Development of the Sternal Wound Infection Prediction Scale.
OBJECTIVE
To develop an instrument to reliably predict the occurrence of sternal wound infection (SWI).


METHODS
Instrument development with retrospective chart review.


METHODS
Southwestern university-affiliated medical center.


METHODS
One hundred eighty-five adults who underwent cardiac surgery. SWI developed in 94 patients, and 91 remained infection free. In phase 1, there were 82 subjects: SWI developed in 41, and 41 remained infection free. In phase 2, there were 103 subjects: SWI developed in 53, and 50 remained infection free.


METHODS
Development of a postoperative SWI.


METHODS
The Sternal Wound Infection Prediction Scale (SWIPS) was developed in 2 phases. Phase 1 consisted of designing the SWIPS with use of 19 risk factors most often identified with SWI and revising this scale (SWIPS-R) with use of 21 risk factors. Eighty-two patient records were reviewed. After determining the mean cutscores in phase 1, phase 2 provided cross-validation results with use of 103 additional patient records.


RESULTS
The SWIPS produced 62.1% correct predictions of infection and noninfection; whereas the SWIPS-R produced 72.8% correct predictions. Phase 2 cross-validation results for the 21 risk factors demonstrated that 62.1% and 72.8% of the patients were correctly diagnosed using the SWIPS and SWIPS-R, respectively. A multivariate logistic regression was also performed on the risk factors to predict infection/noninfection groups for all 185 patients. A reduced logistic regression model included 9 of the risk factors and correctly classified 76.2% of the subjects.


CONCLUSIONS
The SWIPS-R, with 21 risk factors, and the logistic regression model, with 12 risk factors, provided excellent classification rates of infection/noninfection. However, more data need to be collected to further strengthen reliability.
Dept of Audlt Health Nursing, College of Nursing & Health Professions, University of North Carolina at Charlotte 28223-0001, USA.
L C
LC
Hussey
B
B
Leeper
L S
LS
Hynan
D000328:Adult; D000368:Aged; D006801:Humans; D016015:Logistic Models; D011379:Prognosis; D012044:Regression Analysis; D012307:Risk Factors; D013249:Sternum / Q000601:surgery*; D013530:Surgical Wound Infection / Q000209:etiology*