Type:	Package
Title:	Audit and Research Functions for Transplantation
Version:	0.2.0
Description:	A set of vectorised functions to calculate medical equations used in transplantation, focused mainly on transplantation of abdominal organs. These functions include donor and recipient risk indices as used by NHS Blood & Transplant, OPTN/UNOS and Eurotransplant, tools for quantifying HLA mismatches, functions for calculating estimated glomerular filtration rate (eGFR), a function to calculate the APRI (AST to platelet ratio) score used in initial screening of suitability to receive a transplant from a hepatitis C seropositive donor and some biochemical unit converter functions. All functions are designed to work with either US or international units. References for the equations are provided in the vignettes and function documentation.
URL:	https://transplantr.txtools.net, https://github.com/johnasher/transplantr
BugReports:	https://github.com/johnasher/transplantr/issues
Depends:	R (≥ 3.1.0)
Suggests:	dplyr, stringr, knitr, rmarkdown, testthat, spelling
License:	GPL-3
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	6.1.1
VignetteBuilder:	knitr
Language:	en-GB
NeedsCompilation:	no
Packaged:	2020-02-28 00:19:28 UTC; john
Author:	John Asher [aut, cre]
Maintainer:	John Asher <john.asher@outlook.com>
Repository:	CRAN
Date/Publication:	2020-02-28 16:50:03 UTC

AST to Platelet Ratio (APRI)

Description

A vectorised function to calculate the APRI score, a predictor of hepatic fibrosis.

Usage

apri(ast, plt, ast_uln = 40)

Arguments

Details

Reference: Lin ZH, Xin YN, Dong QJ, et al. Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: an updated meta-analysis. Hepatology 2011; 53:726-736.

Value

numeric vector of APRI scores

Examples

apri(ast = 38, plt = 150, ast_uln = 40)

# if the lab upper limit of normal is 40, ast_uln can be omitted
apri(ast = 160, plt = 75)

BAR (Balance of Risk) score in liver transplantation

Description

A vectorised function to calculate the BAR score to predict patient survival after liver transplantation using a composite of donor and recipient factors.

Usage

bar_score(Age, MELD, ReTx, LifeSupport, CIT, DonorAge)

Arguments

Details

Reference: Dutkowski P, Oberkofler CE, Slankamenac K, et al. Are There Better Guidelines for Allocation in Liver Transplantation? A Novel Score Targeting Justice and Utility in the Model for End-Stage Liver Disease Era. Annals of Surgery 2011; 254:745-753.

Value

numeric vector of BAR scores

Examples

bar_score(Age = 63, MELD = 27, ReTx = 0, LifeSupport = 0, CIT = 9.5, DonorAge = 67)

Bilirubin unit converter (mg/dl -> µmol/l)

Description

A vectorised function to convert serum bilirubin levels from mg/dl to µmol/l

Usage

bilirubin_to_SI(bili)

Arguments

Value

numeric vector of bilirubin levels in µmol/l

Examples

bilirubin_to_SI(bili = 3.1)

Bilirubin unit converter (µmol/l -> mg/dl)

Description

A vectorised function to convert serum bilirubin levels from µmol/l to mg/dl

Usage

bilirubin_to_US(bili)

Arguments

Value

numeric vector of bilirubin levels in mg/dl

Examples

bilirubin_to_US(bili = 54)

Convert BUN to urea

Description

A vectorised function to convert blood urea nitrogen (BUN) to urea. The default unit for urea is mmol/l but this can be changed to mg/dl by setting the optional units parameter to "US"

Usage

bun_to_urea(BUN, units = "SI")

Arguments

Value

numeric vector of urea levels

Examples

bun_to_urea(8.0)

Convert CHI number to date of birth

Description

A vectorised function to convert a Scottish CHI number to date of birth in POSIXct date format. Note that this function does not always work as not all CHI numbers correspond accurately to date of birth, and any person born before 1920 will appear to be 100 years younger unless the optional cent parameter set to TRUE. Childen born in or after 2020 will appear 100 years older unless the optional paed parameter is set to TRUE. This function requires the stringr package.

Usage

chi2dob(chi, paed = FALSE, cent = FALSE)

Arguments

Details

The paed and cent parameters can either be provided as vectors for each case, for example in a series where there are patients with dates of birth in both the 1910s and 2010s, or alternatively can be set as a single TRUE or FALSE for the whole series.

Value

a vector of POSIXct dates

Examples

# as a single numeric
chi2dob(1503541234)

# as a single character string, for a patient born in 1919
chi2dob("1108191234", cent = TRUE)

# as a mixed vector of adults and children, including one born in 1919
chi2dob(chi = c("1503541234", "1108191234", "0510141234"),
        cent = c(FALSE, TRUE, FALSE))

eGFR by CKD-EPI equation

Description

A vectorised function to calculate estimated glomerular filtration rate using the CKD-EPI equation. By default the equation accepts serum creatinine in µmol/l but can be changed to mg/dl by setting the units parameter to "US". To allow for serial measurements over time, such as for transplant follow-up data, there is an optional offset = n parameter which increases the age value used in the equation by n years.

Usage

ckd_epi(creat, age, sex, ethnicity, units = "SI", offset = 0)

Arguments

Details

Reference: Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150(9):604-612.

Value

a numeric vector of eGFR values

Examples

ckd_epi(creat = 120, age = 45.2, sex = "M", ethnicity = "non-black")
ckd_epi(creat = 1.5, age = 64.3, sex = "F", ethnicity = "black", units = "US")

eGFR by CKD-EPI equation (US units)

Description

A wrapper function for the ckd_epi() vectorised function to calculate estimated glomerular filtration rate using the CKD-EPI equation, using serum creatinine in mg/dl. To allow for serial measurements over time, such as for transplant follow-up data, there is an optional offset = n parameter which increases the age value used in the equation by n years.

Usage

ckd_epi_US(creat, age, sex, ethnicity, offset = 0)

Arguments

Details

Reference: Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150(9):604-612.

