Naval Submarine

NSMRL REPORT 1181

Medical Research Laboratory

2 SEPTEMBER 92

TRIAL OF A COMPUTER BASED PROGRAM

FOR THE DIAGNOSIS OF ABDOMINAL PAIN

IN MALES

by

P L. Perrotta

and

D. M Stetson

Released by

R. G. Walter, CAPT, DC, USN

Commanding Officer

Naval Submarine Medical Research Laboratory

Approved for public release; distribution unlimited
TRIAL OF A COMPUTER BASED PROGRAM

FOR THE DIAGNOSIS OF ABDOMINAL PAIN IN

MALES

by

Peter L. Perrotta and Douglas M. Stetson

Naval Submarine Medical Research Laboratory

Report 1181

Naval Medical Research and Development Command

Work Unit 63706N M0095.005-5010

Released by

R. G. Walter

Commanding Officer

Approved for public release; distribution unlimited
SUMMARY PAGE

PROBLEM:

To verify the knowledge base of the NSMRL abdominal pain program in previously healthy

males.

FINDINGS:

Overall diagnostic accuracy of the program was found to be 69% compared to the 80% accuracy

rate of emergency room physicians. Sensitivity and specificity for distinguishing surgical from

non-surgical cases was 56% and 85% respectively. Additional measures of program performance are presented.

APPLICATION:

These results can assist in the decision whether to implement this diagnostic program for fleetwide use. Recommendations are given for additional efforts in medical diagnostic software.

ADMINISTRATIVE INFORMATION

This investigation was conducted under Naval Medical Research Development Command

Research Work Unit 63706N-M0095.005-5010. The views expressed in this report are those of

the authors and do not reflect the official policy or position of the Department of the Navy,

Department of Defense, or the U. S. Government. This report was approved for publication on

2 September 1992 and designated Naval Submarine Medical Research Report 1181.

ii
Abstract

This report presents and evaluates data collected in 1988 in an effort to verify the NSMRL abdominal pain diagnostic program. Overall diagnostic accuracy of the program was found to be

69% compared to the 80% accuracy rate of emergency room physicians. Sensitivity and

specificity for distinguishing surgical from non-surgical cases was 56% and 85% respectively.

Additional measures of performance of the abdominal pain program are presented along with the

limitations of the data set and recommendations for future validation efforts.

iii
TRIAL OF A COMPUTER BASED PROGRAM

FOR THE DIAGNOSIS OF ABDOMINAL PAIN

IN MALES

emergency rooms of two Naval

hospitals. Although the Navy hospital

emergency rooms see large numbers

of patients, the minority are Naval

personnel on active duty. In order to

gather a reasonable number of cases

in a shorter period of time, clinical data

was collected from family members

presenting to the emergency room as

well as from active duty personnel.

From this group of patients, only

information about males in the same

age range as submariners and whose

medical history would not disqualify

them from submarine duty would be

used as test data for evaluation of the

abdominal pain program.

Methods

Data Collection

With the approval of the hospital

commanders and the individual

patients involved in the study,

specially hired clerks collected

information from patients during

emergency room visits. All were

college students with a background in

biological sciences. The clerks

avoided delaying care of patients with

acute medical problems and

burdening the hospital staff. They

selected for interview all patients who

listed abdominal pain as part of their

reason for seeking care when they

presented themselves to the

emergency room staff. The clerks

covered the time period from 8:00 AM

to 12:00 midnight.

NSMRL investigators trained the

Background

The Naval Submarine Medical

Research Laboratory (NSMRL)

developed several computer based

diagnostic programs between 1970

and 1988 to be used as diagnostic

aids for corpsman and health care

practitioners in remote duty stations.

One of these (1,2), based on a

Bayesian knowledge base developed

in England (3), assisted in the

diagnosis of acute abdominal pain.

The original algorithm was then

modified for an active duty population

(young healthy males presenting

within 48 hours of illness) (4). A

computer program incorporating this

modified knowledge base was

developed and tested by the

knowledge-base authors in England

using locally obtained clinical data as

well as data obtained from a Navy

hospital in 1980.

In an effort to conduct independent verification of the program's

performance in the hands of

submarine independent duty hospital

corpsmen, NSMRL undertook a study

collecting abdominal pain case data

from submarines at sea. Five years of

data collection at sea yielded very few

cases, largely because submarine

sailors are generally in good health

and carefully screened prior to

deployment (5).

To collect a larger number of cases,

the laboratory undertook a prospective

study in 1988 collecting data from the

1
clerks in use of the abdominal pain

program on portable computers and

provided the clerks with blank data

forms for use in collecting data from

individual patients. When a patient

complaining of abdominal pain visited

the emergency room, a clerk would

collect medical history information

from the patient directly, recording the

results on the data forms. The clerk

would then accompany the patient and

observe the interview and examination

by the emergency room physician. If

at any time a patient requested the

clerks not be present for the interview

or examination, the clerks would leave

and not include this information in the

study database. By observing the

interview and examination conducted

by the physician, the clerk completed

the data collection form. On those

occasions where urgency prevented

the clerk from conducting independent

history taking, the history was

gathered from the observation

process. When the information

gathered by observation was

insufficient to complete the data form,

the clerks would query the examining

physician for the missing information.

