Longer ICU stay and invasive mechanical ventilation accelerate telomere shortening in COVID-19 patients one-year after recovery

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There is an association between shorter telomere length (TL) in COVID-19 patients and hospitalization, severity, or even death. However, it remains unknown whether virus-induced-senescence is reversible. We aim to evaluate the dynamics of TL in COVID-19 patients one year after recovery from intensive care units (ICU). Longitudinal study enrolling 49 patients admitted to ICU due to COVID-19 (August 2020 to April 2021). Relative telomere length (RTL) quantification was carried out in whole blood by monochromatic multiplex real-time quantitative PCR (MMqPCR) assay at hospitalization (baseline) and one year after discharge (one-year visit). The association between RTL and ICU length of stay (LOS), invasive mechanical ventilation (IMV), prone position, and pulmonary fibrosis development at one-year visit. The median age was 60 years, 71.4% were males, median ICU-LOS was 12 days, 73.5% required IMV, and 38.8% required a prone position. Patients with longer ICU-LOS or who required IMV showed greater RTL shortening during follow-up. Patients who required pronation had a greater RTL shortening during follow-up. IMV patients who developed pulmonary fibrosis showed greater RTL reduction and shorter RTL at one-year visit. Patients with longer ICU-LOS and those who required IMV had a shorter RTL in peripheral blood, as observed one year after hospital discharge. Additionally, patients who required IMV and developed pulmonary fibrosis had greater telomere shortening, showing shorter telomeres at one-year visit. These patients may be more prone to develop cellular senescence and lung-related complications; therefore, closer monitoring may be needed. SARS-CoV2 COVID-19 ARDS relative telomere length ICU IMV. Figures Figure 1 Introduction Coronavirus disease 2019 (COVID-19) is the latest pandemic and global emergency declared by the World Health Organization (WHO). COVID-19 is an airborne disease caused by the SARS-CoV-2 novel human coronavirus, causing a respiratory infection that can range from a common cold to more serious conditions, such as pneumonia or acute respiratory distress syndrome (ARDS) ( 1 ). Most severe cases are transferred to the Intensive Care Unit (ICU) (around 20%), often requiring invasive mechanical ventilation (IMV), which typically lasts 10 days ( 2 , 3 ). These supportive vital methods are crucial for the survival of these patients; however, they produce lung injury and induce oxidative stress and a reduction of antioxidant enzymes ( 4 – 6 ). This accelerated oxidative stress, together with normal aging and other comorbidities, causes telomere shortening. When a critical threshold in telomere length is reached, senescence and apoptosis are triggered depending on the cell type. Likewise, these factors promote immune senescence, modifying the function of the immune cells and making them inefficient in maintaining homeostasis, leading to a higher risk of infection and the development and progression of different age-related diseases ( 7 ). Additionally, virus-induced senescence directly impacts lymphocyte telomere length, with consequences mainly in older adults, who are much more likely to die from severe COVID-19. There is an association between shorter telomere size and the need for hospitalization, greater severity of COVID-19, or even death ( 8 – 10 ). Recently, Schneider et al. attributed telomere shortening to an increased risk of mortality with a Hazard Ratio of 1.4 in respiratory pathologies ( 11 ). Additionally, a recent study has demonstrated that individuals who have recovered from SARS-CoV-2 infection have shorter telomere around one year after recovery, finding that this shortening was associated with higher severity but not with other clinical outcomes ( 12 ). However, although it has been shown that telomere shortening occurs during ICU stay due to causes other than COVID-19 ( 13 ), to our knowledge, there are no longitudinal studies evaluating telomere shortening or recovery in patients who were admitted to the ICU. Therefore, this study aimed to evaluate the change in telomere size in patients admitted to the ICU at least one year after hospital discharge. Materials and Methods Design and study population We performed a longitudinal study of COVID-19 patients admitted to the ICU at the Tajo University Hospital (Aranjuez, Madrid) and Infanta Cristina University Hospital (Parla, Madrid) from August 2020 to April 2021, who were followed for at least 12 months from hospital discharge. Patients were diagnosed by laboratory confirmation (RNA detection by PCR or serology-based methodology) or by consideration of clinical manifestations compatible with COVID-19. The STROBE-ID checklist was followed. The study protocol was approved by the Ethics Committee of the Institute of Health Carlos III (PI 33_2020-v3) and the Investigation Committee of both hospitals. Clinical data and samples Epidemiological and clinical variables were collected from medical records with REDCap ( 14 ). Peripheral blood samples were obtained in EDTA tubes upon admission to the ICU and at least one-year after discharge. DNA was isolated with the commercial kit “ReliaPrep™ Blood gDNA Miniprep System” from PROMEGA, according to the manufacturer’s instructions. DNA concentration and quality were determined using NanoDrop™ One/One C (Thermo Scientific™). All samples were then diluted into 10 ng/uL working aliquots. Telomere relative quantification RTL quantification was carried out by monochromatic multiplex real-time quantitative PCR (MMqPCR) assay as previously described ( 10 ) (see Additional File 1 for extended information). Study variables The outcome variable was the change of RTL from baseline to one-year visit. This change was analyzed using the RTL ratio (one-year RTL / baseline RTL). The secondary outcome was the RTL at one-year visit. The study factors included were: a) Hospitalization variables : i) ICU length of stay (ICU-LOS); ii) need for IMV and its duration; iii) prone position during the first 7 days of ICU stay. b) Radiologic alterations in the one-year visit for the subgroup of patients who required IMV : presence of fibrosis on the X-ray image. Statistical Analysis For the descriptive analysis, the McNemar test for categorical variables and the Wilcoxon test for continuous variables were used. Regarding RTL measurement, outlier identification was performed using the interquartile range (IQR) method. Correlation between RTL and age was performed using Spearman correlation. For telomere size differential analysis, we performed the Mann-Whitney test for transversal analysis and the Wilcoxon test for longitudinal analysis between paired samples. We used Generalized Linear Models (GLMs) with gamma distribution to study the association between the baseline RTL, RTL ratio, and one-year RTL values (y, dependent variables) with the need for IMV, IMV duration, ICU-LOS, prone position, and pulmonary fibrosis development at the end of the follow-up (x, independent variables). This test provides the arithmetic means (AMR) ratio and its significance level. GLMs were adjusted by the most relevant covariates by using a stepwise method (forward), where at each step, the covariates were considered to enter according to the lowest Akaike information criteria (AIC) for that specific model. The covariates included were age, gender, body mass index (BMI), PCR plate, and follow-up time (months) when GLMs included variables from one-year visit. Statistical software R (v.4.2.2) was used to perform the statistical analysis. All p -values were two-tailed, and the statistical significance was defined as p ≤ 0.05. Results Patient characteristics Clinical and epidemiological characteristics of the 49 patients according to the baseline and one-year time (after a median of 13.8 months) are shown in Table 1 . Overall, the median age was 60 years; 71.4% were male, and more than 80% were Caucasian. In addition, 42.9% had hypertension, 55.1% obesity, and 37.4% diabetes. Regarding hospitalization variables, 73.5% required IMV, patients had a median ICU-LOS of 12 days and IMV duration of 14 days, and 38.8% needed a prone position (first 7 days). At baseline, no patient was vaccinated but received the first dose before the one-year visit. Table 1 Clinical and epidemiological characteristics of COVID patients at admission ICU and one-year after discharge. Baseline One-year P N 49 49 Age (years) 60.0 (54.0–69.0) - - Gender (Male) 35/49 (71.4%) - - Ethnicity - Caucasian Hispanic Arabian Unknown 40/49 (81.6%) 6/49 (12.2%) 2/49 (4.1%) 1/49 (2.0%) - - BMI (kg/m 2 ) 30.9 (26.3–35.2) 31.67 (28.1, 35.6) 0.197 Smoker status Ex-smoker 15/49 (30.6%) - Smoker 1/49(2.3%) - Comorbidities Arterial hypertension 21/49 (42.9%) 24/49 (49.0%) 0.248 Obesity (BMI > 30) 27/49 (55.1%) 30/49 (61.2%) 0.579 Diabetes 17/49 (37.4%) 20/49 (40.8%) 0.248 Therapy (n = 48) AIIRA 7/48 (14.6%) 9/49 (18.4%) 0.062 ACE 7/48 (14.6%) 10/47 (21.3%) 0.371 Treatment Antibiotics 48/49 (98.0%) Azithromycin (n = 48) 23/48 (47.9%) Corticoids 46/49 (93.9%) Anticoagulants (n = 48) 45/48 (93.8%) COVID-19 symptoms Fever (> 38ºC) 33/48 (68.7%) Temperature (ºC) (n = 30) 38.5 (38.0–39.0) Dyspnea (n = 48) 43/48 (89.6%) Myalgia (n = 42) 30/42 (71.4%) Hospitalization ICUs ICU LOS (days) 12 ( 8 – 26 ) IMV 37/49 (73.5%) IMV days (n = 36) 14 ( 6 – 23 ) High-flow nasal cannulas 40/49 (79.6%) Duration of high-flow nasal cannula therapy (days) (n = 27) 2 ( 1 – 4 ) Prone position (first 7 days) 19/49 (38.8%) SOFA score admission 4 ( 4 – 11 ) SOFA score 48 hours 5 ( 3 – 11 ) One-year after discharge Time from hospital discharge (months) 13.8 (12.5–15.6) Fibrosis (X-ray image) (n = 33) 9/33 (27.3%) Dyspnea (n = 48) 15/48 (31.2%) Myalgia (n = 42) 16/35 (41.7%) Relative telomere length (RTL) 1.35 (1.16–1.60) 1.29 (1.11–1.55) 0.079 Statistics : Patient’s characteristics were summarized using the median (interquartile range) for continuous variables and absolute number (percentage) for categorical variables. Differences between groups were tested using the Wilcoxon test and the McNemar test for continuous variables and categorical variables, respectively. Abbreviations : BMI, body mass index; AIIRA, Angiotensin II receptor antagonists; ACE, angiotensin-converting enzyme inhibitors; ICU-LOS, intensive care unit length of stay; IMV, invasive mechanical ventilation; SOFA, sequential organ failure assessment. We found a negative but not significant physiological correlation between RTL and age at baseline (r=-0.242; p = 0.094) and significant at one-year visit (r=-0.310; p = 0.030) ( Additional File 3 ). Evolution of RTL according to hospitalization variables a) ICU-LOS While no differences were found at baseline, prolonged ICU-LOS was related to RTL differently. Thus, we observed that only those patients with ICU-LOS > 12 days showed significantly shortened telomeres size (p < 0.001), while patients with an ICU-LOS < 12 days showed similar RTL (p = 0.380) during follow-up (Fig. 1 A). b) Need for IMV and its duration No differences in RTL were found at baseline, but those patients who required IMV significantly reduced their RTL during follow-up (p < 0.001). So, those patients admitted to the ICU but who did not receive IMV significantly increased their RTL during follow-up (p = 0.012) (Fig. 1 A) ( Additional File 4 ). Besides, one-year after discharge, patients without IMV showed higher RTL than those with IMV, although this difference did not reach significance p = 0.068). c) Need for a prone position The requirement for a prone position suggests a more severe and worse evolution of ARDS. Therefore, we analyzed the RTL between patients with and without needing a prone position during the first 7 days. While no differences were observed at baseline, those patients who required a prone position significantly reduced their RTL during follow-up (p = 0.005). On the other hand, patients who were not placed in the prone position did not modify their RTL during follow-up (Fig. 1 A ). Radiologic abnormalities at one-year visit For the subgroup of patients who required IMV and had available an X-ray image at one-year visit (n = 33), 63.3% had no radiological alterations, 9.1% had interstitial infiltrates, and 27.3% had fibrosis. Patients with fibrosis showed a higher RTL shortening at one-year visit (p = 0.007) in comparison to those without radiological abnormalities. Additionally, at one-year visit, these differences remained significant, where patients who developed pulmonary fibrosis showed significantly lower RTL (p = 0.040) (Fig. 1 B). All the significant results for each comparison were confirmed by multivariate GLMs adjusted by the covariates selected by a stepwise method ( Additional File 4 ). Discussion In this longitudinal study, we found that patients with longer ICU-LOS and those who required IMV had a greater shortening of the RTL during the first year after hospital discharge. Among those patients who required IMV, a trend toward a decreased RTL at one-year visit was also observed. In addition, patients who developed pulmonary fibrosis showed a deep reduction of RTL during the first year after hospital discharge, showing lower RTL at one-year visit than those who did not have pulmonary fibrosis. To our knowledge, our study is the first one showing an association between RTL shortening and clinical variables of hospitalization after more than one year of follow-up in COVID-19 patients admitted to the ICU. A severe or fatal COVID-19 is more likely to occur at older ages, suggesting that age-related molecular pathways are involved in the severity of this disease ( 15 ). In this regard, several studies have shown an association between shorter telomeres and the need for hospitalization, greater severity, or even mortality in COVID-19 patients ( 8 – 10 ). However, limited studies have evaluated the change in telomere size once patients have been discharged from the hospital. Retuerto et al., after a median of 14 months of follow-up, observed that 35% of study participants had shortened telomere. They did not observe an association between RTL and hospital clinical outcomes, which could probably be due to the fact that its population was not homogeneous, with a mixture of disease severity. However, the patients who had a more severe disease also had the largest telomere shortening ( 12 ). The impact and, consequently, the implications of telomere shortening in COVID-19 patients admitted to the ICU are currently unknown. In this study, patients with longer ICU-LOS shortened RTL during follow-up. This could probably be due to the critical exhaustion of the immune system after a long ICU stay, where the length of telomeres would reach a critical size, which would compromise the telomerase capacity to recover telomere length. Previous studies have demonstrated significant changes in leukocyte telomere size in critical patients during ICU stay ( 13 , 16 ). However, to our knowledge, no studies have investigated the impact of ICU-LOS on the RTL after hospital discharge. Our findings highlight the need for follow-up of patients with longer ICU-LOS over time for future senescence-related complications. Patients requiring IMV had a longer ICU-LOS and a worse prognosis ( 17 ). Overall, we found that, in critically ill COVID-19 patients, the need for IMV was related to a telomere shortening during follow-up, which may reflect lung damage and loss of functionality. To our knowledge, few studies have addressed this issue. Only Liang et al. showed telomere shortening in ICU patients requiring IMV, but it was evaluated solely two days after ICU discharge ( 16 ). Therefore, additional studies with longer follow-ups are needed to elucidate the impact of the IMV on decreasing RTL and its association with the post-COVID syndrome of patients admitted to the ICU. In severe patients with worse evolution of ARDS, a prone position is recommended to improve oxygen saturation and reduce lung damage ( 18 , 19 ). A prone position significantly reduces the rate of tracheal intubation and mortality ( 20 ), although there are also studies with contradictory results ( 21 ). Moreover, among intubated patients, responders to the prone position in terms of oxygenation show better survival than those who do not respond ( 22 ). Regarding evolution after discharge, our study showed that COVID-19 patients who required a prone position shortened telomere during follow-up. To our knowledge, these findings are