scholarly journals A Risk Score for Fluconazole Failure among Patients with Candidemia

2017 ◽  
Vol 61 (5) ◽  
Author(s):  
Luis Ostrosky-Zeichner ◽  
Rachel Harrington ◽  
Nkechi Azie ◽  
Hongbo Yang ◽  
Nanxin Li ◽  
...  
Keyword(s):  
High Risk ◽  
Prediction Model ◽  
Positive Culture ◽  
The United States ◽  
Content Type ◽  
C Statistic ◽  
Lemeshow Test ◽  
Selection Operator ◽  
Risk Predictors ◽  
Antifungal Use

ABSTRACT This study aimed to develop a prediction model to identify patients with candidemia who were at high risk of failing fluconazole treatment. Adult patients in the United States with candidemia who received fluconazole during hospitalization were selected from the Cerner Health Facts Hospital Database (04/2004 to 03/2013). Fluconazole failure was defined as switching/adding another antifungal, positive Candida culture ≥10 days after fluconazole initiation, or death during hospitalization. Patients were randomized into modeling and validation samples. Using the modeling sample, a regression analysis of least absolute shrinkage and selection operator was used to select risk predictors of fluconazole failure (demographics, Candida species, initiation of fluconazole before positive culture and after admission, and comorbidities, procedures, and treatments during the 6 months before admission and fluconazole initiation). The prediction model was evaluated using the validation sample. We found that of 987 identified patients (average age of 61 years, 51% male, 72% Caucasian), 49% failed and 51% did not fail fluconazole treatment. Of those who failed, 70% switched or added another antifungal, 21% had a second positive Candida test, and 42% died during hospitalization. Nine risk factors were included in the prediction model: days to start fluconazole after admission, Candida glabrata or Candida krusei infection, hematological malignancy, venous thromboembolism (VTE), enteral nutrition, use of nonoperative intubation/irrigation, and other antifungal use. All but VTE were associated with a higher risk of failure. The model's c-statistic was 0.65, with a Hosmer-Lemeshow test P value of 0.23. In summary, this prediction model identified patients with a high risk of fluconazole failure, illustrating the potential value and feasibility of personalizing candidemia treatment.

VALIDATION AND COMPARISON OF TWO 30-DAY RE-ADMISSION PREDICTION MODELS IN PATIENTS WITH DIABETES

2019 ◽  
Vol 25 (11) ◽  
pp. 1151-1157
Author(s):  
Ahmad A. Alamer ◽  
Asad E. Patanwala ◽  
Ali M. Aldayyen ◽  
Maryam T. Fazel
Keyword(s):  
Confidence Interval ◽  
Predictive Performance ◽  
The United States ◽  
Brier Score ◽  
Risk Indicator ◽  
C Statistic ◽  
Tertiary Center ◽  
Lemeshow Test ◽  
Receiver Operating ◽  
Diabetes Patients

Objective: The objective was to evaluate the 30-day re-admission predictive performance of the HOSPITAL score and Diabetes Early Re-admission Risk Indicator (DERRI™) in hospitalized diabetes patients. Methods: This was a case-control study in an academic, tertiary center in the United States. Adult hospitalized diabetes patients were randomly identified between January 1, 2014, and September 30, 2017. Patients were categorized into two groups: ( 1) re-admitted within 30 days, and ( 2) not re-admitted within 30 days. Predictive performance of the HOSPITAL and DERRI™ scores was evaluated by calculating receiver operating characteristics curves (c-statistic), Hosmer-Lemeshow goodness-of-fit tests, and Brier scores. Results: A total of 200 patients were included (100 re-admitted, 100 non–re-admitted). The HOSPITAL score had a c-statistic of 0.731 (95% confidence interval [CI], 0.661 to 0.800), Hosmer-Lemeshow test P = .211, and Brier score 0.212. The DERRI™ score had a c-statistic of 0.796 (95% CI, 0.734 to 0.857), Hosmer-Lemeshow test P = .114, and Brier score 0.212. The difference in receiver operating characteristic curves was not statistically significant between the two scores but showed a higher c-statistic with the DERRI™ score ( P = .055). Conclusion: Both HOSPITAL and DERRI™ scores showed good predictive performance in 30-day re-admission of adult hospitalized diabetes patients. There was no significant difference in discrimination and calibration between the scores. Abbreviations: CI = confidence interval; DERRI™ = Diabetes Early Re-admission Risk Indicator; IQR = interquartile range

scholarly journals Genetic Determinants of Resistance to Extended-Spectrum Cephalosporin and Fluoroquinolone in Escherichia coli Isolated from Diseased Pigs in the United States

mSphere ◽  
2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Shivdeep Singh Hayer ◽  
Seunghyun Lim ◽  
Samuel Hong ◽  
Ehud Elnekave ◽  
Timothy Johnson ◽  
...  
Keyword(s):  
United States ◽  
Escherichia Coli ◽  
High Risk ◽  
The United States ◽  
Genetic Determinants ◽  
Content Type ◽  
E Coli ◽  
Extended Spectrum ◽  
Animal Populations ◽  
Swine Population

