1     General Considerations

1     General Considerations

This section describes the implementation of the analysis dataset for QRS instruments as based on the Basic Data Structure (BDS) described in the Analysis Data Model Implementation Guide (ADaMIG). The ADaMIG can be found on the CDISC website at https://www.cdisc.org/standards/foundational/adam. The BDS was chosen as the model for analysis datasets of QRS instruments because it supports a wide variety of analyses, including summaries of total score by timepoint as well as change from baseline by timepoint. This data structure allows the ADaM variables PARAM and PARAMCD to come directly from Study Data Tabulation Model (SDTM) variables RS.RSTEST and RS.RSTESTCD, respectively, for individually captured items, thus ensuring traceability between SDTM and ADaM data. If other analyses are required that are not supported by the BDS, then consideration would be needed as to the appropriate structure. Analysis requirements always drive the design of the analysis datasets.

This ADaM supplement is based on the Acute Physiology and Chronic Health Evaluation II (APACHE II) Clinical Classification Supplement Version 2.0 to the SDTM Implementation Guide for Human Clinical Trials (SDTMIG). 

Note that source SDTM score values may not be suitable for analysis because the values may need to be imputed or transformed. In addition, recalculation of collected values may be needed per analysis rules. In these cases, the derivation of AVAL may not be a simple copying of RS.RSSTRESN. 

These specific analysis implementation details for the APACHE II are meant to be used in conjunction with ADaMIG. All completed questionnaires, ratings, and scales documentation can be found on the CDISC website at: This section describes the implementation of the analysis dataset for QRS instruments as based on the Basic Data Structure (BDS) described in the Analysis Data Model Implementation Guide (ADaMIG). The ADaMIG can be found on the CDISC website at https://www.cdisc.org/standards/foundational/adam. The BDS was chosen as the model for analysis datasets of QRS instruments because it supports a wide variety of analyses, including summaries of total score by timepoint as well as change from baseline by timepoint. This data structure allows the ADaM variables PARAM and PARAMCD to come directly from Study Data Tabulation Model (SDTM) variables RS.RSTEST and RS.RSTESTCD, respectively, for individually captured questions, thus ensuring traceability between SDTM and ADaM data. If other analyses are required that are not supported by the BDS, then consideration would be needed as to the appropriate structure. Analysis requirements always drive the design of the analysis datasets.

This ADaM supplement is based on the Acute Physiology and Chronic Health Evaluation II (APACHE II) Clinical Classification Supplement Version 1.1 to the SDTM Implementation Guide for Human Clinical Trials (SDTMIG). 

Note that source SDTM score values may not be suitable for analysis because the values may need to be imputed or transformed. In addition, recalculation of collected values may be needed per analysis rules. In these cases, the derivation of AVAL may not be a simple copying of RS.RSSTRESN. 

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qrs.

1.1   Representations and Warranties, Limitations of Liability, and Disclaimers

This document is a supplement to the ADaMIG and is covered under Appendix C of that document, which describes representations, warranties, limitations of liability, and disclaimers. Please see Appendix C of the ADaMIG for a complete version of this material.

CDISC does not endorse any QRS instrument and does not specify how to conduct clinical assessments, protocols, or analyses. CDISC disclaims any liability for your use of this material.

1.2   Copyright Status

CDISC believes this instrument to be in the public domain, but you should perform your own assessment. CDISC has included the APACHE II in the CDISC library of QRS data standards supplements. There may be many versions of this instrument in the public domain or copyrighted. CDISC has chosen to use the version attached to the QRS supplement to the SDTMIG, and the QRS supplement to the ADaMIG is based on the same version.

Note: CDISC Controlled Terminology is maintained by National Cancer Institute (NCI) Enterprise Vocabulary Services (EVS). The most recent versions of the SDTM and ADaM controlled terminologies should be accessed through the CDISC website (https://www.cdisc.org/

...

standards/

...

terminology).

1.

...

3   Known Issues

The Acute Physiology and Chronic Health Evaluation (APACHE II) is a severity of disease measurement and mortality estimation tool for adult subjects applied within 24 hours of admission to an intensive care unit (ICU). The instrument's intended use is for newly admitted subjects to the ICU. The instrument consists of individual items that are summed to create a total score. This instrument is generally collected once at Screening/Baseline. The total score is normally collected as part of the instrument with no instructions provided for handling missing data. In the majority of cases, where APACHE II is only assessed once and the collected total score used as a baseline covariate, the SDTM RS domain may be sufficient to support the analysis requirements. If this is the case, a variable in ADSL copied directly from a result/value in SDTM may be sufficient to support analysis needs.

