Sleep and Circadian Health of Critical Survivors: A 12-Month Follow-Up Study.

OBJECTIVES: To investigate the sleep and circadian health of critical survivors 12 months after hospital discharge and to evaluate a possible effect of the severity of the disease within this context. DESIGN: Observational, prospective study. SETTING: Single-center study. PATIENTS: Two hundred sixty patients admitted to the ICU due to severe acute respiratory syndrome coronavirus 2 infection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The cohort was composed of 260 patients (69.2% males), with a median (quartile 1-quartile 3) age of 61.5 years (52.0-67.0 yr). The median length of ICU stay was 11.0 days (6.00-21.8 d), where 56.2% of the patients required invasive mechanical ventilation (IMV). The Pittsburgh Sleep Quality Index (PSQI) revealed that 43.1% of the cohort presented poor sleep quality 12 months after hospital discharge. Actigraphy data indicated an influence of the disease severity on the fragmentation of the circadian rest-activity rhythm at the 3- and 6-month follow-ups, which was no longer significant in the long term. Still, the length of the ICU stay and the duration of IMV predicted a higher fragmentation of the rhythm at the 12-month follow-up with effect sizes (95% CI) of 0.248 (0.078-0.418) and 0.182 (0.005-0.359), respectively. Relevant associations between the PSQI and the Hospital Anxiety and Depression Scale (rho = 0.55, anxiety; rho = 0.5, depression) as well as between the fragmentation of the rhythm and the diffusing lung capacity for carbon monoxide (rho = -0.35) were observed at this time point. CONCLUSIONS: Our findings reveal a great prevalence of critical survivors presenting poor sleep quality 12 months after hospital discharge. Actigraphy data indicated the persistence of circadian alterations and a possible impact of the disease severity on the fragmentation of the circadian rest-activity rhythm, which was attenuated at the 12-month follow-up. This altogether highlights the relevance of considering the sleep and circadian health of critical survivors in the long term.

Artificial nighttime lighting impacts Plasmodium falciparum mature stage V gametocytes infectivity in Anopheles stephensi.

BACKGROUND: Malaria is one of the most important vector-borne diseases of humans with an estimated 241 million cases worldwide in 2020. As an urban and periurban mosquito species, Anopheles stephensi is exposed to artificial human stimuli like light that can alter many aspects of mosquito behaviour, physiology and metabolism. Therefore, fluctuations in the light environment may influence the host, parasite and/or mosquito biology and hence modulate risk for disease transmission. In this study, the effect of artifitial light at night on mosquito infectivity by Plasmodium falciparum during the first hours of blood digestion was tested. METHODS: A total of three independent standard membrane feeding assays were performed to artificially fed septic and aseptic mosquitoes with P. falciparum infected blood. After blood feeding, females were transferred to incubators with different photoperiod cycles, so digestion occurred under day artificial light or dark. At 7 and 16 days post blood feeding, mosquitoes were dissected for midguts and salivary glands, respectively. Percentage of mosquitoes fed, percentage of prevalence and P. falciparum oocyst intensity between septic and aseptic mosquitoes in the two different photoperiod regimes, were compared using a Kruskal-Wallis test followed by a Dunn´s multiple comparison test . RESULTS: The exposition of mosquitoes to light after they took an infected blood meal has a negative effect on the successful progression of P. falciparum in the mosquito midgut. Antibiotic treatment significantly incremented the number of oocysts per midgut. Photophase significantly reduced the median oocyst intensity in both septic and aseptic mosquitoes. The percentage of oocyst reduction, understood as the percentage of reduction in the mean oocyst intensity of the parasite in the mosquito midgut between photophase and scotophase, was 51% in the case of aseptic mosquitoes and 80% for septic mosquitoes, both in the photophase condition. CONCLUSION: Although there are still many gaps in the understanding of parasite-mosquito interactions, these results support the idea that light can, not only, influence mosquito biting behaviour but also parasite success in the mosquito midgut. Hence, light can be considered an interesting additional mosquito-control strategy to reduce mosquito-borne diseases.

Navigating the path of reproducibility in microRNA-based biomarker research with ring trials.

