Jose Manuel Ruiz-Giardín1, Rosa M Martin-Díaz2, Jerónimo Jaqueti-Aroca3, Isabel Garcia-Arata3, Juan Víctor San Martín-López2, Miguel Sáiz-Sánchez Buitrago4. 1. Internal Medicine Department, Fuenlabrada University Hospital, c/ Camino del Molino 2, Fuenlabrada, 28942 Madrid, Spain. Electronic address: josemanuel.ruiz@salud.madrid.org. 2. Internal Medicine Department, Fuenlabrada University Hospital, c/ Camino del Molino 2, Fuenlabrada, 28942 Madrid, Spain. 3. Microbiology Department, Fuenlabrada University Hospital, Fuenlabrada, Madrid, Spain. 4. 12 de Octubre University Hospital, Madrid, Spain.
Abstract
OBJECTIVE: The objective of this study was to predict the diagnosis of bacteraemia as a function of the time at which the automated BacT/Alert system continuously detects microorganism growth. METHODS: A retrospective study of a database of 1334 patients with a positive blood culture between January 2011 and June 2013 was conducted. Together with the final blood culture results and the patient's history, growth was then analysed to assess whether it represented true bacteraemia or bacterial contamination. The earliest detection times of bacterial growth in each batch of blood cultures were analysed in a blinded fashion after classification. RESULTS: In total, 590 batches of blood cultures corresponded to true bacteraemia and 744 to bacterial contamination. In the bacteraemia group, the median growth time was 12.72 h (interquartile range (IQR) 10.08-17.58 h). In the contaminated blood culture group, the median growth time was 20.6h (IQR 17.04-32.16 h) (p<0.001). Analysis of the receiver operating characteristics (ROC) curve (area under the curve 0.80, 95% confidence interval 0.771-0.826) showed that 90% of the contaminants grew after 14.7h (sensitivity 90.5%, specificity 63.4%, positive predictive value (PPV) 65.9%, negative predictive value (NPV) 90.7%). Forty-five percent of the bacteraemia organisms grew in under 12h (sensitivity 45.3%, specificity 95%, PPV 87.8%, NPV 68.7%). Microorganisms such as Candida sp and Bacteroides sp presented median growth times significantly longer than those of the other microorganisms. The administration of antibiotics in the week prior to bacteraemia was found to delay the growth time of microorganisms (p<0.001). CONCLUSIONS: Knowing the time to detection of microorganism growth can help to distinguish between true bacteraemia and bacterial contamination, thus allowing more timely clinical decisions to be made, before definitive microorganism identification.
OBJECTIVE: The objective of this study was to predict the diagnosis of bacteraemia as a function of the time at which the automated BacT/Alert system continuously detects microorganism growth. METHODS: A retrospective study of a database of 1334 patients with a positive blood culture between January 2011 and June 2013 was conducted. Together with the final blood culture results and the patient's history, growth was then analysed to assess whether it represented true bacteraemia or bacterial contamination. The earliest detection times of bacterial growth in each batch of blood cultures were analysed in a blinded fashion after classification. RESULTS: In total, 590 batches of blood cultures corresponded to true bacteraemia and 744 to bacterial contamination. In the bacteraemia group, the median growth time was 12.72 h (interquartile range (IQR) 10.08-17.58 h). In the contaminated blood culture group, the median growth time was 20.6h (IQR 17.04-32.16 h) (p<0.001). Analysis of the receiver operating characteristics (ROC) curve (area under the curve 0.80, 95% confidence interval 0.771-0.826) showed that 90% of the contaminants grew after 14.7h (sensitivity 90.5%, specificity 63.4%, positive predictive value (PPV) 65.9%, negative predictive value (NPV) 90.7%). Forty-five percent of the bacteraemia organisms grew in under 12h (sensitivity 45.3%, specificity 95%, PPV 87.8%, NPV 68.7%). Microorganisms such as Candida sp and Bacteroides sp presented median growth times significantly longer than those of the other microorganisms. The administration of antibiotics in the week prior to bacteraemia was found to delay the growth time of microorganisms (p<0.001). CONCLUSIONS: Knowing the time to detection of microorganism growth can help to distinguish between true bacteraemia and bacterial contamination, thus allowing more timely clinical decisions to be made, before definitive microorganism identification.
Authors: Thomas Rydzak; Ryan A Groves; Ruichuan Zhang; Raied Aburashed; Rajnigandha Pushpker; Maryam Mapar; Ian A Lewis Journal: Nat Commun Date: 2022-04-28 Impact factor: 17.694
Authors: Sandra Christina Burrack-Lange; Yoann Personne; Monika Huber; Elisabeth Winkler; Jan Weile; Cornelius Knabbe; Julia Görig; Holger Rohde Journal: J Med Microbiol Date: 2018-07-27 Impact factor: 2.472
Authors: A E Nieman; P H M Savelkoul; A Beishuizen; B Henrich; B Lamik; C R MacKenzie; D Kindgen-Milles; A Helmers; C Diaz; S G Sakka; R P Schade Journal: BMC Infect Dis Date: 2016-06-30 Impact factor: 3.090