METHODS: 192 patients with MTBI and ICH were treated between November 2019 to December 2020 at a single level II trauma center. The Glasgow Coma Scale (GCS) was used to classify MTBI, and initial head CT was performed according to the Canadian CT head rule. Patients with a higher risk of ICH progression, including the elderly (≥65 years old), patients on antiplatelets or anticoagulants, or patients with an initial head CT that revealed EDH, contusional bleeding, or SDH > 5 mm, and multiple ICH underwent a repeat head CT within 12 to 24 h later. Data regarding types of intervention, length of stay in the hospital, and outcome were collected. The risk of further neurological deterioration and readmission rates were compared between these two groups. All patients were followed up in the clinic after one month or contacted via phone if they did not return.
RESULTS: 189 patients underwent scheduled repeated head CT, 18% had radiological intracranial bleed progression, and 82% had no changes. There were no statistically significant differences in terms of intervention rate, risk of neurological deterioration in the future, or readmission between them.
CONCLUSION: Repeat head CT in mild TBI patients with no neurological deterioration is not recommended, even in patients with a higher risk of ICH progression.
DESIGN: Part 1 involved electroacoustic measurement and biological calibration of a laptop-earphone pair used for the computer-based audiometry (CBA). Part 2 compared CBA thresholds obtained without a sound booth with those measured using the gold-standard clinical audiometry.
STUDY SAMPLE: 17 young normal-hearing volunteers (Part 1) and 43 normal and hearing loss subjects (Part 2) recruited from an audiology clinic via convenience sampling.
RESULTS: The transducer-device combination produced outputs suitable for measuring thresholds down to 0 dB HL. Threshold pairs obtained from the CBA and clinical audiometry were highly correlated (Spearman's correlation coefficient, ρ = 0.92, p 25 dB HL.
CONCLUSIONS: The use of a computer-based audiometer application with consumer insert phone-earmuff combination can offer a cost-effective solution for boothless screening audiometry.
MATERIALS AND METHODS: An auricular prosthesis, a complete denture, and anterior and posterior crowns were constructed using conventional methods and laser scanned to create computerized 3D meshes. The meshes were optimized independently by four computer-aided design software (Meshmixer, Meshlab, Blender, and SculptGL) to 100%, 90%, 75%, 50%, and 25% levels of original file size. Upon optimization, the following parameters were virtually evaluated and compared; mesh vertices, file size, mesh surface area (SA), mesh volume (V), interpoint discrepancies (geometric similarity based on virtual point overlapping), and spatial similarity (volumetric similarity based on shape overlapping). The influence of software and optimization on surface area and volume of each prosthesis was evaluated independently using multiple linear regression.
RESULTS: There were clear observable differences in vertices, file size, surface area, and volume. The choice of software significantly influenced the overall virtual parameters of auricular prosthesis [SA: F(4,15) = 12.93, R2 = 0.67, p < 0.001. V: F(4,15) = 9.33, R2 = 0.64, p < 0.001] and complete denture [SA: F(4,15) = 10.81, R2 = 0.67, p < 0.001. V: F(4,15) = 3.50, R2 = 0.34, p = 0.030] across optimization levels. Interpoint discrepancies were however limited to <0.1mm and volumetric similarity was >97%.
CONCLUSION: Open-source mesh optimization of smaller dental prostheses in this study produced minimal loss of geometric and volumetric details. SculptGL models were most influenced by the amount of optimization performed.
Materials and Methods: This is a single-center quasi-experimental study involving 100 patients seen in the outpatient department with knee osteoarthritis. They were randomly (computer generated) allocated into two arms (high frequency [H-F] or low frequency [L-F]). H-F is set at 100 Hz and L-F is set at 4 Hz. A baseline assessment is taken with the visual analog score (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Oxford Knee Score, and Lequesne index. They were instructed to self-administer the TENS therapy as per protocol and followed up at the 4th and 12th week to be reevaluated on the above scores.
Results: The final results show that both H-F and L-F groups showed improvement in all parameters of the VAS, WOMAC index, Oxford Knee Score, and Lequesne index (73%). Only the pain component of Lequesne index, activities of daily living component of Lequesne index, total Lequesne index, and pain component of WOMAC index shows a statistically significant difference, favoring the H-F group. The H-F group yields a faster result; however, with time the overall effect remains the same in both groups.