The APACHE II total score is designed as a mortality prediction tool. It is not intended to influence the medical management or care of subjects during their ICU stay or to be calculated sequentially to show improvement or effect of interventions. The worst values recorded during the initial 24 hours in the ICU are recommended to be used in calculation of the total score but the measurements initially recorded during the subject’s admission can be used for practical reasons. 

Although the APACHE II total score is the most widely used ICU mortality prediction score, it has a number of limitations and shortcomings. The total score is not intended to be applied to specific populations such as liver failure or HIV subjects and is not accurate when dealing with subjects transferred from another unit or another hospital.

2     Rules and References

The primary source used in the development of this supplement is Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system [1].

...

This document is a supplement to the ADaMIG and is covered under Appendix C of that document, which describes representations, warranties, limitations of liability, and disclaimers. Please see Appendix C of the ADaMIG for a complete version of this material.

CDISC does not endorse any QRS instrument and does not specify how to conduct clinical assessments, protocols, or analyses. CDISC disclaims any liability for your use of this material.

Include this line only for supplements that the US FDA will be reviewing: Although the United States Food and Drug Administration (US FDA) has provided input with regard to this supplement, this input does not constitute US FDA endorsement of any particular instrument.  

1.2   Copyright Status

CDISC believes this instrument to be in the public domain, but you should perform your own assessment. CDISC has included the APACHE II in the CDISC library of QRS data standards supplements. There may be many versions of this instrument in the public domain or copyrighted. CDISC has chosen to use the version attached to the QRS supplement to the SDTMIG, and the QRS supplement to the ADaMIG is based on the same version.

Note: CDISC Controlled Terminology is maintained by National Cancer Institute (NCI) Enterprise Vocabulary Services (EVS). The most recent versions of the SDTM and ADaM controlled terminologies should be accessed through the CDISC website (https://www.cdisc.org/standards/terminology).

1.3   Known Issues

The Acute Physiology and Chronic Health Evaluation (APACHE II) is a severity of disease measurement and mortality estimation tool for adult patients applied within 24 hours of admission to an intensive care unit (ICU). The instrument consists of individual items that are summed up to create a total score. This instrument is generally collected once at Screening/Baseline and used as a predictor of mortality rather than an outcome measure. Individual items on this instrument are summed to create a total score but this total score is generally collected as part of the instrument with no instructions provided for handling missing data. In the majority of cases, where APACHE II is only assessed once and the collected total score used as a baseline covariate, the SDTM RS domain may be sufficient to support the analysis requirements.

2     Rules and References

The primary source used in the development of this supplement is Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Critical Care Medicine 1985; 13(10):818–29. The development of the GDS SHORT FORM is discussed in "Geriatric Depression Scale (GDS): Recent Evidence and Development of a Shorter Version"[2] by Drs. Sheikh and Yesavage. Validation and possible interpretations of the GDS SHORT FORM are discussed in "The Short Form of the Geriatric Depression Scale: A Comparison With the 30-Item Form."[3]

All links are valid and referenced information is current as of the date of this ADaMIG QRS supplement. This supplement does not make recommendations for the handling of missing data or adoption of imputation methods.

3     Scoring Software

There is no known publicly available scoring software as of the date of this ADaMIG QRS supplement.

4     Introduction to the Instrument   

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The APACHE II, is II is a severity-of-disease classification system that uses a point score based on the initial values of 12 routine physiologic measurements, age, and previous health status. Scores range from 0 to 71 and higher scores correspond to more severe disease and a higher risk of death. The composite score is based on findings represented in other SDTM domains such as Laboratory Test Results (LB) and Vital Signs (VS).

5     Key Data Checks

The computed total score consists of integer values ranging from 0 to 71. The classification system consists of 11 physiology measures based on a numeric rating scale ( 0 -4) where 0 reflects to 4,

6     Example

6.1   Background

Analyses based on ADaM datasets may vary depending on the sponsor, therapeutic area, and the needs of regulatory authorities in their decision-making processes. This fictional example is provided for illustrative purposes only. The ADaM dataset describing the analysis results from an instrument is based on the protocol and statistical analysis plan (SAP) for the individual study.

