The coronavirus disease 2019 (COVID-19) created major disruptions at academic centers and healthcare systems globally. Clinical and Translational Science Awards (CTSA) fund hubs supported by the National Center for Advancing Translational Sciences provideinfrastructure and leadership for clinical and translational research at manysuch institutions.

We surveyed CTSA hubs and received responses from 94% of them regarding the impact of the pandemic and the processes employed for the protection of research personnel and participants with respect to the conduct of research, specifically for studies unrelated to COVID-19.

In this report, we describe the results of the survey findings in the context of the current understanding of disease transmission and mitigation techniques.

We reflect on common practices and provide recommendations regarding lessons learned that will be relevant to future pandemics, particularly with regards to staging the cessation and resumption of research activities with an aim to keep the workforce, research participants, and our communities safe in future pandemics.

The National Healthcare Safety Network surgical site infections risk models for hip (HPRO) and knee (KPRO) replacement are intended for case-mix adjustment when reporting surgical site infection rates across institutions, but they are not validated in external data sets

To evaluate the validity of HPRO and KPRO risk models and improvement in risk prediction with inclusion of information on morbid obesity and diabetes mellitus.

Retrospective cohort study.

A single-center cohort of 21,941 hip and knee replacement procedures performed between 2002 and 2009.

Discriminative ability was assessed using the concordance statistic (C statistic). Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit tests.

The discrimination of HPRO was good, with a C statistic of 0.695 for surgical site infections and 0.749 for prosthetic joint infections. The discrimination of KPRO was worse than that of HPRO, with a C statistic of 0.592 for surgical site infections and 0.675 for prosthetic joint infections. Adding morbid obesity and diabetes mellitus to the HPRO and KPRO risk models modestly improved discrimination. There was no significant evidence of miscalibration based on the Hosmer-Lemeshow tests, but calibration of HPRO models appeared to be better than that of the KPRO models.

HPRO performed better than the KPRO in predicting surgical site infections after hip and knee replacements. Both fared well in predicting prosthetic joint infections.

Infect Control Hosp Epidemiol 2014;35(11):1323–1329

To study a cluster of Mycobacterium wolinskyi surgical site infections (SSIs).

Observational and case-control study.

Academic hospital.

Subjects who developed SSIs with M. wolinskyi following cardiothoracic surgery.

Electronic surveillance was performed for case finding as well as electronic medical record review of infected cases. Surgical procedures were observed. Medical chart review was conducted to identify risk factors. A case-control study was performed to identify risk factors for infection; Fisher exact or Kruskal-Wallis tests were used for comparisons of proportions and medians, respectively. Patient isolates were studied using pulsed-field gel electrophoresis (PFGE). Environmental microbiologic sampling was performed in operating rooms, including high-volume water sampling.

Six definite cases of M. wolinskyi SSI following cardiothoracic surgery were identified during the outbreak period (October 1, 2008–September 30, 2011). Having cardiac surgery in operating room A was significantly associated with infection (odds ratio, 40; P = .0027). Observational investigation revealed a cold-air blaster exclusive to operating room A as well a microbially contaminated, self-contained water source used in heart-lung machines. The isolates were indistinguishable or closely related by PFGE. No environmental samples were positive for M. wolinskyi.

No single point source was established, but 2 potential sources, including a cold-air blaster and a microbially contaminated, self-contained water system used in heart-lung machines for cardiothoracic operations, were identified. Both of these potential sources were removed, and subsequent active surveillance did not reveal any further cases of M. wolinskyi SSI.

Infect Control Hosp Epidemiol 2014;35(9):1169-1175

The epidemiology of prosthetic joint infection (PJI) in a population-based cohort has not been studied in the United States.

To provide an accurate assessment of the true incidence, secular trends, clinical manifestations, microbiology, and treatment outcomes of PJI in a population-based cohort.

Historical cohort study.

Olmsted County, Minnesota.

Residents who underwent total knee arthroplasty (TKA) or total hip arthroplasty (THA) between January 1, 1969, and December 31, 2007.

Incidence rates and trends in PJI were assessed using the Kaplan-Meier method and log-rank test, as were treatment outcomes among PJI case patients.

A total of 7,375 THAs or TKAs were implanted in residents of Olmsted County during the study period. Seventy-five discrete joints in 70 individuals developed PJI, during a mean ± SD follow-up of 6.8 ± 6.1 years. The cumulative incidence of PJI was 0.5%, 0.8%, and 1.4% after 1, 5, and 10 years after arthroplasty, respectively. Overall, the rate of survival free of clinical failure after treatment of PJI was 76.8% (95% confidence interval [CI], 64.3–85.2) and 65.2% (95% CI, 33.1–76.2) at 3 and 5 years, respectively. The incidence and treatment outcomes did not significantly differ by decade of implantation, patient age at implantation, gender, or joint location.

The incidence of PJI is relatively low in a population-based cohort and is a function of age of the prosthesis. Incidence trends and outcomes have not significantly changed over the past 40 years.

The goal of this study was to develop a prognostic scoring system for the development of prosthetic joint infection (PJI) that could risk-stratify patients undergoing total hip (THA) or total knee (TKA) arthroplasties.

Previously reported case-control study.

Tertiary referral care setting from 2001 through 2006.

A derivation data set of 339 cases and 339 controls was used to develop 2 scores. A baseline score and a 1-month-postsurgery risk score were computed as a function of the relative contributions of risk factors for each model. Points were assigned for the presence of each factor and then summed to get a subject's risk score.

The following risk factors were detected from multivariable modeling and incorporated into the baseline Mayo PJI risk score: body mass index, prior other operation on the index joint, prior arthroplasty, immunosuppression, ASA score, and procedure duration (c index, 0.722). The 1-month-postsurgery risk score contained the same variables in addition to postoperative wound drainage (c index, 0.716).

The baseline score might help with risk stratification in relation to public reporting and reimbursement as well as targeted prevention strategies in patients undergoing THA or TKA. The application of the 1-month-postsurgery PJI risk score to patients undergoing THA or TKA might benefit those undergoing workup for PJI.