TY - JOUR
AU - Trotti, Lynn Marie
AB - Abstract Study Objectives The objective of this study was to determine the confidence of expert raters in discriminating phasic and tonic electromyographic (EMG) activity. We undertook this study because we suspected that even expert scorers may disagree on whether a given EMG segment contained phasic activity, tonic activity, or both. Methods Six individuals holding either Fellowship status in the American Academy of Sleep Medicine or Board Certification in Sleep Medicine with at least 5 years experience in interpreting polysomnography visually examined 60 segments containing EMG activity. Raters determined their relative confidence that each segment contained phasic and tonic activity by noting whether they were highly certain or somewhat certain that the segment contained such activity or somewhat certain or highly certain that each segment did not contain such activity. Every segment was rated by every rater twice, once for phasic and once for tonic activity. Results Substantial differences among raters existed in certainty regarding presence/absence of both phasic and tonic activity, although raters agreed on segments far above chance. Consensus was higher on certainty regarding presence of phasic, relative to tonic, activity. Conclusions These findings indicate the limitations of visual analyses for discriminating abnormal muscle activity during sleep. Conversely, when expert judgments are combined with digitized measurements of EMG activity in sleep (e.g. REM atonia index), some allowance must be made for the unique contribution of visual analyses to such judgments, most notably for short duration EMG signals. These results may have relevance for polysomnographic interpretation in suspected synucleinopathies. electromyography, visual interpretation, phasic activity, tonic activity Statement of Significance Recognition of features of electromyographic (EMG) activity during human sleep forms a cornerstone for the visual interpretation of polysomnography. Experienced raters examined segments of EMG activity and rated their confidence that the segment did nor did not contain phasic and tonic activity. Each segment was rated for both phasic and tonic activity. Although raters agreed far above chance in their certainty of the presence or absence of both phasic and tonic activity, they demonstrated much higher consensus over what constituted phasic activity. These results have implications for interpreting EMG signals in human sleep recordings. Determination of phasic muscle activity may be best appreciated visually, whereas distinguishing tonic muscle activity with confidence may necessitate quantitative, automated methods. Introduction Since the original descriptions of electromyographic (EMG) activity during paradoxical sleep in the cat made by Jouvet and colleagues over 50 years ago (summarized in ref. 1), the distinction between phasic and tonic EMG activity has assumed great importance in characterizing human sleep. Perhaps most notably, absence of muscle tone (atonia) in the mentalis is considered a hallmark of normal REM sleep, whereas absence of such atonia has been shown to characterize clinical conditions typically associated with alpha-synucleinopathies, including idiopathic REM sleep behavior disorder (RBD), Parkinson’s Disease (PD), Multi-System Atrophy and Lewy Body Dementia [2–23]. Some studies also indicate that such absence of atonia may predict the incidence of such conditions [16, 24–30]. Similarly, high rates of phasic activity in the mentalis and limb muscle groups have been shown to be diagnostically revealing for some of these conditions as well [9, 10, 12–15, 17–19, 24, 31–36]. In some, e.g. ref. 2, 5, 7, 8, 20, 30, 37, but not all, e.g. ref. 9, 12–14, 18, 21, 22, 24, 34, 38, studies, phasic activity has been suggested to provide less clinical differential utility than tonic activity. In reference to the latter, additional consideration of visually analyzed phasic activity from limb sites may provide incremental diagnostic information to REM without atonia recorded in the mentalis [10, 17, 19, 35, 36]. A few studies have also reported more nightly variability in phasic, relative to tonic, activity [7, 39]. There have been many attempts to develop automated systems for measuring such EMG activity in sleep [2–9, 14, 34, 36, 40, 41] but no commercial digital polysomnographic systems, to the best of our knowledge, have implemented “turn key” software to allow derivation of metrics that characterize a patient’s mentalis muscle activity during sleep, or combine muscle activity from multiple sites into a single measure. Most clinical sleep laboratories