Objective To investigate an evaluation method of medical literature applicability to clinical work， and provide a convenient way for physicians to search for the best evidence. Methods Delphi method was used to choose appropriate evaluating indexes， analytic hierarchy process was performed to determine the weighing of each index， and the formula to calculate medical literature applicability was formed. The practicability of this formula was evaluated by consistency checking between the formula’s results and experts’ opinions on literature applicability. Results Five evaluating indexes were determined， including literature’s publishing year （X1）， whether the target questions were covered （X2）, sample size （X3）， trial category （X4）， and journal level （X5）. The formula to calculate medical literature applicability was Y=3.93 X1＋11.78 X2＋14.83 X3＋44.53 X4＋24.93 X5. The result of consistency checking showed that the formula’s results were highly consistent with experts’ opinions （Kappa=0.75， P＜0.001）. Conclusion The applicability formula is a valuable tool to evaluate medical literature applicability.
Objective To assess the consistency of diagnostic results using optical coherence tomography angiography(OCTA) and fundus fluorescein angiography(FFA) in the central retinal vein occlusion(CRVO). Methods A retrospective case series of 26 eyes of 26 patients with CRVO. Simultaneous OCTA and FFA were performed in all patients by using 7-standard field of ETDRS to evaluate the microaneurysms, nonperfused areas, optical disc/retinal neovascularization and macular edema. The consistency was evaluated using weightedKappa statistic values.Kappa≥0.75, consistency is excellent; 0.60≤Kappa＜0.75, consistency is good; 0.40≤Kappa＜0.60, consistency is general;Kappa＜0.40, consistency is poor. Results Examined by OCTA, microaneurysms were found in 23 eyes, nonperfused areas in 16 eyes, optical disc/retinal neovascularization in 8 eyes and macular edema in 21eyes. Performed with FFA, 23 eyes were diagnosed to have microaneurysms, 16 eyes have nonperfused, 8 eyes have optical disc/retinal neovascularization, 22 eyes have macular edema. The consistency was excellent for microaneurysms(Kappa=0.772，P<0.01) and optical disc/retinal neovascularization(Kappa=0.766，P<0.01), good for nonperfused areas (Kappa=0.703，P<0.01) and macular edema(Kappa=0.60，P<0.01). Conclusion There is high consistency between OCTA and FFA in the diagnosis of CRVO, OCTA is an effective method in the examination of CRVO.
Objectives To evaluate the reporting quality of Bland-Altman method consistency evaluation in China from 2014 to 2016. Methods WanFang Data, VIP and CNKI databases were electronically searched to collect literature about the application of Bland-Altman method from 2014 to 2016 in China. Two reviewers screened literature, extracted data, and the data were then statistically analyzed by SPSS 22.0 software. Results A total of 376 articles were included. The published articles on Bland-Altman method had major flaws (not conforming to reporting standards) in the application conditions, evaluation indexes, graphic depiction and so on. Merely 11.4% of the literature set the clinically acceptable consensus values in the pre-period studies. Merely one literature (0.3%) correctly compared the 95%CI of 95%LoA with the clinically acceptable threshold which had been set previously. The offer rates of the differences between the two measurements and the 95%CI, 95%LoA and 95%CI of 95%LoA in the figure were 95.9%, 9.5%, 94.6% and 4.4%, respectively. Conclusions The reporting quality of Bland-Altman method consistency evaluation in China is of low quality, specifically not conforming to reporting standards. We should strengthen the introduction of Bland-Altman methodology to improve the reporting quality.
ObjectivesTo analyze the application value of 6-minute walking test (6MWT) in the clinical evaluation of chronic heart failure (CHF).MethodsPubMed, EMbase, The Cochrane Library, CBM, VIP, WanFang Data and CNKI databases were searched online to collect randomized controlled trials (RCTs) of 6-minute walking distance (6MWD) as the CHF evaluation index. Two reviewers independently screened literature, extracted data, and then analyzed data by using SPSS 17.0 statistical software. The 6MWD with symptom, quality of life, exercise tolerance (ETT), left ventricular ejection fraction (LVEF), peak oxygen consumption (pVO2) were analyzed by Kappa consistency test, and the possible influencing factors of 6MWD were analyzed by logistic regression.ResultsA total of 158 RCTs involving 17 853 patients were included. The results of statistical analysis showed that: 6MWD was consistent with the improvement of symptoms, quality of life, ETT, LVEF and pVO2 (Kappa>0.4). Baseline 6MWD (OR=2.91, 95%CI 1.278 to 6.634,P=0.011) and NYHA Ⅲ-Ⅳ ratio (OR=2.59, 95%CI 1.091 to 6.138, P=0.031) were the independent influencing factors for 6MWD improvement separately.ConclusionsThe 6MWT is an objective and reliable indicator of CHF evaluation.