Value

a numeric vector of eGFR values

Examples

ckd_epi_US(creat = 1.5, age = 64.3, sex = "F", ethnicity = "black")

Creatinine clearance by Cockcroft-Gault equation

Description

A vectorised function to estimate creatinine clearance using the Cockcroft-Gault equation. By default this uses serum creatinine in µmol/l but can be changed to mg/dl by setting the units parameter to "US"

Usage

cockcroft(creat, age, sex, weight, units = "SI")

Arguments

Details

Reference: Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16(1):31-41

Value

numeric vector of creatinine clearances in ml/min

Examples

# calculate creatinine clearance using creatinine in µmol/l
cockcroft(creat = 88.4, age = 25, sex = "F", weight = 60)

# calculate using creatinine in mg/dl
cockcroft(creat = 1, age = 25, sex = "F", weight = 60, units = "US")

Creatinine clearance by Cockcroft-Gault equation (US units)

Description

A wrapper function for cockcroft(), a vectorised function to estimate creatinine clearance using the Cockcroft-Gault equation, but using creatinine in mg/dl

Usage

cockcroft_US(creat, age, sex, weight)

Arguments

Details

Reference: Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16(1):31-41

Value

numeric vector of creatinine clearances in ml/min

Examples

cockcroft_US(creat = 1, age = 25, sex = "F", weight = 60)

Creatinine unit converter (mg/dl -> µmol/l)

Description

A vectorised function to convert serum creatinine levels from mg/dl to µmol/l

Usage

creatinine_to_SI(creat)

Arguments

Value

numeric vector of creatinine levels in µmol/l

Examples

creatinine_to_SI(creat = 2.0)

Creatinine unit converter (µmol/l -> mg/dl)

Description

A vectorised function to convert serum creatinine levels from µmol/l to mg/dl

Usage

creatinine_to_US(creat)

Arguments

Value

numeric vector of creatinine levels in mg/dl

Examples

creatinine_to_US(creat = 176)

Estimated Post-Transplant Survival Score (EPTS)

Description

A vectorised function to calculate EPTS scores as percentiles for norm-related prediction of patient survival after adult renal transplants. This function generates the EPTN scores as percentiles using the most recent lookup table on the OPTN website published in March 2019 and using SRTR data from 2018. The table can be found at https://optn.transplant.hrsa.gov/media/2973/epts_mapping_table_2018.pdf

Usage

epts(age, dm, prev_tx, dx)

Arguments

Details

This function requires the dplyr package to be installed. References: https://optn.transplant.hrsa.gov/resources/allocation-calculators/epts-calculator/ and https://optn.transplant.hrsa.gov/media/1511/guide_to_calculating_interpreting_epts.pdf

Value

numeric vector of EPTS scores as percentiles

Examples

epts(age = 23.5838467, dm = 0, prev_tx = 1, dx = 5.0814511)
epts(age = 52.8788501, dm = 0, prev_tx = 0, dx = 0)
epts(age = 22.5242984, dm = 1, prev_tx = 1, dx = 6.8747433)

EPTS lookup function

Description

A vectorised function to convert EPTS scores to percentiles for norm-related prediction of patient survival after adult renal transplants. This calculator uses the most recent lookup table published in March 2019 and using SRTR data from 2018 from the OPTN website at https://optn.transplant.hrsa.gov/media/2973/epts_mapping_table_2018.pdf

Usage

epts_lookup(raw)

Arguments

Details

This function requires the dplyr package to be installed.

References: https://optn.transplant.hrsa.gov/resources/allocation-calculators/epts-calculator/ and https://optn.transplant.hrsa.gov/media/1511/guide_to_calculating_interpreting_epts.pdf

Value

numeric vector of EPTS scores as percentiles

Examples

epts_lookup(1.54) # 21

Eurotransplant Donor Risk Index in Liver Transplantation (ET-DRI)

Description

A vectorised function to calculate the Eurotransplant Donor Risk Index for liver transplantation. The ET-DRI is a variant of the American DRI published by Feng et al but adapted to the European population. The American liver DRI is available using the transplantr::liver_dri() function.

Usage

et_dri(age, cod, dcd, split, share, cit, ggt, rescue)

Arguments

Details

Reference: Braat AE, Blok JJ, Putter H, et al. The Eurotransplant Donor Risk Index in Liver Transplantation: ET-DRI. American Journal of Transplantation 2012; 12:2789–2796.

Value

numeric vector of ET-DRI scores

Examples

et_dri(age = 39, cod = "trauma", dcd = 0, split = 0, share = "local",
    cit = 8, ggt = 50, rescue = 0) # 1.00

et_dri(age = 25, cod = "cva", dcd = 0, split = 0, share = "local",
    cit = 8, ggt = 50, rescue = 0) # 1.15

HLA mismatch level

Description

Vectorised function to calculate HLA mismatch level as used in UK national deceased donor kidney matching scheme.

Usage

hla_mm_level(a, b, dr)

Arguments

Details

Mismatches should be provided as numeric vectors of integers with values from 0 to 2 The HLA mismatch level is derived from UK kidney matching policies which can be found on the NHS Blood & Transplant ODT website at www.odt.nhs.uk

Value

numeric vector of HLA mismatch levels (1-4)

Examples

hla_mm_level(a = 0, b = 1, dr = 1)

HLA mismatch level from string

Description

Vectorised function to calculate HLA mismatch levels where the HLA A, B and DR mismatch is recorded as a string rather than as separate numeric values, e.g. "1:0:1" or "101". The function calculates the mismatch level as used in the UK national deceased donor kidney matching scheme. By default, the function assumes a single separator character is used between each of the three numbers in the mismatch; if not, set the sep parameter to FALSE. This function needs the stringr package to be installed.

Usage

hla_mm_level_str(mm, sep = TRUE)

Arguments

Details

The HLA mismatch level is derived from UK kidney matching policies which can be found on the NHS Blood & Transplant ODT website at www.odt.nhs.uk

Value

numeric vector of HLA mismatch levels

Examples

# using string of HLA mismatches with colons
hla_mm_level_str("1:1:0")

# using string of HLA mismatches without separator
hla_mm_level_str("211", sep = FALSE)

Ideal body weight

Description

A vectorised function to calculate adult ideal body weight based on height and sex. This function assumes ideal BMI of 21.5 for females and 23 for males.