the first to associate the prone position with reduced telomere size in COVID-19 patients during the first year after hospital discharge. Further studies with a longer follow-up would be needed to study whether telomere size evolves to more critical levels in this subgroup of patients. COVID-19 patients develop fibrotic pulmonary sequelae ( 23 – 25 ). There is also an association between telomere shortening in immune cells and lung disease development, such as idiopathic pulmonary fibrosis ( 7 , 26 – 28 ). In our study, while no significant differences in RTL were observed at baseline, those patients who experienced an RTL shortening during follow-up developed lung fibrosis. Similarly, patients with fibrotic pulmonary sequelae showed shorter RTL at the one-year visit compared to those without radiological abnormalities. To our knowledge, this is the first study assessing the RTL and fibrosis development during follow-up in ICU patients. Still, these findings are in concordance with previous studies in hospitalized patients. McGroder et al. showed that patients with shorter telomere size at hospitalization were more prone to develop fibrotic abnormalities in the lung 4 months later, but the telomere length dynamics were not addressed ( 29 ). Using a different approach (Quantitative telomere Fluorescence in situ Hybridization Q-FISH), Martínez et al. found loss of alveolar type II (ATII) cellularity and shorter telomeres in these cells in post-COVID-19 lung cancer patients. Authors suggested that ATII cell telomere reduction may trigger lung fibrosis development in post-COVID-19 patients ( 30 ), but these results were produced in a cancer background, and studies on non-lung cancer COVID-19 patients should be addressed. Similarly, Mulet et al., in a recent prospective study ( 31 ), described that this attrition could also be evaluated on peripheral blood cells, as COVID-19 patients with radiological signs of fibrosis had significant telomere shortening one year after leaving the hospital. However, this study involved only 19 patients, and the authors did not comment on how they measured telomere length. Retuerto et al. also observed that patients who shortened their peripheral blood leukocyte telomeres after discharge were more prone to show persistent radiographic abnormalities. However, this study was performed during the first pandemic wave, when the hospital admission criteria were exceptional. Our study is the first to confirm these findings in ICU patients, which is a more homogeneous group that showed similar severity and received similar clinical strategies. However, further studies with a longer follow-up of COVID-19 patients would be needed to establish the role of RTL shortening on fibrotic pulmonary sequelae and vice versa. Limitations Several issues must be considered in order to interpret our data correctly. The sample size was limited as only patients with one-year visit were included in the study. This could have limited the power of the statistical analysis, and some significant associations may not have been detected. However, the statistical analysis used was appropriate to address this issue correctly. This study also has several strengths, such as the fact that all patients were recruited during the second and third pandemic waves, where the ICU admission criteria were similar, and the selected method of measuring telomere length. We measured RTL in whole blood, and its determination could be transferred to routine clinical practice. This study addressed a topic that has been scarcely studied until now in critical patients because the recruitment and follow-up of these patients are arduous. In addition, it should be noted that we analyzed RTL before initiating any mechanical ventilation. Conclusions In conclusion, we found that patients with longer ICU stays, need for IMV, and fibrosis development shortened telomere size in the first year after hospital discharge. In addition, patients who required IMV and developed pulmonary fibrosis showed shorter telomeres at one-year visit. These findings suggest that these patients need extensive monitoring as they are at higher risk of developing cellular senescence-related and chronic respiratory complications. Abbreviations Acute respiratory distress syndrome (ARDS) Angiotensin II receptor antagonists (AIIRA) Akaike information criteria (AIC) Alveolar type II (ATII) Arithmeticc means ratio (AMR) Body mass index (BMI) Confidence interval (CI) Ethylenediaminetetraacetic acid (EDTA) Generalized linear models (GLMs) Intensive care unit (ICU) Invasive mechanical ventilation (IMV) Interquartile range (IQR) Length of stay (LOS) Monochromatic multiplex real-time quantitative PCR (MMqPCR) Polymerase chain reaction (PCR) Quantitative telomere fluorescence in situ hybridization (Q-FISH) Relative telomere length (RTL) Research Electronic Data Capture (REDCap) Sequential organ failure assessment (SOFA) Strengthening the reporting of observational studies in epidemiology (STROBE) Telomere length (TL) World health organization (WHO) Declarations Ethics approval and consent to participate The study protocol was approved by the Ethics Committee of the Institute of Health Carlos III (PI 33_2020-v3) and the Investigation Committee of both hospitals. Availability of data and materials All data are available upon request to corresponding authors. Competing interests The authors declare no conflict of interest. Funding Details This study was supported by grants from Instituto de Salud Carlos III (ISCIII; grant number COV20/1144 [MPY224/20] to AFR/MAJS) and Fundación Universidad Alfonso X el Sabio (FUAX) – Santander (1.013.005). The study was also supported by CIBER – Consorcio Centro de Investigación Biomédica en Red-(CB 2021), Instituo de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea – NextGenerationEU (CB21/13/00044). Authors’ Contributions Funding body: MAJS, AFR and RB. Study concept and design: AFR, MAJS, AVB, OMG and RB. Patients’ selection and clinical data acquisition: AVB, OMG, RB, EM, MJMP, BLM, CMP. Sample preparation and analysis: AVB, SBB, RBL. Statistical analysis and interpretation of data: AVB, SBB, RBL, AFR, and MAJS. Writing of the manuscript: AVB, AFR, and MAJS. Critical revision of the manuscript for relevant intellectual content: SR, RB, OMG. Supervision and visualization: AFR and MAJS. All authors read and approved the final manuscript. Acknowledgements This study would not have been possible without the collaboration of all the patients, their families, medical and nursery staff, and data managers who have taken part in the project. References Anka AU, Tahir MI, Abubakar SD, Alsabbagh M, Zian Z, Hamedifar H, et al. Coronavirus disease 2019 (COVID-19): An overview of the immunopathology, serological diagnosis and management. Scand J Immunol. 2021;93(4):e12998. Chang R, Elhusseiny KM, Yeh YC, Sun WZ. COVID-19 ICU and mechanical ventilation patient characteristics and outcomes-A systematic review and meta-analysis. PLoS One. 2021;16(2):e0246318. Wolff D, Nee S, Hickey NS, Marschollek M. Risk factors for Covid-19 severity and fatality: a structured literature review. Infection. 2021;49(1):15–28. 