The example dataset described here is intended to support a variety of analyses, ranging from simple univariate summary statistics on both the actual total scores and change in total score from baseline by visit to other types of by-visit and repeated-measure analyses. For that reason, standard ADaM BDS variables such as AVAL (analysis value) and CHG (change from baseline) have been included in the example. In addition, because scores can be classified into categorizations of depression severity, frequency of subjects reporting each category may also be generated.

In the example presented here, it is assumed that the final GDS SHORT FORM analysis dataset (ADGDSSF) contains all of the original records, plus a record for the computed total score for each patient and assessment timepoint. The date of the assessment—and time of the assessment, if collected—should also be included in the dataset. For traceability, raw item-level responses from the SDTM QS.QSORRES variable, stored separately from the analysis variable AVAL, are included. Derivation type (DTYPE) should be used to clearly indicate those records where missing values or other information has been imputed. If useful for analysis, a summary analysis dataset which includes only the computed total score records may also be created.

This example is based on Yesavage's short form English scoring,[1] which states that if 5 or fewer instrument items are missing, the values of the missing items are imputed as the average of the non-missing responses. If the imputation procedure results in a total score that is not a whole number (e.g., 4.5, 10.2), the total score should be rounded up to the next whole number (i.e., round up to a more severe level of depression). For example, if 3 of the 15 items are missing and the total score based on the 12 non-missing items is 4, then impute the value of each of the 3 missing items as 4/12 = 1/3, for a total score of 4 + (3 * 1/3) = 4 + 1 = 5 (see the Parameter Value Level List - ADGDSSF [AVAL] table). If more than 5 items on the GDS SHORT FORM are missing, no item-level imputation is performed and a total score is not calculated. 

6.2   Example Analysis Dataset, Variable and Value-level Metadata

For Serum Creatinine, the measure is assessed on the same scale but double points are assigned for subjects with acute renal failure. The measure evaluating extent of impaired consciousness is calculated as 15 minus the Glasgow Coma Scale (GCS) Score, so that lower scores indicate mild or no impairment and higher scores represent more severe impairment (possible head and/or central nervous system injury) and range from 0 to 12. Chronological age is divided into age groups which are assigned values of 0, 2, 3, 5, or 6

For subjects with a history of severe organ system insufficiency or who are immunocompromised, a numeric rating of 2 or 5 is assigned for chronic health points, where 2 is assigned “for elective postoperative subjects” and 5 is assigned “for nonoperative or emergency postoperative subjects”. For subjects who do not have a history of severe organ system insufficiency or who are not immunocompromised, a NOT DONE record may be retained from the source RS domain with the conditional branching flag (RSCBRFL="Y") populated. Additionally, a sponsor may choose to set AVAL=0 for subjects who do not meet the criteria for assigning chronic health points. This decision must be clearly documented, as the analysis value of 0 is logically derived or implied.

6     Example

6.1   Background

Analyses based on ADaM datasets may vary depending on the sponsor, therapeutic area, and the needs of regulatory authorities in their decision-making processes. This fictional example is provided for illustrative purposes only. The ADaM dataset describing the analysis results from an instrument is based on the protocol and statistical analysis plan (SAP) for the individual study.

The example dataset described here is intended to support a variety of analyses, ranging from simple univariate summary statistics on the actual total scores to other types of by-visit and repeated-measure analyses. For that reason, standard ADaM BDS variables such as AVAL (analysis value) have been included in the example. In addition, although not illustrated in the example, the APACHE II total score can be divided into categories (e.g., <17, >=17) reflecting disease severity or risk of death, and the frequency of subjects reporting in each category may be generated or used for analysis.

In the example presented here, it is assumed that the final APACHE II analysis dataset (ADAPCH) contains all of the original records, plus a record for the computed total acute physiology score and a record for the computed total APACHE II for each subject and assessment timepoint. The date of the assessment—and time of the assessment, if collected—should also be included in the dataset. For traceability, raw item-level responses from the SDTM RS.RSORRES variable, stored separately from the analysis variable AVAL, are included. Derivation type (DTYPE) should be used to clearly indicate records where missing values have been imputed using sponsor-defined imputation methods. If useful for analysis, a summary analysis dataset which includes only the computed total score records may also be created.

