Body mass index and distribution of body fat can influence sensory detection and pain sensitivity.

BACKGROUND: The aim of this study was to investigate the influence of body fat percentage and its distribution on sensory detection and pain sensitivity responses to experimentally induced noxious stimuli in otherwise pain-free individuals. METHODS: Seventy-two participants were divided into three equal groups according to their body mass index (BMI: normal, overweight and obese). Percentage body fat was estimated using a four-site skinfold method. Measurements of cold pressor pain threshold, tolerance and intensity; contact thermal sensory detection and heat pain threshold and tolerance (TSA-II - NeuroSensory Analyzer, Medoc); and blunt pressure pain threshold (algometer, Somedic SenseLab AB) were taken at the waist and thenar eminence. RESULTS: Mean ± SD pressure pain threshold of the obese group (620.72 ± 423.81 kPa) was significantly lower than normal (1154.70 ± 847.18 kPa) and overweight (1285.14 ± 998.89 kPa) groups. Repeated measures ANOVA found significant effects for site for cold detection threshold (F1,68  = 8.3, p = 0.005) and warm detection threshold (F1,68  = 38.69, p = 0.001) with waist having lower sensory detection thresholds than thenar eminence. For heat pain threshold, there were significant effects for site (F1,68  = 4.868, p = 0.031) which was lower for waist compared with thenar eminence (mean difference = 0.89 °C). CONCLUSION: Obese individuals were more sensitive than non-obese individuals to pressure pain but not to thermal pain. Body sites may vary in their response to different types and intensities of stimuli. The inconsistency of findings within and between research studies should catalyse further research in this field. SIGNIFICANCE: This study provided evidence that body mass index and distribution of body fat can influence sensory detection and pain sensitivity. Obese individuals were more sensitive than normal range body mass index individuals to pressure pain but not to thermal pain. Pain response varied according to subcutaneous body fat at different body sites. These findings strengthen arguments that weight loss should be a significant aspect of a pain management programme for obese pain patients

Am I getting an accurate picture: a tool to assess clinical handover in remote settings?

BACKGROUND: Good clinical handover is critical to safe medical care. Little research has investigated handover in rural settings. In a remote setting where nurses and medical students give telephone handover to an aeromedical retrieval service, we developed a tool by which the receiving clinician might assess the handover; and investigated factors impacting on the reliability and validity of that assessment. METHODS: Researchers consulted with clinicians to develop an assessment tool, based on the ISBAR handover framework, combining validity evidence and the existing literature. The tool was applied 'live' by receiving clinicians and from recorded handovers by academic assessors. The tool's performance was analysed using generalisability theory. Receiving clinicians and assessors provided feedback. RESULTS: Reliability for assessing a call was good (G = 0.73 with 4 assessments). The scale had a single factor structure with good internal consistency (Cronbach's alpha = 0.8). The group mean for the global score for nurses and students was 2.30 (SD 0.85) out of a maximum 3.0, with no difference between these sub-groups. CONCLUSIONS: We have developed and evaluated a tool to assess high-stakes handover in a remote setting. It showed good reliability and was easy for working clinicians to use. Further investigation and use is warranted beyond this setting

Atypical processing of gaze cues and faces explains comorbidity between autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD)

This study investigated the neurobiological basis of comorbidity between autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). We compared children with ASD, ADHD or ADHD+ASD and typically developing controls (CTRL) on behavioural and electrophysiological correlates of gaze cue and face processing. We measured effects of ASD, ADHD and their interaction on the EDAN, an ERP marker of orienting visual attention towards a spatially cued location and the N170, a right-hemisphere lateralised ERP linked to face processing. We identified atypical gaze cue and face processing in children with ASD and ADHD+ASD compared with the ADHD and CTRL groups. The findings indicate a neurobiological basis for the presence of comorbid ASD symptoms in ADHD. Further research using larger samples is needed