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Supplementary Files Additionalfiles.docx Cite Share Download PDF Status: Published Journal Publication published 07 Aug, 2024 Read the published version in Critical Care → Version 1 posted Editorial decision: Revision requested 08 Jul, 2024 Reviews received at journal 11 Jun, 2024 Reviewers agreed at journal 30 May, 2024 Reviewers invited by journal 29 May, 2024 Submission checks completed at journal 26 May, 2024 Editor assigned by journal 26 May, 2024 First submitted to journal 24 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4471434","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":310438351,"identity":"98d847a1-5c3c-453b-80c7-e59c5d819ebb","order_by":0,"name":"Ana VIRSEDA-BERDICES","email":"","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"","lastName":"VIRSEDA-BERDICES","suffix":""},{"id":310438352,"identity":"84fa0855-672f-4f2b-bec7-2d333324cd85","order_by":1,"name":"Raquel BEHAR-LAGARES","email":"","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":false,"prefix":"","firstName":"Raquel","middleName":"","lastName":"BEHAR-LAGARES","suffix":""},{"id":310438353,"identity":"4fb3d742-afc0-48e9-8049-6b052ec5b62d","order_by":2,"name":"Oscar MARTÍNEZ-GONZÁLEZ","email":"","orcid":"","institution":"Hospital Universitario del Tajo","correspondingAuthor":false,"prefix":"","firstName":"Oscar","middleName":"","lastName":"MARTÍNEZ-GONZÁLEZ","suffix":""},{"id":310438354,"identity":"503cc2a5-6391-4ad8-ac6a-3550d75d9c9d","order_by":3,"name":"Rafael BLANCAS","email":"","orcid":"","institution":"Hospital Universitario del Tajo","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"","lastName":"BLANCAS","suffix":""},{"id":310438355,"identity":"4f139ee4-a8e4-4243-bd52-79ccd2069e5a","order_by":4,"name":"Soraya BUENO-BUSTOS","email":"","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":false,"prefix":"","firstName":"Soraya","middleName":"","lastName":"BUENO-BUSTOS","suffix":""},{"id":310438356,"identity":"f1e82d49-848f-4044-b6d7-103ca747c044","order_by":5,"name":"Oscar BROCHADO-KITH","email":"","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":false,"prefix":"","firstName":"Oscar","middleName":"","lastName":"BROCHADO-KITH","suffix":""},{"id":310438357,"identity":"6ac2f4d4-5807-4820-8ad5-46e181dab013","order_by":6,"name":"Eva MANTEIGA","email":"","orcid":"","institution":"Hospital Universitario Infanta Cristina","correspondingAuthor":false,"prefix":"","firstName":"Eva","middleName":"","lastName":"MANTEIGA","suffix":""},{"id":310438358,"identity":"2f6222c2-8cfb-4170-8422-47a756aa3ef3","order_by":7,"name":"María J. MALLOL POYATO","email":"","orcid":"","institution":"Hospital Universitario del Tajo","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"J. MALLOL","lastName":"POYATO","suffix":""},{"id":310438359,"identity":"b0c0c5c2-e2aa-4c9d-948b-efe8958f7306","order_by":8,"name":"Blanca LÓPEZ MATAMALA","email":"","orcid":"","institution":"Hospital Universitario del Tajo","correspondingAuthor":false,"prefix":"","firstName":"Blanca","middleName":"LÓPEZ","lastName":"MATAMALA","suffix":""},{"id":310438360,"identity":"9fdaf82f-7a7d-487a-b8e3-4bbc9164b90b","order_by":9,"name":"Carmen MARTÍN PARRA","email":"","orcid":"","institution":"Hospital Universitario del Tajo","correspondingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"MARTÍN","lastName":"PARRA","suffix":""},{"id":310438361,"identity":"987e8e5d-f7e5-4c35-8518-e876e722d2df","order_by":10,"name":"Salvador RESINO","email":"","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":false,"prefix":"","firstName":"Salvador","middleName":"","lastName":"RESINO","suffix":""},{"id":310438362,"identity":"795f5003-24af-4122-bda7-f0afe488a84f","order_by":11,"name":"María A. JIMÉNEZ-SOUSA","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACxmZk3gcDBgY2ZsYG4rUwziBGCwpg5iFKVTt34uOCijp7fon0h59tCurk+diZGxg+/MHnMN7NxjPOsCXOnJFjLJ1jcNiwDegwxplteLVsk+Zt40kwuJHDANRyIAHkF2ZePN4Batn+m/efhL3BjfTHvy0M6iBa/uB32DagmQaMG24kmEkzGDBDtDCw4feLNM+xhMSZPW/MLHugfjnYi8cvhv1nN37mqQGGGHv64xs//tTJy/cff/jgBx6HGWL15wHcGhgY5PFJjoJRMApGwSgAAwA1gUeMkaEnYQAAAABJRU5ErkJggg==","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":true,"prefix":"","firstName":"María","middleName":"A.","lastName":"JIMÉNEZ-SOUSA","suffix":""},{"id":310438363,"identity":"15b0a4bf-a351-4877-a1f6-82acd312fad6","order_by":12,"name":"Amanda FERNÁNDEZ-RODRÍGUEZ","email":"","orcid":"","institution":"Instituto de Salud Carlos III. Madrid","correspondingAuthor":false,"prefix":"","firstName":"Amanda","middleName":"","lastName":"FERNÁNDEZ-RODRÍGUEZ","suffix":""}],"badges":[],"createdAt":"2024-05-24 09:21:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4471434/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4471434/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13054-024-05051-6","type":"published","date":"2024-08-07T15:56:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58145691,"identity":"53737291-62ac-4c1c-aff6-905a04ba30fe","added_by":"auto","created_at":"2024-06-11 18:33:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":92339,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA) \u003c/strong\u003eEvolution of relative telomere length (RTL) in COVID-19 patients, stratified by length of stay (LOS) in the intensive care unit (ICU), need for invasive mechanical ventilation (IMV), and need for prone position, from baseline to one-year visit (12 months since hospital discharged). \u003cstrong\u003eB)\u003c/strong\u003eDifferences in RTL, one-year visit, in COVID-19 patients who required IMV and had X-ray images, comparing patients without radiological alterations and with fibrosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistics\u003c/strong\u003e: Data represent the crude means and 95% confidence interval for each group of patients. P-values were calculated using the Mann-Whitney test for transversal analysis and the Wilcoxon test for longitudinal analysis between paired samples. R and \u003cem\u003ep\u003c/em\u003e-value in the scatter plot were calculated by a Spearman’s correlation. Statistical significance was determined as \u003cem\u003ep\u003c/em\u003e ≤ 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: RTL, relative telomere length; ICU, intensive care unit; IMV, invasive mechanical ventilation.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4471434/v1/859a5d38dd461acbb6eb195a.png"},{"id":62298391,"identity":"ed8ea48f-ba78-402c-9893-9ae59c9c8797","added_by":"auto","created_at":"2024-08-12 16:12:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":717158,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4471434/v1/9bba111c-2a0b-4c17-b1dd-6abf0e1a47bc.pdf"},{"id":58145693,"identity":"4ed64eed-7be3-4496-9917-e5b007ba68d2","added_by":"auto","created_at":"2024-06-11 18:33:38","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":663294,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-4471434/v1/adab5c4427d95fc1d1af5208.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Longer ICU stay and invasive mechanical ventilation accelerate telomere shortening in COVID-19 patients one-year after recovery","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronavirus disease 2019 (COVID-19) is the latest pandemic and global emergency declared by the World Health Organization (WHO). COVID-19 is an airborne disease caused by the SARS-CoV-2 novel human coronavirus, causing a respiratory infection that can range from a common cold to more serious conditions, such as pneumonia or acute respiratory distress syndrome (ARDS) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost severe cases are transferred to the Intensive Care Unit (ICU) (around 20%), often requiring invasive mechanical ventilation (IMV), which typically lasts 10 days (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). These supportive vital methods are crucial for the survival of these patients; however, they produce lung injury and induce oxidative stress and a reduction of antioxidant enzymes (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This accelerated oxidative stress, together with normal aging and other comorbidities, causes telomere shortening. When a critical threshold in telomere length is reached, senescence and apoptosis are triggered depending on the cell type. Likewise, these factors promote immune senescence, modifying the function of the immune cells and making them inefficient in maintaining homeostasis, leading to a higher risk of infection and the development and progression of different age-related diseases (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally, virus-induced senescence directly impacts lymphocyte telomere length, with consequences mainly in older adults, who are much more likely to die from severe COVID-19. There is an association between shorter telomere size and the need for hospitalization, greater severity of COVID-19, or even death (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Recently, Schneider et al. attributed telomere shortening to an increased risk of mortality with a Hazard Ratio of 1.4 in respiratory pathologies (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Additionally, a recent study has demonstrated that individuals who have recovered from SARS-CoV-2 infection have shorter telomere around one year after recovery, finding that this shortening was associated with higher severity but not with other clinical outcomes (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, although it has been shown that telomere shortening occurs during ICU stay due to causes other than COVID-19 (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), to our knowledge, there are no longitudinal studies evaluating telomere shortening or recovery in patients who were admitted to the ICU. Therefore, this study aimed to evaluate the change in telomere size in patients admitted to the ICU at least one year after hospital discharge.