Sequential evolution of virulence and resistance during clonal spread of community-acquired methicillin-resistant Staphylococcus aureus.

The past two decades have witnessed an alarming expansion of staphylococcal disease caused by community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA). The factors underlying the epidemic expansion of CA-MRSA lineages such as USA300, the predominant CA-MRSA clone in the United States, are largely unknown. Previously described virulence and antimicrobial resistance genes that promote the dissemination of CA-MRSA are carried by mobile genetic elements, including phages and plasmids. Here, we used high-resolution genomics and experimental infections to characterize the evolution of a USA300 variant plaguing a patient population at increased risk of infection to understand the mechanisms underlying the emergence of genetic elements that facilitate clonal spread of the pathogen. Genetic analyses provided conclusive evidence that fitness (manifest as emergence of a dominant clone) changed coincidently with the stepwise emergence of (i) a unique prophage and mutation of the regulator of the pyrimidine nucleotide biosynthetic operon that promoted abscess formation and colonization, respectively, thereby priming the clone for success; and (ii) a unique plasmid that conferred resistance to two topical microbiocides, mupirocin and chlorhexidine, frequently used for decolonization and infection prevention. The resistance plasmid evolved through successive incorporation of DNA elements from non-S. aureus spp. into an indigenous cryptic plasmid, suggesting a mechanism for interspecies genetic exchange that promotes antimicrobial resistance. Collectively, the data suggest that clonal spread in a vulnerable population resulted from extensive clinical intervention and intense selection pressure toward a pathogen lifestyle that involved the evolution of consequential mutations and mobile genetic elements.

Modeling transmission of pathogens in healthcare settings.

PURPOSE OF REVIEW: Mathematical, statistical, and computational models provide insight into the transmission mechanisms and optimal control of healthcare-associated infections. To contextualize recent findings, we offer a summative review of recent literature focused on modeling transmission of pathogens in healthcare settings. RECENT FINDINGS: The COVID-19 pandemic has led to a dramatic shift in the modeling landscape as the healthcare community has raced to characterize the transmission dynamics of SARS-CoV-2 and develop effective interventions. Inequities in COVID-19 outcomes have inspired new efforts to quantify how structural bias impacts both health outcomes and model parameterization. Meanwhile, developments in the modeling of methicillin-resistant Staphylococcus aureus, Clostridioides difficile, and other nosocomial infections continue to advance. Machine learning continues to be applied in novel ways, and genomic data is being increasingly incorporated into modeling efforts. SUMMARY: As the type and amount of data continues to grow, mathematical, statistical, and computational modeling will play an increasing role in healthcare epidemiology. Gaps remain in producing models that are generalizable to a variety of time periods, geographic locations, and populations. However, with effective communication of findings and interdisciplinary collaboration, opportunities for implementing models for clinical decision-making and public health decision-making are bound to increase.

SARS-CoV-2 antibodies: IgA correlates with severity of disease in early COVID-19 infection.

Timing of detection of immunoglobulin G (IgG), immunoglobulin A (IgA), and immunoglobulin M (IgM) antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and their use to support the diagnosis are of increasing interest. We used the Gold Standard Diagnostics ELISA to evaluate the kinetics of SARS-CoV-2 IgG, IgA, and IgM antibodies in sera of 82 hospitalized patients with polymerase chain reaction (PCR)-confirmed coronavirus disease 2019 (COVID-19). Serum samples were collected 1-59 days post-onset of symptoms (PoS) and we examined the association of age, sex, disease severity, and symptoms' duration with antibody levels. We also tested sera of 100 ambulatory hospital employees with PCR-confirmed COVID-19 and samples collected during convalescence, 35-57 days PoS. All but four of the admitted patients (95.1%) developed antibodies to SARS-CoV-2. Antibodies were detected within 7 days PoS; IgA in 60.0%, IgM in 53.3%, and IgG in 46.7% of samples. IgG positivity increased to 100% on Day 21. We did not observe significant differences in the rate of antibody development in regard to age and sex. IgA levels were highest in patients with a severe and critical illness. In multiple regression analyses, only IgA levels were statistically significantly correlated with critical disease (p = .05) regardless of age, sex, and duration of symptoms. Among 100 ambulatory hospital employees who had antibody testing after 4 weeks PoS only 10% had positive IgA antibodies. The most frequently isolated isotype in sera of employees after 30 days PoS was IgG (88%). IgA was the predominant immunoglobulin in early disease and correlated independently with a critical illness. IgG antibodies remained detectable in almost 90% of samples collected up to two months after infection.

