To examine the global burden, associated point sources, and successful prevention and control measures for documented outbreaks of Burkholderia cepacia healthcare-associated infections (HAIs).

Integrative review.

A review of all outbreaks of Burkholderia cepacia HAIs published in the peer-reviewed literature between January 1970 and October 2019 was conducted to identify the global burden, associated point sources, and successful prevention and control measures using the Guidelines for Outbreak Reports and Intervention Studies of Nosocomial Infections (ORION).

In total, we reviewed 125 documented outbreaks of Burkholderia cepacia–related HAIs worldwide. The reported B. cepacia HAIs for this period involved 3,287 patients. The point sources were identified in most outbreaks of B. cepacia HAIs (n = 93; 74.4%); they included medication vials, disinfectants, and antiseptics. Moreover, 95 of the outbreak reports (76%) described effective prevention and control measures, but only 33 reports indicated the use of a combination of environment-, patient- and staff-related measures. None of the outbreak reports used the ORION guidelines.

Outbreaks of Burkholderia cepacia HAIs are an ongoing challenge. They are often associated with immunocompromised patients who acquire the infection from exposure to contaminated medications, products, and equipment. These outbreaks are not infrequent, and a range of infection prevention and control measures have been effective in arresting spread. The use of ORION guidelines for outbreak reporting would improve the quality of information and data to generate evidence for translation into practice.

To determine the effectiveness and ease of use of an electronic reminder device in reducing urinary catheterization duration.

A randomized controlled trial with a cross-sectional anonymous online survey and focus group.

Ten wards in an Australian hospital.

All hospitalized patients with a urinary catheter.

An electronic reminder system, the CATH TAG, applied to urinary catheter bags to prompt removal of urinary catheters.

Catheterization duration and perceptions of nurses about the ease of use.

A Cox proportional hazards model was used to assess the rate of removal of catheters. A phenomenological approach underpinned data collection and analysis methods associated with the focus group.

In total, 1,167 patients with a urinary catheter were included. The mean durations in control and intervention phases were 5.51 days (95% confidence interval [CI], 4.9–6.2) and 5.08 days (95% CI, 4.6–5.6), respectively. For patients who had a CATH TAG applied, the hazard ratio (HR) was 1.02 (95% CI, 0.91–1.14; P = .75). A subgroup analysis excluded patients in an intensive care unit (ICU), and the use of the CATH TAG was associated with a 23% decrease in the mean, from 5.00 days (95% CI, 4.44–5.56) to 3.84 days (95% CI, 3.47–4.21). Overall, 82 nurses completed a survey and 5 nurses participated in a focus group. Responses regarding the device were largely positive, and benefits for patient care were identified.

The CATH TAG did not reduce the duration of catheterization, but potential benefits in patients outside the ICU were identified. Electronic reminders may be useful to aid prompt removal of urinary catheters in the non-ICU hospital setting.

To examine tweeting activity, networks, and common topics mentioned on Twitter at 4 international infection control and infectious disease conferences.

A cross-sectional study.

An independent company was commissioned to undertake a Twitter ‘trawl’ each month between July 1, 2016, and November 31, 2016. The trawl identified any tweets that contained the official hashtags of the conferences for (1) the UK Infection Prevention Society, (2) IDWeek 2016, (3) the Federation of Infectious Society/Hospital Infection Society, and (4) the Australasian College for Infection Prevention and Control. Topics from each tweet were identified, and an examination of the frequency and timing of tweets was performed. A social network analysis was performed to illustrate connections between users. A multivariate binary logistic regression model was developed to explore the predictors of ‘retweets.’

In total, 23,718 tweets were identified as using 1 of the 2 hashtags of interest. The results demonstrated that the most tweets were posted during the conferences. Network analysis demonstrated a diversity of twitter networks. A link to a web address was a significant predictor of whether a tweet would be retweeted (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.9–2.1). Other significant factors predicting a retweet included tweeting on topics such as Clostridium difficile (OR, 2.0; 95% CI, 1.7–2.4) and the media (OR, 1.8; 95% CI, 1.6–2.0). Tweets that contained a picture were significantly less likely to be retweeted (OR, 0.06; 95% CI, 0.05–0.08).

Twitter is a useful tool for information sharing and networking at infection control conferences.