ObjectiveTo observe the interobserver agreement of classification of macular degeneration in severe pathological myopia (PM) by ophthalmologists with different clinical experience. MethodsA retrospective study. From January 2019 to December 2021, 171 eyes of 102 patients with severe PM macular degeneration who were examined at Eye Center of Beijing Tongren Hospital of Capital Medical University were included in the study. The clinical data such as age, gender, axial length, spherical equivalent power, fundus color photography, and optical coherence tomography (OCT) were collected in detail. Six independent ophthalmologists (A, B, C, D, E, F) classified each fundus photography based on META-PM and ATN classification of atrophy (A) system and interobserver agreement was assessed by Kappa statistics. According to the classification standard of traction (T) in the ATN classification, the OCT images were interpreted and classified, in which T0 was subdivided into retinal pigment epithelium (RPE) and choroidal thinning, choroidal neovascularization (CNV) with partial RPE and choroidal atrophy, RPE, and choroidal atrophy. Lamellar macular hole can't be classified by ATN system, which was defined as TX. Kappa (κ) test was used to analyze the consistency of classification results between physicians A, B, C, D, E and F. κ value ≤0.4 indicates low consistency, 0.4＜κ value ≤ 0.6 indicates moderate consistency, and κ value ＞0.6 indicates strong consistency. ResultsAmong the 171 eyes of 102 cases, there were 20 males with 37 eyes (19.6%, 20/102), and 82 females with 134 eyes (80.4%, 82/102); age was 61.97±8.78 years; axial length was (30.87±1.93) mm; equivalent spherical power was (－16.56±7.00) D. Atrophy (A) classification results in META-PM classification and ATN classification, the consistency of physician A, B, C, D, E and physician F were 73.01%, 77.19%, 81.28%, 81.28%, 88.89%; κ value were 0.472, 0.538, 0.608, 0.610, 0.753, respectively. In the ATN classification, the T0, T1, T2, T3, T4, and T5 were in 109, 18, 11, 12, 9, and 8 eyes, respectively; TX was in 4 eyes. ConclusionsThere are differences in the consistency of classification of severe PM macular lesions among physicians with different clinical experience, and the consistency will gradually improve with the accumulation of clinical experience.
Lung cancer is the most threatening tumor disease to human health. Early detection is crucial to improve the survival rate and recovery rate of lung cancer patients. Existing methods use the two-dimensional multi-view framework to learn lung nodules features and simply integrate multi-view features to achieve the classification of benign and malignant lung nodules. However, these methods suffer from the problems of not capturing the spatial features effectively and ignoring the variability of multi-views. Therefore, this paper proposes a three-dimensional (3D) multi-view convolutional neural network (MVCNN) framework. To further solve the problem of different views in the multi-view model, a 3D multi-view squeeze-and-excitation convolution neural network (MVSECNN) model is constructed by introducing the squeeze-and-excitation (SE) module in the feature fusion stage. Finally, statistical methods are used to analyze model predictions and doctor annotations. In the independent test set, the classification accuracy and sensitivity of the model were 96.04% and 98.59% respectively, which were higher than other state-of-the-art methods. The consistency score between the predictions of the model and the pathological diagnosis results was 0.948, which is significantly higher than that between the doctor annotations and the pathological diagnosis results. The methods presented in this paper can effectively learn the spatial heterogeneity of lung nodules and solve the problem of multi-view differences. At the same time, the classification of benign and malignant lung nodules can be achieved, which is of great significance for assisting doctors in clinical diagnosis.
The gait acquisition system can be used for gait analysis. The traditional wearable gait acquisition system will lead to large errors in gait parameters due to different wearing positions of sensors. The gait acquisition system based on marker method is expensive and needs to be used by combining with the force measurement system under the guidance of rehabilitation doctors. Due to the complex operation, it is inconvenient for clinical application. In this paper, a gait signal acquisition system that combines foot pressure detection and Azure Kinect system is designed. Fifteen subjects are organized to participate in gait test, and relevant data are collected. The calculation method of gait spatiotemporal parameters and joint angle parameters is proposed, and the consistency analysis and error analysis of the gait parameters of proposed system and camera marking method are carried out. The results show that the parameters obtained by the two systems have good consistency (Pearson correlation coefficient r ≥ 0.9, P < 0.05) and have small error (root mean square error of gait parameters is less than 0.1, root mean square error of joint angle parameters is less than 6). In conclusion, the gait acquisition system and its parameter extraction method proposed in this paper can provide reliable data acquisition results as a theoretical basis for gait feature analysis in clinical medicine.