Distribution of Late-Onset Neonatal Sepsis Pathogens Differs in Inpatient and Outpatient Settings.

OBJECTIVE: We sought to examine pathogen distribution and clinical presentation of late-onset sepsis (LOS) at an urban tertiary care center. STUDY DESIGN: We performed a retrospective review of all culture-confirmed cases of LOS presenting to our institution from 2013 to 2017. Medical records were evaluated for demographic information, sepsis risk factors, encounter location, and clinical outcome. RESULTS: We identified 97 cases of LOS, with a median age at diagnosis of 25 days. The most common pathogens were Escherichia coli (22.7%), Staphylococcus aureus (17.5%), coagulase-negative staphylococci (12.4%), and Enterococcus faecalis (12.4%). Infections due to E. coli predominated in the outpatient setting (44%), whereas S. aureus and Gram-negative organisms other than E. coli were more frequently isolated from inpatients (21 and 24%, respectively). Gram-positive organisms were more common in infants delivered through cesarean section (p = 0.002) and were associated with more complications (p = 0.03). Escherichia coli LOS presented at an earlier age than S. aureus (15 vs. 32 days; p = 0.04). Of the 15 cases of meningitis, 40% did not have a positive blood culture. CONCLUSION: Pathogen distribution in our population was different from those previously reported, with a higher prevalence of S. aureus. Encounter location and age at presentation varied significantly by pathogen.

Expanded Gram-Negative Antimicrobial Prophylaxis Reduces Surgical Site Infections in Hip Arthroplasty.

BACKGROUND: A first-generation cephalosporin is the recommended antibiotic prophylaxis for implants. However, this standard does not address the increasing prevalence and virulence of gram-negative pathogens infecting patients. We found that gram-negative bacilli caused 30% of our surgical site infections (SSIs) following hip procedures, whereas only 10% of knee SSIs were caused by gram-negative bacilli. To address this, we instituted Expanded Gram-Negative Antimicrobial Prophylaxis (EGNAP) for our hip arthroplasty patients. The purpose of this study is to measure the effect of EGNAP on the SSI rates following primary total hip arthroplasty. METHODS: The study consisted of 10,084 total patients. Before July 2012, all patients were administered 1 g of cefazolin. After July 2012, our protocol was adjusted by adding the EGNAP with either gentamicin or aztreonam to hip patients (group 1) and not to the knee arthroplasty patients (group 2). RESULTS: Group 1 consisted of the 5389 primary hip arthroplasty patients. Of these patients, 4122 (before July 2012) did not receive weight-based high-dose gentamicin and 1267 (after July 2012) did. Before the introduction of EGNAP, group 1 SSI rate was 1.19% (49/4122). After July 2012 when EGNAP was added, the overall group 1 SSI rate decreased to 0.55% (7/1267) (P = .05). During the study period, there was not a significant difference in SSI rate of knee arthroplasty (group 2): 1.08% vs 1.02% (P = .999). CONCLUSIONS: The addition of EGNAP for hip arthroplasty is a safe and effective method to decrease SSIs. LEVEL OF EVIDENCE: III. Case-control study.

The Otto Aufranc Award: Modifiable versus nonmodifiable risk factors for infection after hip arthroplasty.

