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Predictive usefulness of PCR testing in different patterns of Covid-19 symptomatology - Analysis of a French cohort of 12,810 outpatients
Preprint
in En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20124438
ABSTRACT
Polymerase Chain reaction (PCR) is a key tool to diagnose Covid-19. Yet access to PCR is often limited. In this paper, we develop a clinical strategy for prescribing PCR to patients based on data from COVIDOM, a French cohort of 54,000 patients with clinically suspected Covid-19 including 12,810 patients tested by PCR. Using a machine learning algorithm (a decision tree), we show that symptoms alone are sufficient to predict PCR outcome with a mean average precision of 86%. We identify combinations of symptoms that are predictive of PCR positivity (90% for anosmia/ageusia) or negativity (only 30% of PCR+ for a subgroup with cardiopulmonary symptoms) in both cases, PCR provides little added diagnostic value. We deduce a prescribing strategy based on clinical presentation that can improve the global efficiency of PCR testing.
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Full text:
1
Collection:
09-preprints
Database:
PREPRINT-MEDRXIV
Type of study:
Cohort_studies
/
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
Language:
En
Year:
2020
Document type:
Preprint