Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06614023
Status:
COMPLETED
Last Update Posted:
None
First Post:
2024-09-02
Brief Title:
Impact of Body Weight on Outcomes of Patients Undergoing Coronary Artery Bypass Grafting
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Impact of Body Mass Index on Mortality in Patients Undergoing Coronary Artery Bypass Grafting a Retrospective Cohort Study
Status:
COMPLETED
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
All consecutive patients who underwent isolated coronary artery bypass grafting CABG at our institution from 2014 to 2020 were included Patients were divided into 6 groups according to body mass index BMI underweight BMI lt200 kgm2 normal weight BMI 200-249 kgm2 overweight BMI 25-299 kgm2 obesity class I BMI 30-349 kgm2 obesity class II BMI 35-399 kgm2 and obesity class III BMI gt40 kgm2 The long-term mortality was analyzed as primary end-point The univariable and multivariable analysis was performed using logistic regression modeling
Detailed Description:
All consecutive patients aged above eighteen who underwent isolated CABG were enrolled Patients operated on- and off-pump were included We reviewed elective urgent emergency and salvage surgeries Patients with any additional concomitant surgical procedures were excluded
Patients were divided into 6 groups according to body mass index BMI underweight BMI lt200 kgm2 normal weight BMI 200-249 kgm2 overweight BMI 25-299 kgm2 obesity class I BMI 30-349 kgm2 obesity class II BMI 35-399 kgm2 and obesity class III BMI gt40 kgm2
The primary endpoint was long-term mortality The secondary end-point was the rate of sternal wound infections
Summary statistics were calculated Continuous data are described as the median with the interquartile range in parentheses while categorical data are shown as numbers with percentages Differences between groups for normally distributed continuous variables were determined using the one-way analysis of variance with Holm-Sidak post-hoc test The Kruskal Wallis test was used for the analysis of non-normally distributed continuous variables with Dunns test for post hoc comparison The chi-squared test was used for the analysis of categorical variables Bonferonis correction was used for post-hoc analysis The univariable analysis was performed using logistic regression For multivariable analysis a logistic regression model was performed with mortality or wound infection as the dependent variable and all other characteristics summarized in the table 1 as independent variables The backward conditional selection was used for modeling with variables with score statistics lt01 included in the model Significance was assessed at plt005 Multiple imputation was not used to adjust for missing data The number of valid entries for each variable and alterations in the sample size for specific analyses are described
Analyses were performed using IBM SPSS Version 220 and MedCalc Version 1941
Patients were divided into 6 groups according to body mass index BMI underweight BMI lt200 kgm2 normal weight BMI 200-249 kgm2 overweight BMI 25-299 kgm2 obesity class I BMI 30-349 kgm2 obesity class II BMI 35-399 kgm2 and obesity class III BMI gt40 kgm2
The primary endpoint was long-term mortality The secondary end-point was the rate of sternal wound infections
Summary statistics were calculated Continuous data are described as the median with the interquartile range in parentheses while categorical data are shown as numbers with percentages Differences between groups for normally distributed continuous variables were determined using the one-way analysis of variance with Holm-Sidak post-hoc test The Kruskal Wallis test was used for the analysis of non-normally distributed continuous variables with Dunns test for post hoc comparison The chi-squared test was used for the analysis of categorical variables Bonferonis correction was used for post-hoc analysis The univariable analysis was performed using logistic regression For multivariable analysis a logistic regression model was performed with mortality or wound infection as the dependent variable and all other characteristics summarized in the table 1 as independent variables The backward conditional selection was used for modeling with variables with score statistics lt01 included in the model Significance was assessed at plt005 Multiple imputation was not used to adjust for missing data The number of valid entries for each variable and alterations in the sample size for specific analyses are described
Analyses were performed using IBM SPSS Version 220 and MedCalc Version 1941
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None