Infect Control Hosp Epidemiol 2017;38:1271–1276

To measure the interobserver agreement, sensitivity, specificity, positive predictive value, and negative predictive value of data submitted to a statewide surveillance system for identifying central line-associated bloodstream infection (BSI).

Retrospective review of hospital medical records comparing reported data with gold standard according to definitions of central line–associated BSI.

Six Victorian public hospitals with more than 100 beds.

Reporting of surveillance outcomes was undertaken by infection control practitioners at the hospital sites. Retrospective evaluation of the surveillance process was carried out by independent infection control practitioners from the Victorian Hospital Acquired Infection Surveillance System (VICNISS). A sample of records of patients reported to have a central line-associated BSI were assessed to determine whether they met the definition of central line–associated BSI. A sample of records of patients with bacteremia in the intensive care unit during the assessment period who were not reported as having central line–associated BSI were also assessed to see whether they met the definition of central line-associated BSI.

Records of 108 patients were reviewed; the agreement between surveillance reports and the VICNISS assessment was 67.6% (κ = 0.31). Of the 46 reported central line–associated BSIs, 27 were confirmed to be central line–associated BSIs, for a positive predictive value of 59% (95% confidence interval [CI], 43%–73%). Of the 62 cases of bacteremia reviewed that were not reported as central line–associated BSIs, 45 were not associated with a central line, for a negative predictive value of 73% (95% CI, 60%–83%). Estimated sensitivity was 35%, and specificity was 87%. The positive likelihood ratio was 3.0, and the negative likelihood ratio was 0.72.

The agreement between the reporting of central line–associated BSI and the gold standard application of definitions was unacceptably low. False-negative results were problematic; more than half of central line–associated BSIs may be missed in Victorian public hospitals.

To analyze the risk factors for surgical site infection (SSI) complicating coronary artery bypass graft (CABG) surgery and to create an alternative SSI risk score based on the results of multivariate analysis.

A prospective cohort study involving inpatient and laboratory-based surveillance of patients who underwent CABG surgery over a 27-month period from January 1, 2003 through March 31, 2005. Data were obtained from 6 acute care hospitals in Victoria, Australia, that contributed surveillance data for SSI complicating CABG surgery to the Victorian Hospital Acquired Infection Surveillance System Coordinating Centre and the Australasian Society of Cardiac and Thoracic Surgeons, also in Victoria.

A total of 4,633 (93%) of the 4,987 patients who underwent CABG surgery during this period were matched in the 2 systems databases. There were 286 SSIs and 62 deep or organ space sternal SSIs (deep or organ space sternal SSI rate, 1.33%). Univariate analysis revealed that diabetes mellitus, body mass index (BMI) greater than 35, and receipt of blood transfusion were risk factors for all types of SSI complicating CABG surgery. Six multivariate analysis models were created to examine either preoperative factors alone or preoperative factors combined with operative factors. All models revealed diabetes and BMI of 30 or greater as risk factors for SSI complicating CABG surgery. A new preoperative scoring system was devised to predict sternal SSI, which assigned 1 point for diabetes, 1 point for BMI of 30 or greater but less than 35, and 2 points for BMI of 35 or greater. Each point in the scoring system represented approximately a doubling of risk of SSI. The new scoring system performed better than the National Nosocomial Infections Surveillance System (NNIS) risk index at predicting SSI.

A new weighted scoring system based on preoperative risk factors was created to predict sternal SSI risk following CABG surgery. The new scoring system outperformed the NNIS risk index. Future studies are needed to validate this scoring system.

To measure the accuracy and determine the positive predictive value (PPV) and negative predictive value (NPV) of data submitted to a statewide surveillance system for identifying surgical site infection (SSI) complicating coronary artery bypass graft (CABG) surgery.

Retrospective review of hospital medical records comparing SSI data with surveillance data submitted by infection control consultants (ICCs).

Victorian Hospital Acquired Infection Surveillance System (VICNISS) Coordinating Centre in Victoria, Australia.

All patients reported to have an SSI following CABG surgery and a random sample of approximately 10% of patients reported not to have an SSI following CABG surgery.