Usage

ibw(height, sex)

Arguments

Value

numeric vector of ideal body weights in kg

Examples

ibw(height = 183, sex = "M")

US KDPI

Description

Vectorised function to calculate US KDPI percentile as published by OPTN/UNOS. Please note that this function uses creatinine measured in µmol/l by default, but can be changed to mg/dl if the optional units parameter is set to "US".

Usage

kdpi(age, height, weight, eth, htn, dm, cva, creat, hcv, dcd,
  scaling = 1, units = "SI")

Arguments

Details

The KDRI is calculated from KDRI normalised by a scaling factor based on the median KDRI in the previous year. For 2018, this was approximately 1.250609 as is published on the OPTN website. The scaling parameter in this function defaults to 1, so can be left out to calculate the KDPI without scaling.

This function requires the dplyr package to be installed.

Reference: Rao PS, Schaubel DE, Guidinger MK, et al. A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index. Transplantation 2009; 88:231-236.

Value

numeric vector of US KDRI values

Examples

# with creatinine in µmol/l (units = "SI" can be omitted)
kdpi(age = 40, height = 170, weight = 80, eth = "non-black", htn = 0, dm = 0,
    cva = 0, creat = 120, hcv = 0, dcd = 0, scaling = 1.250609, units = "SI")

# with creatinine in mg/dl
kdpi(age = 40, height = 170, weight = 80, eth = "non-black", htn = 0, dm = 0,
    cva = 0, creat = 1.4, hcv = 0, dcd = 0, scaling = 1.250609, units = "US")

US KDPI (US units)

Description

Wrapper function for the kdpi() vectorised function to calculate US KDPI percentile as published by OPTN/UNOS, using creatinine measured in mg/dl (please use the kdpi() function for µmol/l).

Usage

kdpi_US(age, height, weight, eth, htn, dm, cva, creat, hcv, dcd,
  scaling = 1)

Arguments

Details

The KDRI is calculated from KDRI normalised by a scaling factor based on the median KDRI in the previous year. For 2018, this was approximately 1.250609 as is published on the OPTN website. The scaling parameter in this function defaults to 1, so can be left out to calculate the KDPI without scaling.

This function requires the dplyr package to be installed.

Reference: Rao PS, Schaubel DE, Guidinger MK, et al. A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index. Transplantation 2009; 88:231-236.

Value

numeric vector of US KDRI values

Examples

# with creatinine in mg/dl
kdpi_US(age = 40, height = 170, weight = 80, eth = "non-black", htn = 0, dm = 0,
    cva = 0, creat = 1.4, hcv = 0, dcd = 0, scaling = 1.250609)

US KDPI lookup function

Description

A vectorised function to convert kdri KDRI scores to KDPI percentiles. If the OPTN scaling factor was not used when calculating the KDRI, it can be set here using the optional scaling parameter which uses a default value of 1 (for no scaling).

Usage

kdpi_lookup(kdri, scaling = 1)

Arguments

Details

This function requires the dplyr package to be installed.

Value

numeric vector of KDPI percentiles

Examples

# if scaling factor was used when calculating KDRI
kdpi_lookup(1.25)

# if scaling factor for 2018 needs to be applied
kdpi_lookup(1.25, scaling =  1.2506957544151)

Simulated dataset of donors to illustrate KDRI vignette.

Description

A simulated dataset of kidney donors to illustrate the KDRI vignette

Usage

kidney.donors

Format

A data frame with 4 rows and 7 variables:

Donor.Age

donor age in years

Donor.Height

donor height in cm

Donor.Hypertension

donor hypertension

Donor.Sex

donor sex

Donor.CMV

donor CMV status

Donor.GFR

donor GFR

Donor.Hospital_Stay

donor hospital stay in days

...

Simulated dataset to illustrate MELD calculator vignette.

Description

A simulated dataset of liver patient characteristics for the MELD vignette

Usage

liver.pts

Format

A data frame with 4 rows and 6 variables:

Patient.Age

patient age in years

Patient.INR

Patient INR

Patient.Bilirubin

Patient serum bilirubin in µmol/l

Patient.Creatinine

serum serum creatinine in µmol/l

Patient.Sodium

Patient serum sodium in mmol/l

Patient.Dialysed

Whether patient dialysed (1 = yes, 0 = no)

...

Liver Donor Risk Index (DRI)

Description

A vectorised function to calculate the Liver Donor Risk Index as published by Feng and others.

Usage

liver_dri(age, cod, eth, dcd, split, share, cit, height)

Arguments

Details

Reference: Feng S, Goodrich NP, Bragg-Gresham JL et al. Characteristics Associated with Liver Graft Failre: The Concept of a Donor Risk Index. American Journal of Transplantation 2006; 6:783-790.

Value

numeric vector of liver DRI values

Examples

liver_dri(age = 25, cod = "trauma", eth = "white", dcd = 0, split = 0,
    share = "local", cit = 8, height = 170) # 1.00

liver_dri(age = 64, cod = "cva", eth = "white", dcd = 0, split = 0,
    share = "local", cit = 14, height = 170) # 1.88

eGFR by abbreviated MDRD equation

Description

A vectorised function to calculate estimated glomerular filtration rate using the abbreviated (four variable) MDRD equation. By default the equation accepts serum creatinine in µmol/l but can be changed to mg/dl by setting the units parameter to "US". To allow for serial measurements over time, such as for transplant follow-up data, there is an optional offset = n parameter which increases the age value used in the equation by n years.

Usage

mdrd(creat, age, sex, ethnicity, units = "SI", offset = 0)

Arguments

Details

Reference: Levey AS, Greene T, Kusek JW, et al. A simplified equation to predict glomerular filtration rate from serum creatinine. J Am Soc Nephrol 2000; 11:A0828.

Value

a numeric vector of eGFR values

Examples

mdrd(creat = 120, age = 45.2, sex = "M", ethnicity = "non-black")
mdrd(creat = 1.5, age = 64.3, sex = "F", ethnicity = "black", units = "US")

eGFR by abbreviated MDRD equation (US units)

Description

A wrapper for the mdrd4v() vectorised function to calculate estimated glomerular filtration rate using the abbreviated (four variable) MDRD equation, but using serum creatinine in mg/dl. To allow for serial measurements over time, such as for transplant follow-up data, there is an optional offset = n parameter which increases the age value used in the equation by n years.

