Initial Experience of the Synchronized, Real-Time, Interactive, Remote Transthoracic Echocardiogram Consultation System in Rural China: Longitudinal Observational Study
Bibliographic record
Abstract
BACKGROUND: China has a vast territory, and the quality of health care services provided, especially transthoracic echocardiography (TTE), in remote regions is still low. Patients usually need to travel long distances to tertiary care centers for confirmation of a diagnosis. Considering the rapid development of high-speed communication technology, telemedicine will be a significant technology for improving the diagnosis and treatment of patients at secondary care hospitals. OBJECTIVE: This study aimed to discuss the feasibility and perceived clinical value of a synchronized, real-time, interactive, remote TTE consultation system based on cloud computing technology. METHODS: By using the cloud computing platform coupled with unique dynamic image coding and decoding and synchronization technology, multidimensional communication information in the form of voice, texts, and pictures was integrated. A remote TTE consultation system connecting Henan Provincial People's Hospital and two county-level secondary care hospitals located 300 km away was developed, which was used for consultation with 45 patients. RESULTS: This remote TTE consultation system achieved remote consultation for 45 patients. The total time for consultation was 341.31 min, and the mean time for each patient was 7.58 (SD 6.17) min. Among the 45 patients, 3 were diagnosed with congenital heart diseases (7%) and 42 were diagnosed with acquired heart diseases (93%) at the secondary care hospitals. After expert consultation, the final diagnosis was congenital heart diseases in 5 patients (11%), acquired heart disease in 34 patients (76%), and absence of heart abnormalities in 6 patients (13%). Compared with the initial diagnosis at secondary care hospitals, remote consultation using this system revealed new abnormalities in 7 patients (16%), confirmation was obtained in 6 patients (13%), and abnormalities were excluded in 6 patients (13%). The expert opinions agreed with the initial diagnosis in the remaining 26 patients (58%). In addition, several questions about rare illnesses raised by the rural doctors at the secondary care hospitals were answered. CONCLUSIONS: The synchronized real-time interactive remote TTE consultation system based on cloud computing service and unique dynamic image coding and decoding technology had high feasibility and applicability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".