Spanish catheter ablation registry. 23rd official report of the Heart Rhythm Association of the Spanish Society of Cardiology (2023).

INTRODUCTION AND OBJECTIVES: We report the results of the 2023 Spanish catheter ablation registry. METHODS: Procedural data were collected and incorporated into the REDCap platform by all participating centers through a specific form. RESULTS: There were 104 participating centers in 2023 compared with 103 in 2022. In 2023, the total number of ablation procedures was 26 207, indicating a stabilization of the increase observed in 2022 following the pandemic. The increase was mainly due to procedures for atrial fibrillation (AF), with a total of 9942 ablations, representing 38% of all substrates. Notably, pulse-field ablation represented 10.3% of all AF ablation procedures, leading single-shot ablation strategies to outnumber point-by-point AF ablation for the first time in the history of the registry. Cavotricuspid isthmus ablation remained the second most targeted substrate (19% of all substrates, n = 5067). The overall acute success rate remained high (97%), with a downward trend in the complication rate (1.6% vs 1.8% in 2022) and mortality rate (0.03%; n = 7). Compared with 2022, there was a significant increase in procedures performed using electro-anatomical mapping and zero-fluoroscopy techniques for cavotricuspid isthmus ablation (52% vs 26%), AV node re-entrant tachycardia (48% vs 34%), and accessory pathways (62% vs 22%). We registered 466 ablations in pediatric patients. CONCLUSIONS: The data indicate a stabilization in the post-pandemic increase in ablation procedures, with an absolute and relative increase in AF as the predominant substrate. Success rates remained stable with a modest reduction in complication and mortality rates. Full English text available from: www.revespcardiol.org/en.

Spanish pacemaker registry. 21st official report of Heart Rhythm Association of the Spanish Society of Cardiology (2023).

INTRODUCTION: Data on implants of cardiac pacing systems in Spain in 2023 are presented. METHODS: The registry is based on the information provided by centers to the recording platform of the Heart Rhythm Association after device implantations, through Cardiodispositivos, the online platform of the National Registry. Other information sources include: a) data transfers from the manufacturing and marketing industry; b) the European pacemaker patient card; and c) local databases submitted by the implanting centers. RESULTS: In 2023, 112 hospitals participated in the registry (30 more than in 2022). A total of 24 343 device implantations were reported (48.1% more than in 2022) compared with 45 120 reported by Eucomed (European Confederation of Medical Suppliers Associations). Of these, 1646 were cardiac resynchronization therapy pacemakers. The devices showing the largest increases were leadless pacemakers, with 963 devices implanted, representing an 18.1% increase over 2022. The most frequent indication was atrioventricular block followed, for the first time, by atrial tachyarrhythmia with slow ventricular response. The number of devices included in remote monitoring also increased (cardiac resynchronization therapy defibrillators, 71%; cardiac resynchronization therapy pacemakers, 63%; and conventional pacemakers, 28%), although more moderately. CONCLUSIONS: In 2023, there was an increase in the number of institutions participating in the registry. The reporting of device implantations rose by 48.1%, and the implantation of leadless pacemakers grew by 18.1%. Remote monitoring also experienced modest growth compared with previous years.

Novel systematic processing of cardiac magnetic resonance imaging identifies target regions associated with infarct-related ventricular tachycardia.

