Abstract This experiment was to study the feasibility from direct observation of muscle contraction of the lower extremity fromelectrical stimulation threshold of nerve fascicle in identifying the Iα intrafusal afferent fibers during selective posterior rhizotomy (SPR) and to investigate the clinical relationship between the muscle spasm and the electrical stimulation of nerve fascicles. The electrical stimulation threshold of all nerve fascicles in 36 cases during SPR were analysed statistically. The results showed that there was a significant difference between the electrical stimulation threshold of the severed nerve fascicles and intact nerve fascicles no matter the nerve root or each posterior nerve rootlet was examined. It was simple and reliable for surgeons to identify correctly the Iα intrafusal afferent fibers intraoperatively from direct observation of the electrical stimulation threshold of nerve fascicle.
In the clinical evidence-based decision-making process, factors including benefits and harms, evidence certainty, cost and feasibility of interventions should be considered based on the best evidence. The development of decision threshold of effect size (DTES) for patient health outcomes can help stakeholders understand the benefits and harms of interventions, assess evidence certainty, and interpret research results. Based on international experience, the MERGE Working Group through group discussions, semi-structured interviews, expert consensus, and pilot application developed a set of 8-step guidelines for the development of DTES for health outcomes. These steps included necessity assessment, formation of working groups, selection of patient important outcomes, creation of scenarios based on the best evidence, design of expert consultation questionnaires, analysis of expert consultation results, face-to-face expert consensus, dissemination of the application and reevaluation. The DTES guideline development is intended to provide methodological guidance for stakeholders to develop DTES for health outcome indicators in different domains.
ObjectiveTo systematically review the non-inferiority trials in the cardiovascular domain that utilize medical devices as interventions, and investigate its characteristics and threshold settings. MethodsThe PubMed, Embase, and CENTRAL databases were electronically searched to collect non-inferiority trials in the cardiovascular field involving medical devices from inception to July 26, 2023. Two reviewers independently screened literature and extracted data. The reported information included basic characteristics, features of non-inferiority trials, and threshold-setting features of the included studies. Data analysis was performed using Excel 2020 and R 4.2.1 software. ResultsA total of 214 studies were included, with 167 studies (78.0%) focusing on interventions related to coronary artery stents. The trials predominantly utilized a two-arm design (92.9%), with a prevalent use of non-inferiority absolute thresholds (96.7%) as the criteria for non-inferiority determination. In 150 studies (70.1%), non-inferiority thresholds were established based on estimated control group effect values, while 33 studies (15.4%) did not report the source of these values. The non-inferiority trial endpoint outcomes exhibited diversity, and there were substantial differences in threshold settings. The three most studied qualitative indicators were target lesion failure rates (2.1%-8.6%), target vessel failure rates (2.5%-19.6%), and major adverse cardiovascular events rates (2.1%-10.0%). Late lumen loss (0.1-0.4 mm) emerged as the most frequently studied quantitative indicator. After converting absolute non-inferiority thresholds for all indicators into relative thresholds, the range was 1.20-3.67. ConclusionSignificant variations in non-inferiority threshold settings are observed for identical endpoint outcomes across included studies, highlighting a lack of reporting on the rationale behind threshold settings.
It is difficult to distinguish the inferior alveolar nerve (IAN) from other tissues inside the IAN canal due to their similar CT values in the X image which are smaller than that of the bones. The direct reconstruction, therefore, is difficult to achieve the effects. The traditional clinical treatments mainly rely on doctors' manually drawing the X images so that some subjective results could not be avoided. This paper proposes the partition reconstruction of IAN canal based on shape features. According to the anatomical features of the IAN canal, we divided the image into three parts and treated the three parts differently. For the first, the directly part of the mandibular, we used Shape-driven Level-set Algorithm Restrained by Local Information (BSLARLI) segment IAN canal. For the second part, the mandibular body, we used Space B-spline curve fitting IAN canal's center, then along the center curve established the cross section. And for the third part, the mental foramen, we used an adaptive threshold Canny algorithm to extract IAN canal's edge to find center curve, and then along it established the cross section similarly. Finally we used the Visualization Toolkit (VTK) to reconstruct the CT data as mentioned above. The VTK reconstruction result by setting a different opacity and color values of tissues CT data can perspectively display the INA canal clearly. The reconstruction result by using this method is smoother than that using the segmentation results and the anatomical structure of mental foramen position is similar to the real tissues, so it provides an effective method for locating the spatial position of the IAN canal for implant surgeries.
Electric and electronic products are required to pass through the certification on electrical safety performance before entering into the market in order to reduce electrical shock and electrical fire so as to protect the safety of people and property. The leakage current is the most important factor in testing the electrical safety performance and the test theory is based on the perception current effect and threshold. The traditional method testing the current threshold for perception only depends on the sensing of the human body and is affected by psychological factors. Some authors filter the effect of subjective sensation by using physiological and psychological statistical algorithm in recent years and the reliability and consistency of the experiment data are improved. We established an experiment system of testing the human body's current threshold for perception based on EEG feature analysis, and obtained 967 groups of data. We used wavelet packet analysis to detect α wave from EEG, and used FFT to do spectral analysis on α wave before and after the current flew through the human body. The study has shown that about 97.72% α wave energy changes significantly when electrical stimulation occurs. It is well proved that when the EEG feature identification is applied to test the human body current threshold for perception, and meanwhile α wave energy change and human body sensing are used together to confirm if the current flowing through the human body reaches the perception threshold, the measurement of the human body current threshold for perception could be carried out objectively and accurately.
