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Emergency teleradiological activity is an epidemiological estimator and predictor of the covid-19 pandemic in mainland France.
Crombé, Amandine; Lecomte, Jean-Christophe; Banaste, Nathan; Tazarourte, Karim; Seux, Mylène; Nivet, Hubert; Thomson, Vivien; Gorincour, Guillaume.
  • Crombé A; Imadis Teleradiology, Lyon, Bordeaux, Marseille, France.
  • Lecomte JC; University of Bordeaux, Bordeaux, France.
  • Banaste N; Imadis Teleradiology, Lyon, Bordeaux, Marseille, France.
  • Tazarourte K; Centre Hospitalier de Saintonge, Saintes, France.
  • Seux M; Centre Aquitain D'Imagerie, Bordeaux, France.
  • Nivet H; Imadis Teleradiology, Lyon, Bordeaux, Marseille, France.
  • Thomson V; Department of Radiology, Hôpital Nord-Ouest, Villefranche-sur-Saône, France.
  • Gorincour G; Emergency Department, CHU Edouard Herriot, Hospices Civils de Lyon, Lyon, France.
Insights Imaging ; 12(1): 103, 2021 Jul 22.
Article in English | MEDLINE | ID: covidwho-1320536
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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Insights Imaging Year: 2021 Document Type: Article Affiliation country: S13244-021-01040-3

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Insights Imaging Year: 2021 Document Type: Article Affiliation country: S13244-021-01040-3