BACKGROUND AND OBJECTIVES

Telerehabilitation is the remote delivery of rehabilitation services using telecommunication technologies. Its local adoption was catalyzed by the COVID-19 pandemic, prompting the need to assess user acceptance. This study aimed to determine the acceptance of stroke telerehabilitation among patients, carers, and rehabilitation providers in the Department of Physical Medicine and Rehabilitation at St. Luke’s Medical Center – Global City and Quezon City.

METHODS

This descriptive cross-sectional study used purposive sampling to recruit 73 rehabilitation providers and 10 consumers. Data were collected using a self-administered survey based on the Technology Acceptance Model, covering perceived ease of use, usefulness, and behavioral intent. Descriptive and inferential statistics were used for analysis.

RESULTS

Most providers (94.4%) were familiar with telerehabilitation, while only half of the consumers were aware of it. Acceptance was moderate among providers (mean score: 35.75 ± 8.67) and high among consumers (mean score: 31.6 ± 7.52). Female providers were less likely to accept telerehabilitation (p=0.049). Consumers identified financial constraints and lack of a companion as key barriers, while providers cited internet issues and technology use. Both groups viewed telerehabilitation positively for teleconsultation, teletherapy, and telemonitoring. Smartphones were the preferred device; Viber and Facebook Messenger were the most commonly chosen platforms.

CONCLUSION

Stroke telerehabilitation was moderately to highly accepted by rehabilitation stakeholders in two tertiary private hospitals in Manila. Findings may guide institutional planning for telerehabilitation services. Training, infrastructure support, and awareness campaigns can help address implementation barriers.

Human ; Male ; Female ; Adult: 25-44 Yrs Old ; Middle Aged: 45-64 Yrs Old ; Remote Consultation ; Physical And Rehabilitation Medicine ; Tertiary Care Centers ; Telecommunications ; Telerehabilitation ; Cross-sectional Studies ; Technology ; Stroke ; Covid-19

Abstract Background: This study aims to determine the effectiveness of programmed exercise with telerehabilitation at home in patients with obesity and knee osteoarthritis on visual analogue scale scores, body mass index, and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Methods: This research is a pre–post study in patients with obesity and knee osteoarthritis. Research subjects performed a series of exercise programs at home for 28 days. Before the program, there was an initial assessment from a psychologist and a nutritionist. During the program, there was tele-education, telemonitoring, and teleconsultation from doctors. Twenty-six female subjects participated. Results: Visual analogue scale scores decreased statistically significantly every week, until the end of the fourth week, compared with before the intervention (p<0.001). Body mass index and WOMAC scores decreased statistically significantly at the end of the fourth week compared with before the intervention (both p<0.001). Further analysis of all WOMAC components in the intervention group, including pain, stiffness, and physical function, also showed a statistically significant decrease (p<0.001). Conclusion: Programmed exercise as part of telerehabilitation at home has been statistically proven to reduce visual analogue scale scores, body mass index, and WOMAC in patients with obesity and knee osteoarthritis.
Telerehabilitation ; Knee Osteoarthritis ; Obesity ; Body Mass Index ; Visual Analogue Scale ; WOMAC

Background: Telepathology refers to the practice of pathologists from different locations who communicate to arrive at a diagnosis. As of 2016, the estimated pathologist-to-patient ratio is only 1:167,000. The limited number of pathologists available and the bulk of biopsy specimens to be diagnosed is entirely disproportionate thus emphasizing the need for telepathology. However, comprehensive imaging software, high-end communication systems, fast and stable internet connection are all expensive. Thus, it is only practical to utilize free voice and video calling applications like Google Meet®. Objective: The objective of this study was to determine the efficiency of a mobile video sharing application (Google Meet®) in real-time field image transmission for telepathology specifically identifying how many concordant and discordant diagnoses were done and to determine the acceptance rate of the pathologists in terms of quality of images, quality of voice communication, confidence in diagnosis, and Turn-Around Time (TAT). Methodology: A total of 171 benign and malignant cases with released outright histopathology results from January 2023-December 2023 were chosen as samples. Results: The highest concordant diagnoses (100%) were made with malignant gastro-intestinal tract excision, benign and malignant female genital tract, benign and malignant male genital tract, malignant lymphoid neoplasm, polyp, pap smear, and ditzels. The lower concordant diagnoses (80%) were from benign breast excision, malignant head and neck excision, and benign lymphoid neoplasm. The shortest Turn-Around Time (TAT) was observed among ditzels with an average of 2 minutes per slide. Longer Turn-Around Time (TAT) was observed among more difficult cases such as malignant cases of the head and neck, soft tissue, and fine-needle aspiration biopsy or smears. More than 90% of the diagnoses made by the pathologists are concordant with the official result. Conclusion The overall acceptance rate of application of dynamic telepathology is high with a good to average rating in terms of image and audio quality.
Pathologists ; Telepathology ; Communication