The development of microRNA (miRNA)-based biomarkers has gained significant attention due to their potential diagnostic, prognostic and therapeutic applications. However, the reproducibility of miRNA biomarker research faces unique challenges, primarily due to the influence of pre-analytical and analytical factors. The absence of standardized procedures contributes to inconsistencies across studies, alongside challenges in reference gene selection, data analysis methods and miRNA profiling platforms. Inter-laboratory comparison trials, or ring trials, offer a strategic approach to address technical and biological variability in miRNA biomarker studies. These trials promote standardization, identify sources of variability and strengthen the correlation between miRNAs and clinical outcomes. Despite their underutilization in miRNA biomarker research, ring trials represent a valuable tool for enhancing reproducibility and expediting the translation of miRNA-based biomarkers into clinical applications.

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Fast Coincidence Filter for Silicon Photomultiplier Dark Count Rate Rejection.

Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tube signals serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering the Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as a trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method, is presented.

Development of circulating microRNA-based biomarkers for medical decision-making: a friendly reminder of what should NOT be done.

Circulating cell-free microRNAs (miRNAs) represent a major reservoir for biomarker discovery. Unfortunately, their implementation in clinical practice is limited due to a profound lack of reproducibility. The great technical variability linked to major pre-analytical and analytical caveats makes the interpretation of circulating cell-free miRNA data challenging and leads to inconsistent findings. Additional efforts directed to standardization are fundamental. Several well-established protocols are currently used by independent groups worldwide. Nonetheless, there are some specific aspects in specimen collection and processing, sample handling, miRNA quantification, and data analysis that should be considered to ensure reproducibility of results. Here, we have addressed this challenge using an alternative approach. We have highlighted and discussed common pitfalls that negatively impact the robustness of circulating miRNA quantification and their application for clinical decision-making. Furthermore, we provide a checklist usable by investigators to facilitate and ensure the control of the whole miRNA quantification and analytical process. We expect that these recommendations improve the reproducibility of findings, and ultimately, facilitate the incorporation of circulating miRNA profiles into clinical practice as the next generation of disease biomarkers.

Circulating miR-133a-3p defines a low-risk subphenotype in patients with heart failure and central sleep apnea: a decision tree machine learning approach.

BACKGROUND: Patients with heart failure with reduced ejection fraction (HFrEF) and central sleep apnea (CSA) are at a very high risk of fatal outcomes. OBJECTIVE: To test whether the circulating miRNome provides additional information for risk stratification on top of clinical predictors in patients with HFrEF and CSA. METHODS: The study included patients with HFrEF and CSA from the SERVE-HF trial. A three-step protocol was applied: microRNA (miRNA) screening (n = 20), technical validation (n = 60), and biological validation (n = 587). The primary outcome was either death from any cause, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening of heart failure, whatever occurred first. MiRNA quantification was performed in plasma samples using miRNA sequencing and RT-qPCR. RESULTS: Circulating miR-133a-3p levels were inversely associated with the primary study outcome. Nonetheless, miR-133a-3p did not improve a previously established clinical prognostic model in terms of discrimination or reclassification. A customized regression tree model constructed using the Classification and Regression Tree (CART) algorithm identified eight patient subphenotypes with specific risk patterns based on clinical and molecular characteristics. MiR-133a-3p entered the regression tree defining the group at the lowest risk; patients with log(NT-proBNP) ≤ 6 pg/mL (miR-133a-3p levels above 1.5 arbitrary units). The overall predictive capacity of suffering the event was highly stable over the follow-up (from 0.735 to 0.767). CONCLUSIONS: The combination of clinical information, circulating miRNAs, and decision tree learning allows the identification of specific risk subphenotypes in patients with HFrEF and CSA.

Cardiovascular complications of diabetes: role of non-coding RNAs in the crosstalk between immune and cardiovascular systems.

