Protective mechanical ventilation controlled by the real-time mechanical energy measurement

Protective mechanical ventilation controlled by the real-time mechanical energy measurement | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Protective mechanical ventilation controlled by the real-time mechanical energy measurement Filip Burša, Michal Frelich, Peter Sklienka, Zuzana Kučerová, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7022366/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Despite the substantial advancements in mechanical ventilation (MV), mortality remains high. Mechanical energy (ME), MV forces are associated with outcomes. Real-time monitoring of ME and the adjustment of MV according to ME may result in ventilation with lower ME. Methods Randomized controled trial conducted at the ECMO Centre Ostrava, Czech Republic, from March 2023 to March 2024 enrolled adult patients on MV (with or without extracorporeal membrane oxygenation, ECMO) with acute respiratory failure. A system for real-time ME monitoring (geometric method and simplified Becher´s formula) has been developed. In the intervention arm, the physician was able to observe the ME in real time and adjust the MV parameters accordingly. In the control group, the ME was concealed. Results A total of 494 subjects were screened and 33 patients were randomized (further 7 ECMO patients). There was no significant difference between the control and intervention groups. Median ME Geom was 3.22 J/min (maximum 15.2 J/min) and ME Becher of 5.94 J/min (maximum 18.4 J/min). Only a weak (but significant, p = 0.0001) correlation between ME Geom and ME Becher was observed. A highly significant difference was observed in ME between day and night (6 a.m. − 6 p.m.). Conclusion Although real-time ME measurement is feasible, there was no significant difference in ME between the control and intervention groups with low ME in both groups. Experience physicians was capable of safe MV, even if they do not know the exact ME value. The night shift was a high-risk period for developing lung damage due to elevated ME. Trial registration ClinicalTrials NCT06035146 mechanical energy protective ventilation ARDS Figures Figure 1 Figure 2 Figure 3 Background Acute respiratory failure (ARF) requiring mechanical ventilation (MV) is one of the most common reasons for admission to the intensive care unit (ICU). The need for MV may arise due to various pulmonary and non-pulmonary impairments, such as pneumonia, acute respiratory distress syndrome (ARDS), or impaired consciousness following traumatic brain injury, multiple trauma, or major surgical procedures. Despite considerable progress in the management of patients with ARF, mortality rates remain high, reaching up to 45% [ 1 ]. The risk of mortality can be further increased by VILI (ventilatory induced lung injury), which can also develop as a complication of non-safe MV itself. Consequently, the implementation of protective MV is a priority not only in patients with primary pulmonary impairments but in all MV patients. Mechanical ventilation is a non-physiological method of repetitive application of pressure to the lung parenchyma. The non-injurious MV setting, lung protective ventilation (LPV)[ 2 ], is a well-known concept leading to the improvement of the outcomes[ 3 ],[ 4 ]. LPV includes 1) prevention of atelectasis by positive end-expiratory pressure (PEEP) titrated to 5 cm H 2 O or more, 2) low driving pressure (DP) of less than 14 cm H 2 O, 3) low tidal volume (V t ) of 6–8 mL/kg predicted body weight and 4) inspiratory plateau pressure of up to 30 cm H 2 O. However, even this setting may not be safe enough for every patient [ 5 ]. Therefore, it is imperative to individualize the MV to prevent lung damage. As mentioned above, injurious MV with high total energy applied to the lung parenchyma can further damage the lung parenchyma, causing VILI[ 6 ][ 7 ]. The concept of mechanical energy (ME)[ 8 ] is based on describing the contribution of individual MV parameters to the total energy applied to the lung parenchyma. ME is, therefore, a summary parameter characterizing the cumulative action of all ventilator-exerted forces on the lungs. Thresholds of ME associated with the development of VILI have been established, suggesting that maintaining ME below these thresholds can be safer [ 9 ]. Although the measurement of ME was introduced as early as the 1960s[ 10 ], it has not been implemented in routine clinical practice so far. The modern ME concept was first described by Gattinoni et al. [ 8 ], who introduced an equation for volume-controlled ventilation. Over time, formulas for pressure-controlled modes of MV were also developed [ 11 ] and simplified equations for bedside ME monitoring introduced, such as the Becher’s method for pressure-controlled MV [ 12 ] , [ 13 ]. Recently, the geometric method of ME calculation (i.e., determining the area under the pressure–volume ventilation curve) [ 14 ] has been proposed and is regarded as the "gold standard" for accurate ME determination; however, this method requires machine-based calculation. Nevertheless, the comparison of ME calculated using the Becher’s method and geometric method has been performed only in a few studies, with only a simplified geometric method used in these studies[ 11 ]. A comparison of the Becher’s method with a computerized, real-time, highly accurate geometric method considering both inspiration and expiration phases and a high-frequency curve record has not been performed yet. An overview of the possibilities of ME calculation and application as (not only) a prognostic parameter was published previously[ 15 , 16 ]. Still, the complexity and variability of ME calculations are among the key reasons of why ME is not routinely used in clinical practice. It is, therefore, imperative to determine whether ME is a suitable instrument for the individualization of care. The objective of this pragmatic study is to evaluate the impact of the availability of real-time ME measurement in routine clinical practice and the feasibility of MV settings. The primary objective of the study was to determine whether displaying ME alongside the common MV parameters could lead to reducing ME values during ventilation. The secondary objectives were (a) to compare ME values obtained using a simplified Becher’s formula and the geometrical method, (b) to compare ME values during the day and night shifts, and (c) to evaluate the differences between patients with MV on ECMO and without ECMO. Methods Study site and characteristics : A monocentric prospective randomized clinical trial was conducted at the ECMO Centre, Intensive Care Department of the University Hospital Ostrava, Czech Republic, from March 2023 to March 2024. The study was approved by the Ethics Committee of the University Hospital Ostrava (reference Number 517/2022; 25/RVO-FNOs/2022). For unconscious patients, informed consent was signed by two health professionals not involved in the study and/or by a close relative of the patient. The trial was registered at ClinicalTrials.gov on February 15, 2023, NCT06035146. Inclusion and exclusion criteria : The study included 1) patients (both non-ECMO and veno-venous ECMO) with fully pressure-controlled MV, 2) older than 18 years, 3) with primary pulmonary involvement (pneumonia, ARDS), and 4) expected duration of MV longer than 48 hours. Exclusion criteria were 1) patients on assisted or spontaneous ventilation, 2) pregnant women (pregnancy status based on the admission protocol), 3) ICU admission within more than 24 hours of the start of MV, and 4) MV less than 2 days. Data measurement and collection : A system for real-time ME calculation and data archiving has been developed. Ventilator data were encrypted and archived on a server at the VSB – Technical University Ostrava. The system was run on a web interface “VentenApp” serving to: 1) randomize patients and assign them to the interventional or control arms, 2) enter their parameters (demographic data, ventilator mode, ECMO support, etc.), and 3) monitor ME in real time. Ventilator data were acquired using a