SAS Enterprise Guide 6.1: baseline characteristics presentation

2021 ◽  
Vol 21 (1) ◽  
pp. 59-64
Author(s):  
Nikolay S. Bunenkov ◽  
Vladimir V. Komok ◽  
Nikita V. Grudinin ◽  
Vasiliy A. Bobylkov ◽  
Gulnara F. Bunenkova ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Randomized Clinical Trial ◽  
Clinical Laboratory ◽  
Foreign Journal ◽  
Nominal Data ◽  
Saint Petersburg ◽  
Develop Algorithm ◽  
Chi Squared ◽  
Baseline Characteristics ◽  
Medical University

Objective: to develop algorithm of presentation of baseline characteristics of patients which enrolled in prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489). 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. Patients were allocated into three groups of treatment. There is database with clinical, laboratory and instrumental data. Comparison for nominal data (gender and incidence of myocardial infarction and stroke) were calculated with SAS Enterprise Guide 6.1 software with Chi-squared test and exact Fisher test. Baseline characteristics were presented in table. Results. There was developed algorithm of baseline characteristics presentation in APA-table. Conclusion. There was developed algorithm of baseline characteristics presentation SAS Enterprise Guide 6.1 could be useful for manuscript preparing for Russian and foreign journal.

Sas enterprise guide 6.1: independent groups comparison for nominal data

2020 ◽  
Vol 20 (3) ◽  
pp. 89-98
Author(s):  
N. S. Bunenkov ◽  
G. F. Bunenkova ◽  
V. V. Komok ◽  
O. A. Grinenko ◽  
A S. Nemkov
Keyword(s):  
Myocardial Infarction ◽  
Clinical Trial ◽  
Data Analysis ◽  
Randomized Clinical Trial ◽  
Postoperative Bleeding ◽  
Nominal Data ◽  
Saint Petersburg ◽  
Develop Algorithm ◽  
Chi Squared ◽  
Medical University

Objective:to develop algorithm of independent groups comparison for nominal data of prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489) using SAS Enterprise Guide 6.1. 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 2016-2019years with 336 patients. Patients were allocated into three groups of treatment. There is database which include following information: gender, myocardial infarction, stroke and postoperative bleeding. Comparison for nominal data (gender and incidence of myocardial infarction, stroke and bleeding) were calculated with SAS Enterprise Guide6.1 software with Chi-squared test and exact Fisher test. Results.There was developed algorithm of two independent groups comparison for nominal data. Conclusion.Presented algorithm of data analysis allows to compare independent groups for nominal data.

scholarly journals SAS Enterprise Guide 6.1 for physicians: correlation analysis

2020 ◽  
Vol 20 (1) ◽  
pp. 51-56
Author(s):  
Nikolay S. Bunenkov ◽  
Gulnara F. Bunenkova ◽  
Vladimir V. Komok ◽  
Oleg A. Grinenko ◽  
Alexander S. Nemkov
Keyword(s):  
Clinical Trial ◽  
Data Analysis ◽  
Correlation Analysis ◽  
Randomized Clinical Trial ◽  
Clinical Laboratory ◽  
Analysis Data ◽  
Saint Petersburg ◽  
Develop Algorithm ◽  
Efficient Data ◽  
Medical University

Objective: to develop algorithm of correlation analysis of prospective non-randomized clinical trial AMIRICABG (ClinicalTrials.gov Identifier: NCT03050489) data using SAS Enterprise Guide 6.1. Materials and methods. Data collection was performed according prospective non-randomized clinical trial AMIRICABG (ClinicalTrials.gov Identifier: NCT03050489) in Pavlov First Saint Petersburg State Medical University, Saint Petersburg, Russia between 20162019 years with 336 patients. There is database with clinical, laboratory and instrumental data. Correlation analysis was performed with SAS Enterprise Guide 6.1. Results. There was developed algorithm of correlation analysis data of prospective non-randomized clinical trial AMIRICABG (ClinicalTrials.gov Identifier: NCT03050489). This algorithm could be useful for physicians and researchers for data analysis. Conclusion. Presented algorithm of correlation analysis could make easier and improve efficient data analysis with SAS Enterprise Guide 6.1.

scholarly journals SAS Enterprise Guide 6.1 for physicians: getting started

2019 ◽  
Vol 19 (3) ◽  
pp. 27-36 ◽  
Author(s):  
Nikolay S. Bunenkov ◽  
Gulnara F. Bunenkova ◽  
Sergey A. Beliy ◽  
Vladimir V. Komok ◽  
Oleg A. Grinenko ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Data Analysis ◽  
Randomized Clinical Trial ◽  
Clinical Laboratory ◽  
Instrumental Data ◽  
Saint Petersburg ◽  
Develop Algorithm ◽  
Efficient Data ◽  
Medical University ◽  
Efficient Data Analysis

Objective. To develop algorithm of data analysis of prospective non-randomized clinical trial AMIRICABG (ClinicalTrials.gov Identifier: NCT03050489) using SAS Enterprise Guide 6.1. Materials and methods. Data collection was performed according prospective non-randomized clinical trial AMIRICABG in Pavlov First Saint Petersburg State Medical University, Saint Petersburg, Russia between 20162019 years with 336 patients. There is database with clinical, laboratory and instrumental data. Statistical analysis was performed with SAS Enterprise Guide 6.1. Results. There was developed algorithm of data analysis of prospective non-randomized clinical trial AMIRICABG. This algorithm could be useful for physicians and researchers for data analysis. Conclusion. Presented algorithm of data analysis could make easier and improve efficient data analysis. SAS Enterprise Guide 6.1 allows fast and accurate process big data.

scholarly journals SAS ENTERPRISE GUIDE 6.1 FOR PHYSICIANS: MULTIPLE COMPARISONS.