Diabetes mellitus, a group of metabolic disorders characterized by high levels of blood glucose caused by insulin defect or impairment, is a major risk factor for cardiovascular diseases and related mortality. Patients with diabetes experience a state of chronic or intermittent hyperglycemia resulting in damage to the vasculature, leading to micro- and macro-vascular diseases. These conditions are associated with low-grade chronic inflammation and accelerated atherosclerosis. Several classes of leukocytes have been implicated in diabetic cardiovascular impairment. Although the molecular pathways through which diabetes elicits an inflammatory response have attracted significant attention, how they contribute to altering cardiovascular homeostasis is still incompletely understood. In this respect, non-coding RNAs (ncRNAs) are a still largely under-investigated class of transcripts that may play a fundamental role. This review article gathers the current knowledge on the function of ncRNAs in the crosstalk between immune and cardiovascular cells in the context of diabetic complications, highlighting the influence of biological sex in such mechanisms and exploring the potential role of ncRNAs as biomarkers and targets for treatments. The discussion closes by offering an overview of the ncRNAs involved in the increased cardiovascular risk suffered by patients with diabetes facing Sars-CoV-2 infection.

A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study.

BACKGROUND: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. METHODS: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. RESULTS: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. CONCLUSIONS: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.

Bayesian analysis of the Substrate Ablation vs. Antiarrhythmic Drug Therapy for Symptomatic Ventricular Tachycardia trial.

BACKGROUND AND AIMS: Bayesian analyses can provide additional insights into the results of clinical trials, aiding in the decision-making process. We analysed the Substrate Ablation vs. Antiarrhythmic Drug Therapy for Symptomatic Ventricular Tachycardia (SURVIVE-VT) trial using Bayesian survival models. METHODS AND RESULTS: The SURVIVE-VT trial randomized patients with ischaemic cardiomyopathy and monomorphic ventricular tachycardia (VT) to catheter ablation or antiarrhythmic drugs (AAD) as a first-line strategy. The primary outcome was a composite of cardiovascular death, appropriate implantable cardioverter-defibrillator shocks, unplanned heart failure hospitalizations, or severe treatment-related complications. We used informative, skeptical, and non-informative priors with different probabilities of large effects to compute the posterior distributions using Markov Chain Monte Carlo methods. We calculated the probabilities of hazard ratios (HR) being <1, <0.9, and <0.75, as well as 2-year survival estimates. Of the 144 randomized patients, 71 underwent catheter ablation and 73 received AAD. Regardless of the prior, catheter ablation had a >98% probability of reducing the primary outcome (HR < 1) and a >96% probability of achieving a reduction of >10% (HR < 0.9). The probability of a >25% (HR < 0.75) reduction of treatment-related complications was >90%. Catheter ablation had a high probability (>93%) of reducing incessant/slow undetected VT/electric storm, unplanned hospitalizations for ventricular arrhythmias, and overall cardiovascular admissions > 25%, with absolute differences of 15.2%, 21.2%, and 20.2%, respectively. CONCLUSION: In patients with ischaemic cardiomyopathy and VT, catheter ablation as a first-line therapy resulted in a high probability of reducing several clinical outcomes compared to AAD. Our study highlights the value of Bayesian analysis in clinical trials and its potential for guiding treatment decisions. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03734562.

Advances in the screening of antimicrobial compounds using electrochemical biosensors: is there room for nanomaterials?

The abusive use of antimicrobial compounds and the associated appearance of antimicrobial resistant strains are a major threat to human health. An improved antimicrobial administration involves a faster diagnosis and detection of resistances. Antimicrobial susceptibility testing (AST) are the reference techniques for this purpose, relying mainly in the use of culture techniques. The long time required for analysis and the lack of reproducibility of these techniques have fostered the development of high-throughput AST methods, including electrochemical biosensors. In this review, recent electrochemical methods used in AST have been revised, with particular attention on those used for the evaluation of new drug candidates. The role of nanomaterials in these biosensing platforms has also been questioned, inferring that it is of minor importance compared to other applications.

Electrochemical monitoring of enzymatic cleavage in nanochannels with nanoparticle-based enhancement: determination of MMP-9 biomarker.

