{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T21:47:19Z","timestamp":1792014439283,"version":"4.4.0"},"reference-count":44,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T00:00:00Z","timestamp":1694908800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Antibiotics"],"abstract":"<jats:p>Enterobacteriaceae bacteremia, particularly when associated with antimicrobial resistance, can result in increased mortality, emphasizing the need for timely effective therapy. Clinical risk prediction models are promising tools, stratifying patients based on their risk of resistance due to ESBL and carbapenemase-producing Enterobacteriaceae in bloodstream infections (BSIs) and, thereby, improving therapeutic decisions. This systematic review and meta-analysis synthesized the literature on the performance of these models. Searches of PubMed and EMBASE led to the identification of 10 relevant studies with 6106 unique patient encounters. Nine studies concerned ESBL prediction, and one focused on the prediction of carbapenemases. For the two ESBL model derivation studies, the discrimination performance showed sensitivities of 53\u201385% and specificities of 93\u201395%. Among the four ESBL model derivation and validation studies, the sensitivities were 43\u201388%, and the specificities were 77\u201399%. The sensitivity and specificity for the subsequent external validation studies were 7\u201337% and 88\u201396%, respectively. For the three external validation studies, only two models were evaluated across multiple studies, with a pooled AUROC of 65\u201371%, with one study omitting the sensitivity\/specificity. Only two studies measured clinical utility through hypothetical therapy assessments. Given the limited evidence on their interventional application, it would be beneficial to further assess these or future models, to better understand their clinical utility and ensure their safe and impactful implementation.<\/jats:p>","DOI":"10.3390\/antibiotics12091452","type":"journal-article","created":{"date-parts":[[2023,9,17]],"date-time":"2023-09-17T06:36:45Z","timestamp":1694932605000},"page":"1452","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Predicting Extended-Spectrum Beta-Lactamase and Carbapenem Resistance in Enterobacteriaceae Bacteremia: A Diagnostic Model Systematic Review and Meta-Analysis"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4542-6203","authenticated-orcid":false,"given":"Tristan T.","family":"Timbrook","sequence":"first","affiliation":[{"name":"Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT 84112, USA"},{"name":"BioM\u00e9rieux, 69280 Marcy l\u2019Etoile, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2073-8493","authenticated-orcid":false,"given":"McKenna J.","family":"Fowler","sequence":"additional","affiliation":[{"name":"Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, UT 84112, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,17]]},"reference":[{"key":"ref_1","unstructured":"CDC (2019). Antibiotic Resistance Threats in the United States."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1016\/j.idc.2020.08.002","article-title":"Multidrug-Resistant Bacteria in the Community: An Update","volume":"34","author":"Paterson","year":"2020","journal-title":"Infect. Dis. Clin. N. Am."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Serweci\u0144ska, L. (2020). Antimicrobials and Antibiotic-Resistant Bacteria: A Risk to the Environment and to Public Health. Water, 12.","DOI":"10.3390\/w12123313"},{"key":"ref_4","first-page":"Doc05","article-title":"Antibiotic consumption and resistance of gram-negative pathogens (collateral damage)","volume":"6","author":"Cizman","year":"2018","journal-title":"GMS Infect. Dis."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/10410236.2014.943634","article-title":"Antibiotic resistance: A primer and call to action","volume":"30","author":"Smith","year":"2015","journal-title":"Health Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.cmi.2020.10.016","article-title":"Risk factors for carbapenem-resistant Gram-negative bacterial infections: A systematic review","volume":"27","author":"Giannella","year":"2021","journal-title":"Clin. Microbiol. Infect."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Lodise, T.P., Zhao, Q., Fahrbach, K., Gillard, P.J., and Martin, A. (2018). A systematic review of the association between delayed appropriate therapy and mortality among patients hospitalized with infections due to Klebsiella pneumoniae or Escherichia coli: How long is too long?. BMC Infect. Dis., 18.","DOI":"10.1186\/s12879-018-3524-8"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/s11908-022-00785-2","article-title":"Heil. No Crystal Ball? Using Risk Factors and Scoring Systems ot Predict Extended-Spectrum Beta-Lactamase Producing Enterobacterales (ESBL-E) and Carbapenem-Resistant Enterobacterales (CRE) Infections","volume":"24","author":"Li","year":"2022","journal-title":"Curr. Infect. Dis. Rep."},{"key":"ref_9","unstructured":"Andrews, S.R., Timbrook, T.T., Fisher, M.A., and Tritle, B.J. (2023, January 11\u201315). Evaluation of a Rapid Diagnostic Test and Scoring Tools for Predicting Ceftriaxone Resistance in Enterobacterales Bloodstream Infections. Proceedings of the IDWeek 2023, Boston, MA, USA."