custom-designed device developed specifically for this study. The device is based on an ESP32 microcontroller and includes two RS232 interfaces, enabling simultaneous connection to two ports on a ventilator (Hamilton G5, Hamilton Medical AG, Via Crusch 8, 7402 Bonaduz, Switzerland)—one for parameter data and the other for waveform data. The collected data were transmitted via Wi-Fi to an IoT server, where they were aggregated and visualized through a web-based interface showing ventilatory parameters and ME values computed using both Becher’s approximation (ME Becher ) and a geometric method based on the trapezoidal rule (ME Geom ). Subsequently, all data were exported and processed into minute-level averages of all recorded parameters. Data artifacts, such as those caused by ventilator holds or unexpected events, were identified electronically and excluded during the data cleaning phase. In the intervention arm, the physicians were able to observe the ME in real time and adjust the MV parameters accordingly. This pragmatic study observed standard practices; consequently, the setting of the MV was not strictly dictated by the protocol. Typically, the physician examined the patient several (at least three) times a day. The ME value was displayed alongside other parameters on a tablet at the patient's bedside, and the medical staff was able to conduct continuous monitoring. At the beginning of the study, all attending physicians were instructed that ME values above 17 J/min should be prevented as such values have been reported to be associated with adverse outcomes[ 17 ]. In the control group, the ME values were hidden, and the physicians adjusted MV parameters following the best clinical practice to ensure a protective MV setting. The data were collected every 130ms and minute averages of ME values were stored. ME values were calculated using two methods, namely a) according to the formula presented by Becher et al.[ 13 ]: ME = 0.098 × respiratory rate × Vt × (PEEP + DP), and b) using the geometric method[ 8 ] as the area under the pressure-volume curve plotted at 20 ms intervals and then converted into minute averages. It is necessary to emphasize that this study evaluated ME for the entire respiratory system (not ME exclusively for the lung, which would require esophageal pressure monitoring). In addition, ME values normalized to BMI (ME Geometric_BMI and ME Becher_BMI ) and lung compliance (ME Geometric_C and ME Becher_C ) were also calculated. Subsequently, differences in ME between ECMO and non-ECMO patients were also analyzed. Besides, ME during day (6AM-6PM) and night shifts were compared to find out if the lower personnel availability during night shifts affects the ME values, with additional anylse of patients with comliance under 20 cm H 2 O. Data analysis: The level of statistical significance was set at α = 0.05. Categorical variables were characterized by the absolute counts and relative frequencies (in %). Fisher's exact test was employed to assess the statistical differences between groups. Numeric variables were reported as medians with 25–75% quantiles (interquartile range, IQR) and statistically tested with a non-parametric two-sample Wilcoxon rank-sum test. Resulting p-values were adjusted for multiple comparisons using the Holm method. Associations between repeatedly measured variables (e.g., ME Becher vs ME Geometric ) were assessed using linear mixed-effects models. The significance of the fixed effect coefficients was tested using the Satterthwaite's method. The mixed models accounted for per-subject intercept as a random effect. Linear mixed models were fitted with numerical variables normalized with non-linear transformations. The best transformation was selected by the five times repeated out-of-sample 10-fold cross-validation method with Pearson P statistic as the selection criterion. The ME Becher values were standardized using the Yeo-Johnson transformation, the ME Geometric values using the Box Cox transformation. All statistical analyses were performed in R version 4.1.3. R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria [ 18 ]. Results In all, 40 patients met the inclusion and exclusion criteria. Unfortunately, only seven patients who met the inclusion and exclusion criteria were on ECMO at the time of MV patients (two patients in the intervention group and five in the control group), which precluded their meaningful statistical comparison in the primary endpoint. As a significant portion of the gas exchange in these patients is facilitated by ECMO and a more lung-protective ventilation can be applied, they were also removed from the primary analysis, which therefore, only considered non-ECMO patients on MV (Fig. 1.). In all, 222,462 measurements were taken in the non-ECMO group. The control and intervention groups did not differ in baseline parameters (Table 1). ARDS was slightly more common in the intervention group (52% vs 31%), which also had a slightly higher APACHE II score; these differences were, however, not statistically significant. The only significant difference between the control and intervention groups was observed in the SpO 2 /FiO 2 ratio, with a more severe oxygenation failure found in the intervention group (p = 0.0014). No statistically significant difference in ME was detected between the control and intervention groups (see Fig. 2., Table 2.), regardless of whether absolute ME values or ME values normalized to BMI or lung compliance were used for the comparisons. The median ME Geom calculated over all measurements in all 33 patients included in the primary analysis was as low as 3.22 J/min, with a maximum of 15.2 J/min and the Becher method of calculation (median of 5.94 J/min and a maximum of 18.4 J/min). The fact that the non-ECMO control and intervention groups were comparable both in baseline parameters (Table 1) and in ME values allowed us to combine these groups for an additional comparison of ME values between the non-ECMO group as a whole and the combined ECMO group in whom higher level of lung protective ventilation was applied[19, 20]. The ECMO group had significantly worse initial oxygenation (initial SpO2/FiO2, p = 0.014 ), longer MV (p = 0.01), and longer ICU stay (p = 0.02), see Table 1. The prevalence of ARDS was notably high in the ECMO group (85% of patients). In all, 90,895 measurements were taken in the ECMO group. Lower ME Becher values (median 4.99; IQR 3.96–5.31; β = -0.93) were observed in the ECMO group than in the non-ECMO group (6.20; 5.71–8.03; p = 0.0102). The same was true after normalization to BMI – median ME Becher 0.20 (0.16–0.22) in the ECMO group vs 0.23 (0.20–0.27; p = 0.0316) in the non-ECMO group. When the geometric method was used for ME calculation, significant differences between the ECMO and non-ECMO groups were detected only in ME Geometric_C (p = 0.01). A highly significant difference in ME was observed when comparing day (6AM − 6 PM) and night (6 PM − 6 AM) in the combined group of non-ECMO patients, see Fig. 3. The results were significant both when using the geometric method (median ME Geometric−day of 3.15 (2.07–5.24) J/min vs ME Geometric−night of 3.48 (2.48–6.24) J/min; p < 0.001) and the Becher calculation (median day ME Becher−day of 5.76 (4.36–7.56) J/min vs median ME Becher−night of 6.44 (5.39–8.32) J/min; p < 0.001). This was true both for absolute values and specific ME normalized to BMI or lung compliance. The difference was even more pronounced in patients with lung compliance below 20 cm H 2 O/mL (Fig. 3). Interestingly, although the correlation between ME calculated using the geometric method and the Becher formula was statistically significant (p < 0.0001), practically no clinically meaningful correlation (r = − 0.08), was detected. Discussion The study demonstrated that the real-time monitoring of ME is a feasible approach. Our main findings are: 1) The ventilation of patients in both the intervention and control groups occurred with very low ME, with the analysis revealing no statistical difference between these groups, 2) lower ME was found in patients on ECMO support, and 3) ME was lower during