For the first time the use of nanoparticles as carriers of an enzymatic substrate immobilized inside nanoporous alumina membranes is proposed with the aim of amplifying the nanochannel blocking produced and, consequently, improving the efficiency of an enzyme determination through enzymatic cleavage. Streptavidin-modified polystyrene nanoparticles (PSNPs) are proposed as carrier agents, contributing to the steric and the electrostatic blockage due to the charge they present at different pH values. Electrostatic blockage is the predominant effect that governs the blockage in the interior of the nanochannel and is dependent not just in the charge inside the channel, but also in the polarity of the redox indicator used. Hence, the effect of using negatively charged ([Fe(CN)6]4-) and positively charged ([Ru(NH3)6]3+) redox indicator ions is studied for the first time. Under the optimum conditions, matrix-metalloproteinase 9 (MMP-9) is detected at clinically relevant levels (100-1200 ng/mL) showing a detection limit of 75 ng/mL and a quantification limit of 251 ng/mL with good reproducibility (RSD: 8%) and selectivity, also showing an excellent performance in real samples with acceptable recovery percentages (in the range around 80-110%). Overall, our approach represents a cheap and fast sensing methodology of great potential in point-of-care diagnostics.

Dietary microRNAs and cancer: A new therapeutic approach?

Cancer is one of the leading causes of premature death and constitutes a challenge for both low- and high-income societies. Previous evidence supports a close association between modifiable risk factors, including dietary habits, and cancer risk. Investigation of molecular mechanisms that mediate the pro-oncogenic and anti-oncogenic effects of diet is therefore fundamental. MicroRNAs (miRNAs) have received much attention in the past few decades as crucial molecular elements of human physiology and disease. Aberrant expression patterns of these small noncoding transcripts have been observed in a wide array of cancers. Interestingly, human miRNAs not only can be modulated by bioactive dietary components, but it has also been proposed that diet-derived miRNAs may contribute to the pool of human miRNAs. Results from independent groups have suggested that these exogenous miRNAs may be functional in organisms. These findings open the door to novel and innovative approaches to cancer therapy. Here, we provide an overview of the biology of miRNAs, with a special focus on plant-derived dietary miRNAs, summarize recent findings in the field of cancer, address the possible applications to clinical practice and discuss obstacles and challenges in the field.

Sleep and Circadian Health of Critical COVID-19 Survivors 3 Months After Hospital Discharge.

OBJECTIVES: To evaluate the sleep and circadian rest-activity pattern of critical COVID-19 survivors 3 months after hospital discharge. DESIGN: Observational, prospective study. SETTING: Single-center study. PATIENTS: One hundred seventy-two consecutive COVID-19 survivors admitted to the ICU with acute respiratory distress syndrome. INTERVENTIONS: Seven days of actigraphy for sleep and circadian rest-activity pattern assessment; validated questionnaires; respiratory tests at the 3-month follow-up. MEASUREMENTS AND MAIN RESULTS: The cohort included 172 patients, mostly males (67.4%) with a median (25th-75th percentile) age of 61.0 years (52.8-67.0 yr). The median number of days at the ICU was 11.0 (6.00-24.0), and 51.7% of the patients received invasive mechanical ventilation (IMV). According to the Pittsburgh Sleep Quality Index (PSQI), 60.5% presented poor sleep quality 3 months after hospital discharge, which was further confirmed by actigraphy. Female sex was associated with an increased score in the PSQI (p < 0.05) and IMV during ICU stay was able to predict a higher fragmentation of the rest-activity rhythm at the 3-month follow-up (p < 0.001). Furthermore, compromised mental health measured by the Hospital Anxiety and Depression Scale was associated with poor sleep quality (p < 0.001). CONCLUSIONS: Our findings highlight the importance of considering sleep and circadian health after hospital discharge. Within this context, IMV during the ICU stay could aid in predicting an increased fragmentation of the rest-activity rhythm at the 3-month follow-up. Furthermore, compromised mental health could be a marker for sleep disruption at the post-COVID period.

Distinct spectral dynamics of implanted cardiac defibrillator signals in spontaneous termination of polymorphic ventricular tachycardia and fibrillation in patients with electrical and structural diseases.

