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.

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.

GATEKEEPER's Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases.

BACKGROUND: The World Health Organization's strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. OBJECTIVE: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. METHODS: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. RESULTS: Seven European countries were selected, covering Europe's geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence-based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. CONCLUSIONS: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.

Adherence to CPAP Treatment and the Risk of Recurrent Cardiovascular Events: A Meta-Analysis.

Importance: The effect of continuous positive airway pressure (CPAP) on secondary cardiovascular disease prevention is highly debated. Objective: To assess the effect of CPAP treatment for obstructive sleep apnea (OSA) on the risk of adverse cardiovascular events in randomized clinical trials. Data Sources: PubMed (MEDLINE), EMBASE, Current Controlled Trials: metaRegister of Controlled Trials, ISRCTN Registry, European Union clinical trials database, CENTRAL (Cochrane Central Register of Controlled Trials), and ClinicalTrials.gov databases were systematically searched through June 22, 2023. Study Selection: For qualitative and individual participant data (IPD) meta-analysis, randomized clinical trials addressing the therapeutic effect of CPAP on cardiovascular outcomes and mortality in adults with cardiovascular disease and OSA were included. Data Extraction and Synthesis: Two reviewers independently screened records, evaluated potentially eligible primary studies in full text, extracted data, and cross-checked errors. IPD were requested from authors of the selected studies (SAVE [NCT00738179], ISAACC [NCT01335087], and RICCADSA [NCT00519597]). Main Outcomes and Measures: One-stage and 2-stage IPD meta-analyses were completed to estimate the effect of CPAP treatment on risk of recurrent major adverse cardiac and cerebrovascular events (MACCEs) using mixed-effect Cox regression models. Additionally, an on-treatment analysis with marginal structural Cox models using inverse probability of treatment weighting was fitted to assess the effect of good adherence to CPAP (≥4 hours per day). Results: A total of 4186 individual participants were evaluated (82.1% men; mean [SD] body mass index, 28.9 [4.5]; mean [SD] age, 61.2 [8.7] years; mean [SD] apnea-hypopnea index, 31.2 [17] events per hour; 71% with hypertension; 50.1% receiving CPAP [mean {SD} adherence, 3.1 {2.4} hours per day]; 49.9% not receiving CPAP [usual care], mean [SD] follow-up, 3.25 [1.8] years). The main outcome was defined as the first MACCE, which was similar for the CPAP and no CPAP groups (hazard ratio, 1.01 [95% CI, 0.87-1.17]). However, an on-treatment analysis by marginal structural model revealed a reduced risk of MACCEs associated with good adherence to CPAP (hazard ratio, 0.69 [95% CI, 0.52-0.92]). Conclusions and Relevance: Adherence to CPAP was associated with a reduced MACCE recurrence risk, suggesting that treatment adherence is a key factor in secondary cardiovascular prevention in patients with OSA.

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.

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.

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.

Decrease in sleep quality during COVID-19 outbreak.

PURPOSE: The COVID-19 outbreak witnessed in the first months of 2020 has led to unprecedented changes in society's lifestyles. In the current study, we aimed to investigate the effect of this unexpected context on sleep. METHODS: During the COVID-19 outbreak, we performed an online survey with individuals formerly recruited for validation of the Spanish version of the sleep questionnaire Satisfaction, Alertness, Timing, Efficiency, and Duration (SATED). In the current survey, we asked the participants to complete the previously answered questionnaires including the Pittsburgh Sleep Quality Index (PSQI), a modified version of the Epworth Sleepiness Scale (ESS), and the SATED questionnaire. We also assessed the mood by the Profile of Mood States (POMS) questionnaire. RESULTS: The 71 participants were mostly women (75%) with a mean (± SD) age of 40.7 ± 11.9 years. Comparing the previous PSQI score to that during the COVID-19 outbreak, we observed worsening sleep quality (5.45 ± 3.14 to 6.18 ± 3.03 points, p = 0.035). In parallel, there was an increase in the negative mood (p = 0.002). Accordingly, the decrease in sleep quality was substantially correlated with negative mood (p < 0.001). There were no differences in the ESS or SATED. CONCLUSIONS: The COVID-19 outbreak-associated events correlate with decreased sleep quality in association with an increase in negative mood. Considering the importance of sleep for a healthy life, and in particular for immune function, efforts should be made to improve awareness on this matter and to offer psychological assistance to affected individuals.

Management and Treatment of Patients With Obstructive Sleep Apnea Using an Intelligent Monitoring System Based on Machine Learning Aiming to Improve Continuous Positive Airway Pressure Treatment Compliance: Randomized Controlled Trial.

