Model 2.0IG 3.4Content 1.0.0Curated educational coverage
EX / interventions
Exposure
Exposure lessons focus on treatment represented in the study data rather than what a scheduling screen says should occur.
Separate a plan from an administration
A planned dose is an instruction; an observed administration is evidence of an action. A system that treats a scheduled item as a completed event can manufacture exposure. Keep the two states distinct before considering any tabulation.
Look inside the structure
6 selected variables. Follow an identifier to its lesson.
Scroll this table horizontally to inspect every field, or read as records.
| Identifier | Domain | Teaching explanation | Example JSON type | Example value |
|---|---|---|---|---|
| STUDYID | EX | The study identifier places the treatment-exposure teaching record in its study. Preserve that context when interpreting the treatment description and recorded dose. | string | CLD-SYN-001 |
| DOMAIN | EX | The value EX identifies the study-treatment exposure context in this lesson. It distinguishes the treatment and dose representation from the concomitant-medication context illustrated by CM. | string | EX |
| USUBJID | EX | The fictional subject key connects a treatment-exposure record to its participant. Joining exposure and event records by subject alone does not establish their timing or a causal relationship. | string | SYN-001 |
| EXSEQ | EX | This example sequence number separates rows inside the EX teaching extract. It is useful for referring to an observation, but the original collection identifier is retained separately in the mapping manifest. | number | 1 |
| EXTRT | EX | The invented treatment name makes the row's topic readable without importing a product catalog or dictionary. | string | Fictional study treatment |
| EXDOSE | EX | The number illustrates JSON numeric representation. Our selected fields omit unit, schedule and other dosing context, so this row cannot support a dosing interpretation. | number | 10 |
See the relationship in an example
One subject, several identities →
This linked walkthrough illustrates a related engineering concept; it is not an EX output dataset.
Follow the source
Original ClinDevLab explanations. Publisher material is linked, not reproduced. Reviewed 8 October 2026.
- SDTM 2.0https://www.cdisc.org/standards/foundational/sdtm/sdtm-v2-0 · CDISC · 2.0 · accessed 2026-10-08
- SDTMIG 3.4https://www.cdisc.org/standards/foundational/sdtmig/sdtmig-v3-4 · CDISC · 3.4 · accessed 2026-10-08