continue to rely on visual recognition of such abnormal EMG activity, most typically emanating from the mentalis, and employ the American Academy of Sleep Medicine (AASM) criteria for defining REM sleep Behavior Disorder [42]. With this as backdrop, we conducted in this study an exercise in the visual analysis of EMG activity made by individuals highly experienced with NPSG interpretation, both: (1) to determine the limits of what visual scorers can and cannot confidently discriminate from digitally acquired EMG signals displayed on a video monitor; and (2) to guide future development of automated systems that may rely, at least partially, on validation of those signals by experts’ judgments. Our data are not intended to suggest that advanced computational processing techniques of the EMG signals are less valid than visual analyses, but instead to explore the limitations of what visual analyses can and cannot do. Methods Segment selection Rather than select complex segments of EMG activity from synucleinopathic patients, we reasoned that a more fundamental test of discriminative ability of raters would be obtained by focusing on segments of EMG signals from patients undergoing routine studies in the sleep laboratory whose patterns of muscle activity were less likely to represent abnormality. Segments included high quality, artifact free, and low noise recordings. They were selected from bipolar derivations from either mentalis or anterior tibialis surface EMG recordings. The mean duration of segments chosen was 6.6 s and included signals generated during both REM and NREM sleep. None of the patients whose recordings generated the segments used in this study were taking anti-depressant medications. The first two authors (D.L.B. and J.A.F.) attempted to select an equal number of segments that were thought to contain predominantly phasic activity (n = 20), predominantly tonic activity (n = 20), and potentially mixed types of activity (n = 20). All segments were extracted from the original recordings, assigned a random number, scrambled in order of presentation, and copied onto a single electronic file, which was then provided to each of the raters (Supplementary Material). Each rater scored these 60 segments independently and did not discuss their ratings with other raters; they were provided no information about their level of agreement or lack thereof with any other rater until the study was completed and data were analyzed. All segments were deidentified and the study was IRB approved. Instructions to raters Raters were six individuals (D.L.B., S.H., R.S.R., D.B.R., D.A.S., and L.M.T.) holding either Fellowship status from the American Academy of Sleep Medicine or Board Certification in Sleep Medicine with at least 5 years experience in interpreting polysomnography. Raters were told that they would examine visually short segments of EMG activity, which could contain phasic activity, tonic activity, or mixtures of both. Raters were told that there was no correct or absolute classification of the segments as containing phasic or tonic activity. However, they were well-versed with AASM-based definitions of such activity [42]. Each rater was told to rate each segment twice: once for phasic activity and once for tonic activity. For phasic activity, for example, each rater was asked to determine whether within a particular segment they were: “Highly certain that the segment contained phasic activity;” “Somewhat certain that the segment contained phasic activity;” Somewhat certain that the segment did NOT contain phasic muscle activity;” or “Highly certain that the segment did NOT contain phasic muscle activity.” Identically formatted questions were also asked regarding the certainty of a segment containing tonic muscle activity. These instructions yielded a total of 720 ratings in the data set. There were no missing data. Statistics We performed chi-squares to determine whether scorers differed from each other in use of the four level confidence ratings across the segments, whereas Kendall’s coefficient of concordance (W) was used to examine strength of association of agreement among raters’ judgments. W was the preferred statistic (rather than Kappa) because of multiple raters and ordinal level ranking of confidence ratings. We examined consensus using several different thresholds by determining the number (out of 6) raters who employed the same exact rating to characterize a given segment. Analyses were performed separately for confidence ratings for phasic and tonic activity. Results The distribution of raters’ certainty varied widely across segments (for phasic activity, χ2 = 69.8, p < .0001, df 15; for tonic