Saturday, September 01, 2012
Real-life 'Contagion' uses DNA to halt outbreak
Real-life 'Contagion' uses DNA to halt outbreak
August 2012
By Sharon Begley - Reuters
NEW YORK — If Hollywood needs a plot for a medical thriller, scientists at the National Institutes of Health have one: Doctors, using cutting-edge technology called whole-genome sequencing, trace an outbreak of a deadly bacterial infection, identify precisely how it's spreading - and in the final minutes sic poison-spewing robots on the rampaging microbes.
That's essentially what scientists did when Klebsiella pneumoniae, an often-lethal bacterium, spread through NIH's research hospital in Bethesda, Maryland last year, as described in a study published on Wednesday in the journal Science Translational Medicine.
"With whole-genome sequencing," said microbial geneticist Julie Segre of NIH's National Human Genome Research Institute, who led the study, "we were able to understand how the outbreak was moving through the hospital and identify weaknesses" in infection-control practices, finally halting the outbreak.
The unprecedented effort to use genome sequencing to save patients from an infectious outbreak offers hope that the technique could fight other hospital-acquired infections. These infections kill some 99,000 people die from such infections in the United States every year, estimates the U.S. Centers for Disease Control and Prevention. The added health-care costs, according to the CDC: $4.5 billion a year.
Calling it a "compelling story," virologist and microbe hunter Ian Lipkin of Columbia University in New York City said the NIH scientists' feat shows what ultra-fast whole-genome sequencing can accomplish in so-called microbial forensics. In whole-genome sequencing, machines identify the DNA units that make up an organism's entire genome.
Researchers were able "to implicate 'Patient Zero,' track transmission of a drug-resistant bacterium over the course of an important outbreak and provide insights that will inform infection control and patient care," said Lipkin, director of the Center for Infection and Immunity at Columbia's Mailman School of Public Health and a scientific adviser on the 2011 film "Contagion."
The outbreak at NIH's hospital began last summer. In June a 43-year-old patient with antibiotic-resistant K. pneumoniae, which infects the urinary tract and bloodstream and can cause sepsis, a blood infection, was transferred to its intensive-care unit from a New York City hospital. "Patient Zero" was put in an isolation room; staff and visitors had to wear gowns, masks and gloves to enter.
Labels: bacterial infection, bloodstream, DNA, genome sequencing, hospital-acquired infections, K. pneumonia, microbes, sepsis, urinary tract
# posted by Pat O'Connor @ 10:40 AM
Diagnostic methods in sepsis: the need of speed.
Diagnostic methods in sepsis: the need of speed.
August 2012
Source
Laboratory Specialist, Instituto de Química, Universidade de São Paulo, São Paulo, SP, Brazil.
Abstract
Keywords: Sepsis, methods, cytokines.
OBJECTIVE:
Sepsis is a common condition encountered in hospital environments. There is no effective treatment for sepsis, and it remains an important cause of death at intensive care units. This study aimed to discuss some methods that are available in clinics, and tests that have been recently developed for the diagnosis of sepsis.
METHODS:
A systematic review was performed through the analysis of the following descriptors: sepsis, diagnostic methods, biological markers, and cytokines.
RESULTS:
The deleterious effects of sepsis are caused by an imbalance between the invasiveness of the pathogen and the ability of the host to mount an effective immune response. Consequently, the host's immune surveillance fails to eliminate the pathogen, allowing it to spread. Moreover, there is a pro-inflammatory mediator release, inappropriate activation of the coagulation and complement cascades, leading to dysfunction of multiple organs and systems. The difficulty achieve total recovery of the patient is explainable. There is an increased incidence of sepsis worldwide due to factors such as aging population, larger number of surgeries, and number of microorganisms resistant to existing antibiotics.
CONCLUSION: The search for new diagnostic markers associated with increased risk of sepsis development and molecules that can be correlated to certain steps of sepsis is becoming necessary. This would allow for earlier diagnosis, facilitate patient prognosis characterization, and prediction of possible evolution of each case. All other markers are regrettably constrained to research units.
Labels: cytokines, diagnostic methods, immune surveillance, methods, sepsis, treatment
# posted by Pat O'Connor @ 8:57 AM
Thursday, April 26, 2007
Prediction of specific pathogens in patients with sepsis
Prediction of specific pathogens in patients with sepsis: evaluation of TREAT, a computerized decision support system.
