Effect of clinical characteristics on relapse of alcohol dependence: a prospective cohort study / 北京大学学报(医学版)

OBJECTIVE@#To investigate whether craving and demographic factors to predict relapse in alcohol dependence.@*METHODS@#This study was a prospective cohort study. From August 2017 to August 2018, 158 Han male inpatients who met the diagnositic and statistical manual disorders-fourth version(DSM-IV) alcohol dependence diagnostic criteria were recruited from three mental hospitals in China. The participants were interviewed at baseline and followed up by telephone after 3 months for assessment. The baseline assessment after the acute withdrawal period included demographic data and alcohol-related data, clinical institute withdrawal assessment-advanced revised (CIWA-Ar), withdrawal and cue-induced craving on visual analog scale (VAS), Michigan alcoholism screening test (MAST), self-rating anxiety scale (SAS), self-rating depression scale (SDS) and alcohol urge questionnaire (AUQ). According to the follow-up results, "relapse" was defined as the consumption of beverages containing ethanol at any time during the follow-up study, and "time to relapse" was defined as the number of days from the first drinking to the baseline. Whether relapse occurred and the time to relapse were the primary endpoints. Cox proportional hazard regression model was used to analyze the factors affecting the relapse of alcohol dependence.@*RESULTS@#In the study, 158 alcohol dependence patients were finally included, age from 21 to 60 years, with the mean age of (40.31±9.14) years. The relapse rate was 63.7% three months after baseline assessment. According to Cox univariate analysis and multivariate analysis, the age (OR=0.975, P=0.030) and CIWA-Ar scores (OR=1.126, P=0.010) significantly predicted relapse. And there was no significant difference in education level, marital status, withdrawal and cue-induced craving on VAS, SAS and SDS between the relapse group and the non-relapse group (P>0.05).@*CONCLUSION@#Age and severity of alcohol-dependent withdrawal symptoms during hospitalization are significantly related to relapse for alcohol in alcohol-dependent patients. To be exact, the older age is a protective factor, that is to say, the younger patients are prone to relapse, while the risk of relapse is raised by the higher severity of withdrawal symptoms. However, neither cue-induced nor withdrawal craving can predict relapse of alcohol-dependent patients.

Verification of skin paste electrodes used in wireless polysomnography / 北京大学学报(医学版)

OBJECTIVE@#To explore an electrode suitable for wireless portable sleep monitoring equipment and analyze the result of the signals of electrooculogram (EOG) and electroencephalography (EEG) collected by this kind of flexible electrodes.@*METHODS@#The flexible electrodes were prepared by microelectromechanical systems (MEMS) technology. This kind of electrodes consisted parylene, chromium, and gold. Parylene, the flexible substrate of this kind of flexible electrodes, was of biocompatibility. Between parylene and gold there was an adhesion layer of chromium, which connected parylene and gold tightly. Then the flexible electrodes were stuck to medical adhesive tape. The electrodes were designed and made into a grid to make sure that the medical adhesive tape could tape on the skin tightly, so that the contact impedance between the electrodes and the skin would be reduced. Then the alternating current impedance of the electrode were tested by the CHI660E electrochemical workstation after the electrode was achieved. To make sure that this kind of electrodes could be used in EOG monitoring, the electrodes were connected to a wireless signal acquisition suite containing special biological signal acquisition and digital processing chip to gather different sites around the eyes and the electrical signals of different directions of the eye movements, then analyzed the signal-to-noise ratio of the EOG. At the end, the Philips A6 polysomnography was used to compare the noise amplitude of the EEG signals collected by the flexible electrode and the gold cup electrode.@*RESULTS@#The electrodes stuck to the skin tightly, and these electrodes could collect signals that we wanted while the experiment was performed. The alternating current impedance of the flexible electrode was between 4 kΩ and 13 kΩ while with the frequency of alternating current under 100 Hz, most EEG signal frequencies were at this range. The EOG signals collected by the flexible electrodes were in line with the clinical requirements. The noise amplitude of EEG signals collected by the flexible electrodes was lower than that of the electrical signals collected by the gold cup electrodes.@*CONCLUSION@#The flexible electrode could be taken into consideration as an alternative electrode for monitoring EOG and EEG signals, and the wireless portable sleep monitoring devices are to be further developed in the future.

Independent verification of monitor unit calculation for radiation treatment planning system / 癌症

<p><b>BACKGROUND AND OBJECTIVE</b>To ensure the accuracy of dose calculation for radiation treatment plans is an important part of quality assurance (QA) procedures for radiotherapy. This study evaluated the Monitor Units (MU) calculation accuracy of a third-party QA software and a 3-dimensional treatment planning system (3D TPS), to investigate the feasibility and reliability of independent verification for radiation treatment planning.</p><p><b>METHODS</b>Test plans in a homogenous phantom were designed with 3-D TPS, according to the International Atomic Energy Agency (IAEA) Technical Report No. 430, including open, blocked, wedge, and multileaf collimator (MLC) fields. Test plans were delivered and measured in the phantom. The delivered doses were input to the QA software and the independent calculated MUs were compared with delivery. All test plans were verified with independent calculation and phantom measurements separately, and the differences of the two kinds of verification were then compared.</p><p><b>RESULTS</b>The deviation of the independent calculation to the measurements was (0.1 +/- 0.9)%, the biggest difference fell onto the plans that used block and wedge fields (2.0%). The mean MU difference between the TPS and the QA software was (0.6 +/- 1.0)%, ranging from -0.8% to 2.8%. The deviation in dose of the TPS calculation compared to the measurements was (-0.2 +/- 1.7)%, ranging from -3.9% to 2.9%.</p><p><b>CONCLUSIONS</b>MU accuracy of the third-party QA software is clinically acceptable. Similar results were achieved with the independent calculations and the phantom measurements for all test plans. The tested independent calculation software can be used as an efficient tool for TPS plan verification.</p>