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Table 1 General and etiological characteristics of the study population

From: Performance of the Large Language Models in African rheumatology: a diagnostic test accuracy study of ChatGPT-4, Gemini, Copilot, and Claude artificial intelligence

Variables

n

Percentage (%)

Mean age (years)

51.9 ± 20.9

Age groups

 

< 50 years

53

51.46

≥ 50 years

50

48.54

Sex

  

Male

64

62.14

Female

39

37.86

Rheumatological disease categories

  

Infectious diseases

49

47.57

Pott’s disease

23

22.33

Pyogenic spondylodiscitis

7

6.80

Septic arthritis of peripheral joints

10

9.71

Pyogenic zygapophyseal arthritis

2

1.94

Infectious myositis

3

2.91

Acute rheumatic fever

1

0.97

Septic osteonecrosis of the femoral head

2

1.94

Chronic inflammatory rheumatic diseases

17

16.50

Rheumatoid arthritis

7

6.80

Systemic lupus erythematosus

4

3.88

Systemic sclerosis

1

0.97

Dermatomyositis

1

0.97

Post-streptococcal rheumatism

1

0.97

Ankylosing spondylitis

2

1.94

Sjögren’s syndrome

1

0.97

Degenerative diseases

15

14.56

Common low back pain in adults

9

8.74

Avascular necrosis of the femoral head

2

1.94

Acute flare of knee osteoarthritis

2

1.94

Common cervical pain

1

0.97

Microcrystalline diseases

13

12.62

Gout

13

12.62

Neoplastic diseases

9

8.74

Spinal bone metastasis

4

3.88

Benign bone tumor of the spine

1

0.97

Multiple myeloma

3

2.91