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Summary

Lifecycle: draftEditUnder review
What this benchmark means
README.md

Public entries: Python and R. Passing coverage requires an installed inventory.

Goal: give one row for each adverse event and each medication of the same subject given for its term: their sequence numbers (AESEQ, CMSEQ), the medication's name (CMTRT) and its dose as a whole number (CMDOSE); and a run report that counts the doses left empty.

Input: one spec.yaml over adverse events, each with its sequence number and reported term, and concomitant medications, each with its sequence number, name, indication and dose as collected text; one dose is written in words.

Variables:

  • CMTRT: the name of a medication of the same subject whose indication is the event's term.
  • CMDOSE: the medication's dose as a whole number; empty when the collected dose is not a number.

The run report (aecm-report.csv) has one row per item the run handled, each naming the dataset (ARTIFACT), the kind of item (KIND), where the spec states it (SPEC_PATH) and the item's name (NAME): the run and its outcome (OUTCOME) with the rows it built (COUNT); the two collected datasets, each with the records read and its file facts (DETAILS); the pairs that built the rows, out of all pairs (TOTAL); then the doses left empty because they are not numbers, counted once for each pair that holds one. That count gives the rule its empty dose stands in for (RULE) and no output column (TARGET), since each pair's dose is read before any row is built. One row per output column follows, with its missing values and longest text. Nothing is checked, so no row has a label (ID), a SEVERITY, a CONDITION or KEYS.

Note: a subject who reports the same term twice pairs each of its medications with both events, so a dose written in words is left empty in each of those rows, and the run report counts it once for each: twice here.

Inputs

Under review
2 source files

input/ae.csv

Edit
4 rows
input/ae.csv
USUBJIDAESEQAETERM
1HEADACHE
2NAUSEA
3HEADACHE
1FEVER

input/cm.csv

Edit
4 rows
input/cm.csv
USUBJIDCMSEQCMTRTCMINDCCMDOSE
1PARACETAMOLHEADACHE500
2ONDANSETRONNAUSEA8
3IBUPROFENHEADACHEtwo hundred
1IBUPROFENFEVER200

Expected output

Under review
16 expected rows

expected/aecm-report.csv

Edit
10 rows
expected/aecm-report.csv
ARTIFACTKINDSPEC_PATHNAMEIDTARGETRULESEVERITYOUTCOMECONDITIONCOUNTTOTALKEYSDETAILS
aecm.csvrunoutput—————succeeded—6——{}
aecm.csvinputinput.AEAE——————4——{"bytes":72,"path":"input/ae.csv","profile":"csv"}
aecm.csvinputinput.CMCM——————4——{"bytes":151,"path":"input/cm.csv","profile":"csv"}
aecm.csvrowsrows.pairsGIVEN——————66—{}
aecm.csvhandlerintermediates.GIVEN.derivations.CMDOSE.unconvertibleunconvertible——VALUE-3———2——{}
aecm.csvcolumncolumns.USUBJIDUSUBJID——————06—{"max_length":2}
aecm.csvcolumncolumns.AESEQAESEQ——————06—{}
aecm.csvcolumncolumns.CMSEQCMSEQ——————06—{}
aecm.csvcolumncolumns.CMTRTCMTRT——————06—{"max_length":11}
aecm.csvcolumncolumns.CMDOSECMDOSE——————26—{}

expected/aecm.csv

Edit
6 rows
expected/aecm.csv
USUBJIDAESEQCMSEQCMTRTCMDOSE
11PARACETAMOL500
13IBUPROFEN—
22ONDANSETRON8
31PARACETAMOL500
33IBUPROFEN—
11IBUPROFEN200
Shaded columns are derived— = missing value

Human review and assessment

Your review

2 questions and your comments · View benchmark discussions

Mapping spec

Generated from the benchmark YAML; do not edit by hand

Variable NameVariable LabelTypeLengthControlled Terms or FormatOriginCoreConversion DefinitionVariable TypeVariable OrderComments for Define
USUBJIDUnique Subject IdentifierCharDerivedSet per constructed row; see the Row construction sheet.SDTM1
AESEQSequence Number of the Adverse EventNumDerivedSet per constructed row; see the Row construction sheet.SDTM2
CMSEQSequence Number of the MedicationNumDerivedSet per constructed row; see the Row construction sheet.SDTM3
CMTRTReported Name of Drug, Med, or TherapyCharDerivedSet per constructed row; see the Row construction sheet.SDTM4
CMDOSEDose per AdministrationNumDerivedSet per constructed row; see the Row construction sheet.SDTM5
TemplateInclude whenUSUBJIDAESEQCMSEQCMTRTCMDOSE
pairsCopy USUBJID from the AE record whose USUBJID equals AE.USUBJID and CMINDC equals AE.AETERM, where USUBJID is derived as AE.USUBJID, and no match yields blankCopy AESEQ from the AE record whose USUBJID equals AE.USUBJID and CMINDC equals AE.AETERM, where AESEQ is derived as AE.AESEQ, and no match yields blankCopy CMSEQ from the AE record whose USUBJID equals AE.USUBJID and CMINDC equals AE.AETERM, where CMSEQ is derived as CM.CMSEQ, and no match yields blankCopy CMTRT from the AE record whose USUBJID equals AE.USUBJID and CMINDC equals AE.AETERM, where CMTRT is derived as CM.CMTRT, and no match yields blankCopy CMDOSE from the AE record whose USUBJID equals AE.USUBJID and CMINDC equals AE.AETERM, where CMDOSE is derived as {'type': 'int', 'derivation': 'CM.CMDOSE', 'unconvertible': None}, and no match yields blank
VersionDateAuthorDescriptionReviewerSign-off
1.72026-10-20yamaa docs buildRead a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default
1.62026-10-17yamaa docs buildDescribe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.52026-10-17yamaa docs buildName collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part
1.42026-10-15yamaa docs buildState datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.32026-09-29yamaa docs buildShow study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.22026-09-29yamaa docs buildClassify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.12026-09-29yamaa docs buildResolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0yamaa docs buildInitial generation from spec.yaml

yamaa code

Public calls generated from benchmark.yaml; results must match the expected output

R

Edit
3 lines
library(yamaa)yamaa_spec("spec.yaml")$run()$output

Python

Edit
3 lines
import yamaayamaa.spec("spec.yaml").run().output