2020 ◽  
Author(s):  
Nikolai S. Bunenkov ◽  
Gulnara F. Bunenkova ◽  
Vladimir V. Komok ◽  
Oleg A. Grinenko ◽  
Alexander S. Nemkov
Keyword(s):  
Clinical Trial ◽  
Data Analysis ◽  
Randomized Clinical Trial ◽  
Clinical Laboratory ◽  
Multiple Comparisons ◽  
Wilcoxon Test ◽  
Process Data ◽  
Bonferroni Adjustment ◽  
Efficient Data ◽  
Medical University

Objective: to develop algorithm of multiple comparisons data of prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489) using SAS Enterprise Guide 6.1. Materials and methods. Data collection was performed according prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489) in 1Pavlov First St. Petersburg State Medical University, Saint-Petersburg, Russia between 2016-2019 years with 336 patients. There is database with clinical, laboratory and instrumental data. Multiple comparisons test was performed with SAS Enterprise Guide 6.1. Results. There was developed algorithm of multiple comparisons data of prospective non-randomized clinical trial AMIRI CABG (ClinicalTrials.gov Identifier: NCT03050489). This algorithm could be useful for physicians and researchers for data analysis. Conclusion. Presented algorithm of data analysis could make easier and improve efficient data analysis. SAS Enterprise Guide 6.1 allows fast and accurate process data Key words: SAS Enterprise Guide 6.1, statistical analysis, clinical trials, multiple comparisons, Bonferroni adjustment, Kruskal-Wallis test, Wilcoxon test, Tukey test.

scholarly journals Chinese Medicine Formula Huashibaidu Granule Early Treatment for Mild COVID-19 Patients: An Unblinded, Cluster-Randomized Clinical Trial

2021 ◽  
Vol 8 ◽  
Author(s):  
Chen Zhao ◽  
Li Li ◽  
Wei Yang ◽  
Wenliang Lv ◽  
Jian Wang ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Chinese Medicine ◽  
Randomized Clinical Trial ◽  
Early Treatment ◽  
Control Group ◽  
Clinical Endpoint ◽  
Clinical Trial Registration ◽  
Significant Difference ◽  
Baseline Characteristics ◽  
Cluster Randomized

Background: Previous research suggested that Chinese Medicine (CM) Formula Huashibaidu granule might shorten the disease course in coronavirus disease 2019 (COVID-19) patients. This research aimed to investigate the early treatment effect of Huashibaidu granule in well-managed patients with mild COVID-19.Methods: An unblinded cluster-randomized clinical trial was conducted at the Dongxihu FangCang hospital. Two cabins were randomly allocated to a CM or control group, with 204 mild COVID-19 participants in each cabin. All participants received conventional treatment over a 7 day period, while the ones in CM group were additionally given Huashibaidu granule 10 g twice daily. Participants were followed up to their clinical endpoint. The primary outcome was worsening symptoms before the clinical endpoint. The secondary outcomes were cure and discharge before the clinical endpoint and alleviation of composite symptoms after the 7 days of treatment.Results: All 408 participants were followed up to their clinical endpoint and included in statistical analysis. Baseline characteristics were comparable between the two groups (P > 0.05). The number of worsening patients in the CM group was 5 (2.5%), and that in the control group was 16 (7.8%) with a significant difference between groups (P = 0.014). Eight foreseeable mild adverse events occurred without statistical difference between groups (P = 0.151).Conclusion: Seven days of early treatment with Huashibaidu granule reduced the likelihood of worsening symptoms in patients with mild COVID-19. Our study supports Huashibaidu granule as an active option for early treatment of mild COVID-19 in similar well-managed medical environments.Clinical Trial Registration:www.chictr.org.cn/showproj.aspx?proj=49408, identifier: ChiCTR2000029763.

Comparison of baseline characteristics and mortality experience of participants and nonparticipants in a randomized clinical trial

2002 ◽  
Vol 23 (6) ◽  
pp. 686-702 ◽  
Author(s):  
Howard D Sesso ◽  
J.Michael Gaziano ◽  
Martin VanDenburgh ◽  
Charles H Hennekens ◽  
Robert J Glynn ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Randomized Clinical Trial ◽  
Mortality Experience ◽  
Baseline Characteristics

scholarly journals A Randomized Clinical Trial of Palliative Care for People with Heart Failure: Baseline Characteristics (S750)

2014 ◽  
Vol 47 (2) ◽  
pp. 496
Author(s):  
David O'Riordan ◽  
Megan Rathfon ◽  
Kathleen Dracup ◽  
Michael Rabow ◽  
Steven Pantilat ◽  
...  
Keyword(s):  
Heart Failure ◽  
Clinical Trial ◽  
Palliative Care ◽  
Randomized Clinical Trial ◽  
Baseline Characteristics
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