BACKGROUND AND AIMS: There is lack of agreement on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging processing for guiding ventricular tachycardia (VT) ablation. We aim at developing and validating a systematic processing approach on LGE-CMR images to identify VT corridors that contain critical VT isthmus sites. METHODS: Translational study including 18 pigs with established myocardial infarction and inducible VT undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with VT maintenance. Clinical validation was conducted in a multicenter series of 33 patients with ischemic cardiomyopathy undergoing VT ablation. Three-dimensional CMR-LGE images were processed using systematic scanning of 15 signal intensity (SI) cut-off ranges to obtain surface visualization of all potential VT corridors. Analysis and comparisons of imaging and electrophysiological data were performed in individuals with full electrophysiological characterization of the isthmus sites of at least one VT morphology. RESULTS: In both the experimental pig model and patients undergoing VT ablation, all the electrophysiologically-defined isthmus sites (n=11 and n=19, respectively) showed overlapping regions with CMR-based potential VT corridors. Such imaging-based VT corridors were less specific than electrophysiologically-guided ablation lesions at critical isthmus sites. However, an optimized strategy using the 7 most relevant SI cut-off ranges among patients showed an increase in specificity compared to using 15 SI cut-off ranges (70% vs 62%, respectively), without diminishing the capability to detect VT isthmus sites (sensitivity 100%). CONCLUSIONS: Systematic imaging processing of LGE-CMR sequences using several SI cut-off ranges may improve and standardize procedure planning to identify VT isthmus sites.

Low-Resource Time-to-Digital Converters for Field Programmable Gate Arrays: A Review.

A fundamental aspect in the evolution of Time-to-Digital Converters (TDCs) implemented within Field-Programmable Gate Arrays (FPGAs), given the increasing demand for detection channels, is the optimization of resource utilization. This study reviews the principal methodologies employed for implementing low-resource TDCs in FPGAs. It outlines the foundational architectures and interpolation techniques utilized to bolster TDC performances without unduly burdening resource consumption. Low-resource Tapped Delay Line, Vernier Ring Oscillator, and Multi-Phase Shift Counter TDCs, including the use of SerDes, are reviewed. Additionally, novel low-resource architectures are scrutinized, including Counter Gray Oscillator TDCs and interpolation expansions using Process-Voltage-Temperature stable IODELAYs. Furthermore, the advantages and limitations of each approach are critically assessed, with particular emphasis on resolution, precision, non-linearities, and especially resource utilization. A comprehensive summary table encapsulating existing works on low-resource TDCs is provided, offering a comprehensive overview of the advancements in the field.

Guidelines for mitochondrial RNA analysis.

Mitochondria are the energy-producing organelles of mammalian cells with critical involvement in metabolism and signaling. Studying their regulation in pathological conditions may lead to the discovery of novel drugs to treat, for instance, cardiovascular or neurological diseases, which affect high-energy-consuming cells such as cardiomyocytes, hepatocytes, or neurons. Mitochondria possess both protein-coding and noncoding RNAs, such as microRNAs, long noncoding RNAs, circular RNAs, and piwi-interacting RNAs, encoded by the mitochondria or the nuclear genome. Mitochondrial RNAs are involved in anterograde-retrograde communication between the nucleus and mitochondria and play an important role in physiological and pathological conditions. Despite accumulating evidence on the presence and biogenesis of mitochondrial RNAs, their study continues to pose significant challenges. Currently, there are no standardized protocols and guidelines to conduct deep functional characterization and expression profiling of mitochondrial RNAs. To overcome major obstacles in this emerging field, the EU-CardioRNA and AtheroNET COST Action networks summarize currently available techniques and emphasize critical points that may constitute sources of variability and explain discrepancies between published results. Standardized methods and adherence to guidelines to quantify and study mitochondrial RNAs in normal and disease states will improve research outputs, their reproducibility, and translation potential to clinical application.

Circulating long noncoding RNA PDE4DIPP6: A novel biomarker for improving the clinical management of non-ST-segment elevation myocardial infarction.

