(a) Mean Z-scores for the time-weighted averages of galactomannan and beta-D-glucan composite values, and (b) time-weighted averages for beta-D-glucan values, galactomannan values, and galactomannan optical density index, in responders vs non-responders at week 6 and week 12.

<p>GM: Galactomannan, BDG: Beta-D-Glucan, GMI: Galactomannan Optical Density Index, W: Week, R: Responder, NR: Non-responder, N: Number, CI: Confidence Interval.</p><p>^<b>a</b> Some patients did not have data available for both biomarkers throughout the study; therefore, the numbers of patients with BDG, GM and/or GMI at weeks 2 and 6 differ from the total number of patients in the BDG and GM column.</p><p>(a) Mean Z-scores for the time-weighted averages of galactomannan and beta-D-glucan composite values, and (b) time-weighted averages for beta-D-glucan values, galactomannan values, and galactomannan optical density index, in responders vs non-responders at week 6 and week 12.</p

Association of galactomannan assay optical density index (GMI) as a dichotomous variable (positive [GMI ≥ 0.5] vs negative) between baseline and week 2 of treatment with clinical response and survival at 6 and 12 weeks.

<p>GMI: Galactomannan Optical Density Index, OR: Odds Ratio, CI: Confidence Interval</p><p>^a Clinical response: complete or partial response, as described in Methods [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129022#pone.0129022.ref005" target="_blank">5</a>].</p><p>^b Only one patient had positive GMI at baseline and negative GMI by week 2, so this category (+/-) was not included in the analysis.</p><p>^c Due to low number of observations, there was lack of model convergence and no results were generated.</p><p>Association of galactomannan assay optical density index (GMI) as a dichotomous variable (positive [GMI ≥ 0.5] vs negative) between baseline and week 2 of treatment with clinical response and survival at 6 and 12 weeks.</p

Correlation between Circulating Fungal Biomarkers and Clinical Outcome in Invasive Aspergillosis

<div><p>Objective means are needed to predict and assess clinical response in patients treated for invasive aspergillosis (IA). We examined whether early changes in serum galactomannan (GM) and/or β-D-glucan (BDG) can predict clinical outcomes. Patients with proven or probable IA were prospectively enrolled, and serial GM and BDG levels and GM optical density indices (GMI) were calculated twice weekly for 6 weeks following initiation of standard-of-care antifungal therapy. Changes in these biomarkers during the first 2 and 6 weeks of treatment were analyzed for associations with clinical response and survival at weeks 6 and 12. Among 47 patients with IA, 53.2% (25/47) and 65.9% (27/41) had clinical response by weeks 6 and 12, respectively. Changes in biomarkers during the first 2 weeks were associated with clinical response at 6 weeks (GMI, <i>P</i> = 0.03) and 12 weeks (GM+BDG composite, <i>P</i> = 0.05; GM, <i>P</i> = 0.04; GMI, <i>P</i> = 0.02). Changes in biomarkers during the first 6 weeks were also associated with clinical response at 6 weeks (GM, <i>P</i> = 0.05; GMI, <i>P</i> = 0.03) and 12 weeks (BDG+GM, <i>P</i> = 0.02; GM, <i>P</i> = 0.02; GMI, <i>P</i> = 0.01). Overall survival rates at 6 weeks and 12 weeks were 87.2% (41/47) and 79.1% (34/43), respectively. Decreasing biomarkers in the first 2 weeks were associated with survival at 6 weeks (BDG+GM, <i>P</i> = 0.03; BDG, <i>P</i> = 0.01; GM, <i>P</i> = 0.03) and at 12 weeks (BDG+GM, <i>P</i> = 0.01; BDG, <i>P</i> = 0.03; GM, <i>P</i> = 0.01; GMI, <i>P</i> = 0.007). Similar correlations occurred for biomarkers measured over 6 weeks. Patients with negative baseline GMI and/or persistently negative GMI during the first 2 weeks were more likely to have CR and survival. These results suggest that changes of biomarkers may be informative to predict and/or assess response to therapy and survival in patients treated for IA.</p></div

Patient baseline characteristics.