J Antimicrob Chemother. 2007 Apr
Paul M, Nielsen AD, Goldberg E, Andreassen S, Tacconelli E, Almanasreh N, Frank U, Cauda R,
Leibovici L.
Department of Medicine E, Rabin Medical Center, Beilinson Campus, Petah-Tiqva 49100, Israel.
Background
Prediction of bacterial infections and their pathogens allows for early, directed investigation and treatment. We assessed the ability of TREAT, a computerized decision support system, to predict specific pathogens. Methods TREAT uses data available within the first few hours of infection presentation in a causal probabilistic network to predict sites of infection and specific pathogens. We included 3529 patients (920 with microbiologically documented infections) participating in the observational and interventional trials of the TREAT system in Israel, Germany and Italy.
Discriminatory performance of TREAT to predict individual pathogens was expressed by the AUC with 95% confidence intervals. Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit statistic. Results The AUCs for Gram-negative bacteria, including Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella spp. and Escherichia coli, ranged between 0.70 and 0.80 (all significant). Adequate calibration was demonstrated for any Gram-negative infection and individual bacteria, except for E. coli.
Discrimination and calibration were acceptable for Enterococcus spp. (AUC 0.71, 0.65-0.78), but not for Staphylococcus aureus (AUC 0.63, 0.55-0.71). The few infections caused by Candida spp. and Clostridium difficile were well predicted (AUCs 0.74, 0.54-0.95; and 0.94, 0.88-1.00, respectively). The coverage with TREAT's recommendation exceeded that observed with physicians' treatment for all pathogens, except Candida spp.
Conclusions TREAT predicted individual pathogens causing infection well. Prediction of S. aureus was inferior to that observed with other pathogens. TREAT can be used to triage patients by the risk for specific pathogens. The system's predictions enable it to prescribe appropriate antibiotic treatment prior to pathogen identification.
PMID: 17449883 [PubMed - as supplied by publisher]
J Antimicrob Chemother. 2007 Apr
Paul M, Nielsen AD, Goldberg E, Andreassen S, Tacconelli E, Almanasreh N, Frank U, Cauda R,
Leibovici L.
Department of Medicine E, Rabin Medical Center, Beilinson Campus, Petah-Tiqva 49100, Israel.
Background
Prediction of bacterial infections and their pathogens allows for early, directed investigation and treatment. We assessed the ability of TREAT, a computerized decision support system, to predict specific pathogens. Methods TREAT uses data available within the first few hours of infection presentation in a causal probabilistic network to predict sites of infection and specific pathogens. We included 3529 patients (920 with microbiologically documented infections) participating in the observational and interventional trials of the TREAT system in Israel, Germany and Italy.
Discriminatory performance of TREAT to predict individual pathogens was expressed by the AUC with 95% confidence intervals. Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit statistic. Results The AUCs for Gram-negative bacteria, including Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella spp. and Escherichia coli, ranged between 0.70 and 0.80 (all significant). Adequate calibration was demonstrated for any Gram-negative infection and individual bacteria, except for E. coli.
Discrimination and calibration were acceptable for Enterococcus spp. (AUC 0.71, 0.65-0.78), but not for Staphylococcus aureus (AUC 0.63, 0.55-0.71). The few infections caused by Candida spp. and Clostridium difficile were well predicted (AUCs 0.74, 0.54-0.95; and 0.94, 0.88-1.00, respectively). The coverage with TREAT's recommendation exceeded that observed with physicians' treatment for all pathogens, except Candida spp.
Conclusions TREAT predicted individual pathogens causing infection well. Prediction of S. aureus was inferior to that observed with other pathogens. TREAT can be used to triage patients by the risk for specific pathogens. The system's predictions enable it to prescribe appropriate antibiotic treatment prior to pathogen identification.
PMID: 17449883 [PubMed - as supplied by publisher]
Labels: Acinetobacter baumannii, escherichia coli, Klebsiella spp, Pseudomonas aeruginosa, sepsis, Staphylococcus aureus, TREAT
# posted by Pat O'Connor @ 1:22 PM
