COVID-19 Clinical footprint to infer about mortality
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Preprint |
| Publié: |
2021
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866917693158850560 |
|---|---|
| author | Rodríguez, Carlos E. Mena, Ramsés H. |
| author_facet | Rodríguez, Carlos E. Mena, Ramsés H. |
| contents | Information of 1.6 million patients identified as SARS-CoV-2 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalizations and deaths due to the COVID-19 disease. Using the presence or absence of these latter variables a clinical footprint for each patient is created. The risk, expected mortality and the prediction of death outcomes, among other relevant quantities, are obtained and analyzed by means of a multivariate Bernoulli distribution. The proposal considers all possible footprint combinations resulting in a robust model suitable for Bayesian inference. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2104_07172 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | COVID-19 Clinical footprint to infer about mortality Rodríguez, Carlos E. Mena, Ramsés H. Applications Methodology Information of 1.6 million patients identified as SARS-CoV-2 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalizations and deaths due to the COVID-19 disease. Using the presence or absence of these latter variables a clinical footprint for each patient is created. The risk, expected mortality and the prediction of death outcomes, among other relevant quantities, are obtained and analyzed by means of a multivariate Bernoulli distribution. The proposal considers all possible footprint combinations resulting in a robust model suitable for Bayesian inference. |
| title | COVID-19 Clinical footprint to infer about mortality |
| topic | Applications Methodology |
| url | https://arxiv.org/abs/2104.07172 |