ABSTRACT
Objective To investigate the effects of real-time feedback devices on chest compression quality test in non-medical staff during cardiopulmonary resuscitation (CPR) training.Methods A total of 120 volunteers were recruited and trained according to American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care set in 2015.CPR performance with compression for six minutes was tested on a manikin.Volunteers were randomized into 3 groups.Group A was tested without any feedback.Group B was self-corrected in compression quality(include compression depth、rate and rebound of chest wall) using a real-time feedback device (Link CPR).Group C was guided with a metronome.All compression data were collected via WiFi signal and stored.Results Significantly better mean chest compression depth was achieved in group B than that in group A and C(5.38 ± 0.483 cm vs.4.42 ± 0.572cm and 4.25 ± 0.843 cm,P ＜ 0.05).Significantly better compression rate were observed in both group B and C than that in group A (113.4 ± 5.9 and 109.0 ± 6.8 compressions/min vs.129.6 ± 8.3 compressions/min,P ＜ 0.05).Significantly less rebounding were observed in both group B and C compared with group A (56.10 ± 32.3 and 68.30 ± 28.8 compressions vs.174.30 ± 38.8compressions,P ＜ 0.05).Pearson correlation analysis confirmed the compression rate was positively correlated with the numbers of rebounding (r=0.776,P＜0.01).Significant statistical difference in accuracy was observed among the groups (9.8％ vs.72.9％ vs.58.5％,P ＜ 0.05).Conclusions In CPR training test real-time feedback device contributes to the improvement of chest compression quality through self-adjustment of compression depth,rate and rebound.
ABSTRACT
OBJECTIVE: To assess associations between napping and night-time sleep duration with impaired glucose regulation, insulin resistance (IR) and glycated haemoglobin (HbA1c). DESIGN: Cross-sectional study. SETTING: Fujian Province, China, from June 2011 to January 2012. PARTICIPANTS: This study enrolled 9028 participants aged 40-65â years. Data of 7568 participants with no diabetes were included for analysis. Type 2 diabetes was defined applying WHO criteria. OUTCOME MEASURES: Participants' daytime napping and night-time sleep duration data were collected using a standardised self-reported Chinese-language questionnaire about sleep frequency and quality. Anthropometric and laboratory parameters were also measured. IR was defined as a HOMA-IR index value >2.50. ORs and 95% CIs were derived from multivariate logistic regression models. RESULTS: Participants (mean age 51.1±7.0â years) included 3060 males and 4508 females with average night-time sleep of 7.9â h. A higher proportion of males napped than females. After adjustment for potential confounders, ORs for HbA1c >6.0% were 1.28 and 1.26 for those napping ≤1â h and >1â h (p=0.002 and p=0.018), respectively. Statistically significant differences in IR between nappers and non-nappers were only marginal clinically. Odds for HbA1c >6.0% were significantly lower in participants with longer night-time sleep durations than in the reference group (>8â h vs 6-8â h). Odds for IR were significantly lower in participants whose night-time sleep hours deviated from the reference group (<6â h, >8â h vs 6-8â h) CONCLUSIONS: Chinese middle-aged adults with no diabetes who napped had higher HbA1c and IR; those with shorter night-time sleep durations had increased HbA1c. Night-time sleep hours that are either <6 or >8 tend to be associated with lower odds for IR. Further studies are necessary to determine the underlying clinical significance and mechanisms behind these associations.