BACKGROUND: Periprosthetic joint infections (PJIs) are associated with increased morbidity and cost. It would be important to identify any modifiable patient- and surgical-related factors that could be modified before surgery to decrease the risk of PJI. QUESTIONS/PURPOSES: We sought to identify and quantify the magnitude of modifiable risk factors for deep PJIs after primary hip arthroplasty. METHODS: A series of 3672 primary and 406 revision hip arthroplasties performed at a single specialty hospital over a 3-year period were reviewed. All deep PJIs were identified using the Centers for Disease Control and Prevention case definitions (ie, occurs within 30-90 days postoperatively, involves deep soft tissues of the incision, purulent drainage, dehiscence and fever, localized pain or tenderness). Univariate and multivariate analyses determined the association between patient and surgical risk factors and PJIs. For the elective patients, the procedure was performed on the day of admission ("same-day procedure"), whereas for the fracture and nonelective patients, the procedure was performed 1 or more days postadmission ("nonsame-day procedure"). Staphylococcus aureus colonization, tobacco use, and body mass index (BMI) were defined as patient-related modifiable risk factors. RESULTS: Forty-seven (1.3%) deep PJIs were identified. Infection developed in 20 of 363 hips of nonsame-day procedures and 27 of 3309 same-day procedures (p=0.006). There were eight (2%) infections in the revision group. After controlling for confounding variables, our multivariate analysis showed that BMI≧40 kg/m2 (odds ratio [OR], 4.13; 95% confidence interval [CI], 1.3-12.88; p=0.01), operating time>115 minutes (OR, 3.38; 95% CI, 1.23-9.28; p=0.018), nonsame-day surgery (OR, 4.16; 95% CI, 1.44-12.02; p=0.008), and revision surgery (OR, 4.23; 95% CI, 1.67-10.72; p<0.001) are significant risk factors for PJIs. Tobacco use and S aureus colonization were additive risk factors when combined with other significant risk factors (OR, 12.76; 95% CI, 2.47-66.16; p=0.017). CONCLUSIONS: Nonsame-day hip and revision arthroplasties have higher infection rates than same-day primary surgeries. These characteristics are not modifiable and should be categorized as a separate cohort for complication-reporting purposes. Potentially modifiable risk factors in our patient population include operating time, elevated BMI, tobacco use, and S aureus colonization. Modifying risk factors may decrease the incidence of PJIs. When reporting deep PJI rates, stratification into preventable versus nonpreventable infections may provide a better assessment of performance on an institutional and individual surgeon level. LEVEL OF EVIDENCE: Level IV, prognostic study. See Guidelines for Authors for a complete description of levels of evidence.

Risk Factors for Infection Following Total Knee Arthroplasty: A Series of 3836 Cases from One Institution.

Higher PJI rates may be related to identifiable risk factors, which may or may not be modifiable. Identifying risk factors preoperatively provides opportunities for modification and potentially decreasing the incidence of PJI. The purposes of this study were to: (1) retrospectively identify and quantify risk factors for PJI following primary TKA, and (2) to classify those significant risk factors as either non-modifiable or modifiable for intervention prior to surgery. Optimization of modifiable risk factors such as Staphylococcus aureus colonization, and tobacco use prior to primary TKA may decrease the incidence of periprosthetic joint infection after primary TKA, thereby reducing morbidity and the costs associated with treating those infections.

Reassessing provider reporting in the age of electronic surveillance.

CONTEXT: In 2000, the Centers for Disease Control and Prevention began funding health departments to implement integrated electronic systems for disease surveillance. OBJECTIVE: Determine the impact of discontinuing provider reporting for chronic hepatitis B and C, hepatitis A, and select enteric diseases. DESIGN: Laboratory and provider surveillance reports of chronic hepatitis B and C and enteric infections (Shiga toxin-producing Escherichia coli, Campylobacter, Listeria, noncholera Vibrio [eg, Vibrio parahaemolyticus], Salmonella, Shigella, and hepatitis A) diagnosed on January 1, 2007 to December 31, 2010 were compared for completeness and timeliness. Number of cases submitted by laboratories, providers, or both were assessed. RESULTS: From 2007 to 2010, the proportion of cases reported only by providers for enteric disease infections differed by disease, ranging from 4% (Shiga toxin-producing E coli) to 20% (noncholera Vibrio). For chronic hepatitis C, less than 1% of cases were reported by providers only. The number of complete laboratory reports increased over the time period from 80% to 95% for chronic hepatitis and 92% to 94% for enteric infections. Laboratory reports had higher completion for date of birth, sex, and zip codes. Provider reports had less than 60% completion for race/ethnicity versus 20% for laboratories. Laboratories were faster than providers at reporting chronic hepatitis B (median 4 vs 21 days), chronic hepatitis C (4 vs 18 days), Campylobacter (6 vs 10 days), noncholera Vibrio (11 vs 12 days), Salmonella (6 vs 7 days), Shigella (6 vs 13 days), and hepatitis A (3 vs 8 days); providers were faster than laboratories at reporting Shiga toxin-producing E coli (4 vs 7 days) and Listeria (5 vs 6 days). CONCLUSIONS: Laboratories reported more cases and their reports were timelier and more complete for all categories except race/ethnicity for chronic hepatitis, Campylobacter, noncholera Vibrio, Salmonella, Shigella, and hepatitis A. For chronic hepatitis, provider reporting could be eliminated in New York City with no adverse effects on disease surveillance. For enteric infections, more work is needed before discontinuing provider reporting.