BACKGROUND: Long noncoding RNAs (lncRNAs) have emerged as promising diagnostic biomarkers. Here, we investigated the cardiac-expressed and plasma-detectable lncRNA PDE4DIPP6 as a biomarker for non-ST-segment elevation myocardial infarction (NSTEMI), specifically assessing its potential to enhance the diagnostic efficacy of high-sensitivity cardiac troponin (hs-cTnT). METHODS AND RESULTS: The study enrolled individuals presenting with suspected acute coronary syndrome (ACS). LncRNA quantification was performed in plasma samples using RT-qPCR. The discriminatory performance was assessed by calculating the Area Under the Curve (AUC). Reclassification metrics, including the Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) indexes, were utilized to evaluate enhancements in diagnostic accuracy. Among the 252 patients with suspected ACS, 50.8 % were diagnosed with ACS, and 13.9 % with NSTEMI. Initially, the association of lncRNA PDE4DIPP6 with ACS was investigated. Elevated levels of this lncRNA were observed in ACS patients compared to non-ACS subjects. No association was found between lncRNA PDE4DIPP6 levels and potential confounding factors, nor was a significant correlation with hs-cTnT levels (rho = 0.071). The inclusion of lncRNA PDE4DIPP6 on top of hs-cTnT significantly improved the discrimination and classification of ACS patients, as reflected by an enhanced AUC of 0.734, an IDI of 0.066 and NRI of 0.471. Subsequently, the lncRNA PDE4DIPP6 was evaluated as biomarker of NSTEMI. Elevated levels of the lncRNA were observed in NSTEMI patients compared to patients without NSTEMI. Consistent with previous findings, the addition of lncRNA PDE4DIPP6 to hs-cTnT improved the discrimination and classification of patients, increasing the AUC from 0.859 to 0.944, with an IDI of 0.237 and NRI of 0.658. CONCLUSION: LncRNA PDE4DIPP6 offers additional diagnostic insights beyond hs-cTnT, suggesting its potential to improve the clinical management of patients with NSTEMI.

Machine learning for catalysing the integration of noncoding RNA in research and clinical practice.

The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies ("multiomic" strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual constraints are discussed, along with an exploration of ethical considerations inherent to AI applications for healthcare and research. The ultimate goal is to provide a comprehensive examination of the multifaceted landscape of this innovative field and its clinical implications.

Circular RNA regulatory role in pathological cardiac remodelling.

Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed.

Exploring the translational landscape of the long noncoding RNA transcriptome in acute respiratory distress syndrome: it is a long way to the top.

Acute respiratory distress syndrome (ARDS) poses a significant and widespread public health challenge. Extensive research conducted in recent decades has considerably improved our understanding of the disease pathophysiology. Nevertheless, ARDS continues to rank among the leading causes of mortality in intensive care units and its management remains a formidable task, primarily due to its remarkable heterogeneity. As a consequence, the syndrome is underdiagnosed, prognostication has important gaps and selection of the appropriate therapeutic approach is laborious. In recent years, the noncoding transcriptome has emerged as a new area of attention for researchers interested in biomarker development. Numerous studies have confirmed the potential of long noncoding RNAs (lncRNAs), transcripts with little or no coding information, as noninvasive tools for diagnosis, prognosis and prediction of the therapeutic response across a broad spectrum of ailments, including respiratory conditions. This article aims to provide a comprehensive overview of lncRNAs with specific emphasis on their role as biomarkers. We review current knowledge on the circulating lncRNAs as potential markers that can be used to enhance decision making in ARDS management. Additionally, we address the primary limitations and outline the steps that will be essential for integration of the use of lncRNAs in clinical laboratories. Our ultimate objective is to provide a framework for the implementation of lncRNAs in the management of ARDS.

Decoding viral and host microRNA signatures in airway-derived biosamples: Insights for biomarker discovery in viral respiratory infections.

The global public health crisis caused by the COVID-19 pandemic has intensified the global concern regarding viral respiratory tract infections. Despite their considerable impact on health, society and the economy, effective management of these conditions remains a significant challenge. Integrating high-throughput analyses is pivotal for early detection, prognostication of adverse outcomes, elucidating pathogenetic pathways and developing therapeutic approaches. In recent years, microRNAs (miRNAs), a subset of small noncoding RNAs (ncRNAs), have emerged as promising tools for molecular phenotyping. Current evidence suggests that miRNAs could serve as innovative biological markers, aiding in informed medical decision-making. The cost-effective quantification of miRNAs in standardized samples using techniques routinely employed in clinical laboratories has become feasible. In this context, samples obtained from the airways represent a valuable source of information due to their direct exposure to the infectious agent and host response within the respiratory tract. This review explores viral and host miRNA profiling in airway-derived biosamples as a source of molecular information to guide patient management, with a specific emphasis on SARS-CoV-2 infection.

