Methodological considerations
restless, sleep stage, CRPS, pain
The rTMS effect on sleep was assessed with two subjective items and four objective Oura variables. None of these were predefined as a primary outcome measure, and thus concurrent analysis of several parameters increases the risk of false‐positive results. The sample size for this study was defined by the power analysis of the multicenter study, utilizing different outcome variables than in this study.As the most significant LDA‐based model utilized multiple variables (“restless” and “onset_latency”), the findings suggest that it is beneficial to consider simultaneously multiple sleep measures when examining the effects of rTMS treatment on sleep. However, as the variable “restless” that yielded significant results in the univariate analysis was included in all the LDA‐based models with significant findings, the possible benefits of multivariate analyses in examining the effects of rTMS treatment on sleep need to be verified in a larger patient cohort.The small patient cohort limited the number of Oura variables that could be considered in the analyses. The Oura ring provides 13 original measures that could have been used in the multivariate analyses. As our sample consisted of a total of 17 patients, we restricted the testing to the four most likely candidates based on previous studies. However, a recent validation study suggests that several consumer wearables, including the Oura ring, provide reasonable estimations of sleep stage classification as well (Miller et al., Another limiting factor was the small amount of data from individual patients. On average, Oura data were collected during about five and four nights in the pre‐ and posttreatment phases, respectively. However, in several patients, data were available only from three nights either in the pre‐ or posttreatment phase. Thus, the LDA‐based analyses were conducted using data from individual nights only in both the training and testing phase. Accordingly, the classification analyses were likely considerably affected by random variability in the sleep patterns across individual nights. The collection of Oura data for longer periods both in the pre‐ and‐post treatment phases would allow, for example, averaging of data from individual nights, leading to more stable estimates of the Oura variables and more robust dissociation of the patient groups as well as more robust identification of the key sleep measures.As no general normative values for Oura variables exist, we cannot determine if the sleep‐related values in CRPS patients were abnormal as compared with people without pain. Additionally, as there was no significant improvement in self‐reported sleep after the intervention, the clinical relevance of the S2‐targeted rTMS effect on sleep remains to be studied in more detail.