BACKGROUND: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnea (OSA), but treatment compliance is often unsatisfactory. OBJECTIVE: The aim of this study was to assess the effectiveness and cost-effectiveness of an intelligent monitoring system for improving CPAP compliance. METHODS: This is a prospective, open label, parallel, randomized controlled trial including 60 newly diagnosed patients with OSA requiring CPAP (Apnea-Hypopnea Index [AHI] >15) from Lleida, Spain. Participants were randomized (1:1) to standard management or the MiSAOS intelligent monitoring system, involving (1) early compliance detection, thus providing measures of patient's CPAP compliance from the very first days of usage; (2) machine learning-based prediction of midterm future CPAP compliance; and (3) rule-based recommendations for the patient (app) and care team. Clinical and anthropometric variables, daytime sleepiness, and quality of life were recorded at baseline and after 6 months, together with patient's compliance, satisfaction, and health care costs. RESULTS: Randomized patients had a mean age of 57 (SD 11) years, mean AHI of 50 (SD 27), and 13% (8/60) were women. Patients in the intervention arm had a mean (95% CI) of 1.14 (0.04-2.23) hours/day higher adjusted CPAP compliance than controls (P=.047). Patients' satisfaction was excellent in both arms, and up to 88% (15/17) of intervention patients reported willingness to keep using the MiSAOS app in the future. No significant differences were found in costs (control: mean €90.2 (SD 53.14) (US $105.76 [SD 62.31]); intervention: mean €96.2 (SD 62.13) (US $112.70 [SD 72.85]); P=.70; €1=US $1.17 was considered throughout). Overall costs combined with results on compliance demonstrated cost-effectiveness in a bootstrap-based simulation analysis. CONCLUSIONS: A machine learning-based intelligent monitoring system increased daily compliance, reported excellent patient satisfaction similar to that reported in usual care, and did not incur in a substantial increase in costs, thus proving cost-effectiveness. This study supports the implementation of intelligent eHealth frameworks for the management of patients with CPAP-treated OSA and confirms the value of patients' empowerment in the management of chronic diseases. TRIAL REGISTRATION: ClinicalTrials.gov NCT03116958; https://clinicaltrials.gov/ct2/show/NCT03116958.

Impact of OLD/Emphysema in LC Mortality Risk in Screening Programs: An Analysis of NLST and P-IELCAP.

INTRODUCTION: The impact of obstructive lung disease (OLD) and emphysema on lung cancer (LC) mortality in patients undergoing LC screening is controversial. METHODS: Patients with spirometry and LC diagnosed within the first three rounds of screening were selected from the National Lung Screening Trial (NLST) and from the Pamplona International Early Lung Cancer Detection Program (P-IELCAP). Medical and demographic data, tumor characteristics, comorbidities and presence of emphysema were collected. The effect of OLD and emphysema on the risk of overall survival was assessed using unadjusted and adjusted Cox models, competing risk regression analysis, and propensity score matching. RESULTS: Data from 353 patients with LC, including 291 with OLD and/or emphysema and 62 with neither, were analyzed. The median age was 67.3 years-old and 56.1% met OLD criteria, predominantly mild (1: 28.3%, 2: 65.2%). Emphysema was present in 69.4% of the patients. Patients with OLD and/or emphysema had worse survival on univariate analysis (HR: 1.40; 95% CI: 0.86-2.31; p=0.179). However, after adjusting for LC stage, age, and sex, the HR was 1.02 (95% CI: 0.61-1.70; p=0.952). Specific LC survival between both groups showed an adjusted HR of 0.90 (95% CI: 0.47-1.72; p=0.76). Propensity score matching found no statistically significant difference in overall survival (HR: 1.03; 95% CI: 0.59-1.9; p=0.929). CONCLUSION: The survival of LC patients diagnosed in the context of screening is not negatively impacted by the coexistence of mild OLD and/or emphysema.

MicroRNA-centered theranostics for pulmoprotection in critical COVID-19.

Elucidating the pathobiological mechanisms underlying post-acute pulmonary sequelae following SARS-CoV-2 infection is essential for early interventions and patient stratification. Here, we investigated the potential of microRNAs (miRNAs) as theranostic agents for pulmoprotection in critical illness survivors. Multicenter study including 172 ICU survivors. Diffusion impairment was defined as a lung-diffusing capacity for carbon monoxide (DLCO) <80% within 12 months postdischarge. A disease-associated 16-miRNA panel was quantified in plasma samples collected at ICU admission. Bioinformatic analyses were conducted using KEGG, Reactome, GTEx, and Drug-Gene Interaction databases. The results were validated using an external RNA-seq dataset. A 3-miRNA signature linked to diffusion impairment (miR-27a-3p, miR-93-5p, and miR-199a-5p) was identified using random forest. Levels of miR-93-5p and miR-199a-5p were independently associated with the outcome, improving patient classification provided by the electronic health record. The experimentally validated targets of these miRNAs exhibited enrichment across diverse pathways, with telomere length quantification in an additional set of samples (n = 83) supporting the role of cell senescence in sequelae. Analysis of an external dataset refined the pathobiological fingerprint of pulmonary sequelae. Gene-drug interaction analysis revealed four FDA-approved drugs. Overall, this study advances our understanding of lung recovery in postacute respiratory infections, highlighting the potential of miRNAs and their targets for pulmoprotection.

