[Surgical wound infection: the risk factors and a predictive model].
BACKGROUND
The identification of the factors associated with infection of the surgical wound and the groups of patients with greatest risk of developing the same may aid in the elaboration of prevention strategies.


METHODS
A prospective follow up study of a group of 1,143 patients admitted to general and digestive surgical departments in the Ramón y Cajal Hospital over a period of 7 months was carried out to determine the accumulated incidence of infection of the surgical wound and quantify the associated risk factors. A mathematical model was developed by logistic multiple regression analysis allowing the identification of groups of patients with high risk of infection which were internally evaluated posteriorly.


RESULTS
Surgically intervened patients (70% of those admitted) developed a mean of 11 wound infections out of 100 patients. Five independent factors (age, surgical classification, length of intervention, presurgical stay, and presence of a central route) were associated to increased risk of infection.


CONCLUSIONS
The factors associated with surgical wound infection identified in this study are related to the degree of wound contamination, the intrinsic risk of the patients and quality of health care. The model obtained is more efficient than the traditional surgical classification for the identification of groups of patients with high risk of infection.
Asensio Vegas
A
A
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Universidad de Alcalá de Henares, Madrid.
Monge Jodra
V
V
Soriano
C
C
López
R
R
Gil
A
A
Lizán García
M
M
D016009:Chi-Square Distribution; D005260:Female; D006801:Humans; D015994:Incidence; D016013:Likelihood Functions; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016017:Odds Ratio; D011336:Probability; D011379:Prognosis; D011446:Prospective Studies; D012307:Risk Factors; D013030:Spain / Q000453:epidemiology; D013530:Surgical Wound Infection / Q000453:epidemiology*
Infección de la herida quirúrgica: factores de riesgo y modelo predictivo.