Measurement properties studies of patient-reported outcome measures (PROMs) aims to validate the measurement properties of PROMs. In the process of designing and statistical analysis of these measurement properties studies, bias will occur if there are any defects, which will affect the quality of PROMs. Therefore, the COSMIN (consensus-based standards for the selection of health measurement instruments) team has developed the COSMIN risk of bias (COSMIN-RoB) checklist to evaluate risk of bias of studies on measurement properties of PROMs. The checklist can be used to develop systematic reviews of PROMs measurement properties, and for PROMs developers, it can also be used to guide the research design in the measurement tool development process for reducing bias. At present, similar assessment tools are lacking in China. Therefore, this article aims to introduce the primary contents of COSMIN-RoB checklist and to interpret how to evaluate risk of bias of the internal structure studies of PROMs with examples.
Objective To develop a Matlab toolbox to improve the efficiency of musculoskeletal kinematics analysis while ensuring the consistency of musculoskeletal kinematics analysis process and results. Methods Adopted the design concept of “Batch processing tedious operation”, based on the Matlab connection OpenSim interface function ensures the consistency of musculoskeletal kinematics analysis process and results, the functional programming was applied to package the five steps for scale, inverse kinematics analysis, residual reduction algorithm, static optimization analysis, and joint reaction analysis of musculoskeletal kinematics analysis as functional functions, and command programming was applied to analyze musculoskeletal movements in large numbers of patients. A toolbox called LLMKA (Lower Limbs Musculoskeletal Kinematics Analysis) was developed. Taking 120 patients with medial knee osteoarthritis as the research object, a clinical researcher was selected using the LLMKA toolbox and OpenSim to test whether the analysis process and results were consistent between the two methods. The researcher used the LLMKA toolbox again to conduct musculoskeletal kinematics analysis in 120 patients to verify whether the use of this toolbox could improve the efficiency of musculoskeletal kinematics analysis compared with using OpenSim. Results Using the LLMKA toolbox could analyze musculoskeletal kinematics analysis in a large number of patients, and the analysis process and results were consistent with the use of OpenSim. Compared to using OpenSim, musculoskeletal kinematics analysis was completed in 120 patients using the LLMKA toolbox with only 2 operations were needed to enter the patient body mass data, operating steps decreased by 99.19%, total analysis time by 66.84%, and manual participation time by 99.72%, just need 0.079 1 hour (4 minutes and 45 seconds). Conclusion The LLMKA toolbox can complete a large number of musculoskeletal kinematics analysis in patients with one click in a way that is consistent in process and results with using OpenSim, reducing the total time of musculoskeletal kinematics analysis, and liberating clinical researchers from cumbersome steps, making more energy into the clinical significance of musculoskeletal kinematics analysis results.
Objective To validate the effectiveness of a novel comprehensive classification for intertrochanteric fracture (ITF). MethodsThe study included 616 patients with ITF, including 279 males (45.29%) and 337 females (54.71%); the age ranged from 23 to 100 years, with an average of 72.5 years. Two orthopaedic residents (observers Ⅰ and Ⅱ) and two senior orthopaedic surgeons (observers Ⅲ and Ⅳ) were selected to classify the CT imaging data of 616 patients in a random order by using the AO/Orthopaedic Trauma Association (AO/OTA) classification of 1996/2007 edition, the AO/OTA classification of 2018 edition, and the novel comprehensive classification method at an interval of 1 month. Kappa consistency test was used to evaluate the intra-observer and inter-observer consistency of the three ITF classification systems. ResultsThe inter-observer consistency of the three classification systems evaluated by 4 observers twice showed that the 3 classification systems had strong inter-observer consistency. Among them, the κ value of the novel comprehensive classification was higher than that of the AO/OTA classification of 1996/2007 edition and 2018 edition, and the experience of observers had a certain impact on the classification results, and the inter-observer consistency of orthopaedic residents was slightly better than that of senior orthopaedic surgeons. The intra-observer consistency of two evaluations of three classification systems by 4 observers showed that the consistency of the novel comprehensive classification was better for the other 3 observers, except that the consistency of observer Ⅳ in the AO/OTA classification of 2018 version was slightly higher than that of the novel comprehensive classification. The results showed that the novel comprehensive classification has higher repeatability, and the intra-observer consistency of senior orthopaedic surgeons was better than that of orthopaedic residents. ConclusionThe novel comprehensive classification system has good intra- and inter-observer consistency, and has high validity in the classification of CT images of ITF patients; the experience of observers has a certain impact on the results of the three classification systems, and those with more experiences have higher intra-observer consistency.