If the physician was too busy to

provide information, the clerk would

review the written emergency

treatment record to fill in missing

items. Cases which had missing items

were discarded.

At a later time the clerk entered the

information from the data forms into

the abdominal pain computer program

to create a database showing patient

information and computer results.

Those cases which had insufficient

information to make a diagnosis were

not included in the computer

database. In addition, the clerks kept a

written log showing the patients and

the diagnoses assigned at the

emergency room along with a contact

telephone number.

Several weeks to months after the

patients were seen in the emergency

rooms, a clerk or an investigator

contacted each one by telephone to

inquire whether subsequent events

had cast doubt on the emergency

room diagnosis. If the patient was not

seen again for the same problem, the

emergency room diagnosis was taken

to be confirmed. If a patient was

admitted to the hospital the discharge

diagnosis was recorded as the

confirmed diagnosis for the

emergency room visit. The written log

was annotated to reflect the confirmed

diagnoses and patients lost to followup.

Data Review

Case acceptance criteria

Prior to evaluation of any data,

acceptance and exclusion criteria

were determined. The criteria were

selected to mirror those used by the

developer of the knowledge base

upon which the abdominal pain

diagnostic system rests (4). These

criteria were: male patients age 17-

50, who presented to the emergency

room with a complaint of abdominal

pain and who had no chronic illness

which would have been disqualifying

for submarine service.

Case categorization criteria

The abdominal pain diagnostic system

considers only six diagnoses (Table 1:

appendicitis, perforated duodenal

ulcer, small bowel obstruction,

cholecystitis, renal colic, and nonspecific abdominal pain). The

2
program classifies all cases submitted

into one of these categories. de

Dombal (4) previously described how

the program categorizes less common

conditions based on his experience.

Categorization of common conditions

rests on professional judgment of the

reviewers. For example, viral

gastroenteritis is placed in the nonspecific category.

Table 1. Diagnoses Considered by Abdominal Pain Program

Diagnosis Abbreviation

Non-Specific Abdominal Pain NSAP

Appendicitis APPY

Cholecystitis CHOL

Perforated Duodenal Ulcer PDU

Renal Colic RENC

Small Bowel Obstruction SBO

Case grouping

In this analysis, diagnoses were

grouped according to usual treatment

requirements. For the present

evaluation, diagnoses of appendicitis,

perforated duodenal ulcer, and small

bowel obstruction were categorized as

surgical; diagnoses of renal colic,

cholecystitis, and non-specific

abdominal pain were categorized as

non-surgical. This distinction was

made because the most important

decision to be made aboard

submarines is often the decision to

seek medical evacuation and definitive

care.

Data verification

Data analysis was conducted based

on a composite database comprising

elements of other files. To ensure its

accuracy, and before relying on

derivative databases, the source

documents (log books prepared at

Portsmouth and San Diego) were

reviewed to ensure accurate

transcription. Each male case in the

17-50 year old age range was

reviewed in a written log. The

emergency room and confirmed

diagnoses were verified when present,

and their absence was specifically

noted in the composite database.

Each log diagnosis was categorized

into one of the six diagnostic

categories considered by the program.

Rare diagnoses were categorized

according to de Dombal's guidance as

previously described. Cases regarded

as chronic or occurring in patients

having medical conditions

incompatible with submarine service

were excluded.

Database Management

Initially, a computer database was

prepared on site at each study

hospital. This record contained the

elements of the patient descriptions

recorded by the clerks. These

3
databases were examined to ensure

that derivative records, used to create

the composite database, were

complete and accurate. When

questions about the source data

arose, these source files could often

be used to ensure accuracy of the

results. Data taken directly from the

site databases were used as entries in

the abdominal pain diagnostic

program to observe whether the

program's output was faithfully

recorded in derivative databases.

Statistical Analysis

As noted, only cases identified as

male, age 17-50 years, presenting to

the emergency room with abdominal

pain and not evincing chronic

conditions which would have

disqualified them from submarine duty

were analyzed.

All statistical work was done using

SPSS-PC, drawing on the cases

contained in the composite database.

The test data set was subjected to

frequency analysis of individual

diagnoses, distribution of computer

generated diagnostic frequencies

against individual diagnoses, and

cross tabulation of computer

diagnoses against either the final

diagnosis for each case or the

emergency room diagnosis. For

purposes of comparison, the

emergency room diagnoses were also

compared with the final diagnoses

when both were known.

Based on the cross tabulation data,

diagnostic accuracy (percentage of

diagnoses "correct") and

sensitivity/specificity for each

diagnosis was calculated. Chi-square

analysis was performed including

calculation of Cramer's V coefficient,

Goodman and Kruskal's tau

(percentage reduction in error), and

Cohen's kappa (measure of

agreement).

