uk | R Documentation |
Ordering of waitlisted candidates for a given donor and according to UK transplant algorithm.
uk( DRI = "D1", dA = c("1", "2"), dB = c("15", "44"), dDR = c("1", "4"), dABO = "O", donor.age = 65, data = candidates.uk, D1R1 = 1000, D1R2 = 700, D1R3 = 350, D1R4 = 0, D2R1 = 700, D2R2 = 1000, D2R3 = 500, D2R4 = 350, D3R1 = 350, D3R2 = 500, D3R3 = 1000, D3R4 = 700, D4R1 = 0, D4R2 = 350, D4R3 = 700, D4R4 = 1000, ptsDial = 1, a1 = 2300, a2 = 1500, b1 = 1200, b2 = 750, b3 = 400, m = 40, nn = 4.5, o = 4.7, mm1 = -100, mm23 = -150, mm46 = -250, pts = -1000, df.abs = cabs, n = 2, check.validity = TRUE )
DRI |
Donor RisK Index group (env$valid.dris) |
dA |
donor's HLA-A typing. |
dB |
donor's HLA-B typing. |
dDR |
donor's HLA-DR typing. |
dABO |
A character value with ABO blood group ( |
donor.age |
A numeric value with donor's age. |
data |
A data frame containing demographics and medical information for a group of waitlisted transplant for UK transplant. |
D1R1 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D1R2 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D1R3 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D1R4 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D2R1 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D2R2 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D2R3 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D2R4 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D3R1 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D3R2 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D3R3 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D3R4 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D4R1 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D4R2 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D4R3 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
D4R4 |
A numeric value (env$dirj.minimum - env$dirj.maximum) for the combination of indexes DiRj |
ptsDial |
A numeric value for the points corresponding to each month on dialysis |
a1 |
A numeric value for HLA match and age combined formula: b1*cos(age / env$adulthood.age)+a1 |
a2 |
A numeric value for HLA match and age combined formula: b2*cos(age / env$adulthood.age)+a2 |
b1 |
A numeric value for HLA match and age combined formula: b1*cos(age / env$adulthood.age)+a1 |
b2 |
A numeric value for HLA match and age combined formula: b2*cos(age / env$adulthood.age)+a2 |
b3 |
A numeric value for HLA match and age combined formula: b3*sin(age / 50) |
m |
A numeric value for matchability formula: m * (1 + (MS / nn) ^ o) |
nn |
A numeric value for matchability formula: m * (1 + (MS / nn) ^ o) |
o |
A numeric value for matchability formula: m * (1 + (MS / nn) ^ o) |
mm1 |
A numeric value to penalize 1 mm |
mm23 |
A numeric value to penalize 2-3 mm |
mm46 |
A numeric value to penalize 4-6 mm |
pts |
A negative value with penalization for B candidates |
df.abs |
A data frame with candidates' antibodies. |
n |
A positive integer to slice the first candidates. |
check.validity |
Logical to decide whether to validate input. |
uk(DRI = 'D1', dA = c("1","2"), dB = c("15","44"), dDR = c("1","4"), dABO = "O", donor.age = 65, data = candidates.uk, D1R1 = 1000, D1R2 = 700, D1R3 = 350, D1R4 = 0, D2R1 = 700, D2R2 = 1000, D2R3 = 500, D2R4 = 350, D3R1 = 350, D3R2 = 500, D3R3 = 1000, D3R4 = 700, D4R1 = 0, D4R2 = 350, D4R3 = 700, D4R4 = 1000, ptsDial = 1, a1 = 2300, a2 = 1500, b1 = 1200, b2 = 750, b3 = 400, m = 40, nn = 4.5, o = 4.7, mm1 = -100, mm23 = -150, mm46 = -250, pts = -1000, df.abs = cabs, n = 2, check.validity = TRUE)
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