This study aimed to 1) develop the ElectroSacroGram (ESG) protocol based on clinical consensus; 2) evaluate its diagnostic performance compared to expert-performed Digital rectal examination (DRE) and radiological findings.

Accurate assessment of neuro-sacral function after spinal cord injury (SCI) is critical for diagnosis, prognosis, and acute management. However, current bedside standard, the digital rectal examination, remains subjective, and examiner-dependent. Surface electromyography (s-EMG) offers a quantitative alternative but lacks point-of-care integration. We developed and validated the ElectroSacroGram, a digital, s-EMG-based tool for real-time sacral neurophysiological assessment.

In this prospective diagnostic accuracy study at a specialized Level 1 trauma center, 52 patients with suspected SCI and 21 healthy participants underwent ESG and DRE. ESG captured sacral motor (resting anal tone, maximal voluntary anal contraction [maxVAC]), reflex (bulbospongious reflex [BSR]), and sensory (electrical perceptual threshold [EPT]) function using s-EMG and electrical stimulation. A nine-member expert panel selected clinically relevant DRE parameters and quantified content validity using item and scale content validity indices (I/S-CVI). Concurrent validity was evaluated through agreement between DRE and ESG using Cohen’s kappa (k). Diagnostic accuracy was assessed using contingency tables with imaging-confirmed spinal lesions as reference.

Neurologically impaired patients had lower maxVAC and BSR amplitudes and higher EPT than healthy participants. ESG showed excellent content validity (S-CVI=1) versus DRE (S-CVI=0.43). Agreement with DRE was almost perfect for VAC (κ=0.876) and EPT (κ=0.881), moderate for BSR (κ=0.671), and slight for resting anal tone (κ =0.205). ESG detected radiological abnormalities with 83.3% sensitivity, 100% specificity, and 86.5% overall accuracy.

ESG is a novel digital diagnostic tool that enables objective, real-time bedside neuro-sacral assessment. By overcoming the limitations of DRE, ESG may improve diagnostic precision and early decision-making in SCI. Its point-of-care digital format supports future integration with clinical decision support systems. Multicenter validation and longitudinal modeling are warranted.