Results

The initial data collected at the two

Naval hospitals yielded 616 total

cases (Table 2). Of these, less than

one-half were male (34%). Additional

cases were excluded in accordance

with the pre-established criteria (age

17-50, presenting with abdominal

pain, and with no illness disqualifying

for submarine duty). A total of 146

cases remained for analysis. All

remaining results refer to the test set

of males, age 17-50, with no chronic,

submarine disqualifying illness.

Table 2. Preliminary Categorization of Test Data

Number of Cases Percent of Cases

Total Collected (both sites) 616 100

Male 208 34

Age 17-50 171 28

Abdominal Presentation 153 25

No disqualifying illness 146 24

4
cases (43.2%) was Non-Specific

Figure 1 presents the disease Abdominal Pain, the remaining

distribution of the cases analyzed. disease categories included few

Confirmed diagnoses are reported for cases. The category "NONE"

those cases with adequate follow-up, represents cases that had no

Initial diagnosis refers to the diagnosis emergency room diagnosis or no

made by the emergency room confirmed diagnosis.

physician during the initial patient

encounter. The largest category of

Figure I

Distribution of Cases

100

90

80

70

60

# of Cases 50

40

30

20

10

0

Diagnostic Accuracy

The overall accuracy of the abdominal

pain diagnostic system was

determined by dividing the number of

cases the computer correctly

categorized by the number of cases

attempted. Both the confirmed

diagnosis and the emergency room

diagnosis were separately considered

as the correct diagnosis. The accuracy

of the diagnostic program was 69%

when compared to either the final

diagnosis or the emergency room

diagnosis (Table 3). By comparison,

the accuracy of the emergency room

physician on initial examination was

80%.

5

C onfirmed Cases

Initial Cases

NONE NSAP APPY CHOL PDU RENC SBO

Disease Category
Table 3. Diagnostic Accuracy of Program

Comparison Bases Accuracy (%)

Computer Dx -vs- Final Dx 69

Computer Dx -vs- Emergency Room Dx 69

ER Physician Dx -vs- Final Dx 80

Sensitivity and Specificity

The sensitivity of the abdominal pain

diagnostic system for the diagnosis of

appendicitis was determined because

appendicitis is the most common

abdominal medical condition requiring

evacuation and surgical intervention.

Sensitivity is defined as the true

positive rate for the diagnosis (the

fraction of those patients with a

diagnosis of appendicitis correctly

identified by the computer as having

the diagnosis). The specificity of the

abdominal pain diagnostic system is

defined as the true negative rate for a

diagnosis (the fraction of those

patients not diagnosed with a

particular illness who were correctly

identified as not having that illness).

For the diagnosis of appendicitis the

computer program's sensitivity and

specificity were 46% and 86%

respectively (Table 4). Emergency

room physicians sensitivity was 83%

for comparison.

Table 4. Sensitivity and Specificity for Diagnosis of Appendicitis

Sensitivity Specificity

Computer vs. Confirmed Dx 0.46 0.86

Computer vs. Emergency Room Dx 0.50 0.94

Physician vs. Confirmed Dx 0.83 0.83

Cross tabulation data

Cross tabulations were prepared

comparing the computer diagnostic

performance with confirmed

diagnoses and emergency room

diagnoses (Tables 5,6,7). Several

statistics describe the relationship

between the observed results (from

the computer) and the expected

results (either the confirmed

diagnoses or the emergency room

diagnoses) were calculated. Chisquare with Cramer's V coefficient

was used to account for sample size

when comparing group differences.

As Cramer's V coefficient approaches

1 the probability that chance accounts

for the differences between samples

6
Final Dx NSAP APPY CHOL PDU RENC SBO

falls. Calculation of proportional reduction of error (the Goodman and

Kruskal tau) and a measure of

agreement (Cohen's kappa) were

calculated (Table 8).

Tau is used as a measure of the

benefit of using the diagnostic

program over methods based on

knowledge of the underlying disease

prevalence and varies between 0 and

1. If there is no benefit from using the

information about distribution of test

categories over outcome categories,

tau is zero. The significance reported

with tau is the probability that tau is

zero.

Cohen's kappa is an additional

method of evaluating the level of

agreement between the computer

program and the emergency room physicians. The program and

emergency room physicians

categorized 80% (66 out of 82) of the

cases identically but this calculation

does not account that there will be

some fraction of agreement even if

both groups assigned diagnoses at

random. The random agreement

proportion is eliminated by noting the

fraction of cases each observer places

in each category and determining how

many cases would be randomly

assigned to the same category on that

basis. Kappa ranges from 0 to 1, with

1 being associated with total

agreement between the program and

the physicians. Comparing the

abdominal pain program with

emergency room physicians, kappa is

56%.

