# Configure Vault for MedDRA Query-Level Detection The signal detection process detects _Product-Event Combinations_ (PECs) at the _Product Family_-MedDRA Preferred Term (PT) level. If required, you can set up your Vault to detect PECs at the _Product Family_-_MedDRA Query_ level and identify signal events for a group of MedDRA terms.  Depending on your business needs, configure your Vault for _Signal Calculations_ to return case counts and Empirical Bayes Geometric Mean (EBGM) scores: * [**Scenario A**][1]: At the Preferred Term (PT) level and _MedDRA Query_ level for a given _Product Family_ * [**Scenario B**][2]: At the _MedDRA Query_ level for a given _Product Family_, with PTs included in the _MedDRA Query_ in CSV format * [**Scenario C**][3]: At the Preferred Term (PT) level and _MedDRA Query_ level for a given _Product Family_ and _MedDRA Query_ ## Prerequisites Before configuring your Vault to return results at the _MedDRA Query_ level, you must enable Signal Calculations for MedDRA Queries.  ## Scenario A: Identify MedDRA Terms and MedDRA Queries in Statistical Data Records {#scenario-a} In this example scenario, you are configuring your Vault to identify MedDRA terms and _MedDRA Queries_ and generate _Statistical Data_ records according to the following parameters:  * The _Output Type_ for all calculations is _Statistical Data Record_ (or blank). * Standard _MedDRA Queries_ (SMQs) include:  * _Accidents and injuries_ * _Asthma/bronchospasm_ * The _Product Family_ is _Cholecap_. To do this:  1. Create a _Signal Product Profile_ with the following information: * **Name**: Enter `Cholecap`. * **Product Family**: Select **Cholecap** from the drop-down.  * **Source**: Select **Safety Database** from the drop-down. * **Organization**: Select the appropriate _Organization_.  2. Populate the _Alert Rule Sets_ section to specify the rules a PEC must meet to qualify as a potential signal. 3. Create a _Signal Reporting Period_ with the following information:  * **Product Family**: Select **Cholecap** from the drop-down.  * **Start Date**: Use the calendar to select a start date or enter the date manually. * **End Date**: Use the calendar to select an end date or enter the date manually. * **Signal Product Profile**: Select **Cholecap** from the drop-down.  * **Review Type**: Select **Ad-Hoc** from the drop-down. 4. Copy the pharmacovigilance (PV) _Signal Views_ provided by Veeva [as indicated][4] so that you can modify the new custom views according to your business needs. 5. Create a _Signal Calculations Setting_ with the name `Cholecap Calculations Setting`. 6. Create _Signal Calculations_ for this _Signal Calculations Setting_ [as indicated][5]. 7. Navigate to the _Signal Product Profile_ you created and in the **Calculations Setting** field, select **Cholecap Calculations Setting** from the drop-down.  After a user runs the _Signal Calculations_ and creates _Statistical Data_, Vault generates the [specified results][6].  ### Signal Views Table {#scenario-a-views} The following table displays the _Signal Views_ you must copy and rename:  | Signal View to Copy | New Custom Signal View Name | | --------------------------------------------- | -------------------------------- | | [_New Counts-PT-level view_]  | `New Counts (PT)` | | [_Cumulative Counts-PT-level view_] | `Cumulative Counts (PT)` | | [_EBGM Counts-PT-level view_] | `EBGM Counts (PT)` | | [_New Counts-MedDRA Query-level view_] | `New Counts MedDRA Query ` | | [_Cumulative Counts-MedDRA Query-level view_] | `Cumulative Counts MedDRA Query` | | [_EBGM Counts-MedDRA Query-level view_] | `EBGM Counts MedDRA Query ` | ### Signal Calculations Table {#scenario-a-calculations} The following table displays the _Signal Calculations_ you must create:  | Signal Calculation to Create | Query Type | Calculation | Output Type | Signal View | Filter | | ---------------------------- | ---------- | ----------- | ----------- | ----------- | ------ | | PT level | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts (PT)_ | N/A | | PT level | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts (PT)_ | N/A | | PT level | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts (PT)_ | N/A | | _MedDRA Query_ level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Accidents and injuries) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | As the PT-level views in this scenario are not associated with a _MedDRA Query_, you do not need to specify a _MedDRA Query_ filter value for the PT-level calculations. ### Results {#scenario-a-results} For the PT-level [_Signal Calculations_][5], as each of these calculations has an _Output Type_ of _Statistical Data Record_ (or blank), Vault creates a _Statistical Data_ record for each new detected _Product Family_-PT combination. The following table lists the results in each PT-level _Statistical Data_ record:  | Statistical Data Record ID | Product Family | MedDRA Term | MedDRA Query | New Counts (Spontaneous) | Cumulative Counts (Spontaneous) | New Counts (Fatal) | Cumulative Counts (Fatal) | EBGM | | -------------------------- | -------------- | ----------- | ------------ | ------------------------ | ------------------------------- | ------------------ | ------------------------- | ---- | | _SD-0001_ | _Cholecap_ | _Accident at work_ | [Blank] | 3 | 19 | 0 | 1 | 1.12 | | _SD-0002_ | _Cholecap_ | _Animal Bite_ | [Blank] | 4 | 8 | 0 | 0 | 0.89 | | _SD-0003_ | _Cholecap_ | _Back Injury_ | [Blank] | 5 | 20 | 0 | 0 | 1.45 | | _SD-0004_ | _Cholecap_ | _Asthma exercise induced_ | [Blank] | 1 | 20 | 0 | 0 | 1.02 | | _SD-0005_ | _Cholecap_ | _Hyperventilation_ | [Blank] | 0 | 5 | 0 | 0 | 0.95 | | _SD-0006_ | _Cholecap_ | _Wheezing_ | [Blank] | 2 | 10 | 0 | 0 | 1.28 | | _SD-0007_ | _Cholecap_ | _Arthritis_ | [Blank] | 2 | 4 | 0 | 0 | 0.74 | | _SD-0008_ | _Cholecap_ | _Nausea_ | [Blank] | 3 | 10 | 0 | 0 | 1.10 | | _SD-0009_ | _Cholecap_ | _Rash_ | [Blank] | 10 | 30 | 0 | 0 | 1.05 | The _Signal Calculations Setting_ in this scenario includes three PT-level _Signal Calculations_ (new counts, cumulative counts, and EBGM counts). Vault returns detected PTs that exist for the given _Product Family_ (_Cholecap_). Some of the MedDRA terms returned by the PT-level calculations are also associated with the following _MedDRA Queries_: * _Accidents and injuries_: * _Accident at work_ * _Animal Bite_ * _Back Injury_ * _Asthma/bronchospasm_: * _Asthma exercise induced_ * _Hyperventilation_ * _Wheezing_ The _Arthritis_, _Nausea_, and _Rash_ PTs are not associated with either of the selected _MedDRA Query_ values. To identify PTs only from a given _MedDRA Query_, see scenarios [B][2] and [C][3]. For the _MedDRA Query_-level _Signal Calculations_, as each of these calculations has an _Output Type_ of _Statistical Data Record_ (or blank), Vault creates a _Statistical Data_ record for each _Product Family_-_MedDRA Query_ combination. The following table lists the results in each _MedDRA Query_-level _Statistical Data_ record:  | Statistical Data Record ID | Product Family | MedDRA Term | MedDRA Query | New Counts (Spontaneous) | Cumulative Counts (Spontaneous) | New Counts (Fatal) | Cumulative Counts (Fatal) | EBGM | | -------------------------- | -------------- | ----------- | ------------ | ------------------------ | ------------------------------- | ------------------ | ------------------------- | ---- | | _SD-0010_ | _Cholecap_ | [Blank] | _Accidents and injuries_ | 12 | 47 | 0 | 1 | 1.30 | | _SD-0011_ | _Cholecap_ | [Blank] | _Asthma/bronchospasm_ | 3 | 35 | 0 | 0 | 1.24 | The _Signal Calculations Setting_ in this scenario includes six _MedDRA Query_-level _Signal Calculations_ (new counts, cumulative counts, and EBGM counts for each _MedDRA Query_).  ## Scenario B: Identify Preferred Terms for a MedDRA Query in CSV Format {#scenario-b} In this example scenario, you are configuring your Vault to identify _MedDRA Queries_ and MedDRA terms within those queries and generate the respective output according to the following parameters:  * The _Output Types_ are:  * For _MedDRA Query_-level calculations: _Statistical Data Record_ (or blank)  * For PT-level calculations: _CSV Attachment_ * Standard _MedDRA Queries_ (SMQs) include:  * _Accidents and injuries_ * _Asthma/bronchospasm_ * The _Product Family_ is _Cholecap_. To do this:  1. Create a _Signal Product Profile_ with the following information:  * **Name**: Enter `Cholecap`. * **Product Family**: Select **Cholecap** from the drop-down.  * **Source**: Select **Safety Database** from the drop-down. * **Organization**: Select the appropriate _Organization_.  2. Populate the _Alert Rule Sets_ section to specify the rules a PEC must meet to qualify as a potential signal. 3. Create a _Signal Reporting Period_ with the following information:  * **Product Family**: Select **Cholecap** from the drop-down.  * **Start Date**: Use the calendar to select a start date or enter the date manually. * **End Date**: Use the calendar to select an end date or enter the date manually. * **Signal Product Profile**: Select **Cholecap** from the drop-down.  * **Review Type**: Select **Ad-Hoc** from the drop-down. 4. Copy the pharmacovigilance (PV) _Signal Views_ provided by Veeva [as indicated][7] so that you can modify the new custom views according to your business needs. 5. Create a _Signal Calculations Setting_ with the name `Cholecap Calculations Setting`. 6. Create _Signal Calculations_ for this _Signal Calculations Setting_ [as indicated][8]. 7. Navigate to the _Signal Product Profile_ you created and in the **Calculations Setting** field, select **Cholecap Calculations Setting** from the drop-down.  After a user runs the _Signal Calculations_ and creates _Statistical Data_, Vault generates the [specified results][9].  ### Signal Views Table {#scenario-b-views} The following table displays the _Signal Views_ you must copy and rename:  | Signal View to Copy | New Custom Signal View Name | | --------------------------------------------- | --------------------------------- | | [_New Counts-MedDRA Query-level view_] | `New Counts MedDRA Query ` | | [_New Counts-MedDRA Query-PT-level view_]
This view returns new case counts of detected PTs for the _Product Family_ that are included in the given _MedDRA Query_. | `New Counts MedDRA Query (PT)` | | [_Cumulative Counts-MedDRA Query-level view_] | `Cumulative Counts MedDRA Query ` | | [_Cumulative Counts-MedDRA Query-PT-level view_] 
This view returns cumulative case counts of detected PTs for the _Product Family_ that are included in the given _MedDRA Query_. | `Cumulative Counts MedDRA Query (PT)` | | [_EBGM Counts-MedDRA Query-level view_] | `EBGM Counts MedDRA Query ` | | [_EBGM Counts-MedDRA Query-PT-level view_] 
This view returns EBGM case counts of detected PTs for the _Product Family_ that are included in the given _MedDRA Query_. | `EBGM Counts MedDRA Query (PT)` | ### Signal Calculations Table {#scenario-b-calculations} The following table displays the _Signal Calculations_ you must create:  | Signal Calculation to Create | Query Type | Calculation | Output Type | Signal View | Filter | | ---------------------------- | ---------- | ----------- | ----------- | ----------- | ------ | | _MedDRA Query_ level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query_  | _MedDRA Query ID_ > _Accidents and injuries_ | | PT level (Accidents and injuries) | _SQL_ | N/A | _CSV Attachment_ | _New Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | PT