Transcranial Motor-Evoked Potentials Are More Readily Acquired Than Somatosensory-Evoked Potentials in Children Younger Than 6 Years
Bibliographic record
Abstract
BACKGROUND: There is a general belief that somatosensory-evoked potentials (SSEPs) are more easily obtained than transcranial motor-evoked potentials (TcMEPs) in children younger than 6 years. We tested this assumption and the assumption that motor-evoked potentials are rarely obtained in children younger than 2 years. METHODS: The records of all patients who were monitored during surgical procedures between April 1, 2010, and June 30, 2013, were reviewed and those who were younger than 72 months at the time of surgery were identified and analyzed for the rate of obtaining clinically useful SSEPs and motor-evoked potentials. Subgroup analysis was performed by age. RESULTS: A total of 146 patients were identified, 9 had SSEPs without TcMEPs monitored, 117 had both TcMEPs and SSEPs monitored, and the remainder had only electromyographic monitoring. All patients who were to have TcMEPs recorded received a total IV anesthetic. Among the 117 patients who had both SSEPs and TcMEPs monitored, clinically relevant TcMEPs were obtained more frequently than SSEPs (110/117 vs 89/117; χ = 14.82; P = 0.00012). There were significant differences between the rates of obtaining SSEPs and TcMEPs in the 0- to 23-month (P = 0.0038) and 24- to 47-month (P = 0.0056) age groups. Utilization of a double-train stimulation technique facilitated obtaining TcMEPs in the youngest patients. CONCLUSIONS: TcMEPs can be obtained more easily than SSEPs in patients younger than 72 months if a permissive anesthetic technique is used. The success rate for obtaining TcMEPs can be further enhanced by the use of a temporal facilitation (double-train) stimulation technique.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".