Table 5. Computer Diagnosis vs. Confirmed Diagnosis

Totals

61

16

0

0

5

1

Computer Dx

NSAP

APPY

CHOL

PDU

RENC

SBO

50

10

0

0

3

0

6

6

0

0

0

1

1

0

0

0

1

0

1

0

0

0

0

0

1

0

0

0

1

0

2

0

0

0

0

0

Totals 63 13 2 1 2 2 83

7
Table 6. Computer Diagnosis vs. Emergency Room Diagnosis

Initial Dx NSAP APPY CHOL PDU RENC SBO

Totals

Computer Dx

NSAP

APPY

CHOL

PDU

RENC

SBO

Totals

79

7

0

0

4

1

16

17

0

0

0

1

2 1 4 7

0 0 0 0

0 0 0 0

0 0 0 0

0 1 4

0 0 0

91 34 2 2 8

Table 7. Physicians Diagnosis vs. Confirmed Diagnosis

Final Dx NSAP APPY CHOL PDU RENC SBO

Totals

Physician's Dx

NSAP 52 1 2 0 0 0 55

APPY 9 10 0 0 1 0 20

CHOL 0 0 0 0 0 0 0

PDU 0 0 0 1 0 0 1

RENC 2 1 0 0 1 0 4

SBO 0 0 0 0 0 2 2

Totals 63 12 2 1 2 2 82

Table 8. Statistical Summary

Chi-square Significance Cramer's V tau kappa

Computer vs. Final Dx 28 0.02 0.33 0.10 -

Computer vs. ER Dx 71 - 0.28 0.08 0.36

Physician vs. Final Dx 203 - 0.78 0.39 0.56

Grouped Data (Surgical versus Nonsurgical Cases)

Similar calculations were performed

after grouping cases based on

therapeutic implication into either

surgical (appendicitis, perforated

ulcer, small bowel obstruction) or nonsurgical (non-specific abdominal pain,

renal colic, cholecystitis) (Table 9).

Diagnostic accuracy of the program

8

109

24

0

0

9

2

144

0

0

7
improved to 77% when data was

grouped but sensitivity of the

computer program for surgical

diagnoses remained low at 43%

(reflecting that most of the cases

correctly categorized as "surgical"

were appendicitis cases).

Table 9. Sensitivity and Specificity for Diagnosis of Surgical Cases

Accuracy Sensitivity Specificity

Computer vs. Confirmed Dx 77% 0.43 0.85

Computer vs. Emerg. Room Dx 77% 0.41 0.92

ER Physician vs. Confirmed Dx 85% 0.86 0.85

Computer generated probabilities are

compared in Figure 2 for the grouped

data. Both the final confirmed

diagnosis and emergency room

diagnosis are considered. The mean

computer-generated probability is

indicated as well as +/- one standard

deviation. For non-surgical cases

there is little overlap in assigned

probability for surgery required or no

surgery required. But for surgical

cases the overlap is substantial,

indicating that the program generally

categorizes non-surgical cases

properly, but often mischaracterizes

surgical cases as non-surgical.

Probabilities

Figure 2

by Diagnosis (Grouped)

0

5.

100

90

80

70

60

50

40

30

20

10

0

±

p-NOS URG p-SURG p- NOS URG p-SURG

NOSURG SURG

Final Diagnosis

Discussion

Comparison to de Dombal's Findings

The de Dombal final report (4)

described testing of the delivered

Bayesian matrix. Three types of data

were used to test the matrix: (a)

p-NOS URG p-S URG p-NOS URG p-S URG

NOSURG SURG

Inilal Diagnosi

cases which had been used to create

the knowledge base matrix (b)

additional cases from de Dombal's

data file in England and (c) cases

collected from Naval Hospital San

Diego (cases different than those of

this study). Testing was conducted

against the original knowledge base

9

-is D
(3) and a knowledge base modified for

the submarine community (4). These

modifications included assigning equal

conditional probabilities to all vital sign

data and to the findings of rigidity and

bowel sounds, and developing new

conditional probabilities for signs and

symptoms in a male patient population

with no chronic conditions who had

presented for care for abdominal pain

beginning within the past 12 hours.

The knowledge base was most

effective when prior probabilities were

also specified. Appendix A lists the

prior probabilities used by the program

and the conditional probabilities for

each piece of clinical information. The

overall accuracy of the abdominal pain

diagnostic system reported in de

Dombal's final report when tested

against Navy data was 73%. The

Navy case data used (Table 10)

consisted of 141 cases and included

few instances of diagnoses other than

NSAP and APPY. de Dombal

calculated accuracy as number of

cases "correct" out of total tested. In

the group above, the diagnoses of

NSAP and DYSPepsia were

considered equivalent and grouped

together. The test set used in our

analysis is similar in size (145) and

contains a majority of NSAP

diagnoses, a smaller number of

appendicitis cases, and few cases of

the remaining diagnoses. These

results are comparable to those

obtained with the present data set,

where overall accuracy is 69%.