The evaluation of electrolyzed water, sodium dichloroisocyanurate, and peracetic acid with hydrogen peroxide for the disinfection of patient room surfaces.

BACKGROUND: Sporicidal disinfectants are necessary to control Clostridioides difficile and Candida auris. Novel application methods such as electrostatic sprayers may increase disinfection effectiveness. We employed a standardized protocol to assess 3 sporicidal disinfectants: electrolyzed water (EW), sodium dichloroisocyanurate (NaDCC) and peracetic acid/hydrogen peroxide (PAA/H2O2). METHODS: The study was conducted at 2 New York City hospitals (1,082 total beds) over an 18-month period. The 3 chemicals were applied by housekeeping personnel following the hospital protocol; the use of electrostatic sprayers was incorporated into EW and NaDCC. In randomly selected rooms, 5 surfaces were sampled for microbial colony counts after cleaning. Data analyses were performed using negative binomial logistic regression. RESULTS: We collected 774 samples. NaDCC-disinfected surfaces had a lower mean colony count (14 colony forming units [CFU]) compared to PAA/H2O2 (18 CFU, P = .36) and EW (37 CFU, P < .001). PAA/H2O2 and EW had more samples with any growth (both P < .05) compared to NaDCC. NaDCC applied with wipes and an electrostatic sprayer had the lowest number of samples with no growth and <2.5 CFU/cm2 (difference not significant). CONCLUSIONS: The use of NaDCC for surface disinfection resulted in the lowest bacterial colony counts on patient room high touch surfaces in our study.

Hospital and ICU Admission Risk Associated With Comorbidities Among Children With COVID-19 Ancestral Strains.

A large proportion of children have been affected by COVID-19; we evaluated the association between comorbidities and hospitalization/ICU (intensive care unit) admission among 4097 children under age 21 years with symptomatic COVID-19 (not just polymerase chain reaction [PCR]-positive or multisystem inflammatory syndrome in children associated with COVID-19 [MIS-C]) from 2 large health systems from March 2020 to September 2021. Significant comorbidities and demographic factors identified by univariable analysis were included in a multivariable logistic regression compared with children ages 6 to 11 without comorbidities. In all, 475 children (11.6%) were hospitalized, of whom 25.5% required ICU admission. Children under 1 year had high hospitalization risk, but low risk of ICU admission. Presence of at least 1 comorbidity was associated with hospitalization and ICU admission (odds ratio [OR] > 4). Asthma, obesity, chronic kidney disease, sickle cell disease, bone marrow transplantation, and neurologic disorders were associated with hospitalization (adjusted odds ratio [AOR] > 2). Malignancy, intellectual disability, and prematurity were associated with ICU admission (AOR > 4). Comorbidities are significantly associated with hospitalization/ICU admission among children with COVID-19.

Temporal, Seasonal, and Monthly Effects on Total Knee Arthroplasty Surgical Site Infection Rates.

BACKGROUND: Deep surgical site infections (dSSI) following total knee arthroplasty (TKA) are associated with morbidity and poor outcomes. Although numerous patient and non-patient factors have been correlated with dSSI development, the temporal and seasonal variability of dSSI is unclear. The purpose of this study was to investigate the monthly and seasonal variability of dSSI rates following TKA. METHODS: The dSSI database at a single large, urban, academic medical center was reviewed for TKAs performed between January 2009 and August 2018. The monthly and seasonal variability of dSSI was evaluated using a Poisson regression. Additionally, the change in dSSI rate was calculated over the entire study period. RESULTS: We reviewed 15,230 consecutive TKAs. The average dSSI rate following TKA was 1.11% (SD: 0.91). The rate of dSSI decreased over the study period (r = 0.94, 95% CI: 0.85-1.05) but did not reach statistical significance. With summer as the reference season, there were no significant differences in the dSSI rate in fall, winter, or spring. With July as the reference season, there were no differences in the dSSI rate in any other months of the year. CONCLUSION: Although non-significant, this analysis found a decreasing rate of dSSI after TKA over a nearly 10-year period. Interestingly, there was no difference in the dSSI rate following TKA in July as compared to other months or in summer as compared to other seasons. This conflicts with previous reports that have found an increased incidence of dSSI and other complications in July when the graduate medical education calendar begins.

Impact of Prenatal SARS-CoV-2 Infection on Infant Emergency Department Visits and Hospitalization.

