Nemes, Réka

Background/Objectives: The aim of this observational study was to collect hand measurements and anthropometric data in children aged 1–15 years of age to help the design of a pediatric skin electrode for electromyography-based neuromuscular monitoring. Methods: Data collection was performed at the Pediatric Department of the University of Debrecen Medical Centre between 1 December 2019 and 31 January 2021. After gaining written informed consent from the parents or legal representatives and verbal acceptance from age-appropriate (12–35 months) patients, a total of 153 children were enrolled. The following parameters were recorded: demographics (age, sex, weight, height, and hand dominance) and hand size parameters, defined as the distance between the following reference points: the ulnar groove and the midpoint of the hypothenar eminence (A); the midpoint of the hypothenar eminence and the first interphalangeal joint of the 5th finger (B); the ulnar groove and the midpoint of the thenar eminence (C); the midpoint of the thenar eminence and the interphalangeal joint of the thumb (D); the midpoint of the wrist crease and the tip of the third finger; wrist circumference (E); and forearm length. All measurements were made in centimeters (cm). Results: The children were divided into 4 groups (12–23 months, 2–5 years, 6–11 years and 12+ years). The number of children in the groups ranged between 6 and 16. The hand size parameters increased according to the children’s age (A: 4.3 ± 0.4, 5.0 ± 0.7, 6.3 ± 0.6, and 6.9 ± 1.0 cm; B: 3.2 ± 0.4, 4.1 ± 0.7, 5.0 ± 0.6, and 5.9 ± 0.6 cm; C: 3.0 ± 0.3, 3.6 ± 0.7, 4.1 ± 0.6, and 4.9 ± 0.6 cm; D: 4.1 ± 0.4, 4.8 ± 0.8, 6.2 ± 0.8, and 7.2 ± 0.9 cm; E: 10.1 ± 0.6, 12.0 ± 1.1, 15.3 ± 1.3, and 17.7 ± 1.7 cm, respectively, in the four groups, [mean ± SD]). The height of the children showed a closer correlation with hand size parameters (Pearson’s correlation coefficients: 0.702–0.961) than with age (0.665–0.904) or weight (0.675–0.863). The correlation was weaker when data were examined in prespecified age groups. Conclusions: The current pediatric hand size database provides previously unavailable information that was used in one manufacturer’s design, which may help with the future design of pediatric electrodes of electromyography-based neuromuscular monitors; this information may facilitate adoption of quantitative neuromuscular monitoring in routine pediatric anesthesia practice.

AbstractThe set of guidelines for good clinical research practice in pharmacodynamic studies of neuromuscular blocking agents was developed following an international consensus conference in Copenhagen in 1996 (Viby‐Mogensen et al., Acta Anaesthesiol Scand 1996, 40, 59–74); the guidelines were later revised and updated following the second consensus conference in Stockholm in 2005 (Fuchs‐Buder et al., Acta Anaesthesiol Scand 2007, 51, 789–808). In view of new devices and further development of monitoring technologies that emerged since then, (e.g., electromyography, three‐dimensional acceleromyography, kinemyography) as well as novel compounds (e.g., sugammadex) a review and update of these recommendations became necessary. The intent of these revised guidelines is to continue to help clinical researchers to conduct high‐quality work and advance the field by enhancing the standards, consistency, and comparability of clinical studies.There is growing awareness of the importance of consensus‐based reporting standards in clinical trials and observational studies. Such global initiatives are necessary in order to minimize heterogeneous and inadequate data reporting and to improve clarity and comparability between different studies and study cohorts. Variations in definitions of endpoints or outcome variables can introduce confusion and difficulties in interpretation of data, but more importantly, it may preclude building of an adequate body of evidence to achieve reliable conclusions and recommendations. Clinical research in neuromuscular pharmacology and physiology is no exception.

