared to be due to their significantly higher p-indices. Importantly, the ranking completely reversed when using the profit adjusted h-indices, with the Nobel laureates having the highest, the Spinoza Prize laureates having an intermediate, and the top University hospital researchers having the lowest profit adjusted h-indices, respectively, suggesting that exceptional researchers are characterized by a relatively high degree of scientific independency/originality. The concepts and methods introduced here may thus provide a more fair impression of a scientist's autonomous academic performance.