ABSTRACT Fluoroquinolones and cephalosporins are critically important antimicrobial classes for both human and veterinary medicine. We previously found a drastic increase in enrofloxacin resistance in clinical Escherichia coli isolates collected from diseased pigs from the United States over 10 years (2006 to 2016). However, the genetic determinants responsible for this increase have yet to be determined. The aim of the present study was to identify and characterize the genetic basis of resistance against fluoroquinolones (enrofloxacin) and extended-spectrum cephalosporins (ceftiofur) in swine E. coli isolates using whole-genome sequencing (WGS). blaCMY-2 (carried by IncA/C2, IncI1, and IncI2 plasmids), blaCTX-M (carried by IncF, IncHI2, and IncN plasmids), and blaSHV-12 (carried by IncHI2 plasmids) genes were present in 87 (82.1%), 19 (17.9%), and 3 (2.83%) of the 106 ceftiofur-resistant isolates, respectively. Of the 110 enrofloxacin-resistant isolates, 90 (81.8%) had chromosomal mutations in gyrA, gyrB, parA, and parC genes. Plasmid-mediated quinolone resistance genes [qnrB77, qnrB2, qnrS1, qnrS2, and aac-(6)-lb′-cr] borne on ColE, IncQ2, IncN, IncF, and IncHI2 plasmids were present in 24 (21.8%) of the enrofloxacin-resistant isolates. Virulent IncF plasmids present in swine E. coli isolates were highly similar to epidemic plasmids identified globally. High-risk E. coli clones, such as ST744, ST457, ST131, ST69, ST10, ST73, ST410, ST12, ST127, ST167, ST58, ST88, ST617, ST23, etc., were also found in the U.S. swine population. Additionally, the colistin resistance gene (mcr-9) was present in several isolates. This study adds valuable information regarding resistance to critical antimicrobials with implications for both animal and human health. IMPORTANCE Understanding the genetic mechanisms conferring resistance is critical to design informed control and preventive measures, particularly when involving critically important antimicrobial classes such as extended-spectrum cephalosporins and fluoroquinolones. The genetic determinants of extended-spectrum cephalosporin and fluoroquinolone resistance were highly diverse, with multiple plasmids, insertion sequences, and genes playing key roles in mediating resistance in swine Escherichia coli. Plasmids assembled in this study are known to be disseminated globally in both human and animal populations and environmental samples, and E. coli in pigs might be part of a global reservoir of key antimicrobial resistance (AMR) elements. Virulent plasmids found in this study have been shown to confer fitness advantages to pathogenic E. coli strains. The presence of international, high-risk zoonotic clones provides worrisome evidence that resistance in swine isolates may have indirect public health implications, and the swine population as a reservoir for these high-risk clones should be continuously monitored.

scholarly journals Emerging Antimicrobial-Resistant High-Risk Klebsiella pneumoniae Clones ST307 and ST147

2020 ◽  
Vol 64 (10) ◽  
Author(s):  
Gisele Peirano ◽  
Liang Chen ◽  
Barry N. Kreiswirth ◽  
Johann D. D. Pitout
Keyword(s):  
Public Health ◽  
High Risk ◽  
Klebsiella Pneumoniae ◽  
The United States ◽  
Medical Community ◽  
Global Public Health ◽  
African Countries ◽  
Content Type ◽  
Public Health Burden ◽  
Worldwide Distribution