Red blood cell (RBC) transfusions are frequently used in cardiac surgery. A minority of patients assume most of the blood products transfusion during and after cardiac operations. Observational analysis of transfusion in patients undergoing cardiac surgery has uniformly demonstrated that RBC transfusion is associated with a significantly increasing risk of all-cause mortality and other serious adverse outcomes. In addition, it is an established fact that such patients can tolerate relatively low hemoglubin (Hb) levels. Consequently, it becomes widely accepted that appropriate limitation of transfusions could confer a substantial benefit to patients and decrease the use of limited resource. As a result, a restrictive threshold for blood transfusion is likely to be favored under most circumstances. However, an increasing amount of data differing from the observational analysis shows that clinical outcomes in patients who received transfusions with restrictive thresholds for Hb level are not superior to those with liberal thresholds. It has created a new uncertainty regarding the use of a restrictive threshold for transfusion during the perioperative period of cardiac surgery.
To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age: 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (P < 0.05). Next, using the relationship between multiple thresholds and network parameters, the area under the curve (AUC) of each network parameter was extracted as new features (P < 0.05). Finally, support vector machine (SVM) was used to classify the two groups with the network parameters and their AUC as features. The study results show that with strength, average characteristic path length, and average clustering coefficient as features, the classification accuracy in the θ band is increased from 69% to 71%, 66% to 77%, and 50% to 68%, respectively. In the α band, the accuracy is increased from 72% to 79%, 69% to 82%, and 65% to 75%, respectively. And from overall view, when AUC of network parameters was used as a feature in the α band, the classification accuracy is improved compared to the network parameter feature. In the θ band, only the AUC of average clustering coefficient was applied to classification, and the accuracy is improved by 17.6%. The study proved that based on graph theory, the method of feature optimization of brain function network could provide some theoretical support for the computer-aided diagnosis of adolescent depression.
ObjectiveTo evaluate the prognosis of photocoagulation and (or) cryotherapy for prethreshold type 1 and threshold disease of retinopathy of prematurity (ROP).MethodsThe data of 29 eyes of 15 infants who were diagnosed as with prethreshold type 1 or threshold disease of ROP from Jan 30th, 2003 to Jan 13th, 2005 were retrospectively analysed. Pre- and post-operative conditions of ROP were compared in the follow up. Any related local and systemic complications were recorded.ResultsIn 29 eyes which had undergone photocoagulation and (or) cryotherapy, ROP regressed completely in 19 (65.5%), remained dragged retina was found in 7 (24.1%), and retinal detachment was seen in 3 (103%). ROP regressed completely in 12 eyes (41.4%) after the initial treatment and in 7 eyes (24.1%) after the secondary treatment. During the treatment, temporary corneal haze was found in 2 eyes, vitreous hemorrhage occurred in 1 eye, and inadvertent photocoagulation at macular area happened in 1 eye. No systemic complications were found in all cases.ConclusionTimely treatment of photocoagulation and (or) cryotherapy for prethreshold type 1 and threshold disease of ROP may lead to famous prognosis.(Chin J Ocul Fundus Dis,2005,21:278-281)
Aiming at the single treatment and the design separation between treatment and assessment in electrotherapy equipment, a kind of system including low-intermediate frequency treatment and efficacy evaluation was developed. With C8051F020 single-chip microcomputer as the core and the circuit design and software programming used, the system realized the random switch of therapeutic parameters, the collection, display and data storage of pressure pain threshold in the assessment. Experiment results showed that the stimulus waveform, current intensity, frequency, duty ratio of the system output were adjustable, accurate and reliable. The obtained pressure pain threshold had a higher accuracy (<0.3 N) and better stability, guiding the parameter choice in the precise electrical stimulation. It, therefore, provides a reliable technical support for the treatment and curative effect assessment.
The brain-computer interface (BCI) systems used in practical applications require as few electroencephalogram (EEG) acquisition channels as possible. However, when it is reduced to one channel, it is difficult to remove the electrooculogram (EOG) artifacts. Therefore, this paper proposed an EOG artifact removal algorithm based on wavelet transform and ensemble empirical mode decomposition. Firstly, the single channel EEG signal is subjected to wavelet transform, and the wavelet components which involve EOG artifact are decomposed by ensemble empirical mode decomposition. Then the predefined autocorrelation coefficient threshold is used to automatically select and remove the intrinsic modal functions which mainly composed of EOG components. And finally the ‘clean’ EEG signal is reconstructed. The comparative experiments on the simulation data and the real data show that the algorithm proposed in this paper solves the problem of automatic removal of EOG artifacts in single-channel EEG signals. It can effectively remove the EOG artifacts when causes less EEG distortion and has less algorithm complexity at the same time. It helps to promote the BCI technology out of the laboratory and toward commercial application.