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FibroTest has the same prognostic value as a liver biopsy. FibroSure uses quantitative results of five serum biochemical markers, α2-macroglobulin, haptoglobin, apolipoprotein A1, bilirubin, gamma glutamyl transpeptidase (GGT), with a patient’s age and gender to generate a measure of fibrosis and necroinflammatory activity in the liver.
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The site began in 1998 as a pen and paper questionnaire called the Harvard Cancer Risk Index. [2] In January 2000, The Harvard Cancer Risk Index developed into an online assessment and was renamed Your Cancer Risk, and offered assessments for four cancers: breast, colon, lung, and prostate. Six months later, eight additional cancers were added. [3]
Risk is the lack of certainty about the outcome of making a particular choice. Statistically, the level of downside risk can be calculated as the product of the probability that harm occurs (e.g., that an accident happens) multiplied by the severity of that harm (i.e., the average amount of harm or more conservatively the maximum credible amount of harm).
IgG4-related disease (IgG4-RD), formerly known as IgG4-related systemic disease, is a chronic inflammatory condition characterized by tissue infiltration with lymphocytes and IgG4-secreting plasma cells, various degrees of fibrosis (scarring) and a usually prompt response to oral steroids.
The once-daily triple combination treatment, called vanza triple, met the primary goals of the study's two 52-week trials and was non-inferior for lung function to Trikafta, the company's top ...
The corpulence index yields valid results even for very short and very tall persons, [7] which is a problem with BMI — for example, an ideal body weight for a person 152.4 cm tall (48 kg) will render BMI of 20.7 and CI of 13.6, while for a person 200 cm tall (99 kg), the BMI will be 24.8, very close to the "overweight" threshold of 25, while ...
Continuous Individualized Risk Index (CIRI) (initialism pronounced /ˈsɪri/) is to a set of probabilistic risk models [1] utilizing Bayesian statistics for integrating diverse cancer biomarkers over time to produce a unified prediction of outcome risk, as originally described by Kurtz, Esfahani, et al. (2019) [2] [3] [4] from Ash Alizadeh's laboratory at Stanford.