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.

Addressing the unsolved challenges in microRNA-based biomarker development: Suitable endogenous reference microRNAs for SARS-CoV-2 infection severity.

Circulating cell-free microRNAs (miRNAs) are promising biomarkers for medical decision-making. Suitable endogenous controls are essential to ensure reproducibility. We aimed to identify and validate endogenous reference miRNAs for qPCR data normalization in samples from SARS-CoV-2-infected hospitalized patients. We used plasma samples (n = 170) from COVID-19 patients collected at hospital admission (COVID-Ponent project, www.clinicaltrials.gov/NCT04824677). First, 179 miRNAs were profiled using RT-qPCR. After stability assessment, candidates were validated using the same methodology. miRNA stability was analyzed using the geNorm, NormFinder and BestKeeper algorithms. Stability was further evaluated using an RNA-seq dataset derived from COVID-19 hospitalized patients, along with plasma samples from patients with critical COVID-19 profiled using RT-qPCR. In the screening phase, after strict control of expression levels, stability assessment selected eleven candidates (miR-17-5p, miR-20a-5p, miR-30e-5p, miR-106a-5p, miR-151a-5p, miR-185-5p, miR-191-5p, miR-423-3p, miR-425-5p, miR-484 and miR-625-5p). In the validation phase, all algorithms identified miR-106a-5p and miR-484 as top endogenous controls. No association was observed between these miRNAs and clinical or sociodemographic characteristics. Both miRNAs were stably detected and showed low variability in the additional analyses. In conclusion, a 2-miRNA panel composed of miR-106a-5p and miR-484 constitutes a first-line normalizer for miRNA-based biomarker development using qPCR in hospitalized patients infected with SARS-CoV-2.

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.

Volcanic soil gas 4He/CO2 ratio: a useful geochemical tool for real-time eruption forecasting.

At many dormant volcanoes, magmatic gases are not channeled through preferential degassing routes as fumaroles and only percolate through the flanks of the volcano in a diffuse way. This type of volcanic gas emission provides valuable information, even though the soil matrix contains an important atmospheric component. This study aimed to demonstrate that chemical ratios such as He/CO2 in soil gases provide excellent information on the evolution of volcanic unrest episodes and help forecast the volcanic eruption onset. Before and during the occurrence of the October 2011-March 2012 submarine of El Hierro, Canary Islands, more than 8500 soil He analyses and diffuse CO2 emission measurements were performed. The results show that the soil He/CO2 emission ratio began increasing drastically one month before eruption onset, reaching the maximum value 10 days before. During the eruptive period, this ratio also showed a maximum value several days before the period with the highest magma emission rate. The He/CO2 ratio was also helpful in forecasting the eruption onset. We demonstrate that this tool can be applied in real-time during volcanic emergencies. Our results also encourage a reevaluation of the global He emission from the subaerial volcanism.

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.

Practical approach for atrial cardiomyopathy characterization in patients with atrial fibrillation.