a day than at night. ME is a global parameter assessing the composite effect of individual MV parameters on the lung parenchyma [ 8 ]. It is, however, not all-powerful – the idea that the risk of VILI can be fully avoided simply by complying with some ME limit is (albeit attractive) naive [ 21 ]. Even if ME is low, the lung may be damaged by low PEEP and too much lung collapse (and, consequently, higher driving pressure necessary to ensure gas exchange), overdistension from high ventilatory support, etc. The ME concept does not take into account the influence of the O 2 fraction at all, although high FiO 2 can cause hyperoxia-induced lung damage[ 22 ]. Still, it is reasonable to assume that ventilation with ME exceeding a certain limit increases the risk of VILI and is associated with higher mortality; this risk increases with the higher degree of lung damage [ 23 ]. ME also represents the information about the disease severity or else a higher ME could serve as an indicator of the severity of lung damage [ 24 ]. It should be noted that VILI arises as a result of the energy applied to the lung parenchyma (ME lung , mechanical energy of the lung), but monitoring of transpulmonary pressure (P tp ) is required to extract this portion of energy (from the total ME rs ; ME rs , mechanical energy of the respiratory system-lungs, airways, chest wall). Measurement of P tp is, however, not a routinely monitored parameter and may be burdened by measurement errors[ 25 ]. Moreover, a special probe inserted into the esophagus is needed to measure it. Still, the relationship between ME rs and ME lung is usually linear; therefore, limits for the development of VILI have been derived for both ME lung and ME rs, and measurement of ME rs can be considered as a reasonable surrogate for the ME lung [ 26 ]. ME rs higher than 17 J/min was associated with higher in-hospital mortality, as found in an observational study of more than 8,000 patients as well as in other studies[ 17 , 21 , 27 – 29 ]. ME above 8.5 J/min was associated with general anesthesia-related pulmonary complications, especially in unilateral lung ventilation during thoracic surgery. It depends not only on the ME itself but also on the duration of the MV with excessive ME [ 30 ] and on the accumulation and regenerative capacity of the lung[ 31 ]. The present study did not demonstrate the benefit of adjusting the MV parameters according to ME measured in real time as the differences between the intervention and control groups were not statistically significant (although the absolute value ME Geometric tended to be lower in the intervention group). This may, however, be influenced by the fact that the presented study was performed at an ICU that specializes in ARDS patients and ECMO support and ME was so low even in the control group (below ME tresholds). It is a common practice at our department that if we are not able to provide protective MV, the patient is indicated for ECMO support. Increased mortality was observed in a study by Serpa et al.[ 17 ] only when the value of 17 J/min was exceeded. In the study by Parhar et al., higher value of 22 J/min was found to be the threshold for increased mortality[ 28 ]. The fact that the recommended threshold was set at 17 J/min in our study might be an additional reason for not finding any benefits of ME measurement – as ventilation was typically already set protectively, and the shown ME values were very low, there was no need to intervene and change the settings to further reducing ME. One of the most striking results of our study was the observation of the diurnal variation in ME . This may be explained by multiple factors. Firstly, interventions and examinations are performed during the day, which is associated with the handling of patients and their transport and potentially patient-ventilator interference. On the other hand, daytime is a period of more frequent MV parameters checking, deepening of sedation if interfering, as more staff are present at the ICU than at night. Conversely, during nocturnal hours, our objective is to facilitate sleep and promote a state of tranquility in patients. This approach involves a reduction in the frequency of disturbances compared to those that occur during daytime hours. For the purposes of this study, daytime was set from 6 a.m. to 6 p.m., corresponding to the ICU shift change, and also when the patients get bed bath (usually between 8–9 a.m. and p.m.). During the day, ME was statistically significantly lower than during the night in all measurements, and the difference was particularly pronounced in patients with lower lung compliance and more severe lung involvement. It is, therefore, important that in times of fewer staff and less frequent checks, mechanisms to control dangerous ventilation are still in place for patients. In our data, only a weak correlation was found between ME measured by the geometric method and the Becher calculation. The high statistical significance of such a small correlation was likely caused by the large number of repeated measurements. This finding is highly interesting, considering that the geometric method should be an exact method, with ME corresponding to the area under the pressure-volume curve. The curve was rendered very accurately with 20 ms intervals, so the distortion should be minimal. From that perspective, the fact that the correlation with Becher’s method of calculation is very weak indicates that simplified equations, despite their undeniable advantage of simple bedside calculation, can introduce inaccuracies. One of the reasons for this may lie in the fact that Becher's calculation is a simplification of Van Der Meijden's equation[ 32 ], assuming constant airway resistance. However, airway resistance is a function of the airflow and changes during inspiration, which reduces the accuracy of results obtained using this equation. Moreover, Becher's simplification assumes that the pressure wave is ideally squared. The equations do not take into account the inspiratory rise time, although this parameter should not be essential[ 13 ]. Despite this, in the work of Chiumello et al. [ 11 ] high accuracy of the Becher formula with a bias of -0.81 J/min was determined (r 2 = 0.94, p < 0.001). Limitations The main limitation of the study is the small sample size of patients. Usually, patients at our department are ventilated with some degree of assisted ventilation as this helps, among other things, to reduce the risks of respiratory muscle atrophy, and we try to keep sedation as low as possible. However, such patients (i.e., the majority of all patients at the department) had to be excluded from the analyses as ME calculations are accurate only in patients with fully controlled MV. Conclusion The implementation of real-time ME measurement as a tool for the adjustment of MV parameters is feasible. We found that in an ICU of a tertiary centre with good experience with ARDS management and principles of protective ventilation, patients were ventilated with a sufficiently low ME even without knowledge of ME, resulting in no observed difference in ME applied to the patients between the intervention group (with knowledge of ME) and control group (without the knowledge of ME) and both groups were ventilated with very low ME. Significantly higher ME was observed during the night shift, which indicates this period to be more risky in terms of the development ventilation-induced lung damage. Declarations Acknowledgements: Not applicable Ethics approval : The study was approved by the Ethics Committee of the University Hospital Ostrava. Informed consent was obtained from all individual participants included in the study. Author Contributions : FB : Conceptualization, Original draft preparation, Approval of the final text; MF: Conducting the research and investigation process, Approval of the final text; PS : Supervision, Critical revision of the manuscript, Approval of the final text; ZK : Digitalization of the dataset, Approval of the final text; JS : Conducting the research and investigation process, Approval of the final text; DO : design of the machine and the software for ME measurement, data archiving, cleaning, and exporting, Approval of the final text; MP : debug the software, conducting the research and investigation process, Approval of the final text; MB : Statistical analysis, Approval of the final text and JM : Review & Editing, Approval of the final text Funding: This work and the contributions were supported by: the Ministry of Health, Czech Republic – conceptual development of research organization (FNOs/2025). partially supported from the project ``Research of Excellence on Digital Technologies and Wellbeing CZ.02.01.01/00/22_008/0004583'' which is co-financed by the European Union financial support of the European Union under the LERCO project number CZ.10.03.01/00/22_003/0000003 via the Operational Programme Just Transition Competing Interests: The authors have no comment of interest in relation to the manuscript. 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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-7022366","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498060444,"identity":"d95d5426-bb66-4846-9206-200dc1eb1982","order_by":0,"name":"Filip Burša","email":"","orcid":"","institution":"University Hospital Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Filip","middleName":"","lastName":"Burša","suffix":""},{"id":498060445,"identity":"4fcb175c-4a10-458b-a56c-6bfcd759f9e5","order_by":1,"name":"Michal Frelich","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIie3QsQrCMBCA4QuFugS6XqngEwhxaRHEZ6kIzo5OJUVoF30fx4QMLsWuQhddnBx0U3AwVUFc0o4O+cmQ5eOSA7DZ/jEHXIA5ePrGBeEjryVh4HMgNZnpS3Nfoo9qJv3cOR1uDDDK01TcNyVGHU6uNwMJlRsNVpp0C8nluqhwuBIOopFQFymDBHHCFcmqhO1jV7/UTPyHnoK9Y012+CJxAwloTZDURLyJMP8lDLpMCzrRf8mmyAq5NK4tLNXJPy9GiB2lLvdsjGy7lMaNffrZEDHNsNlsNlubntgSSUWMTn3pAAAAAElFTkSuQmCC","orcid":"","institution":"University Hospital Ostrava","correspondingAuthor":true,"prefix":"","firstName":"Michal","middleName":"","lastName":"Frelich","suffix":""},{"id":498060446,"identity":"56e32ccd-1bb3-4f6b-bd33-b544e2bdef11","order_by":2,"name":"Peter Sklienka","email":"","orcid":"","institution":"University Hospital Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Sklienka","suffix":""},{"id":498060447,"identity":"614f43ee-1774-46f6-8cd2-54aca54c30bc","order_by":3,"name":"Zuzana Kučerová","email":"","orcid":"","institution":"University Hospital Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Zuzana","middleName":"","lastName":"Kučerová","suffix":""},{"id":498060448,"identity":"0c050198-7201-40a6-b26a-7c5535d3a0f7","order_by":4,"name":"Jiří Sagan","email":"","orcid":"","institution":"University Hospital Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Jiří","middleName":"","lastName":"Sagan","suffix":""},{"id":498060449,"identity":"bf6f23ce-ecbd-4cb0-b8f6-cb460ca22be4","order_by":5,"name":"David Oczka","email":"","orcid":"","institution":"Vysoka skola banska - Technical unversity of Ostrava","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Oczka","suffix":""},{"id":498060450,"identity":"9691b016-3586-45a3-ba28-d25c698fcc67","order_by":6,"name":"Marek Penhaker","email":"","orcid":"","institution":"Vysoka skola banska - Technical unversity of Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Marek","middleName":"","lastName":"Penhaker","suffix":""},{"id":498060451,"identity":"673cd9d2-68cc-476b-93e4-c10dfd7c2ca0","order_by":7,"name":"Michal Burda","email":"","orcid":"","institution":"University of Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Michal","middleName":"","lastName":"Burda","suffix":""},{"id":498060452,"identity":"5d579f5e-5345-4e05-866c-a011c6aa777c","order_by":8,"name":"Jan Máca","email":"","orcid":"","institution":"University Hospital Ostrava","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Máca","suffix":""}],"badges":[],"createdAt":"2025-07-01 16:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7022366/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7022366/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88891185,"identity":"9d5ffb71-e144-48b4-81f1-4ece7efbdb33","added_by":"auto","created_at":"2025-08-12 12:49:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":90386,"visible":true,"origin":"","legend":"\u003cp\u003ePatient selection and randomization.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7022366/v1/8a06606b14d679bd75ad2b7a.png"},{"id":88891186,"identity":"c6c3b83b-a891-49ff-8c1e-299a4a47c46c","added_by":"auto","created_at":"2025-08-12 12:49:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":95755,"visible":true,"origin":"","legend":"\u003cp\u003eMEGeometric and MEBecher in non-ECMO patients stratified according to the control vs intervention group and normalized values\u003cem\u003e; Interv – intervention, _BMI – normalized to BMI; _C – normalized to lung compliance\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7022366/v1/2fb96101ec62b73978b915d1.png"},{"id":88891188,"identity":"50d8e5a6-5e7a-436f-bff4-0f0b302092ba","added_by":"auto","created_at":"2025-08-12 12:49:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":90502,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of geometric ME during day and night (from 6 AM to 6 PM vs 6\u0026nbsp;PM to 6\u0026nbsp;AM) in patients with compliance under 20 cm H\u003csub\u003e2\u003c/sub\u003eO/ml.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7022366/v1/7e0231f63c1b1cb74ade2072.png"},{"id":88897746,"identity":"711087b7-8040-4d4f-80ca-e95543c1842a","added_by":"auto","created_at":"2025-08-12 13:13:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":822609,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7022366/v1/d96084a0-aa9e-4d67-93af-39d90aa457f9.pdf"},{"id":88891184,"identity":"2f041283-64cd-483f-8fb4-780b68db8854","added_by":"auto","created_at":"2025-08-12 12:49:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":80556,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7022366/v1/5dfc4bbbc984d69ef3e21c3c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Protective mechanical ventilation controlled by the real-time mechanical energy measurement","fulltext":[{"header":"Background","content":"\u003cp\u003eAcute respiratory failure (ARF) requiring mechanical ventilation (MV) is one of the most common reasons for admission to the intensive care unit (ICU). The need for MV may arise due to various pulmonary and non-pulmonary impairments, such as pneumonia, acute respiratory distress syndrome (ARDS), or impaired consciousness following traumatic brain injury, multiple trauma, or major surgical procedures. Despite considerable progress in the management of patients with ARF, mortality rates remain high, reaching up to 45% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The risk of mortality can be further increased by VILI (ventilatory induced lung injury), which can also develop as a complication of non-safe MV itself. Consequently, the implementation of protective MV is a priority not only in patients with primary pulmonary impairments but in all MV patients.\u003c/p\u003e\u003cp\u003eMechanical ventilation is a non-physiological method of repetitive application of pressure to the lung parenchyma. The non-injurious MV setting, lung protective ventilation (LPV)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], is a well-known concept leading to the improvement of the outcomes[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e],[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. LPV includes 1) prevention of atelectasis by positive end-expiratory pressure (PEEP) titrated to 5 cm H\u003csub\u003e2\u003c/sub\u003eO or more, 2) low driving pressure (DP) of less than 14 cm H\u003csub\u003e2\u003c/sub\u003eO, 3) low tidal volume (V\u003csub\u003et\u003c/sub\u003e) of 6–8 mL/kg predicted body weight and 4) inspiratory plateau pressure of up to 30 cm H\u003csub\u003e2\u003c/sub\u003eO. However, even this setting may not be safe enough for every patient [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, it is imperative to individualize the MV to prevent lung damage.\u003c/p\u003e\u003cp\u003eAs mentioned above, injurious MV with high total energy applied to the lung parenchyma can further damage the lung parenchyma, causing VILI[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The concept of mechanical energy (ME)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] is based on describing the contribution of individual MV parameters to the total energy applied to the lung parenchyma. ME is, therefore, a summary parameter characterizing the cumulative action of all ventilator-exerted forces on the lungs. Thresholds of ME associated with the development of VILI have been established, suggesting that maintaining ME below these thresholds can be safer [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough the measurement of ME was introduced as early as the 1960s[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], it has not been implemented in routine clinical practice so far. The modern ME concept was first described by Gattinoni et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], who introduced an equation for volume-controlled ventilation. Over time, formulas for pressure-controlled modes of MV were also developed [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and simplified equations for bedside ME monitoring introduced, such as the Becher’s method for pressure-controlled MV [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003csup\u003e,\u003c/sup\u003e [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Recently, the geometric method of ME calculation (i.e., determining the area under the pressure–volume ventilation curve) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] has been proposed and is regarded as the \"gold standard\" for accurate ME determination; however, this method requires machine-based calculation. Nevertheless, the comparison of ME calculated using the Becher’s method and geometric method has been performed only in a few studies, with only a simplified geometric method used in these studies[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A comparison of the Becher’s method with a computerized, real-time, highly accurate geometric method considering both inspiration and expiration phases and a high-frequency curve record has not been performed yet.\u003c/p\u003e\u003cp\u003eAn overview of the possibilities of ME calculation and application as (not only) a prognostic parameter was published previously[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Still, the complexity and variability of ME calculations are among the key reasons of why ME is not routinely used in clinical practice. It is, therefore, imperative to determine whether ME is a suitable instrument for the individualization of care.\u003c/p\u003e\u003cp\u003eThe objective of this pragmatic study is to evaluate the impact of the availability of real-time ME measurement in routine clinical practice and the feasibility of MV settings. The primary objective of the study was to determine whether displaying ME alongside the common MV parameters could lead to reducing ME values during ventilation. The secondary objectives were (a) to compare ME values obtained using a simplified Becher’s formula and the geometrical method, (b) to compare ME values during the day and night shifts, and (c) to evaluate the differences between patients with MV on ECMO and without ECMO.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStudy site and characteristics\u003c/span\u003e:\u003c/p\u003e\u003cp\u003e A monocentric prospective randomized clinical trial was conducted at the ECMO Centre, Intensive Care Department of the University Hospital Ostrava, Czech Republic, from March 2023 to March 2024. The study was approved by the Ethics Committee of the University Hospital Ostrava (reference Number 517/2022; 25/RVO-FNOs/2022). For unconscious patients, informed consent was signed by two health professionals not involved in the study and/or by a close relative of the patient. The trial was registered at ClinicalTrials.gov on February 15, 2023, NCT06035146.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eInclusion and exclusion criteria\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eThe study included 1) patients (both non-ECMO and veno-venous ECMO) with fully pressure-controlled MV, 2) older than 18 years, 3) with primary pulmonary involvement (pneumonia, ARDS), and 4) expected duration of MV longer than 48 hours. Exclusion criteria were 1) patients on assisted or spontaneous ventilation, 2) pregnant women (pregnancy status based on the admission protocol), 3) ICU admission within more than 24 hours of the start of MV, and 4) MV less than 2 days.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eData measurement and collection\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eA system for real-time ME calculation and data archiving has been developed. Ventilator data were encrypted and archived on a server at the VSB – Technical University Ostrava. The system was run on a web interface “VentenApp” serving to: 1) randomize patients and assign them to the interventional or control arms, 2) enter their parameters (demographic data, ventilator mode, ECMO support, etc.), and 3) monitor ME in real time.\u003c/p\u003e\u003cp\u003eVentilator data were acquired using a custom-designed device developed specifically for this study. The device is based on an ESP32 microcontroller and includes two RS232 interfaces, enabling simultaneous connection to two ports on a ventilator (Hamilton G5, Hamilton Medical AG, Via Crusch 8, 7402 Bonaduz, Switzerland)—one for parameter data and the other for waveform data. The collected data were transmitted via Wi-Fi to an IoT server, where they were aggregated and visualized through a web-based interface showing ventilatory parameters and ME values computed using both Becher’s approximation (ME\u003csub\u003eBecher\u003c/sub\u003e) and a geometric method based on the trapezoidal rule (ME\u003csub\u003eGeom\u003c/sub\u003e). Subsequently, all data were exported and processed into minute-level averages of all recorded parameters. Data artifacts, such as those caused by ventilator holds or unexpected events, were identified electronically and excluded during the data cleaning phase.\u003c/p\u003e\u003cp\u003eIn the intervention arm, the physicians were able to observe the ME in real time and adjust the MV parameters accordingly. This pragmatic study observed standard practices; consequently, the setting of the MV was not strictly dictated by the protocol. Typically, the physician examined the patient several (at least three) times a day. The ME value was displayed alongside other parameters on a tablet at the patient's bedside, and the medical staff was able to conduct continuous monitoring. At the beginning of the study, all attending physicians were instructed that ME values above 17 J/min should be prevented as such values have been reported to be associated with adverse outcomes[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In the control group, the ME values were hidden, and the physicians adjusted MV parameters following the best clinical practice to ensure a protective MV setting. The data were collected every 130ms and minute averages of ME values were stored. ME values were calculated using two methods, namely a) according to the formula presented by Becher et al.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]:\u003c/p\u003e\u003cp\u003eME = 0.098 × respiratory rate × Vt × (PEEP + DP),\u003c/p\u003e\u003cp\u003eand b) using the geometric method[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] as the area under the pressure-volume curve plotted at 20 ms intervals and then converted into minute averages. It is necessary to emphasize that this study evaluated ME for the entire respiratory system (not ME exclusively for the lung, which would require esophageal pressure monitoring). In addition, ME values normalized to BMI (ME\u003csub\u003eGeometric_BMI\u003c/sub\u003e and ME\u003csub\u003eBecher_BMI\u003c/sub\u003e) and lung compliance (ME\u003csub\u003eGeometric_C\u003c/sub\u003e and ME\u003csub\u003eBecher_C\u003c/sub\u003e) were also calculated.