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.

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.

Polysomnographic characterization of circadian blood pressure patterns in patients with obstructive sleep apnea.

We characterized the polysomnography (PSG) parameters associated with alterations in the circadian blood pressure (BP) pattern aiming to identify the main contributors to explain the nondipper profile in obstructive sleep apnea (OSA). This is an observational prospective-multicenter study that included participants referred to the sleep unit for suspected OSA. Following a PSG study, subjects with an apnea-hypopnea index (AHI) ≥5 events/hr were included. Two groups were established based on the 24-hr ambulatory blood pressure monitoring dipping ratio (DR; night/day BP ratio): dippers (DR ≤ 0.9) and nondippers (DR > 0.9). The cohort consisted of 299 patients: 131 (43.8%) dippers and 168 (56.2%) nondippers. A significant increase in the risk of presenting a nondipper BP pattern was found along with AHI gain [odds ratio (OR) (95% CI) = 1.71 (1.28 to 2.28)]. The best AHI cutoff for predicting nondipper status was 25.2 events/hr, increasing the OR (95% CI) to 3.50 (2.02 to 6.07). The hypopnea index [OR (95% CI) = 1.70 (1.27 to 2.26)], TSat90 [OR (95% CI) = 1.41 (1.06 to 1.87)], and respiratory arousal index [OR (95% CI) = 1.74 (1.30 to 2.34)] were individually associated with the risk of a nondipping pattern. Multivariate variable selection processes identified the respiratory arousal index as the most relevant risk factor for the nondipper profile, beyond classical clinical risk factors and usual PSG metrics.

Cerebrospinal fluid lipidomic fingerprint of obstructive sleep apnoea in Alzheimer's disease.

BACKGROUND: Obstructive sleep apnoea (OSA) has a high prevalence in patients with Alzheimer's disease (AD). Both conditions have been shown to be associated with lipid dysregulation. However, the relationship between OSA severity and alterations in lipid metabolism in the brains of patients with AD has yet to be fully elucidated. In this context, we examined the cerebrospinal fluid (CSF) lipidome of patients with suspected OSA to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the effect of OSA on AD. METHODS: The study included 91 consecutive AD patients who underwent overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥ 30/h). The next morning, CSF samples were collected and analysed by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform. RESULTS: The CSF levels of 11 lipid species were significantly different between AD patients with (N = 38) and without (N = 58) severe OSA. Five lipids (including oxidized triglyceride OxTG(57:2) and four unknown lipids) were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Our analyses revealed a 4-lipid signature (including oxidized ceramide OxCer(40:6) and three unknown lipids) that provided an accuracy of 0.80 (95% CI: 0.71-0.89) in the detection of severe OSA. These lipids increased the discriminative power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50-0.74) to 0.85 (0.71-0.93). CONCLUSIONS: Our results reveal a CSF lipidomic fingerprint that allows the identification of AD patients with severe OSA. Our findings suggest that an increase in central nervous system lipoxidation may be the principal mechanism underlying the association between OSA and AD.

Breathing cessation events that compose the apnea-hypopnea index are distinctively associated with the adverse outcomes in Alzheimer's disease.