AIMS: To determine the spectral dynamics of early spontaneous polymorphic ventricular tachycardia and ventricular fibrillation (PVT/VF) in humans. METHODS AND RESULTS: Fifty-eight self-terminated and 173 shock-terminated episodes of spontaneously initiated PVT/VF recorded by Medtronic implanted cardiac defibrillators (ICDs) in 87 patients with various cardiac pathologies were analyzed by short fast Fourier transform of shifting segments to determine the dynamics of dominant frequency (DF) and regularity index (RI). The progression in the intensity of DF and RI accumulations further quantified the time course of spectral characteristics of the episodes. Episodes of self-terminated PVT/VF lasted 8.6 s [95% confidence interval (CI): 8.1-9.1] and shock-terminated lasted 13.9 s (13.6-14.3) (P < 0.001). Recordings from patients with primarily electrical pathologies displayed higher DF and RI values than those from patients with primarily structural pathologies (P < 0.05) independently of ventricular function or antiarrhythmic drug therapy. Regardless of the underlying pathology, the average DF and RI intensities were lower in self-terminated than shock-terminated episodes [DF: 3.67 (4.04-4.58) vs. 4.32 (3.46-3.93) Hz, P < 0.001; RI: 0.53 (0.48-0.56) vs. 0.63 (0.60-0.65), P < 0.001]. In a multivariate analysis controlled by the type of pathology and clinical variables, regularity remained an independent predictor of self-termination [hazard ratio: 0.954 (0.928-0.980)]. Receiver operating characteristic (ROC) curve analysis of DF and RI intensities demonstrated increased predictability for self-termination in time with 95% CI above the 0.5 cut-off limit at about t = 8.6 s and t = 6.95 s, respectively. CONCLUSION: Consistent with the notion that fast organized sources maintain PVT/VF in humans, reduction of frequency and regularity correlates with early self-termination. Our findings might help generate ICD methods aiming to reduce inappropriate shock deliveries.

Impact of time to intubation on mortality and pulmonary sequelae in critically ill patients with COVID-19: a prospective cohort study.

QUESTION: We evaluated whether the time between first respiratory support and intubation of patients receiving invasive mechanical ventilation (IMV) due to COVID-19 was associated with mortality or pulmonary sequelae. MATERIALS AND METHODS: Prospective cohort of critical COVID-19 patients on IMV. Patients were classified as early intubation if they were intubated within the first 48 h from the first respiratory support or delayed intubation if they were intubated later. Surviving patients were evaluated after hospital discharge. RESULTS: We included 205 patients (140 with early IMV and 65 with delayed IMV). The median [p25;p75] age was 63 [56.0; 70.0] years, and 74.1% were male. The survival analysis showed a significant increase in the risk of mortality in the delayed group with an adjusted hazard ratio (HR) of 2.45 (95% CI 1.29-4.65). The continuous predictor time to IMV showed a nonlinear association with the risk of in-hospital mortality. A multivariate mortality model showed that delay of IMV was a factor associated with mortality (HR of 2.40; 95% CI 1.42-4.1). During follow-up, patients in the delayed group showed a worse DLCO (mean difference of - 10.77 (95% CI - 18.40 to - 3.15), with a greater number of affected lobes (+ 1.51 [95% CI 0.89-2.13]) and a greater TSS (+ 4.35 [95% CI 2.41-6.27]) in the chest CT scan. CONCLUSIONS: Among critically ill patients with COVID-19 who required IMV, the delay in intubation from the first respiratory support was associated with an increase in hospital mortality and worse pulmonary sequelae during follow-up.

A Narrow Optical Pulse Emitter Based on LED: NOPELED.

Light sources emitting short pulses are needed in many particle physics experiments using optical sensors as they can replicate the light produced by the particles being detected and are also an important calibration and test element. This work presents NOPELED, a light source based on LEDs emitting short optical pulses with typical rise times of less than 3 ns and Full Width at Half Maximum lower than 7 ns. The emission wavelength depends on the model of LED used. Several LED models have been characterized in the range from 405 to 532 nm, although NOPELED can work with LED emitting wavelengths outside of that region. While the wavelength is fixed for a given LED model, the intensity and the frequency of the optical pulse can be controlled. NOPELED, which also has low cost and simple operation, can be operated remotely, making it appropriate for either different physics experiments needing in-place light sources such as astrophysical neutrino detectors using photo-multipliers or positron emission tomography devices using scintillation counters, or, beyond physics, applications needing short pulses of light such as protein fluorescence or chemodetection of heavy metals.