Usage

mdrd_US(creat, age, sex, ethnicity, offset = 0)

Arguments

Details

Reference: Levey AS, Greene T, Kusek JW, et al. A simplified equation to predict glomerular filtration rate from serum creatinine. J Am Soc Nephrol 2000; 11:A0828.

Value

a numeric vector of eGFR values

Examples

mdrd_US(creat = 1.5, age = 64.3, sex = "F", ethnicity = "black")

MELD score

Description

A vectorised function to calculate the MELD score using µmol/l for bilirubin and creatinine. The units can be changed to mg/dl by setting the optional units parameter to "US". If the patient is on CVVH or has been dialysed at least twice in the same week, the dialysis argument should be set to 1, which changes the creatinine level used in the formula to 4mg/dl (353µmol/l). Following UNOS guidelines, the values for INR as well bilirubin and creatinine (in mg/dl) are set to a minimum value of 1 if less than 1.0

Usage

meld(INR, bili, creat, dialysis, units = "SI")

Arguments

Details

Reference: Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict survival in patients with end-stage liver disease. Hepatology 2001; 33:464-470.

Value

MELD score

Examples

meld(INR = 2.0, bili = 54, creat = 170, dialysis = 0)
meld(INR = 2.0, bili = 3.1, creat = 1.9, dialysis = 0, units = "US")

MELD score (US units)

Description

A wrapper for the vectorised function meld() to calculate the MELD score, but using mg/dl for bilirubin and creatinine. If the patient is on CVVH or has been dialysed at least twice in the same week, the dialysis argument should be set to 1, which changes the creatinine level used in the formula to 4mg/dl. Following UNOS guidelines, the values for INR as well bilirubin and creatinine are set to a minimum value of 1 if less than 1.0

Usage

meld_US(INR, bili, creat, dialysis)

Arguments

Details

Reference: Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict survival in patients with end-stage liver disease. Hepatology 2001; 33:464-470.

Value

MELD score

Examples

meld_US(INR = 2.0, bili = 2.3, creat = 1.9, dialysis = 1)

MELD-Na score

Description

A vectorised function to calculate the MELD-Na score, a variant of the MELD score incorporating serum sodium levels. By default, bilirubin and creatinine are in µmol/l but this can be changed to mg/dl by setting the optional units parameter to "US".

Usage

meld_na(INR, bili, creat, Na, dialysis, units = "SI")

Arguments

Details

Reference: Biggins SW, Kim WR, Terrault NA, et al. Evidence-based incorporation of serum sodium concentration into MELD. Gastroenterology 2006; 130(6):1652-60.

Value

numeric vector of MELD-Na scores

Examples

meld_na(INR = 1.8, bili = 34, creat = 176, Na = 131, dialysis = 0)
meld_na(INR = 1.8, bili = 2, creat = 2, Na = 131, dialysis = 0, units = "US")

MELD-Na score (US units)

Description

A wrapper for meld_na(), a vectorised function to calculate the MELD-Na score, a variant of the MELD score incorporating serum sodium levels. In this wrapper function, bilirubin and creatinine are in mg/dl.

Usage

meld_na_US(INR, bili, creat, Na, dialysis)

Arguments

Details

Reference: Biggins SW, Kim WR, Terrault NA, et al. Evidence-based incorporation of serum sodium concentration into MELD. Gastroenterology 2006; 130(6):1652-60.

Value

numeric vector of MELD-Na scores

Examples

meld_na_US(INR = 1.8, bili = 2, creat = 2, Na = 131, dialysis = 0)

Simulated dataset to illustrate mismatches for HLA vignette.

Description

A simulated dataset of HLA mismatches

Usage

mismatches

Format

A data frame with 4 rows and 5 variables:

HLA.A.MM

HLA A mismatch

HLA.B.MM

HLA B mismatch

HLA.DR.MM

HLA DR mismatch

HLA.MM

HLA mismatch as string

HLA.MM.s

HLA mismatch as string with separators

...

eGFR using Nankivell formula

Description

A vectorised function to calculate eGFR using the Nankivell formula. By default the equation accepts serum creatinine in µmol/l but can be changed to mg/dl by setting the units parameter to "US". The Urea parameter is serum urea in mmol/l, but if the units parameter is set to "US", Blood Urea Nitrogen (BUN) in mg/dl is used instead. It has not been possible to run automated tests to confirm the accuracy of this function, so please use with caution.

Usage

nankivell(SCr, Urea, Weight, Height, Sex, Units = "SI")

Arguments

Details

Reference: Nankivell BJ, Gruenwald SM, Allen RD, Chapman JR: Predicting glomerular filtration rate after renal transplantation. Transplantation 1995; 59:1683-89.

Value

a numeric vector of eGFR values

Examples

nankivell(SCr = 118, Urea = 13.4, Weight = 65, Height = 172, Sex = "M") # 44.55

eGFR using Nankivell formula (US units)

Description

A wrapper function for the nankivell() vectorised function to calculate eGFR using the Nankivell formula, but using creatinine and BUN in mg/dl rather than international units. It has not been possible to run automated tests to confirm the accuracy of this function, so please use with caution.

Usage

nankivell_US(SCr, Urea, Weight, Height, Sex)

Arguments

Details

Reference: Nankivell BJ, Gruenwald SM, Allen RD, Chapman JR: Predicting glomerular filtration rate after renal transplantation. Transplantation 1995; 59:1683-89.

Value

a numeric vector of eGFR values

Examples

nankivell_US(SCr = 1.33, Urea = 13.4, Weight = 65, Height = 172, Sex = "M") # 44.55

eGFR using the Nankivell-SPK formula

Description

A vectorised function to calculate the eGFR using the Nankivell-SPK formula. By default the equation accepts serum creatinine in µmol/l but can be changed to mg/dl by setting the units parameter to "US". To allow for serial measurements over time, such as for transplant follow-up data, there is an optional offset = n parameter which increases the age value used in the equation by n years. It has not been possible to run automated tests to confirm the accuracy of this function, so please use with caution.

