computer analysis of symptom complexes in patients having upper gastrointestinal examinations

Computer Analysis of Symptom Complexes in Patients Having Upper Gastrointestinal Examinations

Paul Ross, MB, BS and Arthur M. Dutton,* PhD

One thousand and forty-six patients, referred for barium meal examination, were interviewed and subsequently examined by one radiologist. Attempts were made to correlate the data obtained from the patient with radiologic diagnosis, using discriminant function analysis and Bayesian conditional probability calculations. Each patient was classified into one of eight diagnostic categories on the basis of these calculations. The accuracy of this method was compared with that of the clinical diagnoses made by the radiologist before examination. Other studies evaluating statistical methods of medical diagnoses have been confined to situations in which clinical diagnostic accuracy is high. As in these, the present study, which is directed to patients who challenge the acumen of the practising physi- cian, yields a diagnostic accuracy similar to that achieved by the clinician.

A phys i c i an m a k e s a d i f fe ren t ia l d iagnos i s of

the disease f rom wh ich a pa t i en t m a y be suffer-

ing by assess ing the s igni f icance of all the

i n f o r m a t i o n t ha t he has on the pa t ien t . T h e

m a t h e m a t i c a l b a s i s of t h i s p r o c e s s , u s i n g

p r o p o s i t i o n a l ca lculus and the in tu i t ive ly .justi-

fied concept of s y m p t o m - d i s e a s e complexes , has

been ,,veil e s t ab l i shed (1). T h e analyses , for the

most par t , have been conf ined to p r o b l e m s in

which cl inical fea tures can be precisely defined,

as in hema to log i c d i so rders (2), t hy ro id dys-

func t ion (3) and congen i ta l hea r t d isease (4), or,

in w h i c h a smal l n u m b e r of selected s y m p t o m s

have had to be cons idered (3). C o m p u t e r - a i d e d

s ta t is t ica l ana lyses of r a d i o g r a p h i c f indings in

lung cancer (6), p r i m a r y bone t u m o r s (7) and

gas t r ic ulcers (8) have also been a t t empted .

W e decided to inves t iga te the va lue of a r igid

s ta t is t ical ana lys i s of the s y m p t o m a t o l o g y of

pa t i en t s w h o p re sen t a real p r o b l e m in d i agno-

sis to p r ac t i s i ng phys ic ians . T h e va r i ab i l i ty in

From the Department of Radiology and Radiation Biol- ogy and Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY.

* Now at Florida Technological University, Orlando, Florida.

cl inical fea tures of pa t i en t s suffer ing f rom

c o m m o n u p p e r digest ive tract d i sorders and

f rom func t iona l c o m p l a i n t s is well known. A

prospec t ive s tudy of the r e l a t i onsh ip be tween

the s y m p t o m s and the radiologic d iagnosis in

pa t i en t s re fer red for b a r i u m meal e x a m i n a t i o n

was u n d e r t a k e n .

MATERIALS AND METHODS

The stud,,,' was done on patients referred for barium meal examination to a private office in Melbourne, Australia. The patients were ambulant, adult caucasians For 6 years before this study was started, one of us (PR) had been in- terviewing all patients referred for barium examinations before fluoroscopy was started. On the basis of this experience, as well as the clinical features of upper gastrointestinal disease described in standard texts, a form was designed for recording the patient's symptoms for the purpose of this study. This was filled out before the fluoroscopic examination and on this basis a clinical diagnosis was made and noted by the principal author, who also performed the radiologic examination. The variability of different physicians in assessing the patient's symptoms was, therefore, elimi- nated. The form was not available when the films were in- terpreted so as to be objective in the radiologic diagnosis. The radiologic findings and diagnosis were then noted on the form.

248 Digestive Diseases, Vol. 17, No. 3 (March 1972)

GASTROINTESTINAL EXAMINATIONS

Table 1. Symptom Categories

1. Age 2. Sex 3. Stress 4. Occupation 5. Build 6. Presenting Symptom I 7. Presenting Symptom II 8. Periodici ty of presenting symptoms 9. Duration of presenting symptoms

10. Site 11, Radiation 12. Nature 13. Duration of pain 14. Aggravation I 15. Extent of Aggravation I 16. Aggravation II 17. Aggravation III 18. Relief of Symptom I 19. Extent of relief of Symptom I 20. Relief of Symptom II 21, Pain dur ing night 22. Pain before breakfast 23, Periodicity 24, Pain on

25. Pain Off 26. Anorexia not related to pain 27. Anorexia dur ing pain 28. Nausea not related to pain 29. Nausea dur ing pain 30. Vomi t ing not related to pain 31. Vomi t ing dur ing pain 32. Weight 33. Bowels not related to pain 34, Bowels dur ing pain 35. Tobacco 36. Alcohol 37. Sal ivat ion 38. Heartburn not related to pain 39. Heartburn dur ing pain 40. Regurgitat ion not related to pain 41. Regurgitat ion dur ing heartburn or bending 42. Belching 43. Abdominal distent ion not related to pain 44. Abdominal distent ion dur ing pain 45, Personal i ty 46. Bread 47. Aspirin 48, Miscellaneous symptoms

After the completion of the study, a set of data sheets was designed to code the information on the forms as numbers suitable for use with IBM-punched cards. Th is contained 48 "symptom categories", each with 2 to 16 subdivisions as shown in Tables 1 and 2.

Diagnostic Criteria Hiatus hernia was diagnosed if, after dr inking 16 ounces

of barium suspension, a pouch, which filled from below, was observed above the d iaphragm when the patient was placed prone with a padded wooden bolster under the abdomen, or was demarcated from the tubular esophagus by a cons t an t r ing , or showed g a s t r i c - t y p e m u c o s a l folds.

Neuromuscular disorder of the esophagus was diagnosed, using criteria described by Johnstone (9). Ter t ia ry contrac- tions of the esophagus were not considered in this category.

The term "atrophic gastr i t is" was used when no folds measuring more than 5 mm in any portion of the stomach, were seen on any of the films (10). A diagnosis of duodenal ulcer was made when a niche was demonstrated or when

the bulb showed a constant deformity in contour involving two margins or one margin with a sharp angulation.

Some patients showed findings whose significance is uncertain. To exclude them from the study would invalidate the gampling assumptions and they could not be classified as

strictly normal. Duodenit is was diagnosed when the radiologic examinat ion showed a coarse i rregular ret icular or cobblestone mucosa in the duodenal bulb, but there was no constant deformity or ulcer niche. Because this finding and persistent duodenal i rr i tabil i ty have been considered to be abnormali t ies which may produce symptoms (11-13), they were placed in a separate category.

A histopathologic examinat ion is the preferred diagnostic and point in diseases with morphologic abnormalit ies. This is of course not possible in studies of diseases in which the involved tissue does not ordinari ly become available for microscopic examination. Radiologic diagnosis for the diseases considered here, usually, is widely accepted, as the definitive investigation and when the examinat ion is done

by an experienced radiologist, the accuracy is high (14). The radiologic diagnoses, which were made on the 1046

patients comprising this study, are listed in Table 3. For purposes of statistical analysis, diagnostic categories must be established, each containing a fairly large number of patients (15). We established eight categories as set out in Table 4. Since the symptomatic significance of small hiatus hernias and those without gastroesophageal reflux has been questioned, they are included in a separate group, Num- ber 2. Frequently, hiatus hernia is associated with another abnormal i tv which may produce symptoms, and this mixed group was separated (Group 4). Patients with evidence of

Digestive Diseases, Vol. 17, No. 3 (March 1972) 249

Table 2. "Symptom Categories"--Sample Page

ROSS & DUTTON

(6) Presenting Symptom I 0 None i Tired 2 Discomfort 3 Distension, wind, fullness 4 Pain 5 Heartburn 6 Regurgitation 7 Nausea and/orvomiting 8 Dysphagia 9 Weight loss