Plasma circular RNA hsa_circ_0001445 and coronary artery disease: Performance as a biomarker.

The role of circular RNAs (circRNAs) as biomarkers remains poorly characterized. Here, we investigated the performance of the circRNA hsa_circ_0001445 as a biomarker of coronary artery disease (CAD) in a real-world clinical practice setting. Plasma hsa_circ_0001445 was measured in a study population of 200 consecutive patients with suspected stable CAD who had undergone coronary computed tomographic angiography (CTA). Multivariable logistic models were constructed combining conventional risk factors with established biomarkers and hsa_circ_0001445. Model robustness was internally validated by the bootstrap technique. Biomarker accuracy was evaluated using the C-index. The integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were also calculated. Risk groups were developed via classification tree models. The stability of plasma hsa_circ_0001445 was evaluated under different clinical conditions. hsa_circ_0001445 levels were associated with higher coronary atherosclerosis extent and severity with a 2-fold increase across tertiles (28.4%-50.0%). Levels of hsa_circ_0001445 were proportional to coronary atherosclerotic burden, even after comprehensive adjustment for cardiovascular risk factors, medications, and established biomarkers (fully adjusted OR = 0.432 for hsa_circ_0001445 as a continuous variable and fully adjusted OR = 0.277 for hsa_circ_0001445 as a binary variable). The classification of patients was improved with the incorporation of hsa_circ_0001445 into a base clinical model (CM) composed of conventional cardiovascular risk factors, showing an IDI of 0.047 and NRI of 0.482 for hsa_circ_0001445 as a continuous variable and an IDI of 0.056 and NRI of 0.373 for hsa_circ_0001445 as a binary variable. A trend toward higher discrimination capacity was also observed (C-indexCM  = 0.833, C-indexCM+continuous hsa_circ_0001445  = 0.856 and C-indexCM+binary hsa_circ_0001445  = 0.855). Detailed analysis of stability showed that hsa_circ_0001445 was present in plasma in a remarkably stable form. In vitro, hsa_circ_0001445 was downregulated in extracellular vesicles secreted by human coronary smooth muscle cells upon exposure to atherogenic conditions. In patients with suspected stable CAD referred for coronary CTA, plasma hsa_circ_0001445 improves the identification of coronary artery atherosclerosis.

Peripheral blood microRNAs and the COVID-19 patient: methodological considerations, technical challenges and practice points.

The COVID-19 emergency pandemic resulting from infection with SARS-CoV-2 represents a major threat to public health worldwide. There is an urgent clinical demand for easily accessible tools to address weaknesses and gaps in the management of COVID-19 patients. In this context, transcriptomic profiling of liquid biopsies, especially microRNAs (miRNAs), has recently emerged as a robust source of potential clinical indicators for medical decision-making. Nevertheless, the analysis of the circulating miRNA signature and its translation to clinical practice requires strict control of a wide array of methodological details. In this review, we indicate the main methodological aspects that should be addressed when evaluating the circulating miRNA profiles in COVID-19 patients, from preanalytical and analytical variables to the experimental design, impact of confounding, analysis of the data and interpretation of the findings, among others. Additionally, we provide practice points to ensure the rigour and reproducibility of miRNA-based biomarker investigations of this condition.Abbreviations: ACE: angiotensin-converting enzyme; ARDS: acute respiratory distress syndrome; COVID-19: coronavirus disease 2019; ERDN: early Detection Research Network; LMWH: low molecular weight heparin; miRNA: microRNA; ncRNA: noncoding RNA; SARS-CoV-2: severe acute respiratory syndrome coronavirus-2; SOP: standard operating procedure.

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients.

BACKGROUND: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. METHODS: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. RESULTS: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). CONCLUSIONS: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation.