PMID- 34250095
OWN - NLM
STAT- MEDLINE
DCOM- 20210716
LR  - 20210716
IS  - 2314-6141 (Electronic)
IS  - 2314-6133 (Print)
VI  - 2021
DP  - 2021
TI  - Studying the Effect of Taking Statins before Infection in the Severity Reduction 
      of COVID-19 with Machine Learning.
PG  - 9995073
LID - 10.1155/2021/9995073 [doi]
LID - 9995073
AB  - Statins can help COVID-19 patients' treatment because of their involvement in 
      angiotensin-converting enzyme-2. The main objective of this study is to evaluate 
      the impact of statins on COVID-19 severity for people who have been taking 
      statins before COVID-19 infection. The examined research patients include people 
      that had taken three types of statins consisting of Atorvastatin, Simvastatin, 
      and Rosuvastatin. The case study includes 561 patients admitted to the Razi 
      Hospital in Ghaemshahr, Iran, during February and March 2020. The illness 
      severity was encoded based on the respiratory rate, oxygen saturation, systolic 
      pressure, and diastolic pressure in five categories: mild, medium, severe, 
      critical, and death. Since 69.23% of participants were in mild severity 
      condition, the results showed the positive effect of Simvastatin on COVID-19 
      severity for people that take Simvastatin before being infected by the COVID-19 
      virus. Also, systolic pressure for this case study is 137.31, which is higher 
      than that of the total patients. Another result of this study is that Simvastatin 
      takers have an average of 95.77 mmHg O(2)Sat; however, the O(2)Sat is 92.42, 
      which is medium severity for evaluating the entire case study. In the rest of 
      this paper, we used machine learning approaches to diagnose COVID-19 patients' 
      severity based on clinical features. Results indicated that the decision tree 
      method could predict patients' illness severity with 87.9% accuracy. Other 
      methods, including the K-nearest neighbors (KNN) algorithm, support vector 
      machine (SVM), Naive Bayes classifier, and discriminant analysis, showed accuracy 
      levels of 80%, 68.8%, 61.1%, and 85.1%, respectively.
CI  - Copyright (c) 2021 Alireza Davoudi et al.
FAU - Davoudi, Alireza
AU  - Davoudi A
AD  - Department of Infectious Diseases, Mazandaran University of Medical Sciences, 
      P.O. Box: 48175-866, Sari, Iran.
AD  - Antimicrobial Resistance Research Center, Communicable Diseases Institute, 
      Mazandaran University of Medical Sciences, Sari, Iran.
FAU - Ahmadi, Mohsen
AU  - Ahmadi M
AUID- ORCID: 0000-0003-1550-110X
AD  - Department of Industrial Engineering, Urmia University of Technology (UUT), P.O. 
      Box: 57166-419, Urmia, Iran.
FAU - Sharifi, Abbas
AU  - Sharifi A
AUID- ORCID: 0000-0002-2915-2740
AD  - Department of Mechanical Engineering, Urmia University of Technology (UUT), P.O. 
      Box: 57166-419, Urmia, Iran.
FAU - Hassantabar, Roshina
AU  - Hassantabar R
AD  - Department of Infectious Diseases, Mazandaran University of Medical Sciences, 
      P.O. Box: 48175-866, Sari, Iran.
AD  - Antimicrobial Resistance Research Center, Communicable Diseases Institute, 
      Mazandaran University of Medical Sciences, Sari, Iran.
FAU - Najafi, Narges
AU  - Najafi N
AD  - Department of Infectious Diseases, Mazandaran University of Medical Sciences, 
      P.O. Box: 48175-866, Sari, Iran.
AD  - Antimicrobial Resistance Research Center, Communicable Diseases Institute, 
      Mazandaran University of Medical Sciences, Sari, Iran.
FAU - Tayebi, Atefeh
AU  - Tayebi A
AD  - Department of Infectious Diseases, Mazandaran University of Medical Sciences, 
      P.O. Box: 48175-866, Sari, Iran.
AD  - Antimicrobial Resistance Research Center, Communicable Diseases Institute, 
      Mazandaran University of Medical Sciences, Sari, Iran.
FAU - Kasgari, Hamideh Abbaspour
AU  - Kasgari HA
AD  - Department of Clinical Pharmacy, Mazandaran University of Medical Science, P.O. 
      Box: 48175-866, Sari, Iran.
FAU - Ahmadi, Fatemeh
AU  - Ahmadi F
AD  - Department of Infectious Diseases, Mazandaran University of Medical Sciences, 
      P.O. Box: 48175-866, Sari, Iran.
AD  - Department of Mechanical Engineering, Urmia University of Technology (UUT), P.O. 
      Box: 57166-419, Urmia, Iran.
FAU - Rabiee, Marzieh
AU  - Rabiee M
AD  - Department of Infectious Diseases, Mazandaran University of Medical Sciences, 
      P.O. Box: 48175-866, Sari, Iran.
AD  - Antimicrobial Resistance Research Center, Communicable Diseases Institute, 
      Mazandaran University of Medical Sciences, Sari, Iran.
LA  - eng
PT  - Journal Article
DEP - 20210619
PL  - United States
TA  - Biomed Res Int
JT  - BioMed research international
JID - 101600173
RN  - 0 (Hydroxymethylglutaryl-CoA Reductase Inhibitors)
RN  - 83MVU38M7Q (Rosuvastatin Calcium)
RN  - A0JWA85V8F (Atorvastatin)
RN  - AGG2FN16EV (Simvastatin)
SB  - IM
MH  - Aged
MH  - Algorithms
MH  - Atorvastatin/administration & dosage/therapeutic use
MH  - *COVID-19/epidemiology/physiopathology
MH  - Drug Prescriptions/*statistics & numerical data
MH  - Female
MH  - Humans
MH  - *Hydroxymethylglutaryl-CoA Reductase Inhibitors/administration & 
      dosage/therapeutic use
MH  - Hypercholesterolemia/drug therapy
MH  - Iran
MH  - Machine Learning
MH  - Male
MH  - Middle Aged
MH  - Retrospective Studies
MH  - Rosuvastatin Calcium/administration & dosage/therapeutic use
MH  - Severity of Illness Index
MH  - Simvastatin/administration & dosage/therapeutic use
PMC - PMC8218917
COIS- The authors declare that they have received no financial support or have no 
      conflicts of interest in this research and its publication.
EDAT- 2021/07/13 06:00
MHDA- 2021/07/17 06:00
PMCR- 2021/06/19
CRDT- 2021/07/12 05:58
PHST- 2021/03/13 00:00 [received]
PHST- 2021/04/25 00:00 [revised]
PHST- 2021/05/27 00:00 [accepted]
PHST- 2021/07/12 05:58 [entrez]
PHST- 2021/07/13 06:00 [pubmed]
PHST- 2021/07/17 06:00 [medline]
PHST- 2021/06/19 00:00 [pmc-release]
AID - 10.1155/2021/9995073 [doi]
PST - epublish
SO  - Biomed Res Int. 2021 Jun 19;2021:9995073. doi: 10.1155/2021/9995073. eCollection 
      2021.