6.2   Example Analysis Dataset, Variable and Value-level Metadata

The ADAPCH Dataset Metadata table shows an example of how the APACHE II may be implemented in ADaM. The dataset metadata is a recommendation for the dataset The ADGDSSF Dataset Metadata table shows an example of how the GDS SHORT FORM may be implemented in ADaM. The dataset metadata is a recommendation for the dataset name, label, structure, and keys. These can be modified for sponsor-specific standards and analyses. 

(Use the table macros to insert these tables. they reside at the end of the document like an appendix)

The ADGDSSF ADAPCH Variable Metadata table contains an example of analysis variable metadata for a subset of possible variables available for the GDS SHORT FORMAPACHE II. Example value-level metadata are found in the Parameter Value Level List - ADGDSSF [AVAL] metadata table. Derivations for AVALCAT1 and AVAL included in the Derivation column were obtained from the scoring instructions  for the GDS SHORT FORM[1] and are described in the Introduction to the Instrument section of this supplement. The ADGDSSF Variable ADAPCH metadata table. The ADAPCH Variable Metadata table does not include all of the possible variables that may be present in the Subject-Level Analysis Dataset (ADSL) and copied to the BDS structure analysis dataset, with the exception of the required STUDYID and USUBJID. For a complete list of available ADSL variables, consult the ADaMIG. Some ADSL variables (e.g., INVNAMREGION1) were included in this example for stratification, and are not required.  Additional Additional covariates or other variables may be added as needed for analysis. There is Common BDS variables such as BASE and CHG have been omitted from the example as the majority analyses of APACHE II do not use these variables. There is no specific ordering of variables recommended in this supplement. The SDTM variables were placed next to the corresponding derived ADaM variables for illustration purposes only. Update the below table according to the current QRS Short_Name instrument. 

The following SDTM variables can be copied into the corresponding equivalent ADaM variables. Note that the SDTM variable values can be converted to mixed case as needed for analysis purposes.  The Action column shown in the table below is optional, and can be removed if all values for these variables are simply copied over from SDTM.  For supplements where the SDTM values are modified, please provide a description of what was done.  For example, in the CHART-SF supplement, PARAM/PARAMCD are modified by replacing the version number with 'A', so that action is described here as "Harmonizing the two methods of administration (Paper and Interview) for individual items.  Fragment representing version number is changed to an 'A'."

...

SDTM Variable

...

ADaM Variable

...

QSTESTCD

...

PARAMCD

...

QSTEST

...

PARAM

...

QSCAT

...

PARCAT1

...

QSSTRESN

...

AVAL

...

All controlled terminology for instruments in both SDTM and ADaM is associated with a specific version of the instrument. When integrating responses from an instrument across studies, it is important to know which version of the instrument was used for each study. When multiple versions of the same instrument exist in an integration, a pooled analysis of responses across different versions can only be performed if determined to be clinically and statistically acceptable. In that case, sponsor-defined terminology, similar to CDISC Controlled Terminology but without the reference to a specific version, should be used for PARAMCD, PARAM and PARCATy.

...

The following SDTM variables can be copied into the corresponding equivalent ADaM variables. Note that the SDTM variable values can be converted to mixed case as needed for analysis purposes.  

All controlled terminology for instruments in both SDTM and ADaM is associated with a specific version of the instrument. When integrating responses from an instrument across studies, it is important to know which version of the instrument was used for each study. When multiple versions of the same instrument exist in an integration, a pooled analysis of responses across different versions can only be performed if determined to be clinically and statistically acceptable. In that case, sponsor-defined terminology, similar to CDISC Controlled Terminology but without the reference to a specific version, should be used for PARAMCD, PARAM and PARCATy.

6.3   Example Analysis Dataset 

The APACHE II Analysis Dataset tables below show the terminology and variables for implementing the example analysis dataset for this instrument in the BDS. This specific example is taken from a Phase II, randomized, controlled, open label multi-center study to assess the efficacy and safety of Drug A for the treatment of SARS-CoV-2 infected subjects with COVID-19 pneumonia and impaired respiratory function. The primary outcome measure is APACHE II Severity of Disease Score on Day 15 or on the Day of Discharge (whichever is earlier). This measure compares "Drug A + SOC" with "SOC" (SOC = Standard of Care). 

