Background: Virtual reality (VR) and augmented reality (AR) are emerging technologies that can be used for cardiopulmonary resuscitation (CPR) training. Compared to traditional face-to-face training, VR/AR-based training has the potential to reach a wider audience, but there is debate regarding its effectiveness in improving CPR quality. Therefore, we conducted a meta-analysis to assess the effectiveness of VR/AR training compared with face-to-face training. Methods: We searched PubMed, Embase, Cochrane Library, Web of Science, CINAHL, China National Knowledge Infrastructure, and Wanfang databases from the inception of these databases up until December 1, 2023, for randomized controlled trials (RCTs) comparing VR- and AR-based CPR training to traditional face-to-face training. Cochrane's tool for assessing bias in RCTs was used to assess the methodological quality of the included studies. We pooled the data using a random-effects model with Review Manager 5.4, and assessed publication bias with Stata 11.0. Results: Nine RCTs (involving 855 participants) were included, of which three were of low risk of bias. Meta-analyses showed no significant differences between VR/AR-based CPR training and face-to-face CPR training in terms of chest compression depth (mean difference [MD], -0.66 mm; 95% confidence interval [CI], -6.34 to 5.02 mm; P = 0.82), chest compression rate (MD, 3.60 compressions per minute; 95% CI, -1.21 to 8.41 compressions per minute; P = 0.14), overall CPR performance score (standardized mean difference, -0.05; 95% CI, -0.93 to 0.83; P = 0.91), as well as the proportion of participants meeting CPR depth criteria (risk ratio [RR], 0.79; 95% CI, 0.53 to 1.18; P = 0.26) and rate criteria (RR, 0.99; 95% CI, 0.72 to 1.35; P = 0.93). The Egger regression test showed no evidence of publication bias. Conclusions: Our study showed evidence that VR/AR-based training was as effective as traditional face-to-face CPR training. Nevertheless, there was substantial heterogeneity among the included studies, which reduced confidence in the findings. Future studies need to establish standardized VR/AR-based CPR training protocols, evaluate the cost-effectiveness of this approach, and assess its impact on actual CPR performance in real-life scenarios and patient outcomes. Trial registration: CRD42023482286.

Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10⁻¹¹. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10⁻¹⁰ for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10⁻⁸ for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

Thus far, when deception behaviors occur, the connectivity patterns and the communication between different brain areas remain largely unclear. In this study, the most important information flows (MIIFs) between different brain cortices during deception were explored. First, the guilty knowledge test protocol was employed, and 64 electrodes’ electroencephalogram (EEG) signals were recorded from 30 subjects (15 guilty and 15 innocent). Cortical current density waveforms were then estimated on the 24 regions of interest (ROIs). Next, partial directed coherence (PDC), an effective connectivity (EC) analysis was applied in the cortical waveforms to obtain the brain EC networks for four bands: delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz) and beta (13–30 Hz). Furthermore, using the graph theoretical analysis, the network parameters with significant differences in the EC network were extracted as features to identify the two groups. The high classification accuracy of the four bands demonstrated that the proposed method was suitable for lie detection. In addition, based on the optimal features in the classification mode, the brain “hub” regions were identified, and the MIIFs were significantly different between the guilty and innocent groups. Moreover, the fronto-parietal network was found to be most prominent among all MIIFs at the four bands. Furthermore, combining the neurophysiology significance of the four frequency bands, the roles of all MIIFs were analyzed, which could help us to uncover the underlying cognitive processes and mechanisms of deception.

Critical patients with COVID-19 are thought to be at high risk of developing chronic pain. However, the exact nature and mechanisms of COVID-19-related chronic pain remain largely unknown. Here, we describe clinical features, treatments and outcome of herpes zoster as well as postherpetic neuralgia in a 70-year-old woman with critical COVID-19. The patient had a history of type 2 diabetes and myasthenia gravis. She developed herpes zoster in the right 10 to 12 lumbar dermatomes in the recovery period of COVID-19. Intravenous (250 mg 3 times a day) and then oral (400 mg 5 times a day) acyclovir was used for antiviral therapy. Pregabalin (75 mg orally twice a day) and ibuprofen was used for analgesia. Her skin lesions resolved 21 days after the onset of rash. However, she continued to have persistent pain in the same dermatomal distribution. After the dosage of pregabalin was increased to 150 mg orally twice a day, her pain was partially relieved. During the telephone follow-up 4 months after herpes zoster eruption, the patient still complained intermittent pain in the right 10 to 12 lumbar dermatomes. Our case draws attention to postherpetic neuralgia in COVID-19 patients and provides a targeted suggestion for this kind of patients.

Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood while it has been suggested that self-reported headache and self-reported migraine were genetically correlated. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank and the self-reported migraine phenotype from the 23andMe using the Unified Score-based Association Test (metaUSAT) software for genetically correlated phenotypes (N = 397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and four loci were newly suggested. The LDL receptor related protein 1 (LRP1)—Signal Transducer and Activator of Transcription 6 (STAT6)—Short chainDehydrogenase/Reductase family 9C member 7 (SDR9C7) region in chromosome 12 was the most significantly associated locus with a leading p value of 1.24 × 10^–62 of rs11172113. The One Cut homeobox 2 (ONECUT2) gene locus in chromosome 18 was the strongest signal among the four new loci with a p value of 1.29 × 10^–9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more variants for headaches. This study has paved way for a large GWAS meta-analysis involving cohorts of different while genetically correlated headache phenotypes.