10 Other

(7) Presenting Symptom II

0 None 1 Tired 2 Discomfort 3 Distension 4 Pain 5 Heartburn 6 Nausea and/or vomit ing 7 Hematemesis and/or melena 8 Obstruction, substernal 9 Poor appetite

10 Belching 11 Flatulence 12 Bowel disturbance 13 Shortness of breath 14. Multiple symptoms 15. Miscellaneous

(8) Periodicity of Presenting Symptoms

1. NA 2. Intermittent 3. Constant

(9) Duration of Presenting Symptoms

0 < l w k 1 1.0-1.9 wks 2 2.0-2.9 wks 3 3.0-3.9 wks 4 1.0-2.9 mos 5 3.0-5.9 mos 6 6.0-11.9 mos 7 1.0-2.9 yrs 8 _> 3.0 yrs

(10) S i te

0 None 1 Epigastrium 2 Periumbil ical 3 RUQ 4 LUQ 5 Diffuse, upper abd. 6 Lower abd. 7 Diffuse abd., various sites 8 substernal 9 Chest(> 1 site)

10 Other than above

(11) Radiation

0 None 1. To right 2. To left 3. Upwards 4 Downwards 5 To back 6 To chest and thrpat 7. To back + chest 8. All over abdomen more than one site abd. 9. Other

10. NA

duodenal ulceration and no other abnormal i ty formed a sizable group, Number 5, as did those with duodenitis or an irr i table duodenal cap (Group 6). The remainder of the patients with positive radiographic findings were classified into one of two groups: a) those with radiologic diagnoses likely to be the cause of symptoms (Group 7) and b) those whose findings were of no clinical significance (Group 8).

TabLe 5 lists the diagnoses made on patients classified in Groups 4 and 7.

Statist ical Analysis Bayes formula has been used to determine the most likely

disease category for an individual who is known to have certain characteris t ics--eg, symptoms (16). Th is method is valid only if the incidence of each combination of characteristics is known for diagnostic category. If more than just a few characteristics are considered, the number of permuta-

tions becomes very large. In our study, 48 variables were considered and even if each was simply dichotomous, there



Table 3. Radiologic Diagnoses

Diagnosis Number Incidence (%)

Normal 431 4t .3 Hiatus hernia 224 21.5 Duodenal ulcer 180 t7.2 Irritable cap 63 5.9 Duodenitis 58 5.5 Gastric ulcer 27 2.5 Duodenal divert iculum 25 2.4 Atrophic gastritis 23 2.2 Gastroesophageal regurgitation 19 1.9 Hypertrophic gastritis 15 1.4 Gastric hypersecretion t5 1.4 Transpyloric herniation of gastric mucosa 12 t.1 Carcinoma of stomach 8 0.8 Antral gastritis 8 0.8 Stricture of lower esophagus 5 0.5 Stricture pyloric region 1 0.1 Neuromuscular disorder of esophagus 3 0.3 Carcinoma esophagus 1 0.1 Esophageal divert iculum 2 0.2 Pharyngeal carcinoma i O.i Postbulbar stenosis t O, t Gastric divert iculum 1 0.1 Associated lesions

Gallstones 19 1.9 Carcinoma of lung 4 0.4 Large bowel lesions 3 0.3

Total 1149 100

Table 4. Diagnostic Categories

Group Diagnosis No. of Patients Total (%)

1 Normal 431 41 2 Hiatus hernia smaller than 4 cm or equal to

or larger than 4 cm without gastroesophageal reflux. 94 9

3 Hiatus hernia 4 cm or larger with gastroesophageal reflux. 74 7

4 Hiatus hernia and another symptomat ic diagnosis. 56 5

5 Duodenal ulcer 153 15 6 Duodenitis and/or irritable duodenal cap 90 9 7 All other symptomat ic diagnoses 81 8 8 All other nonsymptomat ic diagnoses 67 6