BACKGROUND: Previous studies challenge the impact of obstructive sleep apnea (OSA) once patients are diagnosed with Alzheimer's disease (AD). Nevertheless, OSA recognizably disrupts sleep, and relevant associations between sleep, AD pathological markers, and cognition have been demonstrated. We aimed to further explore this, evaluating the associations between each breathing cessation event that compose the apnea-hypopnea index (AHI) and the sleep structure to finally investigate whether this was related to increased levels of AD markers and higher cognitive decline. METHODS: Observational, prospective study, including consecutive patients diagnosed with mild-moderate AD. The participants were submitted to overnight polysomnography followed by a cerebrospinal fluid collection for AD pathological markers levels determination. Neuropsychological assessment was performed at baseline and after 12 months of follow-up. RESULTS: The cohort was composed of 116 patients (55.2% females) with a median [p25;p75] age of 76.0 [72.0;80.0] years and an AHI of 25.9 [15.1;48.5], which was mainly defined by the presence of hypopneas and obstructive apneas. These were distinctively associated with the sleep structure, with obstructive apneas being related to arousals and sleep lightening and hypopneas being related to an increased number of arousals only. Despite having a lower frequency, mixed and central apneas also presented associations with the sleep structure, particularly increasing the time spent in the lighter sleep stages. In relation to AD pathological markers, obstructive and mixed apneas were related to an augment in neurofilament light levels while hypopneas were associated with a higher phosphorylated-tau/amyloid-beta protein ratio. Hypopneas were the most important event for an increased cognitive decline at the 12-month follow-up. CONCLUSIONS: Our findings highlight the importance of a patient-centered approach, with a comprehensive and detailed analysis of the AHI to effectively predict the different outcomes and tailor the appropriate therapeutic strategies.

Metabolipidomic Analysis in Patients with Obstructive Sleep Apnea Discloses a Circulating Metabotype of Non-Dipping Blood Pressure.

A non-dipping blood pressure (BP) pattern, which is frequently present in patients with obstructive sleep apnea (OSA), confers high cardiovascular risk. The mechanisms connecting these two conditions remain unclear. In the present study we performed a comprehensive analysis of the blood metabolipidome that aims to provide new insights into the molecular link between OSA and the dysregulation of circadian BP rhythmicity. This was an observational prospective longitudinal study involving adults with suspected OSA who were subjected to full polysomnography (PSG). Patients with an apnea-hypopnea index ≥ 5 events/h were included. Fasting plasma samples were obtained the morning after PSG. Based on the dipping ratio (DR; ratio of night/day BP values) measured via 24 h ambulatory BP monitoring, two groups were established: dippers (DR ≤ 0.9) and non-dippers (DR > 0.9). Treatment recommendations for OSA followed the clinical guidelines. Untargeted metabolomic and lipidomic analyses were performed in plasma samples via liquid chromatography-tandem mass spectrometry. Non-dipper patients represented 53.7% of the cohort (88/164 patients). A set of 31 metabolic species and 13 lipidic species were differentially detected between OSA patients who present a physiologic nocturnal BP decrease and those with abnormal BP dipping. Among the 44 differentially abundant plasma compounds, 25 were putatively identified, notably glycerophospholipids, glycolipids, sterols, and fatty acid derivates. Multivariate analysis defined a specific metabotype of non-dipping BP, which showed a significant dose-response relationship with PSG parameters of OSA severity, and with BP dipping changes after 6 months of OSA treatment with continuous positive airway pressure (CPAP). Bioinformatic analyses revealed that the identified metabolipidomic profile was found to be implicated in multiple systemic biological pathways, with potential physiopathologic implications for the circadian control of BP among individuals with OSA.

Study protocol for the epigenetic characterization of angor pectoris according to the affected coronary compartment: Global and comprehensive assessment of the relationship between invasive coronary physiology and microRNAs.

BACKGROUND: MicroRNAs (miRNAs) are noncoding RNAs involved in post-transcriptional genetic regulation with a proposed role in intercellular communication. miRNAs are considered promising biomarkers in ischemic heart disease. Invasive physiological evaluation allows a precise assessment of each affected coronary compartment. Although some studies have associated the expression of circulating miRNAs with invasive physiological indexes, their global relationship with coronary compartments has not been assessed. Here, we will evaluate circulating miRNAs profiles according to the coronary pattern of the vascular compartment affectation. STUDY AND DESIGN: This is an investigator-initiated, multicentre, descriptive study to be conducted at three centres in Spain (NCT05374694). The study will include one hundred consecutive patients older than 18 years with chest pain of presumed coronary cause undergoing invasive physiological evaluation, including fractional flow reserve (FFR) and index of microvascular resistance (IMR). Patients will be initially classified into four groups, according to FFR and IMR: macrovascular and microvascular affectation (FFR≤0.80 / IMR≥25), isolated macrovascular affectation (FFR≤0.80 / IMR<25), isolated microvascular affectation (FFR>0.80 / IMR ≥25) and normal coronary indexes (FFR>0.80 / IMR<25). Patients with isolated microvascular affectation or normal indexes will also undergo the acetylcholine test and may be reclassified as a fifth group in the presence of spasm. A panel of miRNAs previously associated with molecular mechanisms linked to chronic coronary syndrome will be analysed using RT-qPCR. CONCLUSIONS: The results of this study will identify miRNA profiles associated with patterns of coronary affectation and will contribute to a better understanding of the mechanistic pathways of coronary pathology.