activity, χ2 = 167.7, p < .0001, df 15). These data suggested considerable differences among raters for determining the relative likelihood that phasic and tonic activity may be present in the segments. Tables 1 and 2 show certainty ratings by rater for phasic and tonic activity, respectively. The differences among raters in confidence levels are readily apparent. Despite these large differences across raters, Kendall’s coefficient of concordance suggested at least a moderate level of agreement of ratings that was statistically significant for both phasic (W = .47, p < .0001) and tonic (W = .58, p < .0001). In short, raters agreed far better than chance in their confidence levels on the presence of phasic and tonic activity, despite substantial individual differences. Elimination of Rater B, whose ratings appeared somewhat at variance with other raters, did not appreciably affect these values (W = .51, for phasic; W = .65 for tonic). Table 1. Confidence ratings for phasic EMG activity Rater Highly certain segment contains phasic activity Somewhat certain segment contains phasic activity Somewhat certain segment does not contain phasic activity Highly certain segment does not contain phasic activity A 24 14 5 17 B 51 6 2 1 C 24 15 8 13 D 26 16 12 6 E 31 16 9 4 F 20 24 13 3 Rater Highly certain segment contains phasic activity Somewhat certain segment contains phasic activity Somewhat certain segment does not contain phasic activity Highly certain segment does not contain phasic activity A 24 14 5 17 B 51 6 2 1 C 24 15 8 13 D 26 16 12 6 E 31 16 9 4 F 20 24 13 3 View Large Table 1. Confidence ratings for phasic EMG activity Rater Highly certain segment contains phasic activity Somewhat certain segment contains phasic activity Somewhat certain segment does not contain phasic activity Highly certain segment does not contain phasic activity A 24 14 5 17 B 51 6 2 1 C 24 15 8 13 D 26 16 12 6 E 31 16 9 4 F 20 24 13 3 Rater Highly certain segment contains phasic activity Somewhat certain segment contains phasic activity Somewhat certain segment does not contain phasic activity Highly certain segment does not contain phasic activity A 24 14 5 17 B 51 6 2 1 C 24 15 8 13 D 26 16 12 6 E 31 16 9 4 F 20 24 13 3 View Large Table 2. Confidence ratings for tonic EMG activity Rater Highly certain segment contains tonic activity Somewhat certain segment contains tonic activity Somewhat certain segment does not contain tonic activity Highly certain segment does not contain tonic activity A 28 16 11 5 B 1 2 5 52 C 8 9 17 26 D 33 12 6 9 E 14 28 10 8 F 16 22 10 12 Rater Highly certain segment contains tonic activity Somewhat certain segment contains tonic activity Somewhat certain segment does not contain tonic activity Highly certain segment does not contain tonic activity A 28 16 11 5 B 1 2 5 52 C 8 9 17 26 D 33 12 6 9 E 14 28 10 8 F 16 22 10 12 View Large Table 2. Confidence ratings for tonic EMG activity Rater Highly certain segment contains tonic activity Somewhat certain segment contains tonic activity Somewhat certain segment does not contain tonic activity Highly certain segment does not contain tonic activity A 28 16 11 5 B 1 2 5 52 C 8 9 17 26 D 33 12 6 9 E 14 28 10 8 F 16 22 10 12 Rater Highly certain segment contains tonic activity Somewhat certain segment contains tonic activity Somewhat certain segment does not contain tonic activity Highly certain segment does not contain tonic activity A 28 16 11 5 B 1 2 5 52 C 8 9 17 26 D 33 12 6 9 E 14 28 10 8 F 16 22 10 12 View Large Complete consensus on exact ratings (i.e. all six raters agreeing unequivocally on a specific rating) was rare and occurred on only six (of 60) (10.0%) segments for phasic confidence ratings and for only five (of 60) (8.3%) segments on tonic confidence ratings. However, when consensus was defined by five or more raters’ agreement in confidence levels, the number of consensually agreed upon segments increased to 13 (21.7%) for phasic activity and 9 (15.0%) for tonic activity. Analyses of these consensually agreed upon segments showed that high certainty for the presence of phasic activity was significantly higher (12/13, 92.3%) than for high certainty of the presence of tonic activity (3/9, 33.3%), a statistically significant difference (χ2 = 7.19, p < .01, df 1). When consensus was defined by four or more raters’ agreement in confidence levels, the number of consensually agreed upon segments increased to 28 (phasic) and 24 (tonic). Analyses of these consensually agreed upon segments showed that high certainty for the presence of phasic activity was significantly higher (27/28; 96.4%) than for high certainty of the presence of tonic activity (15/24, 62.5%), also a statistically significant difference (χ2 = 9.58, p = .002, df 1). A listing of specific segments (by segment number) for these varying levels of consensus are shown in the Supplementary Material. We also examined segments for those showing least agreement, defined as segments for which no more than two of six raters showed exact agreement on certainty. For phasic activity, 9/60 segments (15.0 %) showed such extremes of disagreement, whereas for tonic activity, 18/60 segments (30.0%) showed such extremes of disagreement. Only three segments fulfilled both of these definitions, suggesting that uncertainty for defining one type of activity does not necessarily impact the uncertainty of defining the other type of activity. The specific segments (listed by segment number) falling into these categories are also shown in the Supplementary Material. Discussion In this study, we found that unanimous agreement among raters was a rarity. These data also indicated that raters agreed more often on what constituted phasic activity than they did as to what constituted tonic activity. Although it could be argued that any such exercise in inter-rater agreement depends on the features of the segments selected (e.g. higher density of both phasic and tonic EMG activity might be expected in segments from synucleinopathic patients), our procedure involving raters’ judgments for every segment for BOTH phasic and tonic activity and have them rate their confidence for both the presence AND absence of activity implies that the implications of such ratings are likely to have relevance beyond the specific segments selected here. Reliabilities of confidence ratings would be expected to be no higher (and possibly lower) than those achieved here for more complicated and more ambiguous signal segments. This study was one primarily of pattern recognition, i.e. we made no attempt to distinguish normal from abnormal EMG activity by diagnostic group. A substantial amount of impressive work has focused on the utility of tonic and phasic measures of EMG activity, from not only mentalis, but from limb muscles [10, 12, 19, 35, 36] as well, as a means of differentiating features of sleep among synucleinopathic conditions [20, 23, 30, 43], describing progression of disease in the synucleinopathies [18, 19, 30], and differentiating clinical features of already diagnosed patients, some of whom do and do not have RBD [4, 8, 15, 17, 18, 21]. The goal of the current study was very different. Our rationale was based on the premise that if trained sleep medicine experts had uncertainty about how to characterize EMG activity (as they would in the course of routine PSG interpretation), routine adoption of this terminology for visual analyses of sleep studies could prove be limited value. Our panel was broad and encompassed what is likely to be a representative cross-section of most AASM sleep specialists, and included two pulmonologists, two neurologists and two PhD sleep specialists with extensive background in PSG interpretation. Our data did not address diagnostic utility of the EMG signal, but they may have bearing up on how future studies conceptualize, measure, and study outcomes associated with such activity. There are limitations in our approach. The segments selected for our analyses (Supplementary Material) tended to be brief (median sample length of our 60 segments was 6.6 s), and it is conceivable that this might have biased raters against reliable consensus for tonic EMG activity. As used in clinical sleep medicine, reference to “tonic” EMG activity typically connotes longer intervals of time than does the term “phasic.” For example, the AASM definition [42] to define REM sleep without atonia stipulates tonic activity with a duration of at least 15.0 s or, alternatively, at least five 3.0 s intervals with phasic activity. Other researchers distinguishing the two types of activity allow for a definition inclusive of EMG activations ranging from 5.0 s to 14.9 s [10, 12] to differentiate phasic activity from other longer duration activity (inclusive of tonic activity). Yet others define “long duration” EMG activity in sleep with a 0.5- to 15.0-s window [37], though historically the Montreal group included in their definition of phasic activity durations extending from 0.1 to 5.0 [11] or 0.1 to 10.0 [13] s, whereas tonic activity was longer than this (i.e. >50% of the duration of a 20-s epoch). The Marburg group [14] reported that the vast majority of mentalis EMG activations were <200 ms in duration and considered any duration >2.0 s to represent “long duration” events. Thus, while there is lack of consensus over what duration of EMG activation should be considered “short” or “long,” the durations of at least some of our EMG activity segments fell on the shorter end of what some researchers have called tonic activity and could be considered compatible with the durations of some definitions of phasic activity. It thus is possible that our samples might have biased raters towards higher levels of confidence in their ratings of phasic (versus tonic) activity. Arguing against this reasoning is that complete consensus (i.e. all six raters in exact agreement) was virtually identical for the number of tonic (five) and phasic (six) segments with ratings of high confidence for the presence of such activity. We are not the first group to note the complexity of making the reliable visual differentiation of phasic and tonic activity from surface EMG recordings. It was this issue that prompted the SINBAR (Sleep Innsbruck Barcelona) group to devise a category for “any” EMG activity, which encompassed both phasic and tonic components [10, 36]. Among automated techniques for characterizing EMG activity during sleep and especially for measuring REM sleep without atonia, the REM atonia index developed by Ferri and colleagues is the most extensively examined, with demonstrated age effects [3], absence of atonia in narcolepsy [34], nightly stability [7], and utility in differentiating PD patients with and without RBD history [4], as well as with concurrent validation via visual scoring [5, 8] and refinement of diagnostic threshold values [6]. Because it integrates all components of EMG activity that exceed a moving amplitude threshold over brief time intervals, the REM atonia index ultimately is a more thorough characterization of absence of EMG activity than about what constitutes the presence of EMG activity. Other automated systems, ranging from primitive hybrid analogue/digital approaches [44] to more sophisticated digital systems encompassing amplitude based variance measures [9, 14], some taking into account EMG signal frequency [2, 45], also summate muscle activity across some component of the temporal continuum using alternative computational procedures. Because tonic EMG activity recorded with surface electrodes is assumed to represent an amalgam of motor units firing in varying and mixed sequences [46], it could be contended that phasic events, if reliably and validly ascertained, could well represent the most fundamental and elemental component of muscle activity, albeit one that may be difficult to assess with surface electrodes. Studies comparing EMG recordings made from surface electrodes, however, exhibit good correspondence to motor units recorded with needle electrodes, at least when large muscle groups (e.g. anterior tibialis) are involved and forces generated are small to moderate, rather than extreme [47]. Motor unit potentials, though not usually shown to be abnormal in the synucleinopathies (c.f., motor neuron disease), demonstrate increased amplitude in the anterior tibialis during wakefulness in up to a third of Parkinson’s cases [48], which further increases the potential relevance of phasic muscle activity recorded during sleep from surface electrodes in such patients. Finally, there is one additional rationale arguing for assessment of phasic EMG activity as a potentially meaningful metric in the assessment of synucleinopathies. This derives from the basic science literature reflecting the likely neurobiological substrates for changes in EMG activity during REM sleep in synucleinopathic conditions. Study of sleep in wild type rats where both GABA-A and glycine receptors are blocked pharmacologically, as well as studies of transgenic mice lacking intact function of such these receptors, have shown excessive twitch activity in neck, masseter and limb muscles during REM (and to some extent NREM), but without change in basal muscle tone [49, 50]. This line of research further implies that, together with the purely technical considerations that we have outlined in this study, reliable visual analyses of muscle activity during clinical polysomnography should probably focus more on shorter, rather than longer, duration events. Supplementary material Supplementary material is available at SLEEP online. Notes Conflict of interest statement. 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TI - Inter-rater agreement for visual discrimination of phasic and tonic electromyographic activity in sleep
JF - SLEEP
DO - 10.1093/sleep/zsy080
DA - 2018-05-02
UR - https://www.deepdyve.com/lp/oxford-university-press/inter-rater-agreement-for-visual-discrimination-of-phasic-and-tonic-0CCEpFSdD6
SP - 1
VL - Advance Article
IS - 7
DP - DeepDyve
ER -