ABSTRACT There is an enormous global public health burden due to antimicrobial-resistant (AMR) Klebsiella pneumoniae high-risk clones. K. pneumoniae ST307 and ST147 are recent additions to the family of successful clones in the species. Both clones likely emerged in Europe during the early to mid-1990s and, in a relatively short time, became prominent global pathogens, spreading to all continents (with the exception of Antarctica). ST307 and ST147 consist of multiple clades/clusters and are associated with various carbapenemases (i.e., KPCs, NDMs, OXA-48-like, and VIMs). ST307 is endemic in Italy, Colombia, the United States (Texas), and South Africa, while ST147 is endemic in India, Italy, Greece, and certain North African countries. Both clones have been introduced into regions of nonendemicity, leading to worldwide nosocomial outbreaks. Genomic studies showed ST307 and ST147 contain identical gyrA and parC mutations and likely obtained plasmids with blaCTX-M-15 during the early to mid-2000s, which aided in their global distribution. ST307 and ST147 then acquired plasmids with various carbapenemases during the late 2000s, establishing themselves as important AMR pathogens in certain regions. Both clones are likely underreported due to restricted detection methodologies. ST307 and ST147 have the ability to become major threats to public health due to their worldwide distribution, ability to cause serious infections, and association with AMR, including panresistance. The medical community at large, especially those concerned with antimicrobial resistance, should be aware of the looming threat posed by emerging AMR high-risk clones such as K. pneumoniae ST307 and ST147.

scholarly journals A Nomogram for Predicting Intraoperative Hemodynamic Instability in Patients With Pheochromocytoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Zhiqiang Zhang ◽  
Yunlin Ye ◽  
Jiajie Yu ◽  
Shufen Liao ◽  
Weibin Pan ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Clinical Effectiveness ◽  
Hemodynamic Instability ◽  
Calibration Plot ◽  
Surgical Removal ◽  
Lemeshow Test ◽  
Life Threatening ◽  
Selection Operator ◽  
Risk Predictors ◽  
Good Agreement

PurposeSurgical removal of pheochromocytoma (PCC), including open, laparoscopic, and robot-assisted adrenalectomy, is the cornerstone of therapy, which is associated with high risk of intraoperative and postoperative life-threatening complications due to intraoperative hemodynamic instability (IHD). This study aims to develop and validate a nomogram based on clinical characteristics as well as computed tomography (CT) features for the prediction of IHD in pheochromocytoma surgery.MethodsThe data from 112 patients with pheochromocytoma were collected at a single center between January 1, 2010, and December 31, 2019. Clinical and radiological features were selected with the least absolute shrinkage and selection operator regression analysis to predict IHD then constitute a nomogram. The performance of the nomogram was assessed in terms of discrimination, calibration, and clinical utility.ResultsAge, tumor shape, Mayo Adhesive Probability score, laterality, necrosis, body mass index, and surgical technique were identified as risk predictors of the presence of IHD. The nomogram was then developed using these seven variables. The model showed good discrimination with a C-index of 0.773 (95% CI, 0.683–0.862) and an area under the receiver operating characteristic curve (AUC) of 0.739 (95% CI, 0.642–0.837). The calibration plot suggested good agreement between predicted and actual probabilities. Besides, calibration was tested with the Hosmer–Lemeshow test (P = 0.961). The decision curve showed the clinical effectiveness of the nomogram.ConclusionsOur nomogram based on clinical and CT parameters could facilitate the treatment strategy according to assessment of the risk of IHD in patients with pheochromocytoma.

US policy moves create China openings in Latin America

2017 ◽  
Keyword(s):  
United States ◽  
Latin America ◽  
High Risk ◽  
Financial Institutions ◽  
The United States ◽  
Turn Of The Century ◽  
Economic Institutions ◽  
Trade Integration ◽  
Content Type ◽  
Trade Partner

Subject Chinese opportunities in Latin America. Significance US retrenchment from global economic institutions would create a vacuum that China is well-positioned to fill. In Latin America, this would accelerate trends underway since the turn of the century that have seen China eclipse the United States as the main trade partner and source of financing for several countries. The potential realignment would be greatest in the region’s traditional US allies and enthusiastic participants in US-led institutions: Chile, Colombia, Mexico and Peru. Impacts A less globally engaged United States creates an opportunity for China to promote its financial institutions and trade integration projects. China stands to gain the most in strategic terms in countries hitherto aligned with the United States. This appears propitious for a Chinese strategy of diversification of its ties away from high-risk settings such as Ecuador and Venezuela.

scholarly journals Immune Profiling To Predict Outcome of Clostridioides difficile Infection

mBio ◽  
2020 ◽  
Vol 11 (3) ◽  
Author(s):  
Mayuresh M. Abhyankar ◽  
Jennie Z. Ma ◽  
Kenneth W. Scully ◽  
Andrew J. Nafziger ◽  
Alyse L. Frisbee ◽  
...  
Keyword(s):  
Prediction Model ◽  
Risk Prediction ◽  
Mortality Risk ◽  
The United States ◽  
Host Bacterium ◽  
Clinical Parameters ◽  
Content Type ◽  
Clostridioides Difficile ◽  
Tnf Α ◽  
Immune Profiling