Table 10. Summary of de Dombal's Final Report

Final Dx APPY NSAP DYSP RENC CHOL SBO DVRT OTHER

Computer Dx

APPY

NSAP

DYSP a

RENC

CHOL

PDU

SBO

25

2

0

0

0

0

0

Totals 27

18

49

8

1

1

1

2

80

1

3

10

0

0

0

1

15

0

0

0

4

0

0

0

4

0

2

2

0

2

0

0

6

1

0

0

0

0

0

3

4

0

0

1

0

0

0

0

1

a. The NSMRL program sums

NSAP in its output.

the probability of dyspepsia and NSAP and presents the total as

There are differences between the

sensitivity and specificity for the

diagnosis of appendicitis between de

Dombal's report of the older San

Diego data and the present test set

(Table 11). The program's sensitivity

in diagnosing cases of appendicitis

was substantially better in the prior

test set (92%). We know of nothing to

explain this difference.

10

2

1

0

0

1

0

0

4
Table 11. Comparison With Previously Obtained Naval Data For Appendicitis

Sensitivity Specificity

Previous Data 0.92 0.80

Report Data 0.46 0.86

Limitations of the data

There are two major differences

between the data in de Dombal's

analysis and the present test set.

Firstly, the source data was collected

differently. de Dombal reports that

hospital corpsmen collected the data

he used. This suggests the data was

collected by the person taking the

history and performing the

examination. The data of the present

test set was collected by a third party

with limited medical experience

observing physicians. Secondly, the

diagnostic probabilities were created

by programs using different prior

probabilities. The differing prior

probabilities may interfere with the

appendicitis diagnosis.

Another problem, extending to both

data sets, is the inadequate numbers

of cases in any but the NSAP

category. Because of difficulties in

verification of final diagnoses a large

number of the cases collected in 1988

were excluded. A small number of

additional cases had to be excluded

because of uncertainty about the

actual data included in the original

files.

Recommendations for Further Study

Based on these results, it is not

possible to access the clinical

adequacy of the NSMRL abdominal

pain diagnostic program. Certainly the

program performed poorly with the

cases of appendicitis (sensitivity of

46%). The program also had difficulty

distinguishing surgical from nonsurgical cases. Without the presence

of pre-established criteria for

acceptance or rejection of a diagnostic

system it is difficult to make a

definitive statement regarding the

suitability of a program for clinical use.

Currently, there are no accepted

standards of performance for medical

diagnostic systems prior to

deployment in the Navy.

Knowledge verification may take many

forms. These include review by

experienced practitioners and trial

against accumulated prospective or

retrospective cases. A "goldstandard" test of verification against

which other methods could be

compared would require the testing of

the system against cases

prospectively gathered as was

attempted in this study. Certain goals

should be identified prior to data

collection. This would include the

minimum number of cases that should

be collected for each diagnosis

considered by the program. It is

difficult to estimate the number

necessary, but it is likely that a

minimum of 20 to 30 cases of the less

common illnesses would be desired.

Once collected, these prospective

cases could also be used to alter the

existing knowledge base by changing

11
either the conditional probabilities or

the disease prevalence information

(prior probabilities of disease) in the

database. They could also be used to

create a competing expert system

based on a different technique (e.g.

neural network, discriminate analysis,

etc) and comparing it to the existing

system.

Clinical case data collection is a

difficult task and requires careful

planning which includes establishing

criteria for study subject participation,

completeness of records, and

procedures for follow-up to confirm the

initial diagnosis. These criteria will

reduce case selection bias. Data

would probably be more reliable if it

was collected by medical practitioners

because of the difficulty in performing

and interpreting certain clinical tests

(e.g. the elicitation of rebound

tenderness takes considerable

experience). Case data should be

reduced to machine readable format

daily and reviewed on a frequent

basis. The inpatient and outpatient

diagnoses should be coded by a

medical records professional to

reduce ambiguity. This would require

an aggressive effort to maintain

contact with clinicians, patients, and

medical record personnel.

The data set presented suffered

because of the large number of cases

lost to follow up. Transcription errors

may cast further doubt on the

reliability of data, especially since the

data set is small. Certainly one

confirmed case of perforated duodenal

ulcer is inadequate for testing. The

number of cases could be increased

by collaborating with other large

medical centers, both civilian and

government. Further involvement with

multi-center groups interested in the

development and testing of medical

expert systems could provide

additional case data.

References

1. Southerland DG. ABDX A

Decision Support System for the

Management of Acute Abdominal

Pain Version 3.0 Programmer's

Manual, NSMRL Report 1148,

1989.

2. Caras BC, Southerland DG,

Fisherkeller KD. Medic-Abdominal

Pain User's Manual, NSMRL Report

1146,1989.

3. de Dombal FT, Leaper DJ,

Staniland JR, McCann AP,

Horrocks JC. Computer-Aided

diagnosis of acut'e abdominal pain.

British Medical Journal 1972;2.

4. de Dombal FT. Modification of the

de Dombal computer-based system

for diagnosis of abdominal pain to

optimize its accuracy when applied

to the United States Naval

Submarine Population, Final report

on U.S. Navy Contract No. N68171 -

79-C-9602.

5. Osborne S.F. Computer-assisted

diagnosis of abdominal pain:

Interim Report - July 1982-

September 1983. NSMRL Report

No. 1012, 1983.

12
APPENDIX A

Prior Probabilities of Disease used bv the NSMRL Proaram

Dyspepsia is added to the non-specific abdominal pain category for reporting of results.

Disease

Appendicitis (APPY)

Non-Specific Abdominal Pain (NSAP)

Renal Colic (RENC)

Perforated Duodenal Ulcer (PDU)

Cholecystitis (CHOL)

Small Bowel Obstruction (SBO)

Dyspepsia (DYSP)

Prior Probability

0.18

0.54

0.03

0.01

0.05

0.03

0.16

Conditional Probabilities for Sign/Symptom Complex

Entries range from 0.1 to 99. The program will not accept conditional probabilities of 0

accounting for 0.1 values. The complete matrix is included although certain information

(e.g., females, age >60) are not relevant to our study.

Sign or Symptom

1. MALE

2. FEMALE

3. AGE 0-9

4. AGE 10-19

5. AGE 20-29

6. AGE 30-39

7. AGE 40-49

8. AGE 50-59

9. AGE 60-69

10. AGE >69

11. PAIN ONSET

12. PAIN ONSET

13. PAIN ONSET

14. PAIN ONSET

Conditional Probability

APPY NSAP RENC PDU CHOL SBO

.1 .1 .1 .1

.1 .1 .1 .1

.1 .1 .1 .1

25 19 05 08

48 51 19 16

15 09 32 14

07 17 33 32

06 04 11 30

.1 .1 .1 .1

.1 .1 .1 .1

RUQ 03 01 .1 06

LUQ 01 03 .1 .1

RLQ 19 14 14 03

LLQ 02 09 11 .1

13

.1

.1

.1

.1

08

23

35

34

.1

.1

38

02

.1

.1

DYSP

.1

.1

.1

12

38

21

23

06

.1

.1

12

08

.1

.1

.1

.1

.1

08

16

16

20

40

.1

.1

02

02

02

02
15. PAIN ONSET UPPER 1/2

16. PAIN ONSET LOW HALF

17. PAIN ONSET RT HALF

18. PAIN ONSET LEFT HALF

19. PAIN ONSET CENTRAL

20. PAIN ONSET GENERAL

21. PAIN ONSET RT FLANK

22. PAIN ONSET LT FLANK

23. NO PAIN AT ONSET

24. PAIN NOW RUQ

25. PAIN NOW LUQ

26. PAIN NOW RLQ

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

PAIN

PAIN

PAIN

NOW LLQ

NOW UPPER HALF

NOW LOWER HALF

PAIN NOW RIGHT HALF

PAIN NOW LEFT HALF

PAIN NOW CENTRAL

PAIN NOW GENERAL

PAIN NOW RT FLANK

PAIN NOW LT FLANK

NO PAIN NOW

PAIN INTERMITTENT

PAIN STEADY

PAIN COLICKY

PAIN IS MODERATE

PAIN IS SEVERE

MOVEMENT AGGRAVATES

COUGHING AGGRAVATES

BREATHING AGGRAVATES

FOOD AGGRAVATES

AGGRAVATED BY OTHER

NOTHING AGGRAVATES

PROGRESS - BETTER

10

05

02

01

49

10

.1

.1

.1

01

.1

68

01

02

07

04

.1

14

20

12

06

04

29

04

.1

01

.1

03

02

25

05

17

12

03~

02

21

01

07

18

08

01

.1

18

26

01

.1

.1

14

15

03

05

14

09

01

59

04

03

.1

12

14

.1

.1

.1

02

01

02

.1

46

01

11

.1

07

45

02

03

.1

11

.1

.1

.1

.1

42

.1

.1

.1

42

02

02

.1

09

28

20

.1

.1

46

06

.1

.1

.1

.1

.1

02

08

22

14

.1

.1

40

58

06

03

.1

12

02

.1

.1

.1

12

06

.1

.1

56

02

02

.1

14

03 03 .1 34 .1 14 03

01 01 20 .1 .1 .1 .1

01 01 26 .1 .1 .1 .1

.1 07 05 .1 03 .1 06

05 18 14 05 02 .1 14

80 46 34 86 73 22 61

15 36 52 09 25 80 25

63 50 11 05 27 38 44

37 50 89 95 73 62 56

53 24 17 48 09 18 18

22

02

.1

08

22

18

30

52

40

60

.1

.1

49. PROGRESS - SAME

50. PROGRESS 

- WORSE

51. DURATION <12 HRS

52. DURATION 12-24 

H

53. DURATION 24-48 

H

54. DURATION 48+HRS

55. LYING STILL RELIEVES

56. VOMITING RELIEVES

57. ANTACIDS RELIEVE

58. FOOD RELIEVES

59. RELIEVED BY OTHER

60. NOTHING RELIEVES

09

06

03

10

47

39

35

25

68

32

.1

.1

.1

03

.1

10

70

35

26

39

95

05

.1

.1

12

11

.1

04

37

10

44

46

87

13

.1

.1

06

05

11

17

52

18

49

33

71

29

.1

.1

06

.1

02

14

64

16

50

34

48

52

.1

.1

08

05

06

14

55

43

39

18

86

14

.1

.1

21 13 06 23 03 02 11

04

01

.1

12

63

06

02

01

12

66