In this example, the APACHE II was measured within 24 hours of ICU admission, on or before Day 1 (prior to implementation of treatment), Day 7, and Day 15 or on the day of discharge (whichever was earlier). In the example, as per the SAP, subjects who died on Day 15 or earlier were assigned the highest observed APACHE II score of any of the subjects at any time during the trial (worst case imputation for deaths). This imputation method is for example purposes only and not meant to be a recommendation nor considered a common practice. Missing data values for the parameters required for the derivation of the APACHE II score were replaced by the last available assessment. Item level imputation, in this example, is handled by the investigators and/or clinicians at the site and is considered source data, already captured in SDTM. SOC included a variety of supportive therapies that ranged from the administration of supplementary oxygen to full intensive care support, alongside the use of antiviral treatment, convalescent plasma, corticosteroids, antibiotics or other agents.

In the example, the

...

Variable

...

Where

...

Type

...

Controlled Terms

...

Source

...

Derivation

...

User Notes

...

AVAL

...

PARAMCD NE "GDS02TS" (GDS02- Total Score - Analysis)

...

Num

...

AVAL

...

PARAMCD EQ "GDS02TS" (GDS02- Total Score - Analysis)

...

Num

...

The sum of QS.QSSTRESN for QS.QSTESTCD in ("GDS0201"-"GDS0215") if no question are missing.

• If ≤5 responses are missing on an instrument, then AVAL is 15*(sum of non-missing QS.QSSTRESN for QS.QSTESTCD in ("GDS0201"-"GDS0215")/number of non-missing questions for QS.QSTESTCD in ("GDS0201"-"GDS0215"). If the result is a fraction, round up to the nearest integer.
• If >5 responses are missing, do not calculate a total score, and do not create a total score record.

6.3   Example Analysis Dataset 

The GDS SHORT FORM Summary Analysis Dataset table shows the terminology and variables for implementing the example analysis dataset for this instrument in the BDS. This specific example is taken from a multicenter, randomized, double-blind, active-controlled parallel design study conducted in elderly patients with major depressive disorder. The purpose of the analysis is to compare the effect of Drug A to Drug B on depression in elderly patients using the GDS SHORT FORM to construct an endpoint. All analyses are conducted on an intent-to-treat basis, and the planned duration of treatment is 5 months. The baseline measurement is defined as the last non-missing value collected at or prior to the start of treatment; change from the last non-missing post-baseline value to baseline is used to construct an endpoint. The SAP specifies that planned collected visits, including baseline measurements, are to be used in analyses and displays of results. In fact, whereas no unscheduled visits appear only in listings. The total score records for 1 subject were collected at 3 visits, plus a derived last observed value (LOV) endpoint record for the GDS SHORT FORM. Visit 1 is remapped to AVISIT = "BASELINE". There are 2 visits at AVISIT = "VISIT 2". However, because 1 visit was unscheduled, it is not used in the analysis and the ANL01FL value is null. Visits 5 and 6 are missing because the subject discontinued early due to an adverse event unrelated to treatment.

Update the below dataset and title according to the current QRS Short_Name instrument.  

GDS SHORT FORM Complete Analysis Dataset

exist in the source data. If the planned physiology assessment is not done or invalid, the investigator may choose to use a previous or repeat assessment of that parameter as the value at that visit for the scoring of APACHE II. The records for 2 subjects are shown in the example datasets. The data for 3 visits is shown for the first subject, with no missing data. The data for 1 visit is shown for the second subject, who died before the Day 15 (Day of Discharge) Visit so the APACHE II total score is imputed to the worst case value of any subjects across any timepoints at that visit. Note that the worst case value is not shown in the sample data.

APACHE II Complete Analysis Dataset

The APACHE II Complete Analysis Dataset table shows all of the individual item The GDS SHORT FORM Complete Analysis Dataset table shows all of the individual question responses for this example, as well as the computed total Acute Physiology score and the computed total APACHE II score. This example is considered to be the final analysis dataset for submission. Computed total scores can appear after the individual item responses, with appropriate labels for identification.

