Risk factors for spinal surgical site infection

Background. Surgical site infections (SSI) are one of the most common nosocomial infections in the United States. This study was conducted following an increase in the rate of SSI following spinal procedures at the study hospital. ^ Methods. This study examined patient and hospital associated risk factors for SSI using existing data on patients who had spinal surgery performed at the study hospital between December 2003 and August 2005. There were 59 patients with SSI identified as cases; controls were randomly selected from patients who had spinal procedures performed at the study hospital during the study period, but did not develop infection. Of the 245 original records reviewed, 5% were missing more than half the variables and were eliminated from the data set. A total of 234 patients were included in the final analysis, representing 55 cases and 179 controls. Multivariable analysis was conducted using logistic regression to control for confounding variables. ^ Results. Three variables were found to be significant risk factors for SSI in the study population: presence of comorbidities (odds ratio 3.15, 95% confidence interval 1.20 to 8.26), cut time above the population median of 100 minutes (odds ratio 2.98, 95% confidence interval 1.12 to 5.49), and use of iodine only for preoperative skin antisepsis (odds ratio 0.16, 95% confidence interval 0.06 to 0.45). Several risk factors of specific concern to the study hospital, such as operating room, hospital staff involved in the procedures and workers' compensation status, were not shown to be statistically significant. In addition, multiple factors that have been identified in prior studies, such as method of hair removal, smoking status, or incontinence, were not shown to be statistically significant in this population. ^ Conclusions. This study confirms that increased cut time is a risk for post-operative infection. Use of iodine only was found to decrease risk of infection; further study is recommended in a population with higher usage of chlorhexadine gluconate. Presence of comorbidities at the time of surgery was also found to be a risk factor for infection; however, specific comorbidities were not studied. ^

Learning curve for robotic-assisted laparoscopic colorectal surgery.

BACKGROUND: Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. METHODS: A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. RESULTS: The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m(2), and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 31.54 × case number - 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. CONCLUSIONS: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

Risk factors of pneumonia in traumatic spinal-cord-injured patients

Pneumonia is a well-documented and common respiratory infection in patients with acute traumatic spinal cord injuries, and may recur during the course of acute care. Using data from the North American Clinical Trials Network (NACTN) for Spinal Cord Injury, the incidence, timing, and recurrence of pneumonia were analyzed. The two main objectives were (1) to investigate the time and potential risk factors for the first occurrence of pneumonia using the Cox Proportional Hazards model, and (2) to investigate pneumonia recurrence and its risk factors using a Counting Process model that is a generalization of the Cox Proportional Hazards model. The results from survival analysis suggested that surgery, intubation, American Spinal Injury Association (ASIA) grade, direct admission to a NACTN site and age (older than 65 or not) were significant risks for first event of pneumonia and multiple events of pneumonia. The significance of this research is that it has the potential to identify patients at the time of admission who are at high risk for the incidence and recurrence of pneumonia. Knowledge and the time of occurrence of pneumonias are important factors for the development of prevention strategies and may also provide some insights into the selection of emerging therapies that compromise the immune system. ^