Usage

nankivell_spk(SCr, Age, Sex, Weight, Height, Units = "SI", Offset = 0)

Arguments

Details

Reference: Nankivell BJ, Chapman JR, Allen RD: Predicting glomerular filtration rate after simultaneous pancreas and kidney transplantation. Clin Transplant 1995; 9(2): 129-134

Value

numeric vector of eGFR values

Examples

nankivell_spk(SCr = 118, Age = 74, Sex = "M", Weight = 172, Height = 172) # 48.8

eGFR using the Nankivell-SPK formula (US units)

Description

A wrapper function for the nankivell_spk() vectorised function to calculate the eGFR using the Nankivell-SPK formula using serum creatinine in mg/dl. To allow for serial measurements over time, such as for transplant follow-up data, there is an optional offset = n parameter which increases the age value used in the equation by n years. It has not been possible to run automated tests to confirm the accuracy of this function, so please use with caution.

Usage

nankivell_spk_US(SCr, Age, Sex, Weight, Height, Offset = 0)

Arguments

Details

Reference: Nankivell BJ, Chapman JR, Allen RD: Predicting glomerular filtration rate after simultaneous pancreas and kidney transplantation. Clin Transplant 1995; 9(2): 129-134

Value

numeric vector of eGFR values

Examples

nankivell_spk_US(SCr = 1.33, Age = 74, Sex = "M", Weight = 172, Height = 172) # 49.0

P-PASS pre-procurement pancreas suitability score

Description

A vectorised function to calculate the P-PASS pre-procurement pancreas allocation suitability score used in the Eurotransplant area. The score are between 9 and 27, and in a study published by Vinkers et al. in 2008, pancreata with P-PASS score less than 17 were three times more likely to be transplanted than those with scores of 17 or more.

Usage

p_pass(age, bmi, icu, c.arr, Na, amylase = NULL, lipase = NULL, norad,
  dopam)

Arguments

Details

At least one of amylase or lipase is needed for each case, but this function can take datasets with a mixture of amylase and lipase levels and will allocate points based on the higher points for cases when both are provided.

Reference: Vinkers MT, Rahmel AO, Slot MC, et al. How to recognize a suitable pancreas donor: a Eurotransplant study of preprocurement factors. Transplant Proc 2008; 40(5):1275-8.

Value

numeric vector of P-PASS scores

Examples

# as a single case
p_pass(age = 25, bmi = 19, icu = 0, c.arr = 0, Na = 135,
      amylase = 101, lipase = 120, norad = 0, dopam = 0) # 9

# as a vector with mixed amylase and lipase availability
p_pass(age = c(25, 31, 45), bmi = c(18, 22, 35), icu = c(2, 5, 10), c.arr = c(0, 4, 10),
       Na = c(135, 157, 164), amylase = c(120, NA, 400), lipase = c(155, 170, NA),
      norad = c(0, 0.02, 0.06), dopam = c(0, 5, 11)) # 9, 19, 25

# as a vector with all lipase values missing
p_pass(age = c(25, 31, 45), bmi = c(18, 22, 35), icu = c(2, 5, 10), c.arr = c(0, 4, 10),
       Na = c(135, 157, 164), amylase = c(120, 145, 400), lipase = c(NA, NA, NA),
       norad = c(0, 0.02, 0.06), dopam = c(0, 5, 11)) # 9, 19, 25

P-SOFT Score

Description

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"

Usage

p_soft(Age, BMI, PrevTx, AbdoSurg, Albumin, Dx, ICU, Admitted, MELD,
  LifeSupport, Encephalopathy, PVThrombosis, Ascites, Units = "SI")

Arguments

Details

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.

Value

numeric vector of P-SOFT scores

Examples

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

P-SOFT Score (US units)

Description

A wrapper for the p_soft() 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/dl (rather than g/l in p_soft() function)

Usage

p_soft_US(Age, BMI, PrevTx, AbdoSurg, Albumin, Dx, ICU, Admitted, MELD,
  LifeSupport, Encephalopathy, PVThrombosis, Ascites)

Arguments

Details

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.

Value

numeric vector of P-SOFT scores

Examples

p_soft_US(Age = 65, BMI = 36, PrevTx = 2, AbdoSurg = 1, Albumin = 2.9,
    Dx = 0, ICU = 0, Admitted = 1, MELD = 32, LifeSupport = 0, Encephalopathy = 1,
    PVThrombosis = 1, Ascites = 1) # 37

Pancreas donor risk index

Description

A vectorised function to calculate the Pancreas Donor Risk Index as published by Axelrod et al. By default, the serum creatinine is used in mcmmol/l but this can be changed to mg/dl by setting the optional units parameter to "US"

Usage

pdri(age, sex, creat, eth, bmi, height, cva, cit, dcd, intent = c("SPK",
  "PAK", "Other"), units = "SI")

Arguments

Details

Reference: Axelrod DA, Sung RS, Meyer KH, et al. Systematic evaluation of pancreas allograft quality, outcomes and geographic variation in utilization. Am J Transplant 2010; 10(4):837-45.

Value

numeric vector of pancreas donor risk index values

Examples

pdri(age = 28, sex = "M", creat = 1.0, eth = "other", bmi = 24,
height = 173, cva = 0, cit = 12, dcd = 0, units = "US") # 1.00

pdri(age = 45, sex = "M", creat = 88.4, eth = "other", bmi = 24,
height = 173, cva = 0, cit = 12, dcd = 0, units = "SI") # 1.56

Pedi-SOFT Score

Description

A vectorised function to calculate the Pedi-SOFT score used to predict survival after liver transplantation in children.

Usage

pedi_soft(CTVG, Weight, Dx, LifeSupport, PrevTx)

Arguments

Details

Reference: Rana A, Pallister ZS, Guiteau JJ, et al. Survival Outcomes Following Pediatric Liver Transpantation (Pedi-SOFT) Score: A Novel Predictive Index. American Journal of Transplantation 2015; 15:1855-1863.