To better understand the impact of prenatal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on infants, this study sought to compare the risk of hospital visits and of postnatal SARS-CoV-2 infection between infants born to mothers with and without prenatal SARS-CoV-2 infection. In this retrospective observational cohort study of 6871 mothers and their infants, overall rates of emergency department (ED) visits and hospital admissions in the first 90 days of life were similar for infants born to mothers with and without prenatal SARS-CoV-2 infection. Infants born to negative mothers were more likely than infants of positive mothers to be hospitalized after ED visit (relative risk: 3.76; 95% confidence interval: 1.27-11.13, P = .003). Five infants tested positive; all were born to negative mothers, suggesting that maternal prenatal SARS-CoV-2 infection may protect infants from postnatal infection. The lower acuity ED visits for infants born to mothers with prenatal SARS-CoV-2 infection may reflect a heightened level of concern among these mothers.

Lack of Seasonal and Temporal Variability in Total Hip Arthroplasty Surgical Site Infections.

BACKGROUND: Surgical site infections (SSIs) are a signifi- cant cause of morbidity and mortality following total joint arthroplasty (TJA). While many risk factors are known, the seasonal and temporal associations of SSI are less under- stood. Understanding the associations can help reduce SSI rates. METHODS: We tracked rates of deep surgical site infec- tions (dSSIs) following total hip arthroplasty (THA) at a single large urban academic medical center from January 2009 through August 2018. Using a Poisson regression, we determined the monthly and seasonal variability of dSSIs. We also calculated the change in dSSI rate over the entire 9.67-year study period. RESULTS: In total, 15,703 THA cases between January 2009 and August 2018 were analyzed. There was no signifi- cant difference in the dSSI rate following THA in fall, winter, or spring as compared to summer. Similarly, there was no significant difference in dSSIs in July as compared to other months of the year. The average rate of dSSIs following THA was 1.04 (SD, 0.90) per 100 patients. The dSSI rate following THA decreased over the study period (r = 0.93, 95% CI: 0.84-1.03) but did not reach statistical significance. CONCLUSION: This study demonstrated a non-significant, albeit decreasing, rate of dSSIs following THA over the study period. Contrary to previous reports, there was no difference in the dSSI rate in the summer months as compared to other seasons. The month of the year also does not appear to be a significant risk factor for SSIs, calling into question previous reports arguing for the importance of the "July effect."

Development and validation of a machine learning model to predict mortality risk in patients with COVID-19.

New York City quickly became an epicentre of the COVID-19 pandemic. An ability to triage patients was needed due to a sudden and massive increase in patients during the COVID-19 pandemic as healthcare providers incurred an exponential increase in workload,which created a strain on the staff and limited resources. Further, methods to better understand and characterise the predictors of morbidity and mortality was needed. METHODS: We developed a prediction model to predict patients at risk for mortality using only laboratory, vital and demographic information readily available in the electronic health record on more than 3395 hospital admissions with COVID-19. Multiple methods were applied, and final model was selected based on performance. A variable importance algorithm was used for interpretability, and understanding of performance and predictors was applied to the best model. We built a model with an area under the receiver operating characteristic curve of 83-97 to identify predictors and patients with high risk of mortality due to COVID-19. Oximetry, respirations, blood urea nitrogen, lymphocyte per cent, calcium, troponin and neutrophil percentage were important features, and key ranges were identified that contributed to a 50% increase in patients' mortality prediction score. With an increasing negative predictive value starting 0.90 after the second day of admission suggests we might be able to more confidently identify likely survivors DISCUSSION: This study serves as a use case of a machine learning methods with visualisations to aide clinicians with a better understanding of the model and predictors of mortality. CONCLUSION: As we continue to understand COVID-19, computer assisted algorithms might be able to improve the care of patients.

Seasonal, monthly, and yearly variability of surgical site infections at a single institution-A report of more than 95,000 procedures.

To determine whether deep surgical site infection (dSSI) rate exhibits temporal variability, dSSI rates following 98,068 cases were analyzed. The overall dSSI rate decreased significantly between 2009 and 2018. Summer had a significantly greater rate of dSSI than winter. There was no difference in dSSI rate in July versus other months.

Implementing an Inpatient Pediatric Prospective Audit and Feedback Antimicrobial Stewardship Program Within a Larger Medical Center.

