Development and validation of the electrosacrogram (ESG): a digital point-of-care tool for real-time neuro-sacral assessment after spinal cord injury
Bibliographic record
Abstract
BACKGROUND: Accurate assessment of neuro-sacral function after spinal cord injury/lesion and cauda equina (SCI+) is essential for diagnosis, prognosis and early management. The current bedside standard, the digital rectal examination (DRE), is subjective, invasive, and examiner dependent. Surface electromyography (s-EMG) offers a quantitative alternative but has lacked point-of-care integration. We developed the ElectroSacroGram (ESG), a bedside digital s-EMG tool enabling real-time objective assessment of sacral somatic function after SCI+. This study aimed to (1) develop the ESG protocol based on clinical consensus; and (2) evaluate its diagnostic performance compared to radiological findings and expert-performed DRE. METHODS: In this prospective proof-of-concept diagnostic study at a specialized Level 1 trauma center, 52 adults with suspected SCI + and 21 healthy participants underwent ESG and DRE. ESG quantified sacral motor (resting external anal sphincter tone, maximal voluntary anal contraction (maxVAC), reflex (bulbospongious or bulbocavernosus reflex (BSR)), and sensory (electrical perceptual threshold (EPT)) function using low-intensity electrical stimulation. Clinically relevant DRE parameters were selected by an expert panel. Content validity was assessed using item/scale content validity indices (CVI), agreement with DRE (Cohen's κ) and diagnostic accuracy were calculated against imaging-confirmed spinal lesions. RESULTS: Normative ESG values were established in healthy participants. Neurologically impaired patients showed reduced maxVAC and BSR amplitudes and elevated EPT. ESG demonstrated excellent content validity (S-CVI = 1.00), strong agreement with DRE for VAC (κ = 0.876) and EPT (κ = 0.881), and high diagnostic accuracy (sensitivity 83.3%, specificity 100%, overall accuracy 86.5%). CONCLUSIONS: ESG enables precise, reproducible evaluation of sacral motor, reflex, and sensory integrity in real-time at bedside. By complementing and objectifying the DRE, it offers a promising precision-medicine tool for early neuro-sacral assessment, enhancing clinical research and improving SCI + diagnosis, for the acute phase and in the context of spinal shock.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".