Value

numeric vector of Pedi-SOFT scores

Examples

pedi_soft(CTVG = 1, Weight = 10, Dx = 0, LifeSupport = 0, PrevTx = 0) # 4

PELD score

Description

A vectorised function to generate a PELD score for paediatric liver transplant candidates. The default unit for bilirubin is µmol/l and albumin in g/l, but these can be changed to mg/dl and g/dl respectively by setting the optional units parameter to "US".

Usage

peld(INR, bili, albumin, listing_age, growth_failure, units = "SI")

Arguments

Details

Some labs report albumin in g/dl rather than the g/l used in this function. If units are set to "US" then g/dl is assumed and albumin should be divided by 10 if the lab reports are in g/l. If using SI units, take care to multiply the lab albumin by 10 if the lab output is in g/dl.

Reference: McDiarmid SV, Anand R, Lindblad AS, et. al. Development of a pediatric end-stage liver disease score to predict poor outcome in children awaiting liver transplantation. Transplantation 2002; 74(2):173-81.

Value

numeric vector of PELD scores

Examples

peld(INR = 2, bili = 54, albumin = 25, listing_age = 2, growth_failure = 1)
peld(INR = 2, bili = 3.1, albumin = 25, listing_age = 2, growth_failure = 1, units = "US")

PELD score (US units)

Description

A wrapper for peld(), a vectorised function to generate a PELD score for paediatric liver transplant candidates, using mg/dl as the unit for the serum bilirubin level.

Usage

peld_US(INR, bili, albumin, listing_age, growth_failure)

Arguments

Details

Reference: McDiarmid SV, Anand R, Lindblad AS, et. al. Development of a pediatric end-stage liver disease score to predict poor outcome in children awaiting liver transplantation. Transplantation 2002; 74(2):173-81.

Value

numeric vector of PELD scores

Examples

peld_US(INR = 2, bili = 3.1, albumin = 2.5, listing_age = 2, growth_failure = 1)

Estimated Post-Transplant Survival Score (EPTS)

Description

A vectorised function to calculate raw EPTS scores for norm-related prediction of patient survival after adult renal transplants. This function generates the raw EPTS scores which can be converted to percentiles using the lookup table on the OPTN website at https://optn.transplant.hrsa.gov/media/2973/epts_mapping_table_2018.pdf

Usage

raw_epts(age, dm, prev_tx, dx)

Arguments

Details

References: https://optn.transplant.hrsa.gov/resources/allocation-calculators/epts-calculator/ and https://optn.transplant.hrsa.gov/media/1511/guide_to_calculating_interpreting_epts.pdf

Value

numeric vector of raw EPTS scores

Examples

raw_epts(age = 23.5838467, dm = 0, prev_tx = 1, dx = 5.0814511) # 0.9666517
raw_epts(age = 52.8788501, dm = 0, prev_tx = 0, dx = 0) # 1.440306
raw_epts(age = 22.5242984, dm = 1, prev_tx = 1, dx = 6.8747433) # 1.868751

Simulated dataset to illustrate eGFR calculator vignette.

Description

A simulated dataset of patient characteristics and creatinine levels

Usage

results

Format

A data frame with 4 rows and 6 variables:

Creatinine

serum creatinine in µmol/l

Age

patient age in years

Sex

Patient sex, M or F

Ethnicity

Patient ethnicity

Weight

Patient weight in kg

Height

Patient height in cm

...

Simulated dataset to illustrate eGFR calculator vignette.

Description

A simulated dataset of patient characteristics and creatinine levels

Usage

results_US

Format

A data frame with 4 rows and 6 variables:

Creatinine

serum creatinine in mg/dl

Sex

Patient sex, M or F

Age

patient age in years

Ethnicity

Patient ethnicity

Weight

Patient weight in kg

Height

Patient height in cm

...

eGFR by bedside Schwartz formula

Description

A vectorised formula to calculate estimate glomerular filtration rate in children using the bedside Schwartz formula. By default this uses serum creatinine in µmol/l but this can be changed to mg/dl by setting the optional units parameter to "US".

Usage

schwartz(creat, height, units = "SI")

Arguments

Details

Reference: Schwartz GJ, Munoz A, Schneider MF et al. New equations to estimate GFR in children with CKD. J Am Soc Nephrol 2009; 20(3):629-637.

Value

numeric vector of eGFR values

Examples

# calculate using creatinine in µmol/l
schwartz(creat = 64, height = 101)

# calculate using mg/dl
schwartz(creat = 0.7, height = 101, units = "US")

eGFR by bedside Schwartz formula (US units)

Description

A wrapper function for the schwartz() vectorised formula to calculate estimate glomerular filtration rate in children using the bedside Schwartz formula, using serum creatinine in mg/dl. Use the schwartz() function instead for µmol/l.

Usage

schwartz_US(creat, height)

Arguments

Details

Reference: Schwartz GJ, Munoz A, Schneider MF et al. New equations to estimate GFR in children with CKD. J Am Soc Nephrol 2009; 20(3):629-637.

Value

numeric vector of eGFR values

Examples

# calculate using creatinine in -mg/dl
schwartz_US(creat = 0.7, height = 101)

Simulated dataset to illustrate serial results eGFR calculator vignette.

Description

A simulated dataset of patient characteristics and creatinine levels

Usage

serial.results

Format

A data frame with 4 rows and 6 variables:

Age

patient age in years

Sex

Patient sex, M or F

Ethnicity

Patient ethnicity

Creatinine_1yr

serum creatinine at 1 year, in µmol/l

Creatinine_5yr

serum creatinine at 5 years, in µmol/l

...

SOFT score (Survival Outcomes Following Liver Transplantation)

Description

A vectorised function to calculate SOFT Scores for predicting patient survival after liver transplantation The units for donor serum creatinine are in µmol/l and recipient serum albumin in g/l but they can be changed to mg/dl and g/dl respectively by setting the Units parameter to "US".

Usage

soft(Age, BMI, PrevTx, AbdoSurg, Albumin, Dx, ICU, Admitted, MELD,
  LifeSupport, Encephalopathy, PVThrombosis, Ascites, PortalBleed,
  DonorAge, DonorCVA, DonorSCr, National, CIT, Units = "SI")

Arguments

Details

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.