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1017\/ice.2016.292","article-title":"Clinical Risk Score for Prediction of Extended-Spectrum \u03b2-Lactamase-Producing Enterobacteriaceae in Bloodstream Isolates","volume":"38","author":"Augustine","year":"2017","journal-title":"Infect. Control Hosp. Epidemiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"ofaa278","DOI":"10.1093\/ofid\/ofaa278","article-title":"Minimizing Time to Optimal Antimicrobial Therapy for Enterobacteriaceae Bloodstream Infections: A Retrospective, Hypothetical Application of Predictive Scoring Tools vs Rapid Diagnostics Tests","volume":"7","author":"Cwengros","year":"2020","journal-title":"Open Forum Infect. Dis."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1093\/cid\/ciw425","article-title":"A Clinical Decision Tree to Predict Whether a Bacteremic Patient Is Infected with an Extended-Spectrum \u03b2-Lactamase-Producing Organism","volume":"63","author":"Goodman","year":"2016","journal-title":"Clin. Infect. Dis."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1017\/ice.2019.17","article-title":"A methodological comparison of risk scores versus decision trees for predicting drug-resistant infections: A case study using extended-spectrum beta-lactamase (ESBL) bacteremia","volume":"40","author":"Goodman","year":"2019","journal-title":"Infect. Control Hosp. Epidemiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1080\/23744235.2019.1705389","article-title":"An easy-to-use scoring system for predicting bacteraemia with third-generation cephalosporin-resistant Enterobacterales in a low-resistance setting","volume":"52","author":"Holmgren","year":"2020","journal-title":"Infect. Dis."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e6648","DOI":"10.1097\/MD.0000000000006648","article-title":"A simple scoring algorithm predicting extended-spectrum \u03b2-lactamase producers in adults with community-onset monomicrobial Enterobacteriaceae bacteremia: Matters of frequent emergency department users","volume":"96","author":"Lee","year":"2017","journal-title":"Medicine"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Madrid-Morales, J., Sharma, A., Reveles, K., Velez-Mejia, C., Hopkins, T., Yang, L., Walter, E., and Cadena, J. (2021). Validation of Available Extended-Spectrum-Beta-Lactamase Clinical Scoring Models in Predicting Drug Resistance in Patients with Enteric Gram-Negative Bacteremia Treated at South Texas Veterans Health Care System. Antimicrob. Agents Chemother., 65.","DOI":"10.1128\/AAC.02562-20"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3485","DOI":"10.1128\/AAC.00009-11","article-title":"Identifying patients harboring extended-spectrum-beta-lactamase-producing Enterobacteriaceae on hospital admission: Derivation and validation of a scoring system","volume":"55","author":"Tumbarello","year":"2011","journal-title":"Antimicrob. Agents Chemother."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"ofaa070","DOI":"10.1093\/ofid\/ofaa070","article-title":"Derivation of a Model to Guide Empiric Therapy for Carbapenem-Resistant Klebsiella pneumoniae Bloodstream Infection in an Endemic Area","volume":"7","author":"Weston","year":"2020","journal-title":"Open Forum Infect. Dis."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e45","DOI":"10.1164\/rccm.201908-1581ST","article-title":"Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America","volume":"200","author":"Metlay","year":"2019","journal-title":"Am. J. Respir. Crit. Care Med."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.jclinepi.2014.09.007","article-title":"External validation of new risk prediction models is infrequent and reveals worse prognostic discrimination","volume":"68","author":"Siontis","year":"2015","journal-title":"J. Clin. Epidemiol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.jclinepi.2014.06.018","article-title":"A new framework to enhance the interpretation of external validation studies of clinical prediction models","volume":"68","author":"Debray","year":"2015","journal-title":"J. Clin. Epidemiol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1093\/ckj\/sfaa188","article-title":"External validation of prognostic models: What, why, how, when and where?","volume":"14","author":"Ramspek","year":"2021","journal-title":"Clin. Kidney J."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1016\/S0895-4356(96)00236-3","article-title":"A simulation study of the number of events per variable in logistic regression analysis","volume":"49","author":"Peduzzi","year":"1996","journal-title":"J. Clin. Epidemiol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.jclinepi.2014.11.010","article-title":"Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD statement","volume":"68","author":"Collins","year":"2015","journal-title":"J. Clin. Epidemiol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1177\/09622802231151220","article-title":"Minimum sample size for developing a multivariable prediction model using multinomial logistic regression","volume":"32","author":"Pate","year":"2023","journal-title":"Stat. Methods Med. Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.jclinepi.2021.02.011","article-title":"External validation of clinical prediction models: Simulation-based sample size calculations were more reliable than rules-of-thumb","volume":"135","author":"Snell","year":"2021","journal-title":"J. Clin. Epidemiol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1925","DOI":"10.1093\/eurheartj\/ehu207","article-title":"Towards better clinical prediction models: Seven steps for development and an ABCD for validation","volume":"35","author":"Steyerberg","year":"2014","journal-title":"Eur. Heart J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Haimerl, B.J., Encinas, R., Justo, J.A., Kohn, J., Bookstaver, P.B., Winders, H.R., and Al-Hasan, M.N. (2023). Optimization of Empirical Antimicrobial Therapy in Enterobacterales Bloodstream Infection Using the Extended-Spectrum Beta-Lactamase Prediction Score. Antibiotics, 12.","DOI":"10.3390\/antibiotics12061003"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Pogue, J.M., and Heil, E.L. (2020). The Clinical Impact of a Negative Molecular beta-Lactamase Gene Test for Enterobacteriaceae: Let\u2019s Not Let Perfect Be the Enemy of Really Good. J. Clin. Microbiol., 58.","DOI":"10.1128\/JCM.02098-19"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Pogue, J.M., Heil, E.L., Lephart, P., Johnson, J.K., Mynatt, R.P., Salimnia, H., and Claeys, K.C. (2018). An Antibiotic Stewardship Program Blueprint for Optimizing Verigene BC-GN within an Institution: A Tale of Two Cities. Antimicrob. Agents Chemother., 62.","DOI":"10.1128\/AAC.02538-17"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Tamma, P.D., Aitken, S.L., Bonomo, R.A., Mathers, A.J., van Duin, D., and Clancy, C.J. (2023). Infectious Diseases Society of America 2023 Guidance on the Treatment of Antimicrobial Resistant Gram-Negative Infections. Clin. Infect. Dis., ciad428.","DOI":"10.1093\/cid\/ciad428"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3324","DOI":"10.1128\/JCM.01479-12","article-title":"Identification of blood culture isolates directly from positive blood cultures by use of matrix-assisted laser desorption ionization-time of flight mass spectrometry and a commercial extraction system: Analysis of performance, cost, and turnaround time","volume":"50","author":"Adam","year":"2012","journal-title":"J. Clin. Microbiol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1111\/1469-0691.12640","article-title":"Rapid identification of microorganisms from positive blood cultures by MALDI-TOF mass spectrometry subsequent to very short-term incubation on solid medium","volume":"20","author":"Idelevich","year":"2014","journal-title":"Clin. Microbiol. Infect."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"108.e1","DOI":"10.1016\/j.cmi.2018.03.029","article-title":"Decision-support models for empiric antibiotic selection in Gram-negative bloodstream infections","volume":"25","author":"MacFadden","year":"2019","journal-title":"Clin. Microbiol. Infect."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Lodise, T.P., Bonine, N.G., Ye, J.M., Folse, H.J., and Gillard, P. (2019). Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections. BMC Infect. Dis., 19.","DOI":"10.1186\/s12879-019-4363-y"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"W1","DOI":"10.7326\/M14-0698","article-title":"Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): Explanation and elaboration","volume":"162","author":"Moons","year":"2015","journal-title":"Ann. Intern. Med."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"W1","DOI":"10.7326\/M18-1377","article-title":"PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration","volume":"170","author":"Moons","year":"2019","journal-title":"Ann. Intern. Med."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1097\/EDE.0b013e3181c30fb2","article-title":"Assessing the performance of prediction models: A framework for traditional and novel measures","volume":"21","author":"Steyerberg","year":"2010","journal-title":"Epidemiology"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1136\/heartjnl-2011-301247","article-title":"Risk prediction models: II. External validation, model updating, and impact assessment","volume":"98","author":"Moons","year":"2012","journal-title":"Heart"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e073538","DOI":"10.1136\/bmj-2022-073538","article-title":"Transparent reporting of multivariable prediction models for individual prognosis or diagnosis: Checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)","volume":"381","author":"Snell","year":"2023","journal-title":"BMJ"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Moons, K.G., de Groot, J.A., Bouwmeester, W., Vergouwe, Y., Mallett, S., Altman, D.G., Reitsma, J.B., and Collins, G.S. (2014). Critical appraisal and data extraction for systematic reviews of prediction modelling studies: The CHARMS checklist. PLoS Med., 11.","DOI":"10.1371\/journal.pmed.1001744"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Schardt, C., Adams, M.B., Owens, T., Keitz, S., and Fontelo, P. (2007). Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med. Inform. Decis. Mak., 7.","DOI":"10.1186\/1472-6947-7-16"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.cmi.2022.07.019","article-title":"How to conduct a systematic review and meta-analysis of prognostic model studies","volume":"29","author":"Damen","year":"2023","journal-title":"Clin. Microbiol. Infect."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v036.i03","article-title":"Conducting Meta-Analyses inRwith themetaforPackage","volume":"36","author":"Viechtbauer","year":"2010","journal-title":"J. Stat. Softw."}],"container-title":["Antibiotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2079-6382\/12\/9\/1452\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:52:32Z","timestamp":1760129552000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2079-6382\/12\/9\/1452"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,17]]},"references-count":44,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2023,9]]}},"alternative-id":["antibiotics12091452"],"URL":"https:\/\/doi.org\/10.3390\/antibiotics12091452","relation":{},"ISSN":["2079-6382"],"issn-type":[{"value":"2079-6382","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,17]]}}}