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign and study population\u003c/h2\u003e \u003cp\u003e We performed a longitudinal study of COVID-19 patients admitted to the ICU at the Tajo University Hospital (Aranjuez, Madrid) and Infanta Cristina University Hospital (Parla, Madrid) from August 2020 to April 2021, who were followed for at least 12 months from hospital discharge. Patients were diagnosed by laboratory confirmation (RNA detection by PCR or serology-based methodology) or by consideration of clinical manifestations compatible with COVID-19. The STROBE-ID checklist was followed. The study protocol was approved by the Ethics Committee of the Institute of Health Carlos III (PI 33_2020-v3) and the Investigation Committee of both hospitals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eClinical data and samples\u003c/h2\u003e \u003cp\u003eEpidemiological and clinical variables were collected from medical records with REDCap (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Peripheral blood samples were obtained in EDTA tubes upon admission to the ICU and at least one-year after discharge. DNA was isolated with the commercial kit \u0026ldquo;ReliaPrep\u0026trade; Blood gDNA Miniprep System\u0026rdquo; from PROMEGA, according to the manufacturer\u0026rsquo;s instructions. DNA concentration and quality were determined using NanoDrop\u0026trade; One/One\u003csup\u003eC\u003c/sup\u003e (Thermo Scientific\u0026trade;). All samples were then diluted into 10 ng/uL working aliquots.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTelomere relative quantification\u003c/h2\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRTL quantification was carried out by monochromatic multiplex real-time quantitative PCR (MMqPCR) assay as previously described\u003c/span\u003e (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(see\u003c/span\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eAdditional File 1\u003c/span\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003efor extended information).\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy variables\u003c/h2\u003e \u003cp\u003eThe outcome variable was the change of RTL from baseline to one-year visit. This change was analyzed using the RTL ratio (one-year RTL / baseline RTL). The secondary outcome was the RTL at one-year visit.\u003c/p\u003e \u003cp\u003eThe study factors included were: a) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eHospitalization variables\u003c/span\u003e: i) ICU length of stay (ICU-LOS); ii) need for IMV and its duration; iii) prone position during the first 7 days of ICU stay. b) \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRadiologic alterations in the one-year visit for the subgroup of patients who required IMV\u003c/span\u003e: presence of fibrosis on the X-ray image.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eFor the descriptive analysis, the McNemar test for categorical variables and the Wilcoxon test for continuous variables were used.\u003c/p\u003e \u003cp\u003eRegarding RTL measurement, outlier identification was performed using the interquartile range (IQR) method. Correlation between RTL and age was performed using Spearman correlation.\u003c/p\u003e \u003cp\u003eFor telomere size differential analysis, we performed the Mann-Whitney test for transversal analysis and the Wilcoxon test for longitudinal analysis between paired samples. We used Generalized Linear Models (GLMs) with gamma distribution to study the association between the baseline RTL, RTL ratio, and one-year RTL values (y, dependent variables) with the need for IMV, IMV duration, ICU-LOS, prone position, and pulmonary fibrosis development at the end of the follow-up (x, independent variables). This test provides the arithmetic means (AMR) ratio and its significance level. GLMs were adjusted by the most relevant covariates by using a stepwise method (forward), where at each step, the covariates were considered to enter according to the lowest Akaike information criteria (AIC) for that specific model. The covariates included were age, gender, body mass index (BMI), PCR plate, and follow-up time (months) when GLMs included variables from one-year visit.\u003c/p\u003e \u003cp\u003eStatistical software R (v.4.2.2) was used to perform the statistical analysis. All \u003cem\u003ep\u003c/em\u003e-values were two-tailed, and the statistical significance was defined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eClinical and epidemiological characteristics of the 49 patients according to the baseline and one-year time (after a median of 13.8 months) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Overall, the median age was 60 years; 71.4% were male, and more than 80% were Caucasian. In addition, 42.9% had hypertension, 55.1% obesity, and 37.4% diabetes. Regarding hospitalization variables, 73.5% required IMV, patients had a median ICU-LOS of 12 days and IMV duration of 14 days, and 38.8% needed a prone position (first 7 days). At baseline, no patient was vaccinated but received the first dose before the one-year visit.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical and epidemiological characteristics of COVID patients at admission ICU and one-year after discharge.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOne-year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.0 (54.0\u0026ndash;69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35/49 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003cp\u003eArabian\u003c/p\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40/49 (81.6%)\u003c/p\u003e \u003cp\u003e6/49 (12.2%)\u003c/p\u003e \u003cp\u003e2/49 (4.1%)\u003c/p\u003e \u003cp\u003e1/49 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.9 (26.3\u0026ndash;35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.67 (28.1, 35.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoker status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15/49 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/49(2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArterial hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21/49 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24/49 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity (BMI\u0026thinsp;\u0026gt;\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27/49 (55.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/49 (61.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17/49 (37.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20/49 (40.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTherapy (n\u0026thinsp;=\u0026thinsp;48)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIIRA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7/48 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/49 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7/48 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10/47 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTreatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48/49 (98.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAzithromycin (n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23/48 (47.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorticoids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46/49 (93.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnticoagulants (n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45/48 (93.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOVID-19 symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever (\u0026gt;\u0026thinsp;38\u0026ordm;C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33/48 (68.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature (\u0026ordm;C) (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.5 (38.0\u0026ndash;39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea (n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43/48 (89.