ABSTRACT There is a pressing need for biomarker-based models to predict mortality from and recurrence of Clostridioides difficile infection (CDI). Risk stratification would enable targeted interventions such as fecal microbiota transplant, antitoxin antibodies, and colectomy for those at highest risk. Because severity of CDI is associated with the immune response, we immune profiled patients at the time of diagnosis. The levels of 17 cytokines in plasma were measured in 341 CDI inpatients. The primary outcome of interest was 90-day mortality. Increased tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), C-C motif chemokine ligand 5 (CCL-5), suppression of tumorigenicity 2 receptor (sST-2), IL-8, and IL-15 predicted mortality by univariate analysis. After adjusting for demographics and clinical characteristics, the mortality risk (as indicated by the hazard ratio [HR]) was higher for patients in the top 25th percentile for TNF-α (HR = 8.35, P = 0.005) and IL-8 (HR = 4.45, P = 0.01) and lower for CCL-5 (HR = 0.18, P ≤ 0.008). A logistic regression risk prediction model was developed and had an area under the receiver operating characteristic curve (AUC) of 0.91 for 90-day mortality and 0.77 for 90-day recurrence. While limited by being single site and retrospective, our work resulted in a model with a substantially greater predictive ability than white blood cell count. In conclusion, immune profiling demonstrated differences between patients in their response to CDI, offering the promise for precision medicine individualized treatment. IMPORTANCE Clostridioides difficile infection is the most common health care-associated infection in the United States with more than 20% patients experiencing symptomatic recurrence. The complex nature of host-bacterium interactions makes it difficult to predict the course of the disease based solely on clinical parameters. In the present study, we built a robust prediction model using representative plasma biomarkers and clinical parameters for 90-day all-cause mortality. Risk prediction based on immune biomarkers and clinical variables may contribute to treatment selection for patients as well as provide insight into the role of immune system in C. difficile pathogenesis.

scholarly journals Development and validation of a risk score for the prediction of cardiovascular disease in living donor kidney transplant recipients

2020 ◽  
Author(s):  
Kenji Ueki ◽  
Akihiro Tsuchimoto ◽  
Yuta Matsukuma ◽  
Kaneyasu Nakagawa ◽  
Hiroaki Tsujikawa ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Prediction Model ◽  
Living Donor ◽  
Goodness Of Fit ◽  
Validation Cohort ◽  
University Hospital ◽  
Risk Scores ◽  
Derivation Cohort ◽  
C Statistic ◽  
Lemeshow Test

Abstract Background Cardiovascular disease (CVD) is a major cause of death in kidney transplant (KT) recipients. To improve their long-term survival, it is clinically important to estimate the risk of CVD after living donor KT via adequate pre-transplant CVD screening. Methods A derivation cohort containing 331 KT recipients underwent living donor KT at Kyushu University Hospital from January 2006 to December 2012. A prediction model was retrospectively developed and risk scores were investigated via a Cox proportional hazards regression model. The discrimination and calibration capacities of the prediction model were estimated via the c-statistic and the Hosmer–Lemeshow goodness of fit test. External validation was estimated via the same statistical methods by applying the model to a validation cohort of 300 KT recipients who underwent living donor KT at Tokyo Women’s Medical University Hospital. Results In the derivation cohort, 28 patients (8.5%) had CVD events during the observation period. Recipient age, CVD history, diabetic nephropathy, dialysis vintage, serum albumin and proteinuria at 12 months after KT were significant predictors of CVD. A prediction model consisting of integer risk scores demonstrated good discrimination (c-statistic 0.88) and goodness of fit (Hosmer–Lemeshow test P = 0.18). In a validation cohort, the model demonstrated moderate discrimination (c-statistic 0.77) and goodness of fit (Hosmer–Lemeshow test P = 0.15), suggesting external validity. Conclusions The above-described simple model for predicting CVD after living donor KT was accurate and useful in clinical situations.