Conclusion: Both H-F and L-F groups show improvement in all the component of Lequesne index, Oxford Knee Score, WOMAC index, and VAS with no statistical difference between the two groups. Although H-F yields a faster result, not everyone is able to tolerate the intensity. Therefore, the selection of H-F or L-F should be done on case basis depending on the severity of symptoms, patient's expectation, and patient's ability to withstand the treatment therapy. Based on this 12th week follow-up, both groups will continue to improve with time. A longer study should be conducted to see it this improvement will eventually plateau off or continue to improve until the patient is symptom free.
Methods: The accuracy of Webgazer.js for software-based gaze tracking is tested under different lighting conditions. Predefined time delays of a prototype diagnosis task automation script are contrasted against with manual delays based on human time estimation to understand how automation influences diagnosis accuracy. SLI diagnosis binary classifier was built and tested based on randomised parameters. The obtained results were cross-compared to Singlims_ES.exe for equality.
Results: Webgazer.js achieved an average accuracy of 88.755% under global lighting conditions, 61.379% under low lighting conditions and 52.7% under face-focused lighting conditions. The diagnosis task automation script found to execute with actual time delays with a deviation percentage no more than 0.04%, while manually executing time delays based on human time estimation resulted in a deviation percentage of not more than 3.37%. One-tailed test probability value produced by both the newly built classifier and Singlims_ES were observed to be similar up to three decimal places.
Conclusion: The results obtained should serve as a foundation for further evaluation of computer tools to help speech language pathologists diagnose SLI.
Material and method: Computer-assisted total knee arthroplasty (TKA) or primary osteoarthritis of the knee was performed in 51 knees in 36 patients with a mean age of 69.51 years. All procedures were performed by a single surgeon using the same implant design. The intraclass correlation coefficient (ICC) was used to compare the intra-operative CAN-FRA with the post-operative CT-FRA. The angle between the anatomical epicondylar axis and the posterior condylar axis of the implant (CT-FRA) was measured at two separate timepoints by three observers who were blinded to the intra-operative CAN-FRA. Internal rotation was defined as rotation in the negative direction, while external rotation was defined as positive.
Results: The mean intra-operative CAN-FRA was 0.1° ± 2.8° (range -5.0° to 5.5°). The mean post-operative CT-FRA was -1.3° ± 2.1° (range -4.6° to 4.4°). The mean difference between the CAN-FRA and the CT-FRA was -1.3° ± 2.2° (range -7.9° to 2.4°). The respective ICC values for the three observers were 0.92, 0.94, and 0.93, while the respective intra-observer coefficients were 0.91, 0.85, and 0.90. The ICC for the intra-operative CAN-FRA versus the post-operative CT-FRA was 0.71.
Conclusion: This study shows that using a computer-assisted navigation system in TKA achieves reliable results and helps to achieve optimal positioning of the femoral component and rotation alignment correction.
OBJECTIVE: This paper aimed to describe the development process of the COVID-19 Symptom Monitoring System (CoSMoS), which consists of a self-monitoring, algorithm-based Telegram bot and a teleconsultation system. We describe all the essential steps from the clinical perspective and our technical approach in designing, developing, and integrating the system into clinical practice during the COVID-19 pandemic as well as lessons learned from this development process.
METHODS: CoSMoS was developed in three phases: (1) requirement formation to identify clinical problems and to draft the clinical algorithm, (2) development testing iteration using the agile software development method, and (3) integration into clinical practice to design an effective clinical workflow using repeated simulations and role-playing.
RESULTS: We completed the development of CoSMoS in 19 days. In Phase 1 (ie, requirement formation), we identified three main functions: a daily automated reminder system for patients to self-check their symptoms, a safe patient risk assessment to guide patients in clinical decision making, and an active telemonitoring system with real-time phone consultations. The system architecture of CoSMoS involved five components: Telegram instant messaging, a clinician dashboard, system administration (ie, back end), a database, and development and operations infrastructure. The integration of CoSMoS into clinical practice involved the consideration of COVID-19 infectivity and patient safety.
CONCLUSIONS: This study demonstrated that developing a COVID-19 symptom monitoring system within a short time during a pandemic is feasible using the agile development method. Time factors and communication between the technical and clinical teams were the main challenges in the development process. The development process and lessons learned from this study can guide the future development of digital monitoring systems during the next pandemic, especially in developing countries.