Atrial fibrillation (AF) causes progressive structural and electrical changes in the atria that can be summarized within the general concept of atrial remodeling. In parallel, other clinical characteristics and comorbidities may also affect atrial tissue properties and make the atria susceptible to AF initiation and its long-term persistence. Overall, pathological atrial changes lead to atrial cardiomyopathy with important implications for rhythm control. Although there is general agreement on the role of the atrial substrate for successful rhythm control in AF, the current classification oversimplifies clinical management. The classification uses temporal criteria and does not establish a well-defined strategy to characterize the individual-specific degree of atrial cardiomyopathy. Better characterization of atrial cardiomyopathy may improve the decision-making process on the most appropriate therapeutic option. We review current scientific evidence and propose a practical characterization of the atrial substrate based on 3 evaluation steps starting with a clinical evaluation (step 1), then assess outpatient complementary data (step 2), and finally include information from advanced diagnostic tools (step 3). The information from each of the steps or a combination thereof can be used to classify AF patients in 4 stages of atrial cardiomyopathy, which we also use to estimate the success on effective rhythm control.

microRNA Expression Profile in Obesity-Induced Kidney Disease Driven by High-Fat Diet in Mice.

Obesity is one of the main causes of chronic kidney disease; however, the precise molecular mechanisms leading to the onset of kidney injury and dysfunction in obesity-associated nephropathy remain unclear. The present study aimed to unveil the kidney microRNA (miRNA) expression profile in a model of obesity-induced kidney disease in C57BL/6J mice using next-generation sequencing (NGS) analysis. High-fat diet (HFD)-induced obesity led to notable structural alterations in tubular and glomerular regions of the kidney, increased renal expression of proinflammatory and profibrotic genes, as well as an elevated renal expression of genes involved in cellular lipid metabolism. The miRNA sequencing analysis identified a set of nine miRNAs differentially expressed in the kidney upon HFD feeding, with miR-5099, miR-551b-3p, miR-223-3p, miR-146a-3p and miR-21a-3p showing the most significant differential expression between standard diet (STD) and HFD mice. A validation analysis showed that the expression levels of miR-5099, miR-551b-3p and miR-146a-3p were consistent with NGS results, while Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses revealed that these three validated miRNAs modulated target genes involved in metabolic and adipocytokine pathways, fatty acid and lipid metabolism, and inflammatory, senescence and profibrotic pathways. Our results suggest that differentially expressed miRNAs play pivotal roles in the intricate pathophysiology of obesity-associated kidney disease and could potentially create novel treatment strategies to counteract the deleterious effects of obesity on kidney function.

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.

MicroRNA-guided drug discovery for mitigating persistent pulmonary complications in critical COVID-19 survivors: A longitudinal pilot study.

BACKGROUND AND PURPOSE: The post-acute sequelae of SARS-CoV-2 infection pose a significant global challenge, with nearly 50% of critical COVID-19 survivors manifesting persistent lung abnormalities. The lack of understanding about the molecular mechanisms and effective treatments hampers their management. Here, we employed microRNA (miRNA) profiling to decipher the systemic molecular underpinnings of the persistent pulmonary complications. EXPERIMENTAL APPROACH: We conducted a longitudinal investigation including 119 critical COVID-19 survivors. A comprehensive pulmonary evaluation was performed in the short-term (median = 94.0 days after hospital discharge) and long-term (median = 358 days after hospital discharge). Plasma miRNAs were quantified at the short-term evaluation using the gold-standard technique, RT-qPCR. The analyses combined machine learning feature selection techniques with bioinformatic investigations. Two additional datasets were incorporated for validation. KEY RESULTS: In the short-term, 84% of the survivors exhibited impaired lung diffusion (DLCO  < 80% of predicted). One year post-discharge, 54.4% of this patient subgroup still presented abnormal DLCO . Four feature selection methods identified two specific miRNAs, miR-9-5p and miR-486-5p, linked to persistent lung dysfunction. The downstream experimentally validated targetome included 1473 genes, with heterogeneous enriched pathways associated with inflammation, angiogenesis and cell senescence. Validation studies using RNA-sequencing and proteomic datasets emphasized the pivotal roles of cell migration and tissue repair in persistent lung dysfunction. The repositioning potential of the miRNA targets was limited. CONCLUSION AND IMPLICATIONS: Our study reveals early mechanistic pathways contributing to persistent lung dysfunction in critical COVID-19 survivors, offering a promising approach for the development of targeted disease-modifying agents.