Development and Testing of a Risk Assessment Model for Venous Thrombosis in Medical Inpatients: the Medical Inpatients and Thrombosis (MITH) Study Score

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 173-173
Author(s):  
Neil Zakai ◽  
Peter Callas ◽  
Allen Repp ◽  
Mary Cushman
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Risk Factor ◽  
High Risk ◽  
Venous Thrombosis ◽  
Medical Record ◽  
The United States ◽  
Assessment Model ◽  
C Statistic ◽  
Medical Inpatients

Abstract Abstract 173FN2 Introduction: Multiple government organizations (i.e. the Joint Commission in the United States and the National Institute for Health and Clinical Excellence in the United Kingdom) mandate venous thrombosis (VT) risk assessment for hospitalized patients and provision of VT prophylaxis, however there are no validated VT risk assessment models (RAM) available for use in medical inpatients. Methods: Between January 2002 and June 2009 all cases of VT complicating medical admissions were identified using ICD-9 codes and confirmed by medical record review at a 500 bed teaching hospital. Two controls without VT were frequency matched to each case by admission service (medicine, cardiology, and oncology) and admission year. VT required positive imaging or autopsy. Medical history, presenting conditions, and use of VT prophylaxis in cases and controls were assessed by chart review. Weighted logistic regression was used to calculate odds ratios (OR) and the Taylor series method for 95% confidence intervals (CI) accounting for VT prophylaxis use (both mechanical and pharmacologic). A RAM was developed using clinical judgment and sequentially adding risk factors into a multivariable model. A point value was assigned for each risk factor by dividing the b coefficients' by the lowest b coefficient value and rounding to the nearest integer. To validate the model, the 95% CI for the C-statistic was calculated using bootstrapping with 1000 replicate samples. Results: 299 cases of VT and 601 matched controls were reviewed. The rate of VT per 1000 admissions (95% CI) was 4.6 (3.9, 5.4). Table 1 presents the RAM with the point value for each risk factor. The c-statistic for the model was 0.73 (95% CI 0.70, 0.76). Using a cut-off of ≥2 points as high risk, 79% of cases and 39% of controls were classified as high risk. The probability of VT in the absence of VT prophylaxis for a score <2 was 1.5 (95% CI 1.0, 2.3) per 1000 admissions and for a score ≥2 was 8.8 (95% CI 4.1, 18.8) per 1000 admissions. To evaluate a score assessed by clinical characteristics only, we assessed a score with the same risk factors but removing platelet count and white cell count from the model. The C-statistic was 0.71 (95% CI 0.68, 0.74) and 74% of cases and 39% of controls were high risk. Stratification by admission service or admission to an intensive care unit did not affect interpretation of the results. Conclusion: We present an internally validated RAM that assesses the risk of VT complicating medical admission. The score is simple, relies only on information easily known at the time of admission, and could be incorporated into an electronic medical record. It will allow clinicians to assess VT risk at admission for medical inpatients and weigh the risks and benefits of pharmacologic VT prophylaxis. The RAM will enable further studies to determine optimal VT prevention strategies in medical inpatients. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Predicting Risk of Venous Thromboembolism in Multiple Myeloma: The Impede VTE Score

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 141-141
Author(s):  
Kristen M. Sanfilippo ◽  
Suhong Luo ◽  
Tzu-Fei Wang ◽  
Tanya Wildes ◽  
Joseph Mikhael ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Venous Thromboembolism ◽  
High Risk ◽  
Prediction Model ◽  
Risk Prediction ◽  
Risk Score ◽  
Research Funding ◽  
Risk Prediction Model ◽  
Low Risk ◽  
C Statistic

