Description Usage Arguments Details Value Examples
A vectorised function to calculate the pre-procurement component of the SOFT score used to predict patient survival after liver transplantation. The function needs the MELD score as one of its inputs - this is available using the transplantr::meld() function. The units for albumin are g/l but this is changed to g/dl if the optional Units parameter is set to "US"
1 2 | p_soft(Age, BMI, PrevTx, AbdoSurg, Albumin, Dx, ICU, Admitted, MELD,
LifeSupport, Encephalopathy, PVThrombosis, Ascites, Units = "SI")
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Age |
numeric vector of patient ages in years |
BMI |
numeric vector of patient BMI in kg/m2 |
PrevTx |
numeric vector of number of previous transplants |
AbdoSurg |
numeric vector of whether previous abdominal surgery (1 = "yes", 0 = "no") |
Albumin |
numeric vector of serum albumin in g/l |
Dx |
numeric vector of whether on dialysis before transplant (1 = "yes", 0 = "no") |
ICU |
numeric vector of whether patients in intensive care unit before transplant (1 = "yes", 0 = "no") |
Admitted |
numeric vector of whether admitted to hospital pre-transplant (1 = "yes", 0 = "no") |
MELD |
numeric vector of MELD scores |
LifeSupport |
numeric vector of whether on life support pre-transplant (1 = "yes", 0 = "no") |
Encephalopathy |
numeric vector of whether encephalopathy present (1 = "yes", 0 = "no") |
PVThrombosis |
numeric vector of whether portal vein thrombosis (1 = "yes", 0 = "no") |
Ascites |
numeric vector of whether ascites pre-transplant (1 = "yes", 0 = "no") |
Units |
optional scalar for albumin units (one of "SI" for g/l, "US" for g/dl) |
Reference: Rana A, Hardy MA, Halazun KJ, et al. Survival Outcomes Following Liver Transplantation (SOFT) Score: A Novel Method to Predict Patient Survival Following Liver Transplantation. American Journal of Transplantation 2008; 8:2537-2546.
numeric vector of P-SOFT scores
1 2 3 | p_soft(Age = 65, BMI = 36, PrevTx = 2, AbdoSurg = 1, Albumin = 29, Dx = 0,
ICU = 0, Admitted = 1, MELD = 32, LifeSupport = 0, Encephalopathy = 1,
PVThrombosis = 1, Ascites = 1) # 37
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