BACKGROUND: Pediatric antimicrobial stewardship programs (ASPs) within larger institutions have unique opportunities to develop programs specialized to the needs of the pediatric program. In January 2013, our institution established a formalized pediatric ASP utilizing the prospective audit and feedback process. In an effort to standardize therapy and improve quality of care, members of the ASP developed evidence-based guidelines for management of common inpatient pediatric infections. ASP members met periodically with faculty and house staff to discuss guidelines and ways to improve prescribing. METHODS: Provider adherence with clinical inpatient practice guidelines, frequency of interventions suggested by ASP, and acceptance of interventions by providers were elements used to measure process change. We measured outcome data by analyzing antimicrobial utilization (defined as days of therapy) and length of therapy. RESULTS: Over a period of 2 years, institutional ASP guidelines were applicable to nearly half (44%) of all antimicrobial orders. Interventions were performed on 30% of all antimicrobial orders, of which 89% were accepted. Total antimicrobial days of therapy and length of therapy decreased significantly when comparing pre- and post-ASP. Overall, the susceptibility profiles of common bacterial pathogens to antibiotics remained stable. CONCLUSIONS: Pediatric ASPs within larger institutions have opportunities to create programs specific to the needs of the population they serve. We observed high rates of adherence by providers and a subsequent reduction in antibiotic utilization when implementing an audit feedback-based process.

Implementation and evaluation of an automated surveillance system to detect hospital outbreak.

BACKGROUND: The timely identification of a cluster is a critical requirement for infection prevention and control (IPC) departments because these events may represent transmission of pathogens within the health care setting. Given the issues with manual review of hospital infections, a surveillance system to detect clusters in health care settings must use automated data capture, validated statistical methods, and include all significant pathogens, antimicrobial susceptibility patterns, patient care locations, and health care teams. METHODS: We describe the use of SaTScan statistical software to identify clusters, WHONET software to manage microbiology laboratory data, and electronic health record data to create a comprehensive outbreak detection system in our hospital. We also evaluated the system using the Centers for Disease Control and Prevention's guidelines. RESULTS: During an 8-month surveillance time period, 168 clusters were detected, 45 of which met criteria for investigation, and 6 were considered transmission events. The system was felt to be flexible, timely, accepted by the department and hospital, useful, and sensitive, but it required significant resources and has a low positive predictive value. CONCLUSIONS: WHONET-SaTScan is a useful addition to a robust IPC program. Although the resources required were significant, this prospective, real-time cluster detection surveillance system represents an improvement over historical methods. We detected several episodes of transmission which would have eluded us previously, and allowed us to focus infection prevention efforts and improve patient safety.

Prior Staphylococcus Aureus Nasal Colonization: A Risk Factor for Surgical Site Infections Following Decolonization.

INTRODUCTION: Staphylococcus aureus (S aureus) decolonization regimens are being used to mitigate the risk of surgical site infection (SSI). However, their efficacy is controversial, with mixed results reported in the literature. METHODS: Before undergoing primary total knee arthroplasty (TKA), total hip arthroplasty (THA), or spinal fusion, 13,828 consecutive patients were screened for nasal S aureus and underwent a preoperative decolonization regimen. Infection rates of colonized and noncolonized patients were compared using unadjusted logistic regression. An adjusted regression analysis was performed to determine independent risk factors for SSI. RESULTS: The rate of SSI in colonized patients was 4.35% compared with only 2.39% in noncolonized patients. In our TKA cohort, unadjusted logistic regression identified S aureus colonization to be a significant risk factor for SSI (odds ratio [OR], 2.9; P < 0.001). After controlling for other potential confounders including age, body mass index, tobacco use, and American Society of Anesthesiologists score, an SSI was 3.8 times more likely to develop in patients colonized with S aureus (OR, 3.8; P = 0.0025). The THA and spine colonized patients trended toward higher risk in both unadjusted and adjusted models; however, the results were not statistically significant. DISCUSSION: The results of our study suggest that decolonization may not be fully protective against SSI. The risk of infection after decolonization is not lowered to the baseline of a noncolonized patient. LEVEL OF EVIDENCE: Level IV.

Comparison of two methods of documenting urinary and central venous catheters at an academic medical center.

Accurate documentation of the use of invasive devices, such as urinary and central line catheters, is important to track potential catheter-associated infections. Real-time identification of device infections allows practitioners to initiate timely apparent-cause analyses, therefore allowing rapid improvement of practice. For this reason, it was crucial to ensure our institution's mechanism to capture possible catheter-associated infections is validated after the adoption of a new electronic medical record system.