Abstract Introduction: Venous thromboembolism (VTE) is a common cause of morbidity and mortality among patients with multiple myeloma (MM). Thromboprophylaxis is a safe and effective way to decrease VTE in other high-risk populations. Current guidelines recommend use of thromboprophylaxis in MM patients at high-risk of VTE, but no validated model predicts VTE in MM. A risk prediction model for VTE in MM would allow for use of thromboprophylaxis in MM patients at high-risk of VTE while sparing those at low risk. Therefore, we sought to develop a risk prediction model for VTE in MM. Patients and Methods: Using a nationwide cohort of Veterans, we identified 4,448 patients diagnosed with MM between 1999 and 2014. We retrospectively followed patients for 180 days after start of MM chemotherapy. We identified candidate risk factors through literature review for inclusion into the time-to-event models. We used the methods of Fine and Gray to model time to VTE while accounting for the competing risk of (non-VTE) death. To minimize immortal time bias, all treatment variables were entered as time-varying variables. Using a backward, step-wise approach, we retained variables in the model with a p ≤ 0.05, or with a p < 0.50 with findings consistent with prior literature. Using beta coefficients, we developed a risk score by multiplying by a common factor and rounding to the nearest integer. The risk score for each patient was the sum of all scores for each predictor variable. We assessed model performance with Harrell's c-statistic and with the inverse probability of censoring weighting approach. Through bootstrap analysis, we validated the model internally. We carried out all statistical analyses using SAS version 9.4 (SAS Institute, Cary, NC). Results: The median time from MM diagnosis to start of treatment was 37 days. A total of 53 patients (5.7%) developed VTE within 6 months after start of MM-specific therapy. The mean time from chemotherapy start to VTE was 69 days, with 69% of VTE events occurring in the first 3 months of chemotherapy. The factors associated with VTE were combined to develop the IMPEDE VTE score (IMID 3 points, BMI 1 point, Pathologic fracture pelvis/femur 2 points, ESA 1 point, Dexamethasone (High-dose 4 points, Low-Dose 2 points)/Doxorubicin 2 points, Ethnicity/Race= Asian -3 points, history of VTE 3 points, Tunneled line/CVC 2 points) (Table 1). In addition, use of therapeutic anticoagulation (-5 points) with warfarin or low molecular weight heparin (LWMH) and use of prophylactic LMWH or aspirin (-2 points) were associated with a decreased risk of VTE. The model showed satisfactory discrimination in both the derivation cohort (Harrell's c-statistic = 0.66) and in the bootstrap validation, c-statistic = 0.65 (95% CI: 0.62 - 0.69). Using three risk groups, the incident rate of VTE with the first 6-months of starting chemotherapy was 3.1% for scores ≤ 3 (low-risk), 7.5% for a score of 4-6 (intermediate-risk), and 13.3% for patients with a score of ≥ 7 (high-risk). The risk of developing VTE within 6 months after starting chemotherapy was significantly higher for patients with intermediate- and high-risk scores compared to low-risk (Table 2). Conclusions and Relevance: We developed a risk prediction rule, IMPEDE VTE, which can identify patients with MM at high-risk of developing VTE after starting chemotherapy. IMPEDE VTE could guide clinicians in selecting patients for thromboprophylaxis in MM. Disclosures Sanfilippo: BMS/Pfizer: Speakers Bureau. Wang:Daiichi Sankyo: Consultancy, Other: Travel. Wildes:Janssen: Research Funding. Mikhael:Onyx, Celgene, Sanofi, AbbVie: Research Funding. Carson:Flatiron Health: Employment; Washington University in St. Louis: Employment; Roche: Consultancy.

scholarly journals Validation of Active Surveillance Testing for Clostridium difficile Colonization Using the cobas Cdiff Test

2018 ◽  
Vol 56 (4) ◽  
Author(s):  
Parul A. Patel ◽  
Donna M. Schora ◽  
Kamaljit Singh ◽  
Lance R. Peterson
Keyword(s):  
Clostridium Difficile ◽  
Active Surveillance ◽  
Positive Culture ◽  
The United States ◽  
Nucleic Acid Amplification ◽  
Hospital System ◽  
Content Type ◽  
Asymptomatic Patients ◽  
Toxigenic Culture ◽  
Active Surveillance Testing

ABSTRACT Clostridium difficile infection (CDI) is not declining in the United States. Nucleic acid amplification tests (NAAT) are used as part of active surveillance testing programs to prevent health care-associated infection. The objective of this study was to validate the cobas Cdiff Test on the cobas 4800 System (cobas) within a four-hospital system using prospectively collected perirectal swabs from asymptomatic patients at admission and during monthly intensive care unit (ICU) screening in an infection control CDI reduction program. Performance of the cobas was compared to that of toxigenic culture. Each positive cobas sample and the next following negative patient swab were cultured. The study design gave 273 samples processed by both cobas (137 positive and 136 negative) and culture (one negative swab was not cultured). Discrepant analysis was performed using a second NAAT, the Xpert C. difficile Epi test (Xpert). This strategy was compared to a medical record review for antibiotic receipt that would inhibit growth of C. difficile in colonic stool. None of the cobas-negative samples were culture positive. The cobas positive predictive value was 75.2% (95% confidence interval [CI], 66.9% to 82%) and positive percent agreement was 100% (95% CI, 96.0% to 100%). Overall agreement between cobas and direct toxigenic culture was 87.6% (95% CI, 83.1% to 91%). For the cobas-positive/culture-negative (discrepant) samples, 7 Xpert-positive samples were from patients receiving inhibitory antimicrobials; only 4 of 23 Xpert-negative samples received these agents ( P = 0.00006). Our results support use of the cobas as a reliable assay for an active surveillance testing program to detect asymptomatic carriers of toxigenic C. difficile .

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