\u003c/p\u003e\u003cp\u003eSubsequently, differences in ME between ECMO and non-ECMO patients were also analyzed. Besides, ME during day (6AM-6PM) and night shifts were compared to find out if the lower personnel availability during night shifts affects the ME values, with additional anylse of patients with comliance under 20 cm H\u003csub\u003e2\u003c/sub\u003eO.\u003c/p\u003e\u003ch2\u003eData analysis:\u003c/h2\u003e\u003cp\u003eThe level of statistical significance was set at α = 0.05. Categorical variables were characterized by the absolute counts and relative frequencies (in %). Fisher's exact test was employed to assess the statistical differences between groups. Numeric variables were reported as medians with 25–75% quantiles (interquartile range, IQR) and statistically tested with a non-parametric two-sample Wilcoxon rank-sum test. Resulting p-values were adjusted for multiple comparisons using the Holm method.\u003c/p\u003e\u003cp\u003eAssociations between repeatedly measured variables (e.g., ME\u003csub\u003eBecher\u003c/sub\u003e vs ME\u003csub\u003eGeometric\u003c/sub\u003e) were assessed using linear mixed-effects models. The significance of the fixed effect coefficients was tested using the Satterthwaite's method. The mixed models accounted for per-subject intercept as a random effect. Linear mixed models were fitted with numerical variables normalized with non-linear transformations. The best transformation was selected by the five times repeated out-of-sample 10-fold cross-validation method with Pearson P statistic as the selection criterion. The ME\u003csub\u003eBecher\u003c/sub\u003e values were standardized using the Yeo-Johnson transformation, the ME\u003csub\u003eGeometric\u003c/sub\u003e values using the Box Cox transformation.\u003c/p\u003e\u003cp\u003eAll statistical analyses were performed in R version 4.1.3. R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn all, 40 patients met the inclusion and exclusion criteria. Unfortunately, only seven patients who met the inclusion and exclusion criteria were on ECMO at the time of MV patients (two patients in the intervention group and five in the control group), which precluded their meaningful statistical comparison in the primary endpoint. As a significant portion of the gas exchange in these patients is facilitated by ECMO and a more lung-protective ventilation can be applied, they were also removed from the primary analysis, which therefore, only considered non-ECMO patients on MV (Fig. 1.).\u003c/p\u003e\n\u003cp\u003eIn all, 222,462 measurements were taken in the non-ECMO group. The control and intervention groups did not differ in baseline parameters (Table 1). ARDS was slightly more common in the intervention group (52% vs 31%), which also had a slightly higher APACHE II score; these differences were, however, not statistically significant. The only significant difference between the control and intervention groups was observed in the SpO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e ratio, with a more severe oxygenation failure found in the intervention group (p = 0.0014).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNo statistically significant difference in ME was detected between the \u003cstrong\u003econtrol and intervention groups\u003c/strong\u003e (see Fig. 2., Table 2.), regardless of whether absolute ME values or ME values normalized to BMI or lung compliance were used for the comparisons. The median ME\u003csub\u003eGeom\u003c/sub\u003e calculated over all measurements in all 33 patients included in the primary analysis was as low as 3.22 J/min, with a maximum of 15.2 J/min and the Becher method of calculation (median of 5.94 J/min and a maximum of 18.4 J/min).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe fact that the non-ECMO control and intervention groups were comparable both in baseline parameters (Table 1) and in ME values allowed us to combine these groups for an additional comparison of ME values between the non-ECMO group as a whole and the combined ECMO group in whom higher level of lung protective ventilation was applied[19, 20]. The ECMO group had significantly worse initial oxygenation (initial SpO2/FiO2, p = 0.014 ), longer MV (p = 0.01), and longer ICU stay (p = 0.02), see Table 1. The prevalence of ARDS was notably high in the ECMO group (85% of patients). In all, 90,895 measurements were taken in the ECMO group. Lower ME\u003csub\u003eBecher\u003c/sub\u003e values (median 4.99; IQR 3.96–5.31; β = -0.93) were observed in the ECMO group than in the non-ECMO group (6.20; 5.71–8.03; p = 0.0102). The same was true after normalization to BMI – median ME\u003csub\u003eBecher\u003c/sub\u003e 0.20 (0.16–0.22) in the ECMO group vs 0.23 (0.20–0.27; p = 0.0316) in the non-ECMO group. When the geometric method was used for ME calculation, significant differences between the ECMO and non-ECMO groups were detected only in ME\u003csub\u003eGeometric_C\u003c/sub\u003e (p = 0.01).\u003c/p\u003e\n\u003cp\u003eA highly significant difference in ME was observed when \u003cstrong\u003ecomparing day\u003c/strong\u003e (6AM − 6 PM) \u003cstrong\u003eand night\u003c/strong\u003e (6 PM − 6 AM) in the combined group of non-ECMO patients, see Fig. 3. The results were significant both when using the geometric method (median ME\u003csub\u003eGeometric−day\u003c/sub\u003e of 3.15 (2.07–5.24) J/min vs ME\u003csub\u003eGeometric−night\u003c/sub\u003e of 3.48 (2.48–6.24) J/min; p \u0026lt; 0.001) and the Becher calculation (median day ME\u003csub\u003eBecher−day\u003c/sub\u003e of 5.76 (4.36–7.56) J/min vs median ME\u003csub\u003eBecher−night\u003c/sub\u003e of 6.44 (5.39–8.32) J/min; p \u0026lt; 0.001). This was true both for absolute values and specific ME normalized to BMI or lung compliance. The difference was even more pronounced in patients with lung compliance below 20 cm H\u003csub\u003e2\u003c/sub\u003eO/mL (Fig. 3).\u003c/p\u003e\n\u003cp\u003eInterestingly, although the correlation between ME calculated using the geometric method and the Becher formula was statistically significant (p \u0026lt; 0.0001), practically no clinically meaningful correlation (r = − 0.08), was detected.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study demonstrated that the real-time monitoring of ME is a feasible approach. Our main findings are: 1) The ventilation of patients in both the intervention and control groups occurred with very low ME, with the analysis revealing no statistical difference between these groups, 2) lower ME was found in patients on ECMO support, and 3) ME was lower during a day than at night.\u003c/p\u003e\u003cp\u003eME is a global parameter assessing the composite effect of individual MV parameters on the lung parenchyma [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. It is, however, not all-powerful \u0026ndash; the idea that the risk of VILI can be fully avoided simply by complying with some ME limit is (albeit attractive) naive [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Even if ME is low, the lung may be damaged by low PEEP and too much lung collapse (and, consequently, higher driving pressure necessary to ensure gas exchange), overdistension from high ventilatory support, etc. The ME concept does not take into account the influence of the O\u003csub\u003e2\u003c/sub\u003e fraction at all, although high FiO\u003csub\u003e2\u003c/sub\u003e can cause hyperoxia-induced lung damage[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Still, it is reasonable to assume that ventilation with ME exceeding a certain limit increases the risk of VILI and is associated with higher mortality; this risk increases with the higher degree of lung damage [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. ME also represents the information about the disease severity or else a higher ME could serve as an indicator of the severity of lung damage [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIt should be noted that VILI arises as a result of the energy applied to the lung parenchyma (ME\u003csub\u003elung\u003c/sub\u003e, mechanical energy of the lung), but monitoring of transpulmonary pressure (P\u003csub\u003etp\u003c/sub\u003e) is required to extract this portion of energy (from the total ME\u003csub\u003ers\u003c/sub\u003e ; ME\u003csub\u003ers\u003c/sub\u003e, mechanical energy of the respiratory system-lungs, airways, chest wall). Measurement of P\u003csub\u003etp\u003c/sub\u003e is, however, not a routinely monitored parameter and may be burdened by measurement errors[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Moreover, a special probe inserted into the esophagus is needed to measure it. Still, the relationship between ME\u003csub\u003ers\u003c/sub\u003e and ME\u003csub\u003elung\u003c/sub\u003e is usually linear; therefore, limits for the development of VILI have been derived for both ME\u003csub\u003elung\u003c/sub\u003e and ME\u003csub\u003ers,\u003c/sub\u003e and measurement of ME\u003csub\u003ers\u003c/sub\u003e can be considered as a reasonable surrogate for the ME\u003csub\u003elung\u003c/sub\u003e [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. ME\u003csub\u003ers\u003c/sub\u003e higher than 17 J/min was associated with higher in-hospital mortality, as found in an observational study of more than 8,000 patients as well as in other studies[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. ME above 8.5 J/min was associated with general anesthesia-related pulmonary complications, especially in unilateral lung ventilation during thoracic surgery. It depends not only on the ME itself but also on the duration of the MV with excessive ME [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and on the accumulation and regenerative capacity of the lung[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe present study did not demonstrate the benefit of adjusting the MV parameters according to ME measured in real time as the differences between the \u003cb\u003eintervention and control groups\u003c/b\u003e were not statistically significant (although the absolute value ME\u003csub\u003eGeometric\u003c/sub\u003e tended to be lower in the intervention group). This may, however, be influenced by the fact that the presented study was performed at an ICU that specializes in ARDS patients and ECMO support and ME was so low even in the control group (below ME tresholds). It is a common practice at our department that if we are not able to provide protective MV, the patient is indicated for ECMO support.\u003c/p\u003e\u003cp\u003eIncreased mortality was observed in a study by Serpa et al.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] only when the value of 17 J/min was exceeded. In the study by Parhar et al., higher value of 22 J/min was found to be the threshold for increased mortality[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The fact that the recommended threshold was set at 17 J/min in our study might be an additional reason for not finding any benefits of ME measurement \u0026ndash; as ventilation was typically already set protectively, and the shown ME values were very low, there was no need to intervene and change the settings to further reducing ME.\u003c/p\u003e\u003cp\u003eOne of the most striking results of our study was the observation of the \u003cb\u003ediurnal variation in ME\u003c/b\u003e. This may be explained by multiple factors. Firstly, interventions and examinations are performed during the day, which is associated with the handling of patients and their transport and potentially patient-ventilator interference. On the other hand, daytime is a period of more frequent MV parameters checking, deepening of sedation if interfering, as more staff are present at the ICU than at night. Conversely, during nocturnal hours, our objective is to facilitate sleep and promote a state of tranquility in patients. This approach involves a reduction in the frequency of disturbances compared to those that occur during daytime hours. For the purposes of this study, daytime was set from 6 a.m. to 6 p.m., corresponding to the ICU shift change, and also when the patients get bed bath (usually between 8\u0026ndash;9 a.m. and p.m.). During the day, ME was statistically significantly lower than during the night in all measurements, and the difference was particularly pronounced in patients with lower lung compliance and more severe lung involvement. It is, therefore, important that in times of fewer staff and less frequent checks, mechanisms to control dangerous ventilation are still in place for patients.\u003c/p\u003e\u003cp\u003eIn our data, only a weak correlation was found between ME measured by the geometric method and the Becher calculation. The high statistical significance of such a small correlation was likely caused by the large number of repeated measurements. This finding is highly interesting, considering that the geometric method should be an exact method, with ME corresponding to the area under the pressure-volume curve. The curve was rendered very accurately with 20 ms intervals, so the distortion should be minimal. From that perspective, the fact that the correlation with Becher\u0026rsquo;s method of calculation is very weak indicates that simplified equations, despite their undeniable advantage of simple bedside calculation, can introduce inaccuracies. One of the reasons for this may lie in the fact that Becher's calculation is a simplification of Van Der Meijden's equation[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], assuming constant airway resistance. However, airway resistance is a function of the airflow and changes during inspiration, which reduces the accuracy of results obtained using this equation. Moreover, Becher's simplification assumes that the pressure wave is ideally squared. The equations do not take into account the inspiratory rise time, although this parameter should not be essential[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite this, in the work of Chiumello et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] high accuracy of the Becher formula with a bias of -0.81 J/min was determined (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eLimitations\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe main limitation of the study is the small sample size of patients. Usually, patients at our department are ventilated with some degree of assisted ventilation as this helps, among other things, to reduce the risks of respiratory muscle atrophy, and we try to keep sedation as low as possible. However, such patients (i.e., the majority of all patients at the department) had to be excluded from the analyses as ME calculations are accurate only in patients with fully controlled MV.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe implementation of real-time ME measurement as a tool for the adjustment of MV parameters is feasible. We found that in an ICU of a tertiary centre with good experience with ARDS management and principles of protective ventilation, patients were ventilated with a sufficiently low ME even without knowledge of ME, resulting in no observed difference in ME applied to the patients between the intervention group (with knowledge of ME) and control group (without the knowledge of ME) and both groups were ventilated with very low ME. Significantly higher ME was observed during the night shift, which indicates this period to be more risky in terms of the development ventilation-induced lung damage.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e: The study was approved by the Ethics Committee of the University Hospital Ostrava. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: \u003cstrong\u003eFB\u003c/strong\u003e: Conceptualization, Original draft preparation, Approval of the final text; \u003cstrong\u003eMF:\u003c/strong\u003e Conducting the research and investigation process, Approval of the final text; \u003cstrong\u003ePS\u003c/strong\u003e: Supervision, Critical revision of the manuscript, Approval of the final text; \u003cstrong\u003eZK\u003c/strong\u003e: Digitalization of the dataset, Approval of the final text; \u003cstrong\u003eJS\u003c/strong\u003e: Conducting the research and investigation process, Approval of the final text; \u003cstrong\u003eDO\u003c/strong\u003e: design of the machine and the software for ME measurement, data archiving, cleaning, and exporting, Approval of the final text; \u003cstrong\u003eMP\u003c/strong\u003e: debug the software, conducting the research and investigation process, Approval of the final text; \u003cstrong\u003eMB\u003c/strong\u003e: Statistical analysis, Approval of the final text \u0026nbsp;and \u003cstrong\u003eJM\u003c/strong\u003e: Review \u0026amp; Editing, Approval of the final text\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eFunding:\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis work and the contributions were supported by:\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003ethe Ministry of Health, Czech Republic \u0026ndash; conceptual development of research organization (FNOs/2025).