Total 1046 100


ROSS & DUTTON

Table 5. Radiologic Diagnoses in Groups 4 and 7

No. o f Hiatus Hernia and Other Symptomatic Diagnoses patients

Group 4 Duodenal ulcer 24 Irritable cap 11 Duodenitis 7 Narrowing lower esophagus 5 Gallstones 2 Gastric ulcer 2 Gastrod u oden itis 2 Postbulbar ulcer 1 Gastric carcinoma 1 Duodenal ulcer and gallstones 1

Total 56

Other Symptomatic Diagnoses

Group 7 Gastric ulcer Gastric ulcer and duodenal ulcer Gastroesophageal regurgitation Gastroesophageal regurgitation and irritable cap Gastroesophageal regurgitation and duodenal ulcer Gastroesophageal regurgitation and atrophic gastritis Gastroesophageal regurgitation and duodenal diverticulum Gastroesophageal regurgitation and transpyloric herniation Gastroesophageal regurgitation and carcinoma lung Gallstones Gallstones and irritable cap Gallstones and duodenitis Gallstones and duodenal diverticulum Gastric carcinoma Duodenitis and transpyloric herniation Irritable cap and other diagnosis Irritable cap and transpyloric herniation Irritable cap and gastric hypersecretion Gastroduodenitis Carcinoma of lung Large bowel lesion Carcinoma esophagus Narrowing pyloric region Pharyngeal carcinoma and atrophic gastritis

24 1

13 1 1 1 1 1 1

11 2 2 1 7 2 1 1 1 1 3 2 1 1 1

Total 81

would be 2 ~ possible profiles. It follows that there would be no patients in most of the profiles and only small numbers of pat ients in the remainder.

Unless one can be sure that each of the characteristics considered is independent of the others, it is incorrect to de-

termine the incidence of the various characteristics in the diagnostic categories and obtain a probabil i ty value for a par t icular "symptom profi le" by mult iplying the individual

probabi l i t ies There is no simple way of determining whether or not the characteristics are independent variables



and the magnitude of the error introduced by making the assumption of independence is unknown.

The problem of classifying an individual in a disease category, on the basis of a symptom complex, can be considered in the light of a statistical method referred to as discriminant function analysis (17). This solves the following taxonomic problem. Given an individual with a number of known variables h, t 2 . . . . . . . tp, some or all of which may be highly correlated, decide on this basis to which of the 2 possible groups he belongs. One can substitute a single factor Y, defined as a linear compound of the variables so that Y = lit 1 + 12t 2 + . . . . . . . . . . . lptp. The values of the constants 1 can be calculated if there are a number of people with known variables in each of the 2 groups. The means of the Y's for each of the groups Yt and 5z2 and their standard deviations s 1 (y) and s 2 (y) could then be calculated. The pooled standard deviation is

s(y) - [nls12(y) + n2s22(y)] / (n I + n2)

It is proposed that one determines the 1 's so as to maximize the ratio

( Y l - 5,2) 2 Z - s2 ( y )

Maximizing Z, mathematically, as Cornfield (18), will make the probability of a correct classification as large as possible, because it weighs the variables so as to maximize the difference between the two groups.

In the case of M populations, the classification is based on comparisons among M-weighted combinations of the variables and again these scores are weighted in such a way as to make the probability of a correct classification as large as possible.

It is emphasized that: a) these discviminant functions are based on population information about correcth" classified individuals; b) they are simple linear combinations of the measurements and c) certain general statistical assumptions about the population are made, namely the populations are multivariate normal and they have common variance- covariance patterns. We used modified forms of published programs (19, 20) to calculate the discriminant functions. These programs use sample properties to estimate corre- sponding population characteristics. Thus, sample means and sample variances and covariances are treated as if they were the true population parameters. A large number of correctly classified individuals and the values of their multiple measurements are required for this analysis.

Prior probabilities of the diseases, themselves, were es- timated by the overall proportion of people in each of the disease categories and incorporated into the diseriminant analysis.

On the basis of ~he coded values of all 48 variables, the set of weights for the linear discriminant score was obtained. These weights were then used to obtain scores and to clas- sify each individual in the study into the most likely disease group--ie, the group for which the score was highest.

