Archive for September 22, 2012

Potential for false positive HIV test results with the serial rapid HIV testing algorithm.

BMC Res Notes. 2012 Mar 19  V.5  P.154.

Baveewo S, Kamya MR, Mayanja-Kizza H, Fatch R, Bangsberg DR, Coates T, Hahn JA, Wanyenze RK.

Department of Medicine, Makerere University School of Medicine, Kampala, Uganda. baveewosteven@yahoo.co.uk

Abstract

BACKGROUND:

Rapid HIV tests provide same-day results and are widely used in HIV testing programs in areas with limited personnel and laboratory infrastructure. The Uganda Ministry of Health currently recommends the serial rapid testing algorithm with Determine, STAT-PAK, and Uni-Gold for diagnosis of HIV infection. Using this algorithm, individuals who test positive on Determine, negative to STAT-PAK and positive to Uni-Gold are reported as HIV positive. We conducted further testing on this subgroup of samples using qualitative DNA PCR to assess the potential for false positive tests in this situation.

RESULTS:

Of the 3388 individuals who were tested, 984 were HIV positive on two consecutive tests, and 29 were considered positive by a tiebreaker (positive on Determine, negative on STAT-PAK, and positive on Uni-Gold). However, when the 29 samples were further tested using qualitative DNA PCR, 14 (48.2%) were HIV negative.

CONCLUSION:

Although this study was not primarily designed to assess the validity of rapid HIV tests and thus only a subset of the samples were retested, the findings show a potential for false positive HIV results in the subset of individuals who test positive when a tiebreaker test is used in serial testing. These findings highlight a need for confirmatory testing for this category of individuals.

PDF

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392728/pdf/1756-0500-5-154.pdf

September 22, 2012 at 8:49 am

Monte Carlo simulations: maximizing antibiotic pharmacokinetic data to optimize clinical practice for critically ill patients

Journal of Antimicrobial Chemotherapy Feb. 2011 V.66 N.2 P.227-231

Jason A. Roberts1,2,3, Carl M. J. Kirkpatrick4 and Jeffrey Lipman1,2,*

1Burns, Trauma and Critical Care Research Centre, The University of Queensland, Brisbane, Australia

2Department of Intensive Care, Royal Brisbane and Women’s Hospital, Brisbane, Australia

3Pharmacy Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia

4School of Pharmacy, The University of Queensland, Brisbane, Australia

Infections in critically ill patients continue to result in unacceptably high morbidity and mortality. Although few data exist for correlating antibiotic exposure with outcome, antibiotic dosing is likely to be highly important for maximizing resolution of infection in many patients. The practical and financial difficulties of performing pharmacokinetic (PK) studies in critically ill patients mean that analyses to maximize data such as Monte Carlo simulation (MCS) are highly valuable. MCS uses computer software to perform virtual clinical trials. The building blocks for MCS are: firstly, a robust population PK model from the patient population of interest; secondly, descriptors of the effect of covariates that influence the PK parameters; thirdly, description of the susceptibility of bacteria to the antibiotic and finally a PK/pharmacodynamic (PD) target associated with antibiotic efficacy. Probability of target attainment (PTA) outputs can then be generated that describe the proportion of patients that will achieve a pre-specified PD target for an MIC distribution. Such analyses can then inform dosing requirements, which can be used to have a high likelihood of achieving PK/PD targets for organisms with different MICs. In this issue of JAC, Zelenitsky et al. provide a very useful example of MCS for interpreting the optimal methods for dosing meropenem, piperacillin/tazobactam, cefepime and ceftobiprole in critically ill patients.

PDF

http://jac.oxfordjournals.org/content/66/2/227.full.pdf+html

September 22, 2012 at 8:48 am

The Pneumonia Severity Index: A Decade after the Initial Derivation and Validation

Clin Infect Dis.  2008  V.47  Suppl 3  S133-S139.

Drahomir Aujesky1 and Michael J. Fine3,3

1Division of General Internal Medicine, University of Lausanne, Lausanne, Switzerland

2Veterans Affairs Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, University of Pittsburgh, Pittsburgh, Pennsylvania

3Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania

The prognosis of community-acquired pneumonia ranges from rapid resolution of symptoms and full recovery of functional status to the development of severe medical complications and death. The pneumonia severity index is a rigorously studied prediction rule for prognosis that objectively stratifies patients into quintiles of risk for short-term mortality on the basis of 20 demographic and clinical variables routinely available at presentation. The pneumonia severity index was derived and validated with data on >50,000 patients with community-acquired pneumonia by use of well-accepted methodological standards and is the only pneumonia decision aid that has been empirically shown to safely increase the proportion of patients given treatment in the outpatient setting. Because of its prognostic accuracy, methodological rigor, and effectiveness and safety as a decision aid, the pneumonia severity index has become the reference standard for risk stratification of community-acquired pneumonia….

PDF

http://cid.oxfordjournals.org/content/47/Supplement_3/S133.full.pdf+html

September 22, 2012 at 8:47 am


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