<p>IA: Invasive Aspergillosis, GMI: Galactomannan Optical Density Index, BDG: β-D-glucan.</p><p>^aUnderlying disease, comorbidities, and microbiologic diagnostic tests were not mutually exclusive.</p><p>^bAdministration of corticosteroids (0.3 mg/kg/day of prednisone equivalent) for a minimum of 3 weeks prior to enrollment.</p><p>^cFour patients with proven IA had a positive culture for <i>Aspergillus</i> species: 3 from normally sterile sites and 1 from a sputum/bronchoalveolar lavage culture.</p><p>^dPatients with positive GM and BDG as tested at the institutions they were enrolled at are included in this Table. Some of them had negative GM and BDG when tested at the central laboratory for the purposes of this study.</p><p>^eOne patient had both sinusitis and lower tract respiratory involvement.</p><p>^fSix and 2 patients were treated with liposomal amphotericin B and amphotericin B deoxycholate, respectively.</p><p>^gOne patient was treated with fluconazole alone and the other patient received blinded treatment with a mould acting agent as part of a clinical trial.</p><p>^hPatients received more than one agent concomitantly: echinocandin and voriconazole (n = 2), echinocandin and amphotericin B deoxycholate (n = 1), and voriconazole and amphotericin B deoxycholate (n = 1).</p><p>Patient baseline characteristics.</p

Image_1_Frequency and impact on renal transplant outcomes of urinary tract infections due to extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species.TIF

BackgroundEnterobacterales are often responsible for urinary tract infection (UTI) in kidney transplant recipients. Among these, Escherichia coli or Klebsiella species producing extended-spectrum beta-lactamase (ESBL) are emerging. However, there are only scarce data on frequency and impact of ESBL-UTI on transplant outcomes.MethodsWe investigated frequency and impact of first-year UTI events with ESBL Escherichia coli and/or Klebsiella species in a prospective multicenter cohort consisting of 1,482 kidney transplants performed between 2012 and 2017, focusing only on 389 kidney transplants having at least one UTI with Escherichia coli and/or Klebsiella species. The cohort had a median follow-up of four years.ResultsIn total, 139/825 (17%) first-year UTI events in 69/389 (18%) transplant recipients were caused by ESBL-producing strains. Both UTI phenotypes and proportion among all UTI events over time were not different compared with UTI caused by non-ESBL-producing strains. However, hospitalizations in UTI with ESBL-producing strains were more often observed (39% versus 26%, p = 0.04). Transplant recipients with first-year UTI events with an ESBL-producing strain had more frequently recurrent UTI (33% versus 18%, p = 0.02) but there was no significant difference in one-year kidney function as well as longer-term graft and patient survival between patients with and without ESBL-UTI.ConclusionFirst-year UTI events with ESBL-producing Escherichia coli and/or Klebsiella species are associated with a higher need for hospitalization but do neither impact allograft function nor allograft and patient survival.</p

Synopsis of novel HBV MHR mutations (n = 62) identified in four continental populations and their prevalence in various HBV genotypes.

<p>Mutations in the “a” determinant region are in italics, those in its flanking regions are highlighted <b>bold</b>.</p

Frequencies of 62 novel HBsAg MHR mutations (aa 99–170) in various HBV genotypes.

<p>Frequencies are defined as the percentage of patients carrying a novel mutation in a given HBV genotype.</p

Localization of the 62 novel amino acid exchanges within the HBsAg MHR (aa 99–170).

<p>Novel mutations are color coded to show their relative frequency (yellow, green, red). The “a” determinant region, composed of loop 1 (aa124-137) and loop 2 (aa139-147), is boxed. The start and end of the MHR are highlighted by blue arrows. Numbered balls designate cytosine amino acid residues.</p

Continental distribution of HBV genotypes.

<p>The predominant genotypes are highlighted for each (sub)continent.</p

Global distribution of the novel HBsAg MHR mutations.

<p>The relative contribution (%, dark green sectors) to the total pool of 62 novel mutations is shown for all countries in which previously unknown mutants were identified (n = 14). Note that individual percentages do not add up to 100% because various countries share mutations. For more details see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172101#pone.0172101.s012" target="_blank">S10</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172101#pone.0172101.s013" target="_blank">S11</a> Tables.</p