Value

numeric vector of SOFT Scores

Examples

soft(Age = 35, BMI = 20, PrevTx = 0, AbdoSurg = 1, Albumin = 30, Dx = 0,
    ICU = 0, Admitted = 0, MELD = 29, LifeSupport = 0, Encephalopathy = 1,
    PVThrombosis = 0, Ascites = 1, PortalBleed = 0, DonorAge = 44, DonorCVA = 0,
    DonorSCr = 110, National = 0, CIT = 8) # 7

SOFT score from P-SOFT

Description

A vectorised function to calculate SOFT Scores for predicting patient survival after liver transplantation when the P-SOFT score is already known. The P-SOFT Score can be calculated using the transplantr::p_soft() function. Alternatively, the SOFT Score can be calculated in full, including the P-SOFT parameters using the transplantr::soft() function. The units for donor serum creatinine are in µmol/l but can be changed to mg/dl by setting the Units parameter to "US".

Usage

soft2(PSoft, PortalBleed, DonorAge, DonorCVA, DonorSCr, National, CIT,
  Units = "SI")

Arguments

Details

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.

Value

numeric vector of SOFT Scores

Examples

soft2(PSoft = 4, PortalBleed = 0, DonorAge = 61, DonorCVA = 1, DonorSCr = 140,
    National = 1, CIT = 12) # 13

SOFT score from P-SOFT (US units)

Description

A wrapper using US units for the soft2() vectorised function to calculate SOFT Scores for predicting patient survival after liver transplantation when the P-SOFT score is already known. The P-SOFT Score can be calculated using the transplantr::p_soft() function. Alternatively, the SOFT Score can be calculated in full, including the P-SOFT parameters using the transplantr::soft() or transplantr::soft_US() function. The units for donor serum creatinine are in mg/dl

Usage

soft2_US(PSoft, PortalBleed, DonorAge, DonorCVA, DonorSCr, National, CIT)

Arguments

Details

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.

Value

numeric vector of SOFT Scores

Examples

soft2_US(PSoft = 4, PortalBleed = 0, DonorAge = 61, DonorCVA = 1, DonorSCr = 1.6,
    National = 1, CIT = 12) # 13

SOFT score (Survival Outcomes Following Liver Transplantation) (US units)

Description

A wrapper function using US units for the soft() vectorised function to calculate SOFT Scores for predicting patient survival after liver transplantation. The units for donor serum creatinine and recipient serum albumin in g/l.

Usage

soft_US(Age, BMI, PrevTx, AbdoSurg, Albumin, Dx, ICU, Admitted, MELD,
  LifeSupport, Encephalopathy, PVThrombosis, Ascites, PortalBleed,
  DonorAge, DonorCVA, DonorSCr, National, CIT)

Arguments

Details

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.

Value

numeric vector of SOFT Scores

Examples

soft_US(Age = 35, BMI = 20, PrevTx = 0, AbdoSurg = 1, Albumin = 3.0, Dx = 0,
    ICU = 0, Admitted = 0, MELD = 29, LifeSupport = 0, Encephalopathy = 1,
    PVThrombosis = 0, Ascites = 1, PortalBleed = 0, DonorAge = 44, DonorCVA = 0,
    DonorSCr = 1.2, National = 0, CIT = 8) # 7

UKELD score

Description

A vectorised function to calculate the UKELD score using SI units for bilirubin and creatinine.

Usage

ukeld(INR, bili, creat, Na, units = "SI")

Arguments

Details

Reference: Barber KM, Madden S, Allen J, et al. Elective liver transplant list mortality: development of a United Kingdom end-stage liver disease score. Transplantation 2011; 92(4):469-76.

Value

numeric vector of UKELD scores

Examples

ukeld(INR = 1.0, bili = 212, creat = 54, Na = 126)

UKELD score (US units)

Description

A vectorised function to calculate the UKELD score using US units for bilirubin and creatinine.

Usage

ukeld_US(INR, bili, creat, Na)

Arguments

Details

Reference: Barber KM, Madden S, Allen J, et al. Elective liver transplant list mortality: development of a United Kingdom end-stage liver disease score. Transplantation 2011; 92(4):469-76.

Value

UKELD score

Examples

ukeld_US(INR = 2.0, bili = 1.8, creat = 170, Na = 130)

UK Kidney Donor Risk Index (NHSBT, 2019 version)

Description

A vectorised function to calculate the UK Kidney Donor Risk Index as used in the new national kidney matching scheme implemented in September 2019.

Usage

ukkdri(age, height, htn, sex, cmv, gfr, hdays)

Arguments

Details

The UK KDRI is documented in the UK kidney matching policy which can be found on the NHS Blood & Transplant ODT website at www.odt.nhs.uk

Value

numeric vector of UK Kidney Donor Risk Index values (2019 version)

Examples

ukkdri(age = 50, height = 170, htn = 1, sex = "F", cmv = 0, gfr = 90, hdays = 2)

UK Kidney Donor Risk Index Quartile (2019)

Description

Vectorised function to convert UKKDRI values to quartiles of risk. The function takes a numeric vector of UKKDRI values as input, and returns a vector of quartiles. By default this is also a numeric vector with values 1-4, but this can be changed to a character string vector of D1-D4 to match the nomenclature in the NHSBT ODT documentation by setting the prefix parameter to TRUE. The output can also be as a vector of factors by setting fct to TRUE (this can be combined with the prefix parameter).

Usage

ukkdri_q(dri, prefix = FALSE, fct = FALSE)

Arguments

Details

The UK KDRI quartile ranges are documented in the UK kidney matching policy which can be found on the NHS Blood & Transplant ODT website at www.odt.nhs.uk

Value

vector of UKKDRI quartiles

Examples

# obtain quartile of a single value
ukkdri_q(1.01)

# factor vector of results with prefix
dri = c(0.69, 1.01, 1.36, 1.54)
ukkdri_q(dri, prefix = TRUE, fct = TRUE)

UK Kidney Recipient Risk Index (NHSBT, 2019 version)

Description

A vectorised function to calculate the UK Kidney Recipient Risk Index as used in the new national kidney matching scheme implemented in September 2019.

