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Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic.
Neuraz, Antoine; Lerner, Ivan; Digan, William; Paris, Nicolas; Tsopra, Rosy; Rogier, Alice; Baudoin, David; Cohen, Kevin Bretonnel; Burgun, Anita; Garcelon, Nicolas; Rance, Bastien.
  • Neuraz A; Department of Biomedical Informatics, Necker-Enfant Malades Hospital, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France.
  • Lerner I; Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
  • Digan W; LIMSI, CNRS, Université Paris Saclay, Orsay, France.
  • Paris N; Department of Biomedical Informatics, Necker-Enfant Malades Hospital, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France.
  • Tsopra R; Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
  • Rogier A; Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
  • Baudoin D; Department of Biomedical Informatics, Georges Pompidou European Hospital, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France.
  • Cohen KB; DSI WIND, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France.
  • Burgun A; Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
  • Garcelon N; Department of Biomedical Informatics, Georges Pompidou European Hospital, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France.
  • Rance B; Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
J Med Internet Res ; 22(8): e20773, 2020 Aug 14.
Article in English | MEDLINE | ID: covidwho-725194
ABSTRACT

BACKGROUND:

A novel disease poses special challenges for informatics solutions. Biomedical informatics relies for the most part on structured data, which require a preexisting data or knowledge model; however, novel diseases do not have preexisting knowledge models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to a novel knowledge model. However, although this idea has often been suggested, no opportunity has arisen to actually test it in real time. The current coronavirus disease (COVID-19) pandemic presents such an opportunity.

OBJECTIVE:

The aim of this study was to evaluate the added value of information from clinical text in response to emergent diseases using natural language processing (NLP).

METHODS:

We explored the effects of long-term treatment by calcium channel blockers on the outcomes of COVID-19 infection in patients with high blood pressure during in-patient hospital stays using two sources of information data available strictly from structured electronic health records (EHRs) and data available through structured EHRs and text mining.

RESULTS:

In this multicenter study involving 39 hospitals, text mining increased the statistical power sufficiently to change a negative result for an adjusted hazard ratio to a positive one. Compared to the baseline structured data, the number of patients available for inclusion in the study increased by 2.95 times, the amount of available information on medications increased by 7.2 times, and the amount of additional phenotypic information increased by 11.9 times.

CONCLUSIONS:

In our study, use of calcium channel blockers was associated with decreased in-hospital mortality in patients with COVID-19 infection. This finding was obtained by quickly adapting an NLP pipeline to the domain of the novel disease; the adapted pipeline still performed sufficiently to extract useful information. When that information was used to supplement existing structured data, the sample size could be increased sufficiently to see treatment effects that were not previously statistically detectable.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Natural Language Processing / Calcium Channel Blockers / Coronavirus Infections / Betacoronavirus / Hypertension Type of study: Case report / Experimental Studies / Prognostic study / Reviews Topics: Long Covid Limits: Humans Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 20773

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Natural Language Processing / Calcium Channel Blockers / Coronavirus Infections / Betacoronavirus / Hypertension Type of study: Case report / Experimental Studies / Prognostic study / Reviews Topics: Long Covid Limits: Humans Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: 20773