03

.1

.1

26

65

02

03

01

06

65

02

.1

.1

21

74

10

.1

.1

20

68

03

05

03

26

58

14
61. NAUSEA PRESENT

62. NO NAUSEA

63. VOMITING PRESENT

64. NO VOMITING

65. BOWELS NORMAL

66. CONSTIPATION PRESENT

67. DIARRHEA PRESENT

68. BLOOD IN STOOLS

69. MUCUS IN STOOLS

70. APPETITE DECREASED

71. APPETITE NORMAL

72. JAUNDICE PRESENT

73. NO JAUNDICE

74. URINATION NORMAL

75. URINATION 

-FREQUENT

76. URINATION 

- PAINFUL

77. URINATION 

- DARK

78. BLOOD IN URINE

79. PREVIOUS INDIGESTION

80. NO PREV. INDIGESTION

81. PREV. SIMILAR PAIN

82. NO PREV. SIM. PAIN

83. PREV. ABD. SURGERY

84. NO PREV. ABD. SURG.

85. PREVIOUS ILLNESS(es)

86. NO PREVIOUS ILLNESS

87. TAKING MEDS

88. NOT TAKING MEDS

89. TEMP <98.6

90. TEMP 98.6 

- 100.2

91. TEMP 100.3 

- 102

92. TEMP >102

93. PULSE <80

94. PULSE 80-99

95. PULSE >99

96. SYST. BP <90

97. SYST. BP 90-129

98. SYST. BP >129

99. DIAST. BP <70

100. DIAST. BP 70-89

101. DIAST. BP >89

102. MOOD NORMAL

103. MOOD DISTRESSED

104. MOOD ANXIOUS

105. COLOR NORMAL

106. COLOR PALE

65 62 72 61 68 81

35 38 28 39 32 19

55 42 70 54 72 86

45 58 30 46 28 14

80 86 81 87 75 66

11 04 11 11 16 28

09 08 08 02 08 06

.1 01 .1 .1 01 .1

.1 .1 .1 .1 .1 .1

70 37 40 48 62 66

30 63 60 52 37 34

.1 .1 02 .1 .1 .1

99 99 98 99 99 99

90 88 59 96 90 94

06 06 23 03 05 .1

04 06 18 01 03 04

.1 .1 04 .1 02 02

.1 .1 01 .1 .1 .1

19 20 18 71 48 21

81 80 82 29 52 79

37 40 46 47 75 57

63 60 54 53 25 43

02 13 18 21 31 86

98 87 82 79 69 14

.1 .1 .1 .1 .1 .1

.1 .1 .1 .1 .1 .1

10 11 18 25 35 31

90 89 82 75 65 69

.1 .1 .1 .1 .1 .1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

71

17

12

58

14

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

71

14

15

81

12

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

65

28

07

75

23

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

.1

20

59

20

43

48

7111

61

21

.1

.1

.1

.1

.1

.1

.1

73

14

14

69

29

31

411

61

31

.1

.1

.1

.1

.1

.1

.1

38

45

17

60

32

15

65

35

62

38

76

09

11

06

.1

46

54

02

98

96

02

.1

02

.1

68

32

67

33

22

78

.1

.1

44

56

.1

.11

21

711

.1

.1

.1

.1

.1

.1

.1

62

12

25

76

16
107. COLOR FLUSHED 28 07 02 05 02 05 06

108. COLOR JAUNDICED .1 .1 .1 .1 .1 .1 02

109. COLOR CYANOTIC .1 .1 .1 04 .1 03 .1

110. WBC < 8000 07 40 01 01 01 01 40

111. WBC 8 100-10 000 07 23 01 01 01 01 23

112. WBC 10 100-12 000 18 17 01 01 01 01 17

113. WBC 12 100-15 000 32 11 01 01 01 01 11

114. WBC >15 000 35 08 01 01 01 01 08

115. ABD INSPECT. NORMAL 87 99 96 39 89 82 92

116. VISIBLE PERISTALISIS .1 .1 .1 .1 .1 06 .1

117. DECREASED ABD MOVE. 13 01 04 61 11 12 08

118. ABD SCARS PRESENT 02 14 20 21 28 84 23

119. NO ABDOMINAL SCARS 98 86 80 79 72 16 77

120. GUARDING PRESENT 72 24 23 62 62 38 30

121. NO GUARDING 28 76 77 38 38 62 70

122. RIGIDITY PRESENT .1 .1 .1 .1 .1 .1 .1

123. NO RIGIDITY .1 .1 .1 .1 .1 .1 .1

124. BOWEL SOUNDS NORMAL .1 .1 .1 .1 .1 .1 .1

125. BOWEL SOUNDS ABSENT .1 .1 .1 .1 .1 .1 .1

126. HYPER. BOWEL SOUNDS .1 .1 .1 .1 .1 .1 .1

127. ABDOMEN DISTENDED 03 01 03 03 10 63 .1

128. NO ABD DISTENTION 97 99 97 97 90 37 99

129. MASS(es) PRESENT 01 01 05 01 11 12 .1

130. NO ABD MASSES 99 99 95 99 89 88 99

131. TENDERNESS RUQ 01 04 01 03 69 .1 11

132. TENDERNESS LUQ .1 05 01 .1 .1 .1 03

133. TENDERNESS RLQ 87 29 15 03 02 06 02

134. TENDERNESS LLQ 02 11 12 01 02 06 .1