Pulpitis is a common infective oral disease in clinical situations. The regulatory mechanisms of immune defense in pulpitis are still being investigated. Osteomodulin (OMD) is a small leucine-rich proteoglycan family member distributed in bones and teeth. It is a bioactive protein that promotes osteogenesis and suppresses the apoptosis of human dental pulp stem cells (hDPSCs). In this study, the role of OMD in pulpitis and the OMD-induced regulatory mechanism were investigated. The OMD expression in normal and inflamed human pulp tissues was detected via immunofluorescence staining. Intriguingly, the OMD expression decreased in the inflammatory infiltration area of pulpitis specimens. The cellular experiments demonstrated that recombined human OMD could resist the detrimental effects of lipopolysaccharide (LPS)-induced inflammation. A conditional Omd knockout mouse model with pulpal inflammation was established. LPS-induced inflammatory impairment significantly increased in conditional Omd knockout mice, whereas OMD administration exhibited a protective effect against pulpitis. Mechanistically, the transcriptome alterations of OMD overexpression showed significant enrichment in the nuclear factor-κB (NF-κB) signaling pathway. Interleukin-1 receptor 1 (IL1R1), a vital membrane receptor activating the NF-κB pathway, was significantly downregulated in OMD-overexpressing hDPSCs. Additionally, the interaction between OMD and IL1R1 was verified using co-immunoprecipitation and molecular docking. In vivo, excessive pulpal inflammation in Omd-deficient mice was rescued using an IL1R antagonist. Overall, OMD played a protective role in the inflammatory response via the IL1R1/NF-κB signaling pathway. OMD may optimize the immunomodulatory functions of hDPSCs and can be used for regenerative endodontics.
Pulpitis/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction ; Humans ; Mice ; Mice, Knockout ; Dental Pulp/metabolism* ; Disease Models, Animal ; Lipopolysaccharides

Tooth pulpitis is a prevalent oral disorder. Understanding the underlying mechanisms of pulpitis and developing effective treatment strategies hold great significance. Ferroptosis has recently emerged as a new form of cell death, but the role of ferroptosis in pulpitis remains largely unknown. In our study, single-cell RNA sequencing (scRNA-seq) was used to identify cellular heterogeneity between 3 pulpitis tissue and 3 healthy pulp tissue, and explored ferroptosis occurrence in pulpitis tissue and inflamed dental pulp cells (DPCs). In scRNA-seq, 40 231 cells (Pulpitis: 17 814; Healthy pulp: 22 417) were captured, and visualized into 12 distinct cell clusters. Differentially expressed ferroptosis-related genes (DE-FRGs) were almost presented in each cluster in pulpitis vs healthy pulp. ROS and Fe²⁺ levels significantly rose, and immunohistochemistry showed low expression of GPX4 and high expression of PTGS2 in pulpitis. In LPS-stimulated DPCs, thymosin α1 increased the expression of GPX4 and FTL, and decreased expression of TNF-α, IL-1β, IL-6, and Fe²⁺ levels. In rat pulpitis models, both prothymosin α (PTMA, precursor of thymosin α1) gelatin sponge placed at the hole of pulp (LPS-P(gs)) and PTMA injection in pulp (LPS-P(i)) significantly reduced infiltration of inflammatory cells and expression of PTGS2, and increased the expression of GPX4. In RNA sequencing, the expression of DE-FRGs were reversed when thymosin α1 were added in LPS-stimulated DPCs. Collectively, single-cell atlas reveals cellular heterogeneity between pulpitis and healthy pulp, and ferroptosis occurrence in pulpitis. Thymosin α1 may reduce ferroptosis in DPCs to alleviate pulpitis and thus potentially has the ability to treat pulpitis.
Ferroptosis/drug effects* ; Dental Pulp/drug effects* ; Animals ; Pulpitis/pathology* ; Rats ; Thymalfasin/pharmacology* ; Humans ; Male ; Thymosin/pharmacology* ; Disease Models, Animal ; Rats, Sprague-Dawley

OBJECTIVES: This study aimed to investigate the influence of the dimensional stability of 3D printed resin master model on the replication accuracy of implant replicas. METHODS: Ten digital impressions of patients undergoing continuous crowns or fixed bridge restoration supported by two implants were obtained, and resin models with implant replicas were 3D printed. Scanning rods were fixed on the replicas 3, 7, and 14 days after printing. The 3D, linear, and angular deviations of the scanning rods at different times were analyzed through Geomagic Wrap 2021 software. RESULTS: The position of the replicas shifted mesiolingually, in the same direction as the shrinkage of the model. From day 7 onward, the 3D, distance linear, and angular deviations of the replicas (scanning rod) significantly increased compared with those on the 3rd day (P<0.05). On the 14th day, the changes were even more pronounced, with the above deviations showing statistical significance (P<0.05) compared with those for the 3-day and 7-day groups. No statistical difference in height linear deviation was observed among the groups. CONCLUSIONS The insufficient dimensional stability of 3D printed resin models can lead to changes in the relative position and angle of the replicas, thereby affecting the accuracy of the replicas in recreating the implant's position. Complete manufacturing of prosthesis is recommended within 7 days after the model is printed.
Printing, Three-Dimensional ; Humans ; Dental Implants ; Models, Dental ; Dental Impression Technique ; Crowns