RESULTS

T a b l e 6 s h o w s t h e p e r c e n t a g e of p a t i e n t s in

e a c h d i s ea se g r o u p c lass i f ied c o r r e c t l y by th i s

p r o c e d u r e as wel l as t h e p e r c e n t a g e of p a t i e n t s

c o r r e c t l y c lass i f ied c l in ica l ly , on the bas i s of t h e

i n t e r v i e w be fo re t h e r a d i o l o g i c e x a m i n a t i o n w a s

done . T h e ove ra l l d i a g n o s t i c a c c u r a c y of t he

s ta t i s t i ca l m e t h o d is 4 8 . 7 %, a n d tha t o b t a i n e d

c l in ica l ly w a s 39 .9%.

T h e p r o b a b i l i t y of co r r ec t c l a s s i f i ca t ion ,

b a s e d on c h a n c e a lone , is o b t a i n e d by t a k i n g t h e

p r i o r p r o b a b i l i t y of t h e l a rges t g r o u p . T h e n ,

e a c h p a t i e n t w o u l d be c lass i f ied as n o r m a l , g iv-

ing an ove ra l l d i a g n o s t i c a c c u r a c y of 41 .2%,

o b t a i n e d by a 100% c o r r e c t d i a g n o s i s in G r o u p

1, all o t h e r s b e i n g inco r rec t .

D I S C U S S I O N

T h e overa l l p r o p o r t i o n of p a t i e n t s c o r r e c t l y

d i a g n o s e d c l in ica l ly , c o r r e s p o n d s c lose ly to t h a t

w h i c h w o u l d be o b t a i n e d by c h a n c e . T h i s p o o r

c l in ica l a c c u r a c y is a t t r i b u t a b l e l a rge ly to

d i a g n o s i n g d i s ea se in p a t i e n t s w h o h a d a n o r -

ma l b a r i u m m e a l e x a m i n a t i o n . At t h e e x p e n s e

of a s m a l l e r y ie ld o f co r r ec t d i a g n o s e s in inos t o f

t he o t h e r d i a g n o s t i c c a t ego r i e s , t h e s ta t i s t i ca l

a n a l y s i s a c h i e v e d a b e t t e r ove ra l l a c c u r a c y bv

c o r r e c t l y d i a g n o s i n g th i s g r o u p of p a t i e n t s m o s t

of t he t ime . H o w e v e r , a l t h o u g h the p a t i e n t s in

th is s t u d y i n c l u d e d a l a r g e p r o p o r t i o n of n o r -

ma ls , as d e t e r m i n e d by u p p e r g a s t r o i n t e s t i n a l

ser ies , t h e s e p a t i e n t s w e r e r e f e r r e d for r a d i o -

logic e x a m i n a t i o n p r e c i s e l y b e c a u s e t h e y p r e -

s e n t e d c l in ica l f e a t u r e s sugges t i ve o f o r g a n i c

d isease . It is no t u n e x p e c t e d t h e n , t h a t t he c l in-

ical f e a t u r e s of p a t i e n t s c lass i f ied as n o r m a l on

r a d i o l o g i c e x a m i n a t i o n , s h o u l d m i m i c t h o s e of

u p p e r g a s t r o i n t e s t i n a l d isease . M o r e o v e r , t he

d i a g n o s t i c a c c u r a c y b o t h c l in ica l ly a n d u s i n g

d i s c r i m i n a n t f u n c t i o n a n a l y s i s w a s h i g h e s t in

t h e n o r m a l g r o u p a n d in t h o s e w i t h t h e m o s t

wel l d e f i n e d s y m p t o m c o m p l e x , n a m e l y , t he

d u o d e n a l u lce r g r o u p .

It s e e m s l ikely t h a t t h e o v e r l a p in t h e s y m p -

toms , a t t r i b u t a b l e to f u n c t i o n a l u p p e r g a s -


ROSS & DUTTON

trointestinal disorders and those due to various organic diseases are such that accurate differ- entiation on this basis will not be possible. It is not probable that significant improvement will be obtained by using a more detailed question- naire or that there will be less accuracy if the assessment is made on the basis of a question- naire filled out by the patient.