level (Accidents and injuries) | _SQL_ | N/A | _CSV Attachment_ | _Cumulative Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Accidents and injuries) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | PT level (Accidents and injuries) | _Advanced_ | _EBGM_ | _CSV Attachment_ | _EBGM Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | PT level (Asthma/bronchospasm) | _SQL_ | N/A | _CSV Attachment_ | _New Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query_  | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | PT level (Asthma/bronchospasm) | _SQL_ | N/A | _CSV Attachment_ | _Cumulative Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | PT level (Asthma/bronchospasm) | _Advanced_ | _EBGM_ | _CSV Attachment_ | _EBGM Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | As all PT-level views are associated with a _MedDRA Query_ in this scenario, you must specify a _MedDRA Query_ filter value for the PT-level calculations as well.  ### Results {#scenario-b-results} For the _MedDRA Query_-level [_Signal Calculations_][8], as each of these calculations has an _Output Type_ of _Statistical Data Record_ (or blank), Vault creates a _Statistical Data_ record for each _Product Family_-_MedDRA Query_ combination. The following table lists the results in a _MedDRA Query_-level _Statistical Data_ record:  | Statistical Data Record ID | Product Family | MedDRA Term | MedDRA Query | New Counts (Spontaneous) | Cumulative Counts (Spontaneous) | New Counts (Fatal) | Cumulative Counts (Fatal) | EBGM | | -------------------------- | -------------- | ----------- | ------------ | ------------------------ | ------------------------------- | ------------------ | ------------------------- | ---- | | _SD-0001_ | _Cholecap_ | [Blank] | _Accidents and injuries_ | 12 | 47 | 0 | 1 | 1.30 | | _SD-0002_ | _Cholecap_ | [Blank] | _Asthma/bronchospasm_ | 3 | 35 | 0 | 0 | 1.24 | The _Signal Calculations Setting_ in this scenario includes six _MedDRA Query_-level _Signal Calculations_ (new counts, cumulative counts, and EBGM counts for each _MedDRA Query_).  For the PT-level _Signal Calculations_, as each of these calculations has an _Output Type_ of _CSV Attachment_, Vault attaches a CSV to the first _Statistical Data_ record matching on the following: * _Product Family_ (_Cholecap_) * _MedDRA Query_ (_Accidents and injuries_ or _Asthma/bronchospasm_) * _Signal Reporting Period_ * _Source_ Each CSV lists new detected _Product Family_-PT combinations, where the PTs also belong to the respective _MedDRA Query_. The following table lists the results in each PT-level CSV attachment:
CSV Attachment Attached to Product Family MedDRA Term MedDRA Query New Counts (Spontaneous) Cumulative Counts (Spontaneous) New Counts (Fatal) Cumulative Counts (Fatal) EBGM
calculation_result_SCALC-0001 SD-0001 Cholecap Accident at work [Blank] 3 19 0 1 1.12
Cholecap Animal Bite [Blank] 4 8 0 0 0.89
Cholecap Back Injury [Blank] 5 20 0 0 1.45
calculation_result_SCALC-0002 SD-0002 Cholecap Asthma exercise induced [Blank] 1 20 0 0 1.02
Cholecap Hyperventilation [Blank] 0 5 0 0 0.95
Cholecap Wheezing [Blank] 2 10 0 0 1.28
The _Signal Calculations Setting_ in this scenario includes six PT-level _Signal Calculations_ (new counts, cumulative counts, and EBGM counts for each _MedDRA Query_). Vault returns detected PTs that exist for the given _Product Family_-_MedDRA Query_ combinations. In this scenario, Vault returns PTs for the following _MedDRA Queries_: * _Accidents and injuries_: * _Accident at work_ * _Animal Bite_ * _Back Injury_ * _Asthma/bronchospasm_: * _Asthma exercise induced_ * _Hyperventilation_ * _Wheezing_ ## Scenario C: Identify Preferred Terms for a MedDRA Query in Statistical Data Records {#scenario-c} In this example scenario, you are configuring your Vault to identify _MedDRA Queries_ and MedDRA terms within those queries and generate _Statistical Data_ records according to the following parameters:  * The _Output Type_ for all calculations is _Statistical Data Record_ (or blank). * Standard _MedDRA Queries_ (SMQs) include:  * _Accidents and injuries_ * _Asthma/bronchospasm_ * The _Product Family_ is _Cholecap_. To do this:  1. Create a _Signal Product Profile_ with the following information:  * **Name**: Enter `Cholecap`.  * **Product Family**: Select **Cholecap** from the drop-down.  * **Source**: Select **Safety Database** from the drop-down.  * **Organization**: Select the appropriate _Organization_.  2. Populate the _Alert Rule Sets_ section to specify the rules a PEC must meet to qualify as a potential signal. 3. Create a _Signal Reporting Period_ with the following information:  * **Product Family**: Select **Cholecap** from the drop-down.  * **Start Date**: Use the calendar to select a start date or enter the date manually. * **End Date**: Use the calendar to select an end date or enter the date manually. * **Signal Product Profile**: Select **Cholecap** from the drop-down.  * **Review Type**: Select **Ad-Hoc** from the drop-down. 4. Copy the pharmacovigilance (PV) _Signal Views_ provided by Veeva [as indicated][10] so that you can modify the new custom views according to your business needs. 5. Create a _Signal Calculations Setting_ with the name `Cholecap Calculations Setting`. 6. Create _Signal Calculations_ for this _Signal Calculations Setting_ [as indicated][11]. 7. Navigate to the _Signal Product Profile_ you created and in the **Calculations Setting** field, select **Cholecap Calculations Setting** from the drop-down.  After a user runs the _Signal Calculations_ and creates _Statistical Data_, Vault generates the [specified results][12].  ### Signal Views Table {#scenario-c-views} The following table displays the _Signal Views_ you must copy and rename:  | Signal View to Copy | New Custom Signal View Name | | --------------------------------------------- | --------------------------------- | | [_New Counts-MedDRA Query-level view_] | `New Counts MedDRA Query ` | | [_New Counts-MedDRA Query-PT-level view_] 
This view returns new case counts of detected PTs for the _Product Family_ that are included in the given _MedDRA Query_. | `New Counts MedDRA Query (PT)` | | [_Cumulative Counts-MedDRA Query-level view_] | `Cumulative Counts MedDRA Query ` | | [_Cumulative Counts-MedDRA Query-PT-level view_]
 This view returns cumulative case counts of detected PTs for the _Product Family_ that are included in the given _MedDRA Query_. | `Cumulative Counts MedDRA Query (PT)` | | [_EBGM Counts-MedDRA Query-level view_] | `EBGM Counts MedDRA Query ` | | [_EBGM Counts-MedDRA Query-PT-level view_] 
This view returns EBGM case counts of detected PTs for the _Product Family_ that are included in the given _MedDRA Query_. | `EBGM Counts MedDRA Query (PT)` | ### Signal Calculations Table {#scenario-c-calculations} The following table displays the _Signal Calculations_ you must create:  | Signal Calculation to Create | Query Type | Calculation | Output Type | Signal View | Filter | | ---------------------------- | ---------- | ----------- | ----------- | ----------- | ------ | | _MedDRA Query_ level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | PT level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | PT level (Accidents and injuries) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Accidents and injuries) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query_ | _MedDRA Query ID_ > _Accidents and injuries_ | | PT level (Accidents and injuries) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Accidents and injuries_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | PT