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30/42 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospitalization ICUs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU LOS (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37/49 (73.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIMV days (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-flow nasal cannulas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40/49 (79.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of high-flow nasal\u003c/p\u003e \u003cp\u003ecannula therapy (days) (n\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProne position (first 7 days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19/49 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9 CR10\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score 48 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8 CR9 CR10\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOne-year after discharge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime from hospital discharge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.8 (12.5\u0026ndash;15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrosis (X-ray image) (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/33 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea (n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15/48 (31.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16/35 (41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRelative telomere length (RTL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35 (1.16\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29 (1.11\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eStatistics\u003c/b\u003e: Patient\u0026rsquo;s characteristics were summarized using the median (interquartile range) for continuous variables and absolute number (percentage) for categorical variables. Differences between groups were tested using the Wilcoxon test and the McNemar test for continuous variables and categorical variables, respectively. \u003cb\u003eAbbreviations\u003c/b\u003e: BMI, body mass index; AIIRA, Angiotensin II receptor antagonists; ACE, angiotensin-converting enzyme inhibitors; ICU-LOS, intensive care unit length of stay; IMV, invasive mechanical ventilation; SOFA, sequential organ failure assessment.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe found a negative but not significant physiological correlation between RTL and age at baseline (r=-0.242; p\u0026thinsp;=\u0026thinsp;0.094) and significant at one-year visit (r=-0.310; p\u0026thinsp;=\u0026thinsp;0.030) (\u003cb\u003eAdditional File 3\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEvolution of RTL according to hospitalization variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea)\u003c/b\u003e \u003cem\u003eICU-LOS\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWhile no differences were found at baseline, prolonged ICU-LOS was related to RTL differently. Thus, we observed that only those patients with ICU-LOS\u0026thinsp;\u0026gt;\u0026thinsp;12 days showed significantly shortened telomeres size (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while patients with an ICU-LOS\u0026thinsp;\u0026lt;\u0026thinsp;12 days showed similar RTL (p\u0026thinsp;=\u0026thinsp;0.380) during follow-up (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eb)\u003c/b\u003e \u003cem\u003eNeed for IMV and its duration\u003c/em\u003e\u003c/p\u003e \u003cp\u003eNo differences in RTL were found at baseline, but those patients who required IMV significantly reduced their RTL during follow-up (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). So, those patients admitted to the ICU but who did not receive IMV significantly increased their RTL during follow-up (p\u0026thinsp;=\u0026thinsp;0.012) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) (\u003cb\u003eAdditional File 4\u003c/b\u003e). Besides, one-year after discharge, patients without IMV showed higher RTL than those with IMV, although this difference did not reach significance p\u0026thinsp;=\u0026thinsp;0.068).\u003c/p\u003e \u003cp\u003e \u003cb\u003ec)\u003c/b\u003e \u003cem\u003eNeed for a prone position\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe requirement for a prone position suggests a more severe and worse evolution of ARDS. Therefore, we analyzed the RTL between patients with and without needing a prone position during the first 7 days. While no differences were observed at baseline, those patients who required a prone position significantly reduced their RTL during follow-up (p\u0026thinsp;=\u0026thinsp;0.005). On the other hand, patients who were not placed in the prone position did not modify their RTL during follow-up (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eRadiologic abnormalities at one-year visit\u003c/h2\u003e \u003cp\u003eFor the subgroup of patients who required IMV and had available an X-ray image at one-year visit (n\u0026thinsp;=\u0026thinsp;33), 63.3% had no radiological alterations, 9.1% had interstitial infiltrates, and 27.3% had fibrosis. Patients with fibrosis showed a higher RTL shortening at one-year visit (p\u0026thinsp;=\u0026thinsp;0.007) in comparison to those without radiological abnormalities. Additionally, at one-year visit, these differences remained significant, where patients who developed pulmonary fibrosis showed significantly lower RTL (p\u0026thinsp;=\u0026thinsp;0.040) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eAll the significant results for each comparison were confirmed by multivariate GLMs adjusted by the covariates selected by a stepwise method (\u003cb\u003eAdditional File 4\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this longitudinal study, we found that patients with longer ICU-LOS and those who required IMV had a greater shortening of the RTL during the first year after hospital discharge. Among those patients who required IMV, a trend toward a decreased RTL at one-year visit was also observed. In addition, patients who developed pulmonary fibrosis showed a deep reduction of RTL during the first year after hospital discharge, showing lower RTL at one-year visit than those who did not have pulmonary fibrosis. To our knowledge, our study is the first one showing an association between RTL shortening and clinical variables of hospitalization after more than one year of follow-up in COVID-19 patients admitted to the ICU.\u003c/p\u003e \u003cp\u003eA severe or fatal COVID-19 is more likely to occur at older ages, suggesting that age-related molecular pathways are involved in the severity of this disease (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In this regard, several studies have shown an association between shorter telomeres and the need for hospitalization, greater severity, or even mortality in COVID-19 patients (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, limited studies have evaluated the change in telomere size once patients have been discharged from the hospital. Retuerto et al., after a median of 14 months of follow-up, observed that 35% of study participants had shortened telomere. They did not observe an association between RTL and hospital clinical outcomes, which could probably be due to the fact that its population was not homogeneous, with a mixture of disease severity. However, the patients who had a more severe disease also had the largest telomere shortening (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The impact and, consequently, the implications of telomere shortening in COVID-19 patients admitted to the ICU are currently unknown.\u003c/p\u003e \u003cp\u003eIn this study, patients with longer ICU-LOS shortened RTL during follow-up. This could probably be due to the critical exhaustion of the immune system after a long ICU stay, where the length of telomeres would reach a critical size, which would compromise the telomerase capacity to recover telomere length. Previous studies have demonstrated significant changes in leukocyte telomere size in critical patients during ICU stay (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, to our knowledge, no studies have investigated the impact of ICU-LOS on the RTL after hospital discharge. Our findings highlight the need for follow-up of patients with longer ICU-LOS over time for future senescence-related complications.