OBJECTIVES: To evaluate the accuracy of a self-developed extraoral scanning system based on four-camera stereophotogrammetric technology in the acquisition of three-dimensional positional information on dental implants and conduct a comparative study involving an intraoral scanning system. METHODS: With the use of an in vitro edentulous jaw model with implants, extraoral (experimental group) and intraoral (control group) scanning systems were employed to obtain STL (Standard Tessellation Language) datasets containing three-dimensional morphological and positional information on scan bodies. In addition, a dental model scanner was used to obtain reference data. The three-dimensional morphological, linear, and angular deviations between groups and reference data were analyzed using Geomagic Wrap 2021 software to compare trueness and precision. RESULTS: The extraoral scanning system demonstrated superior trueness in three-dimensional morphological, linear, and angular deviations compared with the intraoral scanning system, with statistically significant differences (P<0.001). The extraoral scanning system also showed a higher precision in three-dimensional morphological deviation (P<0.001). As the number of implants increased, the extraoral scanning system exhibited increased three-dimensional morphological and linear deviations (P<0.001) but maintained a stable angular deviation. The intraoral scanning system displayed significant increases in three-dimensional morphological, linear, and angular deviations with the increase in the number of implants (P<0.05). CONCLUSIONS The stereophotogrammetry-based extraoral scanning system outperforms intraoral scanning system in terms of the accuracy for multi-unit implant positioning and provides a novel approach for attaining a fully digital workflow for implant rehabilitation in edentulous jaws.
Jaw, Edentulous ; Humans ; Dental Impression Technique ; Dental Implants ; Imaging, Three-Dimensional/methods* ; Photogrammetry/methods* ; Models, Dental

OBJECTIVES: This study aimed to use machine learning algorithms to build a prediction model of the first permanent molar caries of 9-year-old children in Suzhou and screen out risk factors. METHODS: Random stratified whole group sampling was applied to randomly select 9-year-old students from 38 primary schools in 14 townships and streets in Wuzhong District for oral examination and questionnaire survey. Multifactor Logistics regression was used to analyze the risk factors of tooth decay. The data set was randomly divided into training sets and verification sets according to 8∶2, and R 4.3.1 was used to build five machine learning algorithms: random forest, decision tree, extreme gradient boosting (XGBoost), Logistics regression, and lightweight gradient enhancement (LightGBM). The predictive effect of these five models was evaluated using the area under the characteristic curve (AUC). The marginal contribution of quantitative characteristics to the caries prediction model was determined through Shapley additive explanations (SHAP). RESULTS: This study included 7 225 samples that met the standard. The caries rate of the first permanent molar was 54.96%. Multifactor Logistic regression analysis showed that sweet drinks, dessert and candy, snack frequency, and snacks before going to bed after brushing teeth were correlated with the occurrence of first permanent molar caries (P<0.05). The AUC values of decision tree, Logistic regression, LightGBM, random forest, and XGBoost were 75.5%, 83.9%, 88.6%, 88.9%, and 90.1%, respectively. Compared with the variables after single heat coding, the SHAP value of high-frequency sweets (such as dessert candy ≥2 times a day, mother's sugary diet ≥2 times a day) and bad oral hygiene habits (such as frequent snacks before going to bed after brushing teeth and irregular brushing teeth) exhibited the highest positive. CONCLUSIONS XGBoost algorithm has a good prediction effect for first permanent molar caries in 9-year-old children. High-frequency sweet factors and bad oral hygiene habits have a strong positive impact on the risk of first permanent molar caries and are key drivers that can be used in the formulation of targeted interventions.
Humans ; Dental Caries/epidemiology* ; Child ; Machine Learning ; China/epidemiology* ; Molar ; Risk Factors ; Female ; Logistic Models ; Male ; Decision Trees ; Algorithms

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*

Heart failure (HF) is the end-stage of all cardiac diseases, characterized by high prevalence, high mortality, and heavy social and economic burden. Early warning of HF exacerbation is of great value for outpatient management and reducing readmission rates. Currently, remote dynamic monitoring technology, which captures changes in hemodynamic and physiological parameters of HF patients, has become the primary method for early warning and is a hot research topic in clinical studies. This paper systematically reviews the progress in this field, which was categorized into invasive monitoring based on implanted devices, non-invasive monitoring based on wearable devices, and other monitoring technologies based on audio and video. Invasive monitoring primarily involves direct hemodynamic parameters such as left atrial pressure and pulmonary artery pressure, while non-invasive monitoring covers parameters such as thoracic impedance, electrocardiogram, respiration, and activity levels. These parameters exhibit characteristic changes in the early stages of HF exacerbation. Given the clinical heterogeneity of HF patients, multi-source information fusion analysis can significantly improve the prediction accuracy of early warning models. The results of this study suggest that, compared with invasive monitoring, non-invasive monitoring technology, with its advantages of good patient compliance, ease of operation, and cost-effectiveness, combined with AI-driven multimodal data analysis methods, shows significant clinical application potential in establishing an outpatient management system for HF.
Humans ; Heart Failure/physiopathology* ; Monitoring, Physiologic/methods* ; Wearable Electronic Devices ; Remote Sensing Technology ; Early Diagnosis ; Electrocardiography ; Hemodynamics