Usage

ukkrri(age, dx, wait, dm)

Arguments

Details

The UK KRRI is documented in the UK kidney matching policy which can be found on the NHS Blood & Transplant ODT website at www.odt.nhs.uk

Value

numeric vector of UK Kidney Recipient Risk Index values

Examples

ukkrri(age = 45, dx = 0, wait = 750, dm = 0)

UK Kidney Recipient Risk Index Quartile (2019)

Description

Vectorised function to convert UKKRRI values to quartiles of risk. The function takes a numeric vector of UKKRRI values as input, and returns a vector of quartiles. By default this is also a numeric vector with values 1-4, but this can be changed to a character string vector of R1-R4 to match the nomenclature in the NHSBT ODT documentation by setting the prefix parameter to TRUE. The output can also be as a vector of factors by setting fct to TRUE (this can be combined with the prefix parameter).

Usage

ukkrri_q(rri, prefix = FALSE, fct = FALSE)

Arguments

Details

The UK KRRI quartile ranges are documented in the UK kidney matching policy which can be found on the NHS Blood & Transplant ODT website at www.odt.nhs.uk

Value

vector of UKKRRI quartiles

Examples

# obtain quartile of a single value
ukkrri_q(1.01)

# factor vector of results with prefix
rri = c(0.69, 0.75, 0.96, 1.36)
ukkrri_q(rri, prefix = TRUE, fct = TRUE)

Convert urea to BUN

Description

A vectorised function to convert urea to blood urea nitrogen (BUN), By default the urea is measured in mmol/l but this can be changed to mg/dl by setting the optional units parameter to "US"

Usage

urea_to_bun(urea, units = "SI")

Arguments

Value

numeric vector of blood urea nitrogen (BUN) levels in mg/dl

Examples

urea_to_bun(5.4)

US Kidney Donor Risk Index

Description

Vectorised function to calculate US Kidney Donor Risk Index as published by UNOS. Please note that this function uses creatinine measured in µmol/l by default, but can be changed to mg/dl if the optional units parameter is set to "US".

Usage

uskdri(age, height, weight, eth, htn, dm, cva, creat, hcv, dcd,
  scaling = 1, units = "SI")

Arguments

Details

The KDRI is normalised by a scaling factor based on the median KDRI in the previous year. For 2018, this was approximately 1.250609 as is published on the OPTN website. The scaling parameter in this function defaults to 1, so can be left out to calculate the KDRI without scaling.

Reference: Rao PS, Schaubel DE, Guidinger MK, et al. A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index. Transplantation 2009; 88:231-236.

Value

numeric vector of US KDRI values

Examples

# with creatinine in µmol/l (units = "SI" can be omitted)
uskdri(age = 40, height = 170, weight = 80, eth = "non-black", htn = 0, dm = 0,
    cva = 0, creat = 120, hcv = 0, dcd = 0, scaling = 1.250609, units = "SI")

# with creatinine in mg/dl
uskdri(age = 40, height = 170, weight = 80, eth = "non-black", htn = 0, dm = 0,
    cva = 0, creat = 1.4, hcv = 0, dcd = 0, scaling = 1.250609, units = "US")

US Kidney Donor Risk Index (US units)

Description

Wrapper function for the uskdri() vectorised function to calculate US Kidney Donor Risk Index as published by UNOS but using mg/dl as the units for creatinine.

Usage

uskdri_US(age, height, weight, eth, htn, dm, cva, creat, hcv, dcd,
  scaling = 1)

Arguments

Details

The KDRI is normalised by a scaling factor based on the median KDRI in the previous year. For 2018, this was approximately 1.250609 as is published on the OPTN website. The scaling parameter in this function defaults to 1, so can be left out to calculate the KDRI without scaling.

Reference: Rao PS, Schaubel DE, Guidinger MK, et al. A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index. Transplantation 2009; 88:231-236.

Value

numeric vector of US KDRI values

Examples

uskdri(age = 40, height = 170, weight = 80, eth = "non-black", htn = 0, dm = 0,
    cva = 0, creat = 1.4, hcv = 0, dcd = 0)

eGFR using the Walser formula

Description

A vectorised function to calculate eGFR using the Walser formula. By default the equation accepts serum creatinine in µmol/l but can be changed to mg/dl by setting the units parameter to "US". It has not been possible to run automated tests to confirm the accuracy of this function, so please use with caution.

Usage

walser(SCr, Age, Weight, Sex, Units = "SI")

Arguments

Details

Reference: Walser M, Drew HH, Guldan JL. Prediction of glomerular filtration rate in advanced chronic renal failure. Kidney International 1993; 44:2245-1148.

Value

numeric vectors of eGFR values

Examples

walser(SCr = 118, Age = 74, Weight = 65, Sex = "M") # 56.1

eGFR using the Walser formula (US units)

Description

A wrapper function for the walser() vectorised function to calculate eGFR using the Walser formula, using serum creatinine in mg/dl. It has not been possible to run automated tests to confirm the accuracy of this function, so please use with caution.

Usage

walser_US(SCr, Age, Weight, Sex)

Arguments

Details

Reference: Walser M, Drew HH, Guldan JL. Prediction of glomerular filtration rate in advanced chronic renal failure. Kidney International 1993; 44:2245-1148.

Value

numeric vectors of eGFR values

Examples

walser_US(SCr = 1.33, Age = 74, Weight = 65, Sex = "M") # 56.3

UK Kidney Donor Risk Index (2012 version)

Description

A vectorised function to calculate the UK Kidney Donor Risk Index as published by Watson et al. in 2012. Please note that this is not the same risk index as used in the new UK kidney matching scheme starting in September 2019.

Usage

watson_ukkdri(age, htn, weight, hdays, adrenaline)

Arguments

Details

Reference: Watson CJE, Johnson RJ, Birch R, et al. A Simplified Donor Risk Index for Predicting Outcome After Deceased Donor Kidney Transplantation. Transplantation 2012; 93(3):314-318

Value

numeric vector of UK Kidney Donor Risk Index (2012) values

Examples

watson_ukkdri(age = 40, htn = 0, weight = 75, hdays = 0, adrenaline = 0) # 1.00