\u003c/p\u003e \u003cp\u003ePatients requiring IMV had a longer ICU-LOS and a worse prognosis (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Overall, we found that, in critically ill COVID-19 patients, the need for IMV was related to a telomere shortening during follow-up, which may reflect lung damage and loss of functionality. To our knowledge, few studies have addressed this issue. Only Liang et al. showed telomere shortening in ICU patients requiring IMV, but it was evaluated solely two days after ICU discharge (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Therefore, additional studies with longer follow-ups are needed to elucidate the impact of the IMV on decreasing RTL and its association with the post-COVID syndrome of patients admitted to the ICU.\u003c/p\u003e \u003cp\u003eIn severe patients with worse evolution of ARDS, a prone position is recommended to improve oxygen saturation and reduce lung damage (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). A prone position significantly reduces the rate of tracheal intubation and mortality (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), although there are also studies with contradictory results (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Moreover, among intubated patients, responders to the prone position in terms of oxygenation show better survival than those who do not respond (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Regarding evolution after discharge, our study showed that COVID-19 patients who required a prone position shortened telomere during follow-up. To our knowledge, these findings are the first to associate the prone position with reduced telomere size in COVID-19 patients during the first year after hospital discharge. Further studies with a longer follow-up would be needed to study whether telomere size evolves to more critical levels in this subgroup of patients.\u003c/p\u003e \u003cp\u003eCOVID-19 patients develop fibrotic pulmonary sequelae (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). There is also an association between telomere shortening in immune cells and lung disease development, such as idiopathic pulmonary fibrosis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In our study, while no significant differences in RTL were observed at baseline, those patients who experienced an RTL shortening during follow-up developed lung fibrosis. Similarly, patients with fibrotic pulmonary sequelae showed shorter RTL at the one-year visit compared to those without radiological abnormalities. To our knowledge, this is the first study assessing the RTL and fibrosis development during follow-up in ICU patients. Still, these findings are in concordance with previous studies in hospitalized patients. McGroder et al. showed that patients with shorter telomere size at hospitalization were more prone to develop fibrotic abnormalities in the lung 4 months later, but the telomere length dynamics were not addressed (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Using a different approach (Quantitative telomere Fluorescence \u003cem\u003ein situ\u003c/em\u003e Hybridization Q-FISH), Mart\u0026iacute;nez et al. found loss of alveolar type II (ATII) cellularity and shorter telomeres in these cells in post-COVID-19 lung cancer patients. Authors suggested that ATII cell telomere reduction may trigger lung fibrosis development in post-COVID-19 patients (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), but these results were produced in a cancer background, and studies on non-lung cancer COVID-19 patients should be addressed. Similarly, Mulet et al., in a recent prospective study (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), described that this attrition could also be evaluated on peripheral blood cells, as COVID-19 patients with radiological signs of fibrosis had significant telomere shortening one year after leaving the hospital. However, this study involved only 19 patients, and the authors did not comment on how they measured telomere length. Retuerto et al. also observed that patients who shortened their peripheral blood leukocyte telomeres after discharge were more prone to show persistent radiographic abnormalities. However, this study was performed during the first pandemic wave, when the hospital admission criteria were exceptional.\u003c/p\u003e \u003cp\u003eOur study is the first to confirm these findings in ICU patients, which is a more homogeneous group that showed similar severity and received similar clinical strategies. However, further studies with a longer follow-up of COVID-19 patients would be needed to establish the role of RTL shortening on fibrotic pulmonary sequelae and vice versa.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eSeveral issues must be considered in order to interpret our data correctly. The sample size was limited as only patients with one-year visit were included in the study. This could have limited the power of the statistical analysis, and some significant associations may not have been detected. However, the statistical analysis used was appropriate to address this issue correctly. This study also has several strengths, such as the fact that all patients were recruited during the second and third pandemic waves, where the ICU admission criteria were similar, and the selected method of measuring telomere length. We measured RTL in whole blood, and its determination could be transferred to routine clinical practice. This study addressed a topic that has been scarcely studied until now in critical patients because the recruitment and follow-up of these patients are arduous. In addition, it should be noted that we analyzed RTL before initiating any mechanical ventilation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, we found that patients with longer ICU stays, need for IMV, and fibrosis development shortened telomere size in the first year after hospital discharge. In addition, patients who required IMV and developed pulmonary fibrosis showed shorter telomeres at one-year visit. These findings suggest that these patients need extensive monitoring as they are at higher risk of developing cellular senescence-related and chronic respiratory complications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAcute respiratory distress syndrome (ARDS)\u003c/p\u003e\n\u003cp\u003eAngiotensin II receptor antagonists (AIIRA)\u003c/p\u003e\n\u003cp\u003eAkaike information criteria (AIC)\u003c/p\u003e\n\u003cp\u003eAlveolar type II (ATII)\u003c/p\u003e\n\u003cp\u003eArithmeticc means ratio (AMR)\u003c/p\u003e\n\u003cp\u003eBody mass index (BMI)\u003c/p\u003e\n\u003cp\u003eConfidence interval (CI)\u003c/p\u003e\n\u003cp\u003eEthylenediaminetetraacetic acid\u0026nbsp;(EDTA)\u003c/p\u003e\n\u003cp\u003eGeneralized linear models (GLMs)\u003c/p\u003e\n\u003cp\u003eIntensive care unit (ICU)\u003c/p\u003e\n\u003cp\u003eInvasive mechanical ventilation (IMV)\u003c/p\u003e\n\u003cp\u003eInterquartile range (IQR)\u003c/p\u003e\n\u003cp\u003eLength of stay (LOS)\u003c/p\u003e\n\u003cp\u003eMonochromatic multiplex real-time quantitative PCR (MMqPCR)\u003c/p\u003e\n\u003cp\u003ePolymerase chain reaction (PCR)\u003c/p\u003e\n\u003cp\u003eQuantitative telomere fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridization (Q-FISH)\u003c/p\u003e\n\u003cp\u003eRelative telomere length (RTL)\u003c/p\u003e\n\u003cp\u003eResearch Electronic Data Capture (REDCap)\u003c/p\u003e\n\u003cp\u003eSequential organ failure assessment\u0026nbsp;(SOFA)\u003c/p\u003e\n\u003cp\u003eStrengthening the reporting of observational studies in epidemiology (STROBE)\u003c/p\u003e\n\u003cp\u003eTelomere length (TL)\u003c/p\u003e\n\u003cp\u003eWorld health organization (WHO)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Committee of the Institute of Health Carlos III (PI 33_2020-v3) and the Investigation Committee of both hospitals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data are available upon request to corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding Details\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from Instituto de Salud Carlos III (ISCIII; grant number COV20/1144 [MPY224/20] to AFR/MAJS) and Fundaci\u0026oacute;n Universidad Alfonso X el Sabio (FUAX) \u0026ndash; Santander (1.013.005). The study was also supported by CIBER \u0026ndash; Consorcio Centro de Investigaci\u0026oacute;n Biom\u0026eacute;dica en Red-(CB 2021), Instituo de Salud Carlos III, Ministerio de Ciencia e Innovaci\u0026oacute;n and Uni\u0026oacute;n Europea \u0026ndash; NextGenerationEU (CB21/13/00044).