SAS ENTERPRISE GUIDE 6.1: LINEAR REGRESSION.

Nikolay S. Bunenkov; Vladimir V. Komok; Vailiy A. Bobylkov; Nikita V. Grudinin; Gulnara F. Bunenkova; Oleg A. Grinenko; Alexander S. Nemkov

doi:10.17816/MAJ35252

Medical academic journal ›› 2020, Vol. 20 ›› Issue (4) : 69 -79. DOI: 10.17816/MAJ35252

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SAS ENTERPRISE GUIDE 6.1: LINEAR REGRESSION.

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Pavlov First Saint Petersburg State Medical University

1Pavlov First Saint Petersburg State Medical University, Saint Petersburg, Russia

Federal State Budgetary Institution “Academician V.I. Shumakov Federal Research Center of Transplantology and Artificial Organs”, Ministry of Health of the Russian Federation, Moscow

aspirant, Department of Faculty Surgery

PhD, cardiac surgeon, Department of Cardiac Surgery No. 2

resident

caridac surgeon, Department of Lung Transplantation

resident, Department of Hospital Therapy

Doctor of Medical Science, Vice-Rector

Doctor of Medical Science, Professor, cardiac surgeon, Department of Cardiac Surgery No. 2

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Abstract

Objective: to develop algorithm of prediction of troponin I elevation 3^d day postoperatively depending on troponin I level on 1^st after on-pump coronary artery bypass grafting using SAS Enterprise Guide 6.1 software.

Materials and methods

Data collection was performed according to prospective non-randomized clinical trial AMIRI — CABG in Pavlov First St. Petersburg State Medical University, Saint Petersburg, Russia between 2016-2019 years with 336 patients with indications to coronary artery bypass grafting.

Algorithm was developed for on-pump group (n=128). There is database which include following information: troponin I level 1^st and 3^в days postoperatively. There was determined distribution of variables and linear regression was used for predicting model construction and its precision was estimated as well.

Results. There was developed algorithm of prediction of myocardial damage after on-pump coronary artery bypass grafting with linear regression model using SAS Enterprise Guide 6.1 software.

Conclusion. Presented algorithm of linear regression allows to compare independent groups for nominal data.

Keywords

SAS Enterprise Guide / linear regression

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Nikolay S. Bunenkov, Vladimir V. Komok, Vailiy A. Bobylkov, Nikita V. Grudinin, Gulnara F. Bunenkova, Oleg A. Grinenko, Alexander S. Nemkov. SAS ENTERPRISE GUIDE 6.1: LINEAR REGRESSION.. Medical academic journal, 2020, 20(4): 69-79 DOI:10.17816/MAJ35252

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