135. TENDER UPPER HALF 02 11 .1 30 14 14 61

136. TENDER LOWER HALF 02 11 02 01 .1 10 03

137. TENDER RIGHT HALF 07 06 11 10 03 02 06

138. TENDER LEFT HALF .1 05 11 .1 .1 02 02

139. CENTRAL TENDERNESS .1 03 .1 01 .1 14 02

140. GENERAL TENDERNESS 03 01 .1 55 02 40 08

141. TENDERNESS RT FLANK 01 01 19 01 .1 .1 .1

142. TENDERNESS LT FLANK .1 01 23 .1 .1 .1 .1

143. NO TENDERNESS .1 19 19 .1 11 10 12

144. MURPHY'S POSITIVE 01 03 .1 03 68 .1 02

145. MURPHY'S NEGATIVE 99 97 99 97 32 99 98

146. REBOUND PRESENT 80 23 05 54 10 33 18

147. NO REBOUND 20 77 95 46 90 66 82

148. RECTAL- NORMAL 57 72 91 80 92 91 98

149. RECTAL MASS .1 01 .1 .1 02 .1 .1

150. LT RECTAL TENDERNESS 03 04 05 .1 .1 .1 .1

151. RT RECTAL TENDERNESS 27 14 .1 03 02 03 02

152. GEN. RECTAL TENDERNESS 12 09 04 17 04 06 .1

16
UNCLASS IFIED

StýCUHITY CLASSIFICATION OF THIS PAGE

Form Approved REPORT DOCUMENTATION PAGE I OMB No. 074-0188

la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS

UNCLASSIFIED

2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAILABILITY OF THE REPORT

Approved for publiq release;

2b. DECLASSIFICATION/DOWNGRADING SCHEDULE distribution unln=ited

4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S)

NSMRL REPORT 1181 NA

6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION

Naval Submarine Medical (If Applicable) Naval Medical Research and Development Research Laboratory Command

6c. ADDRESS (City, State, Zip Code) 7b. ADDRESS (City, State, Zip Code)

Box 900, Naval Submarine Base, NLON, 8901 Wisconsin Ave., Bethesda, MD

Groton, CT 06349-5900 20889-5606

8a. NAME OF FUNDING/SPONSORING 8b. OFFICE SYMBOL 9. PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER ORGANIZATION (If Applicable)

Same as 7aI

8c. ADDRESS (City, State, Zip Code) 10. SOURCE OF FUNDING NUMBERS

Same as 7b PROGRAM PROJECT NO. TASKNO. WORKUNIT

ELEMENT NO. ACCESSION NO

63706N M0095 005 DN277023

11. TITLE (Include Security Classification)

Trial of a computer based program for the diagnosis of abdominal pain in males

12. PERSONAL AUTHOR(S)

P. L. Perrotta and D. M. Stetson

13a. TYPE OF REPORT 13b. TIME COVERED 14. DATE OF REPO~rT (Yef, Mon#7, D) 15. PAGECOUNT

Interim I FROM -TO 92 September 02 20

16. SUPPLEMENTARY NOTATION

17. COSATI CODES 18. SUBJECT TERMS (Continue on reverse if necessary and identify by block number)

FIELD GROUP SUB-GROUP Computer based diagnosis; abdominal pain; males

19. ABSTRACT (Continue on reverse if necessary and identify by block number)

This report presents and evaluates data collected in 1988 in an effort to verify the NSMRL abdominal pain

diagnositc program. Overall diagnostic accuracy of the program was found to be 69% comparede to the 80%

accuracy rate of emergency room physicians. Sensitivity and specificity for distinguishing surgical from

non-surgical cases was 56% and 85% respectively. Additional measures of performance of the abdominal pain

program are presented along with the limitations of the data set and recommendations for future validation

efforts.

20. DISTRIBUTION/AVAILABILITY OF ABSTRACT 21. ABSTRACT SECURITY CLASSIFICATION

N]UNCLASSIFIED/UNLIMITED --SAME AS REPORT []DTIC USERS UNCLASSIFIED

22a. NAME OF RESPONSIBLE INDIVIDUAL 22b. TELEPHONE (Include Area Code) 22c. OFFICE SYMBOL

Susan D. Monty, Publications Office (203) 449-3967

1 . . . . . . . . . ..

DD Form 1473, JUN 86 Previous editions are obsolete.

S/N 0102-LF-014-6603

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