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026rsquo; Contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding body: MAJS, AFR and RB.\u003c/p\u003e\n\u003cp\u003eStudy concept and design: AFR, MAJS, AVB, OMG and RB.\u003c/p\u003e\n\u003cp\u003ePatients\u0026rsquo; selection and clinical data acquisition: AVB, OMG, RB, EM, MJMP, BLM, CMP.\u003c/p\u003e\n\u003cp\u003eSample preparation and analysis: AVB, SBB, RBL.\u003c/p\u003e\n\u003cp\u003eStatistical analysis and interpretation of data: AVB, SBB, RBL, AFR, and MAJS.\u003c/p\u003e\n\u003cp\u003eWriting of the manuscript: AVB, AFR, and MAJS.\u003c/p\u003e\n\u003cp\u003eCritical revision of the manuscript for relevant intellectual content: SR, RB, OMG.\u003c/p\u003e\n\u003cp\u003eSupervision and visualization: AFR and MAJS.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study would not have been possible without the collaboration of all the patients, their families, medical and nursery staff, and data managers who have taken part in the project.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAnka AU, Tahir MI, Abubakar SD, Alsabbagh M, Zian Z, Hamedifar H, et al. Coronavirus disease 2019 (COVID-19): An overview of the immunopathology, serological diagnosis and management. Scand J Immunol. 2021;93(4):e12998.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang R, Elhusseiny KM, Yeh YC, Sun WZ. COVID-19 ICU and mechanical ventilation patient characteristics and outcomes-A systematic review and meta-analysis. PLoS One. 2021;16(2):e0246318.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolff D, Nee S, Hickey NS, Marschollek M. Risk factors for Covid-19 severity and fatality: a structured literature review. Infection. 2021;49(1):15\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoelsson JP, Asbjarnarson A, Sigurdsson S, Kricker J, Valdimarsdottir B, Thorarinsdottir H, et al. Ventilator-induced lung injury results in oxidative stress response and mitochondrial swelling in a mouse model. 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Aging (Albany NY). 2020;12(20):19911\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaridoss M, Ayyasamy L, Bagepally BS. Is COVID-19 severity associated with telomere length? A systematic review and meta-analysis. Virus Genes. 2023;59(4):489\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVirseda-Berdices A, Concostrina-Martinez L, Martinez-Gonzalez O, Blancas R, Resino S, Ryan P, et al. Relative telomere length impact on mortality of COVID-19: Sex differences. J Med Virol. 2023;95(1):e28368.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchneider CV, Schneider KM, Teumer A, Rudolph KL, Hartmann D, Rader DJ, et al. Association of Telomere Length With Risk of Disease and Mortality. JAMA Intern Med. 2022;182(3):291\u0026ndash;300.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRetuerto M, Lledo A, Fernandez-Varas B, Guerrero-Lopez R, Usategui A, Lalueza A, et al. Shorter telomere length is associated with COVID-19 hospitalization and with persistence of radiographic lung abnormalities. Immun Ageing. 2022;19(1):38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZribi B, Uziel O, Lahav M, Mesilati Stahy R, Singer P. Telomere Length Changes during Critical Illness: A Prospective, Observational Study. Genes (Basel). 2019;10(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBecerra-Munoz VM, Nunez-Gil IJ, Eid CM, Garcia Aguado M, Romero R, Huang J, et al. Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19. 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Arch Bronconeumol. 2024;60(1):62\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"critical-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cric","sideBox":"Learn more about [Critical Care](http://ccforum.biomedcentral.com/)","snPcode":"13054","submissionUrl":"https://submission.nature.com/new-submission/13054/3","title":"Critical Care","twitterHandle":"@Crit_Care","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV2, COVID-19, ARDS, relative telomere length, ICU, IMV.","lastPublishedDoi":"10.21203/rs.3.rs-4471434/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4471434/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSARS-CoV-2 causes virus-induced-senescence. There is an association between shorter telomere length (TL) in COVID-19 patients and hospitalization, severity, or even death. However, it remains unknown whether virus-induced-senescence is reversible. We aim to evaluate the dynamics of TL in COVID-19 patients one year after recovery from intensive care units (ICU). Longitudinal study enrolling 49 patients admitted to ICU due to COVID-19 (August 2020 to April 2021). Relative telomere length (RTL) quantification was carried out in whole blood by monochromatic multiplex real-time quantitative PCR (MMqPCR) assay at hospitalization (baseline) and one year after discharge (one-year visit). The association between RTL and ICU length of stay (LOS), invasive mechanical ventilation (IMV), prone position, and pulmonary fibrosis development at one-year visit. The median age was 60 years, 71.4% were males, median ICU-LOS was 12 days, 73.5% required IMV, and 38.8% required a prone position. Patients with longer ICU-LOS or who required IMV showed greater RTL shortening during follow-up. Patients who required pronation had a greater RTL shortening during follow-up. IMV patients who developed pulmonary fibrosis showed greater RTL reduction and shorter RTL at one-year visit. Patients with longer ICU-LOS and those who required IMV had a shorter RTL in peripheral blood, as observed one year after hospital discharge. Additionally, patients who required IMV and developed pulmonary fibrosis had greater telomere shortening, showing shorter telomeres at one-year visit. These patients may be more prone to develop cellular senescence and lung-related complications; therefore, closer monitoring may be needed.\u003c/p\u003e","manuscriptTitle":"Longer ICU stay and invasive mechanical ventilation accelerate telomere shortening in COVID-19 patients one-year after recovery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-11 18:33:34","doi":"10.21203/rs.3.rs-4471434/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-08T10:34:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-11T12:08:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"253797218066540253623411993680229372815","date":"2024-05-30T11:27:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-29T12:35:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-27T00:01:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-27T00:01:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Critical Care","date":"2024-05-24T09:19:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"critical-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cric","sideBox":"Learn more about [Critical Care](http://ccforum.biomedcentral.com/)","snPcode":"13054","submissionUrl":"https://submission.nature.com/new-submission/13054/3","title":"Critical Care","twitterHandle":"@Crit_Care","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"463a0e6d-10c7-4274-95e6-3bed8be35eb4","owner":[],"postedDate":"June 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-12T16:02:59+00:00","versionOfRecord":{"articleIdentity":"rs-4471434","link":"https://doi.org/10.1186/s13054-024-05051-6","journal":{"identity":"critical-care","isVorOnly":false,"title":"Critical Care"},"publishedOn":"2024-08-07 15:56:57","publishedOnDateReadable":"August 7th, 2024"},"versionCreatedAt":"2024-06-11 18:33:34","video":"","vorDoi":"10.1186/s13054-024-05051-6","vorDoiUrl":"https://doi.org/10.1186/s13054-024-05051-6","workflowStages":[]},"version":"v1","identity":"rs-4471434","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4471434","identity":"rs-4471434","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}