Background The paucity of easy-to-use, reliable objective neuromuscular monitors is an obstacle to universal adoption of routine neuromuscular monitoring. Electromyography (EMG) has been proposed as the optimal neuromuscular monitoring technology since it addresses several acceleromyography limitations. This clinical study compared simultaneous neuromuscular responses recorded from induction of neuromuscular block until recovery using the acceleromyography-based TOF-Watch SX and EMG-based TetraGraph. Methods Fifty consenting patients participated. The acceleromyography and EMG devices analyzed simultaneous contractions (acceleromyography) and muscle action potentials (EMG) from the adductor pollicis muscle by synchronization via fiber optic cable link. Bland–Altman analysis described the agreement between devices during distinct phases of neuromuscular block. The primary endpoint was agreement of acceleromyography- and EMG-derived normalized train-of-four ratios greater than or equal to 80%. Secondary endpoints were agreement in the recovery train-of-four ratio range less than 80% and agreement of baseline train-of-four ratios between the devices. Results Acceleromyography showed normalized train-of-four ratio greater than or equal to 80% earlier than EMG. When acceleromyography showed train-of-four ratio greater than or equal to 80% (n = 2,929), the bias was 1.3 toward acceleromyography (limits of agreement, –14.0 to 16.6). When EMG showed train-of-four ratio greater than or equal to 80% (n = 2,284), the bias was –0.5 toward EMG (–14.7 to 13.6). In the acceleromyography range train-of-four ratio less than 80% (n = 2,802), the bias was 2.1 (–16.1 to 20.2), and in the EMG range train-of-four ratio less than 80% (n = 3,447), it was 2.6 (–14.4 to 19.6). Baseline train-of-four ratios were higher and more variable with acceleromyography than with EMG. Conclusions Bias was lower than in previous studies. Limits of agreement were wider than expected because acceleromyography readings varied more than EMG both at baseline and during recovery. The EMG-based monitor had higher precision and greater repeatability than acceleromyography. This difference between monitors was even greater when EMG data were compared to raw (nonnormalized) acceleromyography measurements. The EMG monitor is a better indicator of adequate recovery from neuromuscular block and readiness for safe tracheal extubation than the acceleromyography monitor. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

BACKGROUND: There is a need for easy to use, reliable neuromuscular monitors (NMMs). This multicenter, prospective, unblinded study compared the discomfort associated with neurostimulation in unmedicated healthy volunteers when using the new electromyography (EMG)-based TetraGraph and acceleromyography (AMG)-based TOF-Watch NMMs. The secondary aim was to compare the repeatability of the train-of-four (TOF) ratios (TOFRs) obtained with the 2 devices. METHODS: The TOF measurements of 135 volunteers from 3 university hospitals were analyzed (age: 38.3 ± 12 years [mean ± standard deviation [SD]]; male/female ratio = 63:72). The left or right ulnar nerve was stimulated at the wrist in TOF mode with 20, 30, 40, and 50 mA stimulating current intensities with both devices in random order. The TOF-Watch used standard electrocardiography (ECG) electrodes (Red Dot; 3M Health Care) for nerve stimulation. The stimulating surface area of 1 ECG electrode is 113 mm 2 . The piezoelectric probe was attached to the thumb, and a hand adapter was used to ensure consistency of AMG measurements. The TetraGraph uses proprietary surface strip electrodes for nerve stimulation and muscle action potential recording, whose stimulating surface area is roughly twice as big as that of standard ECG electrodes (228.5 mm 2 ). The volunteers were asked to rate the discomfort associated with neurostimulation on a 0–10 verbal numerical rating scale (VNRS) score anchored with 0 (no pain) and 10 (worst pain ever experienced). A linear mixed-effects model was used to evaluate the difference in VNRS scores between devices. P <.05 was accepted as the level of significance. RESULTS: In the linear mixed-effects model, there were no differences in VNRS scores between devices at any of the stimulating current intensities, P = .38. The median (range) VNRS scores obtained with TOF-Watch and TetraGraph devices were 2 (0–7) vs 2 (0–8) at 20 mA, 3 (1–9) vs 3 (1–9) at 30 mA, 5 (1–10) vs 5 (1–10) at 40 mA, and 5 (1–10) vs 6 (1–10) at 50 mA stimulating current intensities. The mean of the 1469 TOFRs obtained with TetraGraph was 100.43% ± 7.74% (standard error = 0.2%). Due to technical difficulties, the repeatability of the TOFRs could not be determined. CONCLUSIONS: Despite the different size and design of the stimulating electrodes, the 2 NMMs caused the same level of discomfort in unmedicated healthy volunteers.