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. 2025 Aug 22;272(9):586. doi: 10.1007/s00415-025-13261-3

Table 1.

Baseline demographic and clinical characteristics of patient electrodiagnostic reports

Features Total (n = 200) Intervention (AI–physician) (n = 100) Control (Physician) (n = 100) p value
Age [median, IQR] 53.0 [40.0–65.0] 55.0 [43.0–68.0] 51.0 [38.0–62.0] 0.072
Male (n, %) 102 (51.0%) 56 (56.0%) 46 (46.0%) 0.157
Abnormal tests 146 (73.0%) 75 (75.0%) 71 (71.0%) 0.522
Normal tests 54 (27.0%) 25 (25.0%) 29 (29.0%) 0.522
Correctness of AI model of detecting abnormality tests 70 (93.3%)
Correctness of AI model of detecting normal tests 23 (92.0%)
Diagnosis found in the reports
 Polyneuropathy diagnosis 26 (13.0%) 13 (13.0%) 13 (13.0%) 1.000
 Mononeuropathy diagnosis 64 (32.0%) 32 (32.0%) 32 (32.0%) 1.000
 Radiculopathy 68 (34.0%) 36 (36.0%) 32 (32.0%) 0.548
 Plexopathy 2 (1.0%) 1 (1.0%) 1 (1.0%) 1.000
 Myopathy 2 (1.0%) 1 (1.0%) 1 (1.0%) 1.000
 Motor neuron disease 0 (0.0%) 0 (0.0%) 0 (0.0%)
Patient Comorbidities
 Diabetes mellitus 4 (2.0%) 2 (2.0%) 2 (2.0%) 1.000
 Dyslipidemia 20 (10.0%) 10 (10.0%) 10 (10.0%) 1.000
 Hypertension 18 (9.0%) 9 (9.0%) 9 (9.0%) 1.000
 Congestive heart failure 0 (0.0%) 0 (0.0%) 0 (0.0%)
 Ischemic heart disease 4 (2.0%) 2 (2.0%) 2 (2.0%) 1.000
 Cancer 8 (4.0%) 4 (4.0%) 4 (4.0%) 1.000