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Abstract Rationale It is unknown whether lactate monitoring aimed to decrease levels during initial treatment in critically ill patients improves outcome. Objectives To assess the effect of lactate monitoring and resuscitation directed at decreasing lactate levels in intensive care unit (ICU) patients admitted with a lactate level of greater than or equal to 3.0 mEq/L. Methods Patients were randomly allocated to two groups. In the lactate group, treatment was guided by lactate levels with the objective to decrease lactate by 20% or more per 2 hours for the initial 8 hours of ICU stay. In the control group, the treatment team had no knowledge of lactate levels (except for the admission value) during this period. The primary outcome measure was hospital mortality. Measurements and Main Results The lactate group received more fluids and vasodilators. However, there were no significant differences in lactate levels between the groups. In the intention-to-treat population (348 patients), hospital mortality in the control group was 43.5% (77/177) compared with 33.9% (58/171) in the lactate group (P = 0.067). When adjusted for predefined risk factors, hospital mortality was lower in the lactate group (hazard ratio, 0.61; 95% confidence interval, 0.43–0.87; P = 0.006). In the lactate group, Sequential Organ Failure Assessment scores were lower between 9 and 72 hours, inotropes could be stopped earlier, and patients could be weaned from mechanical ventilation and discharged from the ICU earlier. Conclusions In patients with hyperlactatemia on ICU admission, lactate-guided therapy significantly reduced hospital mortality when adjusting for predefined risk factors. As this was consistent with important secondary endpoints, this study suggests that initial lactate monitoring has clinical benefit. Clinical trial registered with www.clinicaltrials.gov (NCT00270673).

Purpose To illustrate the impact on the validity of trial results due to excluding patients from a randomized controlled trial for whom no deferred consent could be obtained after randomization because study procedures had already been finished. Methods The unadjusted and adjusted primary outcome measures of a recent randomized controlled multicentre study in the field of intensive care medicine were compared, including ( n  = 348) or excluding ( n  = 289) patients with missing deferred consent. Results Thirty-nine patients (11%) died early, before the patient or his/her proxy could be approached and consent be obtained. In another 20 patients (6%), it was not possible to inform proxies and ask consent within the period of study procedures. A significant treatment effect ( p  = 0.006) in the adjusted analysis became non-significant ( p  = 0.35) when the patients with missing deferred consent were excluded. Conclusions Exclusion of patients without obtained deferred consent can reduce statistical power, introduce selection bias, make randomization asymmetrical, decrease external validity and thereby jeopardize study results. This may have implications for emergency research in various disciplines.

PurposeQuantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [18F]DCFPyL PET metrics to predict metastatic disease or high-risk pathological tumor features.MethodsIn a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [18F]DCFPyL PET-CT. Primary tumors were delineated using 50–70% peak isocontour thresholds on images with and without partial-volume correction (PVC). Four hundred and eighty standardized radiomic features were extracted per tumor. Random forest models were trained to predict lymph node involvement (LNI), presence of any metastasis, Gleason score ≥ 8, and presence of extracapsular extension (ECE). For comparison, models were also trained using standard PET features (SUVs, volume, total PSMA uptake). Model performance was validated using 50 times repeated 5-fold cross-validation yielding the mean receiver-operator characteristic curve AUC.ResultsThe radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p < 0.01), nodal or distant metastasis (AUC 0.86 ± 0.14, p < 0.01), Gleason score (0.81 ± 0.16, p < 0.01), and ECE (0.76 ± 0.12, p < 0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance.ConclusionMachine learning-based analysis of quantitative [18F]DCFPyL PET metrics can predict LNI and high-risk pathological tumor features in primary PCa patients. These findings indicate that PSMA expression detected on PET is related to both primary tumor histopathology and metastatic tendency. Multicenter external validation is needed to determine the benefits of using radiomics versus standard PET metrics in clinical practice.

ObjectiveGout is characterised by severe interleukin (IL)-1-mediated joint inflammation induced by monosodium urate crystals. Since IL-37 is a pivotal anti-inflammatory cytokine suppressing the activity of IL-1, we conducted genetic and functional studies aimed at elucidating the role of IL-37 in the pathogenesis and treatment of gout.MethodsVariant identification was performed by DNA sequencing of all coding bases of IL37 using molecular inversion probe-based resequencing (discovery cohort: gout n=675, controls n=520) and TaqMan genotyping (validation cohort: gout n=2202, controls n=2295). Predictive modelling of the effects of rare variants on protein structure was followed by in vitro experiments evaluating the impact on protein function. Treatment with recombinant IL-37 was evaluated in vitro and in vivo in a mouse model of gout.ResultsWe identified four rare variants in IL37 in six of the discovery gout patients; p.(A144P), p.(G174Dfs*16), p.(C181*) and p.(N182S), whereas none emerged in healthy controls (Fisher’s exact p-value=0.043). All variants clustered in the functional domain of IL-37 in exon 5 (p-value=5.71×10−5). Predictive modelling and functional studies confirmed loss of anti-inflammatory functions and we substantiated the therapeutic potential of recombinant IL-37 in the treatment of gouty inflammation. Furthermore, the carrier status of p.(N182S)(rs752113534) was associated with increased risk (OR=1.81, p-value=0.031) of developing gout in hyperuricaemic individuals of Polynesian ancestry.ConclusionHere, we provide genetic as well as mechanistic evidence for the role of IL-37 in the pathogenesis of gout, and highlight the therapeutic potential of recombinant IL-37 for the treatment of gouty arthritis.

ObjectivesThe study of the proinflammatory role of uric acid has focused on the effects of its crystals of monosodium urate (MSU). However, little is known whether uric acid itself can directly have proinflammatory effects. In this study, we investigate the priming effects of uric acid exposure on the cytokine production of primary human cells upon stimulation with gout-related stimuli.MethodsPeripheral blood mononuclear cells (PBMCs) were harvested from patients with gout and healthy volunteers. Cells were pretreated with or without uric acid in soluble form for 24 h and then stimulated for 24 h with toll-like receptor (TLR)2 or TLR4 ligands in the presence or absence of MSU crystals. Cytokine production was measured by ELISA; mRNA levels were assessed using qPCR.ResultsThe production of interleukin (IL)-1β and IL-6 was higher in patients compared with controls and this correlated with serum urate levels. Proinflammatory cytokine production was significantly potentiated when cells from healthy subjects were pretreated with uric acid. Surprisingly, this was associated with a significant downregulation of the anti-inflammatory cytokine IL-1 receptor antagonist (IL-1Ra). This effect was specific to stimulation by uric acid and was exerted at the level of gene transcription. Epigenetic reprogramming at the level of histone methylation by uric acid was involved in this effect.ConclusionsIn this study we demonstrate a mechanism through which high concentrations of uric acid (up to 50 mg/dL) influence inflammatory responses by facilitating IL-1β production in PBMCs. We show that a mechanism for the amplification of IL-1β consists in the downregulation of IL-1Ra and that this effect could be exerted via epigenetic mechanisms such as histone methylation. Hyperuricaemia causes a shift in the IL-1β/IL-1Ra balance produced by PBMCs after exposure to MSU crystals and TLR-mediated stimuli, and this phenomenon is likely to reinforce the enhanced state of chronic inflammation.