Article: Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France.
2021 Volume 12, Issue 1, Page(s) 103
Abstract: ... radiological markers of COVID-19-related emergency activity as global estimators of pandemic evolution ... Teleradiological and epidemiological time series were aligned. Their relationships were estimated through a cross ... Concomitantly, 227,677 hospitalisations were reported. Teleradiological and epidemiological time series were ...
| Abstract | Background: COVID-19 pandemic highlighted the need for real-time monitoring of diseases evolution to rapidly adapt restrictive measures. This prospective multicentric study aimed at investigating radiological markers of COVID-19-related emergency activity as global estimators of pandemic evolution in France. We incorporated two sources of data from March to November 2020: an open-source epidemiological dataset, collecting daily hospitalisations, intensive care unit admissions, hospital deaths and discharges, and a teleradiology dataset corresponding to the weekly number of CT-scans performed in 65 emergency centres and interpreted remotely. CT-scans specifically requested for COVID-19 suspicion were monitored. Teleradiological and epidemiological time series were aligned. Their relationships were estimated through a cross-correlation function, and their extremes and breakpoints were compared. Dynamic linear models were trained to forecast the weekly hospitalisations based on teleradiological activity predictors. Results: A total of 100,018 CT-scans were included over 36 weeks, and 19,133 (19%) performed within the COVID-19 workflow. Concomitantly, 227,677 hospitalisations were reported. Teleradiological and epidemiological time series were almost perfectly superimposed (cross-correlation coefficients at lag 0: 0.90-0.92). Maximal number of COVID-19 CT-scans was reached the week of 2020-03-23 (1 086 CT-scans), 1 week before the highest hospitalisations (23,542 patients). The best valid forecasting model combined the number of COVID-19 CT-scans and the number of hospitalisations during the prior two weeks and provided the lowest mean absolute percentage (5.09%, testing period: 2020-11-02 to 2020-11-29). Conclusion: Monitoring COVID-19 CT-scan activity in emergencies accurately and instantly predicts hospitalisations and helps adjust medical resources, paving the way for complementary public health indicators. |
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| Language | English |
| Publishing date | 2021-07-22 |
| Publishing country | Germany |
| Document type | Journal Article |
| ZDB-ID | 2543323-4 |
| ISSN | 1869-4101 |
| ISSN | 1869-4101 |
| DOI | 10.1186/s13244-021-01040-3 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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