The clinician uses his medical knowledge to assign subjective probabilities to various diagnostic possibilities. It might be expected that in the situations where the diagnostic accuracy is low, statistical analysis would result in an improvement. If the present study is representative of our conclusions it seems that no increased accuracy results and that further efforts in this direction are unlikely to be productive. In the field of difficult medical diagnoses, statistical methods with computer technics will probably be most fruitful (21) in situations where the amount of data on a patient is very large or in- cludes the collective experience of many who have helped in the evaluation of unusual features and in raising the possibility of unusual diseases.

R E F E R E N C E S

1. Ledley RS, Lusted LB: The role of computers in medical diagnosis. Med DoKum 5:70-78, 1961

2. Lipkir M, Engle RL Jr, Davis BJ et al: Digital computer as aid to differential diagnosis. Arch Int Med 108:124-140, 1961

3. Overall JE, Williams CM: Models for Medical Diagnosis Factor Analysis, Part Two, Experi- mental. Med DoKum 5:78-84, 1961

4. Warner HR, Toronto AF, Veasev LG. et a~: A mathematical approach to medical diagnosis- application to congenital heart disease. JAMA 177:177-183, 1961

5. Rinaldo JA, Scheinok P, Rupe CE: Symptom diagnosis. A mathematical analvsis of epigas- tric pain...\nn Intern Med 59: 145-154, 1963

6. Lodwick GS, Keats TE, Dorst JP: The coding of Roentgen images for computer analysis as applied to lung cancer. Radiology 8l :185-200, Aug 1963

7. Lodwick GS, Cosmo LH, Smith WE. et al: Computer diagnosis of primary bone tumors. Radiology 80:273-275, 1963

8. Wilson W J, Templeton AW, Turner AH, et al: The computer analysis and diagnosis of gastric ulcers. Radiology 85:1064-1073, 1965

9. Johnstone AS: Diffuse spasm and diffuse muscle hypertrophy of lower oesophagus. Br J Radiol 33:723-735, 1960

10. Bock OAA: Radiological diagnosis of gastric atrophy. Br J Radiol 36:578-582, 1963

11. Fraser GM, Pitman RG, Lawrie JM, et al: The significance of the radiological finding of coarse mucosal folds in the duodenum. Lancet 2:979, 1964

12. Ostrow JD, Resnick RH: Hyperchlorhydria, duodenitis and duodenal ulcer. A clinical study of their inter-relationships. Ann Intern Med 51:1303, 1959

13. Rhodes J, Ewms KT. Lawrie JH, et al: Coarse mucosal folds in the duodenum. Q J Med 37:151-169, 1968

14. Ross P: The accuracy of radiological examinations. MedJ Aust 1:534, 1964

15. Bailey NTJ: Probability methods of diagnosis based on small samples, Mathematics and Computer Science in Biology and Medicine. London, Her Majesty's Stationery Office, 1965, 103-110

16. Vanderplas JM: A method for determining probabilities for correct use of Bares" theorem in medical diagnosis. Comput Biomed Res 1:215-220, 1967

17. Anderson TW: Introduction to Multivariate Statistical Analysis. John Wiley and Sons, 1958, pp 147-152

18. Cornfield J: Discriminant functions, Proceed- ings of the Sixth IBM Medical Symposium, Oct 1964, pp 1-22

19. Biomedical Computer Programs. Edited hy WJ Dixon. Health Sciences Computing Facility. Department of Preventive Medicine and Public Health, School of Medicine University of Cali- fornia, Los Angeles, Sept 1965

20. IBM, System/360 Scientific Subroutine Package (360-A-CM-03X), Version 2, 1967

21. Ross P: Computers in medical diagnosis. Crit Rev in Radiol Sci. To be published


computer analysis of symptom complexes in patients having upper gastrointestinal examinations

Documents