Number of publications that reported on specific biomarkers (2010–2105).

<p>The counts in this figure represent the number of publications evaluating a specific host biomarker, regardless of specimen. Biomarker combinations are not represented in this graph. The multi-gene classifier studies screened >1000 host transcripts each, with a final data set of ranging from 10–52 host gene transcripts; however, for the purposes of this graph, a single count was entered for each multi-gene classifier study, regardless of the number of transcripts profiled.</p

Risk of Bias for 26 Quality Measures: Systematic Review (2010-April 2015).

<p>* Criteria that are specified by both QUADAS tool and Lijmer et al. (1999).</p

Blood cells and hematologic markers as clinical predictors of bacterial infections ranked by diagnostic performance: comprehensive review 2010–2015.

<p>Blood cells and hematologic markers as clinical predictors of bacterial infections ranked by diagnostic performance: comprehensive review 2010–2015.</p

Summary of high-performing host biomarkers with statistically significant findings.

<p>Summary of high-performing host biomarkers with statistically significant findings.</p

Cell surface markers evaluated as predictors of bacterial infection ranked by diagnostic parameters: comprehensive review 2010–2015.

<p>Cell surface markers evaluated as predictors of bacterial infection ranked by diagnostic parameters: comprehensive review 2010–2015.</p

PRISMA flow chart of study selection.

<p>(a) Includes Cochrane Database of Systematic Review, Science Daily, and free-text searches online. (b) Includes instances of: detection of a single type of pathogen, measures prognosis/severity, does not differentiate bacterial infection, prevalence studies, and detection of co-infections or cross-reactivity. (c) Study evaluation was limited solely to tick-born infections. (d) Assessed for additional relevant references.</p

Cytokine markers as clinical predictors of bacterial infections ranked by diagnostic performance: comprehensive review 2010–2015.

<p>Cytokine markers as clinical predictors of bacterial infections ranked by diagnostic performance: comprehensive review 2010–2015.</p

Inflammation markers as clinical predictors of bacterial infections ranked by diagnostic performance: comprehensive review 2010–2015.

<p>Inflammation markers as clinical predictors of bacterial infections ranked by diagnostic performance: comprehensive review 2010–2015.</p

Summary of multi-gene classifiers: comprehensive review 2010–2015.

<p>Summary of multi-gene classifiers: comprehensive review 2010–2015.</p

Evaluation of the Loop Mediated Isothermal DNA Amplification (LAMP) Kit for Malaria Diagnosis in <i>P. vivax</i> Endemic Settings of Colombia

<div><p>Background</p><p>Most commonly used malaria diagnostic tests, including microscopy and antigen-detecting rapid tests, cannot reliably detect low-density infections which are frequent in low transmission settings. Molecular methods such as polymerase chain reaction (PCR) are highly sensitive but remain too laborious for field deployment. In this study, the applicability of a malaria diagnosis kit based on loop-mediated isothermal amplification (mLAMP) was assessed in malaria endemic areas of Colombia with <i>Plasmodium vivax</i> predominance.</p><p>Methodology/Principal Findings</p><p>First, a passive case detection (PCD) study on 278 febrile patients recruited in Tierralta (department of Cordoba) was conducted to assess the diagnostic performance of the mLAMP method. Second, an active case detection (ACD) study on 980 volunteers was conducted in 10 sentinel sites with different epidemiological profiles. Whole blood samples were processed for microscopic and mLAMP diagnosis. Additionally RT-PCR and nested RT-PCR were used as reference tests. In the PCD study, <i>P. falciparum</i> accounted for 23.9% and <i>P. vivax</i> for 76.1% of the infections and no cases of mixed-infections were identified. Microscopy sensitivity for <i>P. falciparum</i> and <i>P. vivax</i> were 100% and 86.1%, respectively. mLAMP sensitivity for <i>P. falciparum</i> and <i>P. vivax</i> was 100% and 91.4%, respectively. In the ACD study, mLAMP detected 65 times more cases than microscopy. A high proportion (98.0%) of the infections detected by mLAMP was from volunteers without symptoms.</p><p>Conclusions/Significance</p><p>mLAMP sensitivity and specificity were comparable to RT-PCR. LAMP was significantly superior to microscopy and in <i>P. vivax</i> low-endemicity settings and under minimum infrastructure conditions, it displayed sensitivity and specificity similar to that of single-well RT-PCR for detection of both <i>P. falciparum</i> and <i>P. vivax</i> infections. Here, the dramatically increased detection of asymptomatic malaria infections by mLAMP demonstrates the usefulness of this new tool for diagnosis, surveillance, and screening in elimination strategies.</p></div