The VICNISS ascertainment rate for CABG procedures in Victoria was 95%. One hundred sixty-nine medical records were reviewed, and reviewers agreed with ICCs about 46 (96%) of the patients reported as infected by the ICCs and 31 (91%) of the patients identified with a sternal SSI by the ICCs. In one-third of SSIs, the depth of SSI documented by ICCs was discordant with that documented by the reviewers. Disagreement about patients with donor site SSI was frequent. When the review findings were used as the reference standard, the PPV for ICC-reported SSI was 96% (95% confidence interval [CI], 86%-99%), and the NPV was 97% (95% CI, 92%-99%). For ICC-reported sternal SSI, the PPV was 91% (95% CI, 76%-98%) and the NPV was 98% (95% CI, 94%-100%).

There was broad agreement on the number of infected patients and the number of patients with sternal SSI. However, discordance was frequent with respect to the depth of sternal SSI and the identification of donor site SSI. We recommend modifications to the methodology for National Noscomial Infection Surveillance System-based surveillance for SSI following CABG surgery.

The Victorian Hospital Acquired Infection Surveillance System (VICNISS) hospital-acquired infection surveillance system was established in 2002 in Victoria, Australia, and collates surgical site infection (SSI) surveillance data from public hospitals in Australia.

To evaluate the association between the US National Nosocomial Infections Surveillance (NNIS) system's risk index and SSI rates for 7 surgical procedures.

SSI surveillance was performed with NNIS definitions and methods for surgical procedures performed between November 2002 and September 2004. Correlations were assessed using the Goodman-Kruskal γ statistic.

Data were submitted for the following numbers of procedures: appendectomy, 545; coronary artery bypass graft (CABG), 4,632; cholecystectomy, 1,001; colon surgery, 623; cesarean section, 4,857; hip arthroplasty, 3,825; and knee arthroplasty, 2,416. NNIS risk index and increasing SSI rate were moderately well correlated for appendectomy (γ = 0.55), colon surgery (γ = 0.48), and cesarean section (γ = 0.42). A fairly positive correlation was found for cholecystectomy (γ = 0.17), hip arthroplasty (γ = 0.2), and knee arthroplasty (γ = 0.16). However, for CABG surgery, a poor association was found (γ = 0.02).

The NNIS risk index was positively correlated with an increasing SSI rate for all 7 procedures; the strongest correlation was found for appendectomy, cesarean section, and colon surgery, and the poorest correlation was found for CABG surgery. We believe that risk stratification with the NNIS risk index is appropriate for comparison of data for most procedures and superior to use of no risk adjustment. However, for some procedures, particularly CABG, further studies of alternative risk indexes are needed to better stratify patients.

To develop a new, simple, and practical risk index for patients undergoing coronary artery bypass graft (CABG) surgery, to develop a preoperative risk index that is predictive of surgical-site infection (SSI), and to compare the new risk indices with the National Nosocomial Infections Surveillance (NNIS) System risk index.

Potential risk factor and infection data were collected prospectively and analyzed by multivariate analysis. Two new risk indices were constructed and then compared with the NNIS System risk index for predictive power for SSI.

Alfred Hospital is a 350-bed, university-affiliated, tertiary-care referral center. The cardiothoracic unit performs approximately 650 CABG procedures per year.

All patients undergoing CABG surgery within the cardiothoracic unit at Alfred Hospital between December 1, 1996, and September 29, 2000, were included.

Potential risk factor data were complete for 2,345 patients. There were 199 SSIs. Obesity (odds ratio [OR], 1.78; 95% confidence interval [CI95], 1.24 to 2.55), peripheral or cerebrovascular disease (OR, 1.64; CI95, 1.16 to 2.33), insulin-dependent diabetes mellitus (OR, 2.29; CI95, 1.15 to 4.54), and a procedure lasting longer than 5 hours (OR, 1.75; CI95,1.18 to 2.58) were identified as independent risk factors for SSI. With the use of a different combination of these risk factors, two risk indices were constructed and compared using the Goodman-Kruskal nonparametric correlation coefficient (G). Risk index B had the highest G value (0.3405; CI95, 0.2245 to 0.4565), compared with the NNIS System risk index G value (0.3142; CI95, 0.1462 to 0.4822). The G value for risk index A constructed from preoperative variables only, was 0.3299 (CI95 0.2039 to 0.4559).

Two new risk indices have been developed. Both indices are as predictive as the NNIS System risk index. One of the new risk indices can also be applied preoperatively.