GDS SHORT FORM

2012-11-16

0

GDS02-Dropped Activities and Interests

GDS SHORT FORM

DR. JOHN SMITH

GDS02-Life Is Empty

GDS SHORT FORM

NO

0

GDS SHORT FORM

GDS02-Good Spirits Most of Time

GDS SHORT FORM

DR. JOHN SMITH

GDS02-Afraid of Something Bad Happening

GDS SHORT FORM

GDS02-Feel Happy Most of Time

GDS SHORT FORM

2012-11-16

16NOV2012

1

NO

1

DR. JOHN SMITH

GDS02-Often Feel Helpless

GDS SHORT FORM

GDS02-Prefer to Stay Home

GDS SHORT FORM

2012-11-16

0

GDS SHORT FORM

DR. JOHN SMITH

GDS02-Wonderful to Be Alive

GDS SHORT FORM

2012-11-16

16NOV2012

1

NO

1

GDS SHORT FORM

YES

1

GDS02-Feel Full of Energy

GDS SHORT FORM

BASELINE

0

2012-11-16

16NOV2012

1

YES

0

GDS02-Feel Hopeless

GDS SHORT FORM

DR. JOHN SMITH

GDS02-Most People Better Off Than You

GDS SHORT FORM

0

GDS SHORT FORM

DR. JOHN SMITH

GDS02-Satisfied With Life

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

0

GDS02-Dropped Activities and Interests

GDS0202

2

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

0

GDS02-Life Is Empty

GDS0203

3

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

0

19

GDS02-Bored Often

GDS0204

4

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

1

DR. JOHN SMITH

GDS02-Good Spirits Most of Time

GDS0205

5

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

1

GDS02-Afraid of Something Bad Happening

GDS0206

6

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

1

DR. JOHN SMITH

GDS02-Feel Happy Most of Time

GDS0207

7

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

1

GDS02-Often Feel Helpless

GDS0208

8

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

1

GDS02-Prefer to Stay Home

GDS0209

9

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

0

GDS02-Memory Problems

GDS0210

10

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

0

GDS02-Wonderful to Be Alive

GDS0211

11

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

1

DR. JOHN SMITH

12

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

1

GDS02-Feel Full of Energy

GDS0213

13

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

0

GDS02-Feel Hopeless

GDS0214

14

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

YES

1

DR. JOHN SMITH

GDS02-Most People Better Off Than You

GDS0215

15

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

NO

0

GDS02- Total Score - Analysis

GDS02TS

16

GDS SHORT FORM

VISIT 2

2

VISIT 2

2

2012-12-15

15DEC2012

30

8

Possible Depression

10

-2

Y

GDS02-Satisfied With Life

GDS0201

1

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

0

GDS02-Dropped Activities and Interests

GDS0202

2

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

0

GDS02-Life Is Empty

GDS0203

3

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

1

34

GDS02-Bored Often

GDS0204

4

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

1

GDS02-Good Spirits Most of Time

GDS0205

5

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

1

GDS02-Afraid of Something Bad Happening

GDS0206

6

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

1

DR. JOHN SMITH

DRUG A

GDS02-Feel Happy Most of Time

GDS0207

7

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

0

101

GDS02-Often Feel Helpless

GDS0208

8

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

1

DR. JOHN SMITH

GDS02-Prefer to Stay Home

GDS0209

9

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

0

GDS02-Memory Problems

GDS0210

10

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

0

GDS02-Wonderful to Be Alive

GDS0211

11

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

1

DR. JOHN SMITH

12

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

1

GDS02-Feel Full of Energy

GDS0213

13

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

0

GDS02-Feel Hopeless

GDS0214

14

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

YES

1

GDS02-Most People Better Off Than You

GDS0215

15

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

NO

0

GDS02- Total Score - Analysis

GDS02TS

16

GDS SHORT FORM

UNSCHEDULED 2.01

2.01

UNSCHEDULED 2.01

2

2012-12-28

28DEC2012

43

9

Possible Depression

10

-1

GDS02-Satisfied With Life

GDS0201

1

GDS SHORT FORM

VISIT 3

3

VISIT 3

3

0.46

AVERAGE

GDS02-Dropped Activities and Interests

GDS0202

2

GDS SHORT FORM

VISIT 3

3

VISIT 3

3

0.46

AVERAGE

GDS02-Life Is Empty

GDS0203

3

GDS SHORT FORM

VISIT 3

3

VISIT 3

3

2013-01-12

12JAN2013

58

NO

0