scholarly journals A Risk Index for Sternal Surgical Wound Infection After Cardiovascular Surgery

2003 ◽  
Vol 24 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Michele Kohli ◽  
Lilian Yuan ◽  
Michael Escobar ◽  
Tyrone David ◽  
Grant Gillis ◽  
...  

AbstractObjectives:To identify factors that increase the risk of sternal surgical wound infection after cardiovascular surgery and to develop a bedside clinical risk index using these factors.Design:A risk index was developed using clinical data collected from a cohort of 11,508 cardiac surgery patients and validated using three independent subsets of the data. With two of these subsets, we derived a logistic regression equation and then modified the scoring algorithm to simplify the calculation of patient risk scores by clinicians. The final subset was used to validate the index. The area under the receiver operating characteristic (aROC) curve was the primary measure of goodness of fit.Setting:Toronto General Hospital, a teaching hospital and the largest center for cardiac surgery in Ontario, Canada.Patients:Cardiac surgery patients receiving cardiopulmonary bypass between April 1, 1990, and December 31, 1995, who survived at least 6 days after surgery.Results:Variables that were used to construct the risk index included reoperation due to complication (odds ratio, 4.3; range, 1.9 to 8.5), diabetes (odds ratio, 2.4; range, 1.5 to 3.7), more than 3 days in the intensive care unit (odds ratio, 5.4; range, 3.2 to 8.7), and use of the internal mammary artery for revascularization (odds ratio, 3.2; range, 1.7 to 5.8). Validation showed that the index had an aROC curve of 0.64.Conclusions:The risk index described in this article allows clinicians to quickly stratify patients into four risk groups associated with an increasing risk of sternal surgical wound infection. It may be used perioperatively or as part of a wound infection surveillance system.

1991 ◽  
Vol 91 (3) ◽  
pp. S152-S157 ◽  
Author(s):  
David H. Culver ◽  
◽  
Teresa C. Horan ◽  
Robert P. Gaynes ◽  
William J. Martone ◽  
...  

1987 ◽  
Vol 156 (6) ◽  
pp. 967-973 ◽  
Author(s):  
T. Nagachinta ◽  
M. Stephens ◽  
B. Reitz ◽  
B. F. Polk

Author(s):  
Giovanna Bianca Figueira Rocha ◽  
Andryele Santana Miranda ◽  
Omar Pereira de Almeida Neto ◽  
Maria Beatriz Guimares Ferreira ◽  
Iolanda Alves Braga ◽  
...  

Introduction: Due to importance of surgeries for treatment of heart diseases, it is necessary to recognize surgical site infection and other Healthcare-Related Infections as the main post-surgical complications. Objective:  To analyze the association and correlation between clinical and propaedeutic variables with the prevalence of wound infection in patients undergoing cardiac surgery  Methodology:  Quantitative, analytical study with a retrospective approach. Data collection  was performed in the Medical Archive Sector of the Clinical Hospital of Uberlandia (HCU), using a previously structured instrument. Results:  A total of 453 medical records were evaluated, mainly masculine gender (n=313; 69.1%). A time patient hospital stays had a mean of 36.47±28.7days, surgical indication of myocardial revascularization (n=278; 61.4%). The rate of surgical wound infection (SWI) found was 19%. Correlation and clinical associations were: Time of surgery and left ventricle ejection fraction (LVEF) (r=0,10; p<0,05); time hospital stay and almost all echocardiographic variables, weight and height (p=0.01); Systolic blood pressure (SBP) and left ventricle posterior wall (LVPW) (r=0.16), LVEF (r=0.12) and intraventricular septum (r=0.13), (p<0.01); Diastolic blood pressure (DBP) and left ventricle posterior wall (LVPW) (r= 0.10; p<0.01). Conclusion: The study has hight potential to increase scientific evidences and improving  cardiovascular care, cardiovascular surgery field and prevention of healthcare-associated infections.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
T Besbes ◽  
S Mleyhi ◽  
J Sahli ◽  
M Messai ◽  
J Ziadi ◽  
...  

Abstract Background Early prediction of patients at highest risk of a poor outcome after cardiovascular surgery, including death can aid medical decision making, and adapt health care management in order to improve prognosis. In this context, we conducted this study to validate the CASUS severity score after cardiac surgery in the Tunisian population. Methods This is a retrospective cohort study conducted among patients who underwent cardiac surgery under extracorporeal circulation during the year 2018 at the Cardiovascular Surgery Department of La Rabta University Hospital in Tunisia. Data were collected from the patients hospitalization records. The discrimination of the score was assessed using the ROC curve and the calibration using the Hosmer-Lemeshow goodness of fit test and then by constructing the calibration curve. Overall correct classification was also obtained. Results In our study, the observed mortality rate was 10.52% among the 95 included patients. The discriminating power of the CASUS score was estimated by the area under the ROC curve (AUC), this scoring system had a good discrimination with AUC greater than 0.9 from postoperative Day 0 to Day 5.From postoperative day 0 to day 5, the Hosmer-Lemeshow's test gave a value of chi square test statistic ranging from 1.474 to 8.42 and a value of level of significance ranging from 0.39 to 0.99 indicating a good calibration. The overall correct classification rate from postoperative day 0 to day 5 ranged from 84.4% to 92.4%. Conclusions Despite the differences in the profile of the risk factors between the Tunisian population and the population constituting the database used to develop the CASUS score, we can say that this risk model presents acceptable performances in our population, attested by adequate discrimination and calibration. Prospective and especially multicentre studies on larger samples are needed before definitively conclude on the performance of this model in our country. Key messages The casus score seems to be valid to predict mortality among patients undergoing cardiac surgery. Multicenter study on larger sample is needed to derive and validate models able to predict in-hospitals mortality.


1983 ◽  
Vol 36 (2) ◽  
pp. 161-166
Author(s):  
SARAH F. GRAPPEL ◽  
LILLIAN PHILLIPS ◽  
HUGH B. LEWIS ◽  
D. GWYN MORGAN ◽  
PAUL ACTOR

Sign in / Sign up

Export Citation Format

Share Document