level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _New Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | PT level (Asthma/bronchospasm) | _SQL_ | N/A | _Statistical Data Record_ (or blank) | _Cumulative Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | _MedDRA Query_ level (Asthma/bronchospasm) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | | PT level (Asthma/bronchospasm) | _Advanced_ | _EBGM_ | _Statistical Data Record_ (or blank) | _EBGM Counts MedDRA Query (PT)_ | _MedDRA Query ID_ > _Asthma/bronchospasm_ | As all PT-level views are associated with a _MedDRA Query_ in this scenario, you must specify a _MedDRA Query_ filter value for the PT-level calculations as well.  ### Results {#scenario-c-results} For the PT-level [_Signal Calculations_][11], as each of these calculations has an _Output Type_ of _Statistical Data Record_ (or blank), Vault creates a _Statistical Data_ record for each new detected _Product Family_-PT combination, where the PTs also belong to the respective _MedDRA Query_. The following table lists the results in each PT-level _Statistical Data_ record:  | Statistical Data Record ID | Product Family | MedDRA Term | MedDRA Query | New Counts (Spontaneous) | Cumulative Counts (Spontaneous) | New Counts (Fatal) | Cumulative Counts (Fatal) | EBGM | | -------------------------- | -------------- | ----------- | ------------ | ------------------------ | ------------------------------- | ------------------ | ------------------------- | ---- | | _SD-0001_ | _Cholecap_ | _Accident at work_ | [Blank] | 3 | 19 | 0 | 1 | 1.12 | | _SD-0002_ | _Cholecap_ | _Animal Bite_ | [Blank] | 4 | 8 | 0 | 0 | 0.89 | | _SD-0003_ | _Cholecap_ | _Back Injury_ | [Blank] | 5 | 20 | 0 | 0 | 1.45 | | _SD-0004_ | _Cholecap_ | _Asthma exercise induced_ | [Blank] | 1 | 20 | 0 | 0 | 1.02 | | _SD-0005_ | _Cholecap_ | _Hyperventilation_ | [Blank] | 0 | 5 | 0 | 0 | 0.95 | | _SD-0006_ | _Cholecap_ | _Wheezing_ | [Blank] | 2 | 10 | 0 | 0 | 1.28 | The _Signal Calculations Setting_ in this scenario includes six PT-level _Signal Calculations_ (new counts, cumulative counts, and EBGM counts for each _MedDRA Query_). Vault returns detected PTs that exist for the given _Product Family_-_MedDRA Query_ combinations. In this scenario, Vault returns PTs for the following _MedDRA Queries_: * _Accidents and injuries_: * _Accident at work_ * _Animal Bite_ * _Back Injury_ * _Asthma/bronchospasm_: * _Asthma exercise induced_ * _Hyperventilation_ * _Wheezing_ For the _MedDRA Query_-level _Signal Calculations_, as each of these calculations has an _Output Type_ of _Statistical Data Record_ (or blank), Vault creates a _Statistical Data_ record for each _Product Family_-_MedDRA Query_ combination. The following table lists the results in each _MedDRA Query_-level _Statistical Data_ record:  | Statistical Data Record ID | Product Family | MedDRA Term | MedDRA Query | New Counts (Spontaneous) | Cumulative Counts (Spontaneous) | New Counts (Fatal) | Cumulative Counts (Fatal) | EBGM | | -------------------------- | -------------- | ----------- | ------------ | ------------------------ | ------------------------------- | ------------------ | ------------------------- | ---- | | _SD-0007_ | _Cholecap_ | [Blank] | _Accidents and injuries_ | 12 | 47 | 0 | 1 | 1.30 | | _SD-0008_ | _Cholecap_ | [Blank] | _Asthma/bronchospasm_ | 3 | 35 | 0 | 0 | 1.24 | The _Signal Calculations Setting_ in this scenario includes six _MedDRA Query_-level _Signal Calculations_ (new counts, cumulative counts, and EBGM counts for each _MedDRA Query_). [1]: #scenario-a [2]: #scenario-b [3]: #scenario-c [4]: #scenario-a-views [5]: #scenario-a-calculations [6]: #scenario-a-results [7]: #scenario-b-views [8]: #scenario-b-calculations [9]: #scenario-b-results [10]: #scenario-c-views [11]: #scenario-c-calculations [12]: #scenario-c-results