\u003c/li\u003e\n \u003cli\u003epartially supported from the project ``Research of Excellence on Digital Technologies and Wellbeing CZ.02.01.01/00/22_008/0004583\u0026apos;\u0026apos; which is co-financed by the European Union\u003c/li\u003e\n \u003cli\u003efinancial support of the European Union under the LERCO project number CZ.10.03.01/00/22_003/0000003 via the Operational Programme Just Transition\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e The authors have no comment of interest in relation to the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e: Data is available on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMaca J, Jor O, Holub M, et al. Past and Present ARDS Mortality Rates: A Systematic Review. \u003cem\u003eRespir Care\u003c/em\u003e. 2017;62(1):113-122. doi:10.4187/respcare.04716\u003c/li\u003e\n\u003cli\u003eYndrome S, Etwork N. The New England Journal of Medicine VENTILATION WITH LOWER TIDAL VOLUMES AS COMPARED WITH TRADITIONAL TIDAL VOLUMES FOR ACUTE LUNG INJURY AND THE ACUTE RESPIRATORY DISTRESS SYNDROME A BSTRACT Background Traditional approaches to mechanical. 2000;342:1301. Accessed February 18, 2022. www.ardsnet.org\u003c/li\u003e\n\u003cli\u003eRittayamai N, Brochard L. Recent advances in mechanical ventilation in patients with acute respiratory distress syndrome. \u003cem\u003eEuropean Respiratory Review\u003c/em\u003e. 2015;24(135):132-140. doi:10.1183/09059180.00012414\u003c/li\u003e\n\u003cli\u003eGu\u0026eacute;rin C, Papazian L, Reignier J, Ayzac L, Loundou A, Forel JM. Effect of driving pressure on mortality in ARDS patients during lung protective mechanical ventilationin two randomized controlled trials. \u003cem\u003eCrit Care\u003c/em\u003e. 2016;20(1):1-9. doi:10.1186/s13054-016-1556-2\u003c/li\u003e\n\u003cli\u003eGattinoni L, Marini JJ, Pesenti A, Quintel M, Mancebo J, Brochard L. The \u0026ldquo;baby lung\u0026rdquo; became an adult. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2016;42(5):663-673. doi:10.1007/s00134-015-4200-8\u003c/li\u003e\n\u003cli\u003ede Prost N, Ricard JD, Saumon G, Dreyfuss D. Ventilator-induced lung injury: historical perspectives and clinical implications. \u003cem\u003eAnn Intensive Care\u003c/em\u003e. 2011;1(1):28. doi:10.1186/2110-5820-1-28\u003c/li\u003e\n\u003cli\u003eNieman GF, Satalin J, Andrews P, Habashi NM, Gatto LA. Lung stress, strain, and energy load: engineering concepts to understand the mechanism of ventilator-induced lung injury (VILI). \u003cem\u003eIntensive Care Med Exp\u003c/em\u003e. 2016;4(1):16. doi:10.1186/s40635-016-0090-5\u003c/li\u003e\n\u003cli\u003eGattinoni L, Tonetti T, Cressoni M, et al. Ventilator-related causes of lung injury: the mechanical power. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2016;42(10):1567-1575. doi:10.1007/s00134-016-4505-2\u003c/li\u003e\n\u003cli\u003eCressoni M, Gotti M, Chiurazzi C, et al. Mechanical power and development of ventilator-induced lung injury. \u003cem\u003eAnesthesiology\u003c/em\u003e. 2016;124(5):1100-1108. doi:10.1097/ALN.0000000000001056\u003c/li\u003e\n\u003cli\u003ePeters RM. The energy cost (work) of breathing. \u003cem\u003eAnn Thorac Surg\u003c/em\u003e. 1969;7(1):51-67. doi:10.1016/S0003-4975(10)66146-2\u003c/li\u003e\n\u003cli\u003eChiumello D, Gotti M, Guanziroli M, et al. Bedside calculation of mechanical power during volume-and pressure-controlled mechanical ventilation. \u003cem\u003eCrit Care\u003c/em\u003e. 2020;Jul 11;24(1):417. doi:10.1186/s13054-020-03116-w\u003c/li\u003e\n\u003cli\u003eGiosa L, Busana M, Pasticci I, et al. Mechanical power at a glance: a simple surrogate for volume-controlled ventilation. \u003cem\u003eIntensive Care Med Exp\u003c/em\u003e. 2019;Dec; 7: 61. doi:10.1186/s40635-019-0276-8\u003c/li\u003e\n\u003cli\u003eBecher T, Van Der Staay M, Sch\u0026auml;dler D, Frerichs I, Weiler N. Calculation of mechanical power for pressure-controlled ventilation. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2019;45:1321-1323. doi:10.1007/s00134-019-05636-8\u003c/li\u003e\n\u003cli\u003eMarini JJ, Rodriguez RM, Lamb V. Bedside estimation of the inspiratory work of breathing during mechanical ventilation. \u003cem\u003eChest\u003c/em\u003e. 1986;89(1):56-63. doi:10.1378/CHEST.89.1.56\u003c/li\u003e\n\u003cli\u003eBur\u0026scaron;a F, Oczka D, Jor O, et al. The Impact of Mechanical Energy Assessment on Mechanical Ventilation: A Comprehensive Review and Practical Application. \u003cem\u003eMed Sci Monit\u003c/em\u003e. 2023;29:e941287. doi:10.12659/MSM.941287\u003c/li\u003e\n\u003cli\u003eBur\u0026scaron;a F, Frelich M, Sklienka P, Jor O, M\u0026aacute;ca J. Mechanick\u0026aacute; energie uměl\u0026eacute; plicn\u0026iacute; ventilace: zbytečn\u0026yacute; nebo nezbytn\u0026yacute; parametr? \u003cem\u003ehttp://aimjournal.cz/doi/1036290/aim2023065.html\u003c/em\u003e. 2023;34(4):165-171. doi:10.36290/AIM.2023.065\u003c/li\u003e\n\u003cli\u003eSerpa Neto A, Deliberato RO, Johnson AEW, et al. Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2018;44(11):1914-1922. doi:10.1007/S00134-018-5375-6\u003c/li\u003e\n\u003cli\u003eR: The R Project for Statistical Computing. Accessed June 10, 2025. https://www.r-project.org/\u003c/li\u003e\n\u003cli\u003eSzuldrzynski K, Kowalewski M, Swol J. Mechanical ventilation during extracorporeal membrane oxygenation support \u0026ndash; New trends and continuing challenges. \u003cem\u003ePerfusion (United Kingdom)\u003c/em\u003e. 2024;39(1_suppl):107S-114S. doi:10.1177/02676591241232270,\u003c/li\u003e\n\u003cli\u003eRehder KJ, Alibrahim OS. Mechanical Ventilation during ECMO: Best Practices. \u003cem\u003eRespir Care\u003c/em\u003e. 2023;68(6):838-845. doi:10.4187/RESPCARE.10908,\u003c/li\u003e\n\u003cli\u003eDamiani LF, Basoalto R, Retamal J, Bruhn A, Bugedo G. Mechanical Power of Ventilation: From Computer to Clinical Implications. \u003cem\u003eRespir Care\u003c/em\u003e. 2023;68(12):1748-1756. doi:10.4187/RESPCARE.11462,\u003c/li\u003e\n\u003cli\u003eHochberg CH, Semler MW, Brower RG. Oxygen toxicity in critically ill adults. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 2021;204(6):632-641. doi:10.1164/RCCM.202102-0417CI,\u003c/li\u003e\n\u003cli\u003eV Costa EL, Slutsky AS, Brochard LJ, et al. Ventilatory Variables and Mechanical Power in Patients with Acute Respiratory Distress Syndrome. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e. 2021;204:303-311. doi:10.1164/rccm.202009-3467OC\u003c/li\u003e\n\u003cli\u003eZhang Z, Zheng B, Liu N, Ge H, Hong Y. Mechanical power normalized to predicted body weight as a predictor of mortality in patients with acute respiratory distress syndrome. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2019;45(6):856-864. doi:10.1007/S00134-019-05627-9\u003c/li\u003e\n\u003cli\u003eMietto C, Malbrain MLNG, Chiumello D. Transpulmonary pressure monitoring during mechanical ventilation: a bench-to-bedside review. \u003cem\u003eAnestezjol Intens Ter\u003c/em\u003e. 2015;47(J):27-37. doi:10.5603/AIT.a2015.0065\u003c/li\u003e\n\u003cli\u003eCressoni M, Gotti M, Chiurazzi C, et al. Supplemental Digital Content 1 Mechanical power and the development of Ventilator-Induced Lung Injury.\u003c/li\u003e\n\u003cli\u003eFuller BM, Page D, Stephens RJ, et al. Pulmonary Mechanics and Mortality in Mechanically Ventilated Patients Without Acute Respiratory Distress Syndrome: A Cohort Study. \u003cem\u003eShock\u003c/em\u003e. 2018;49(3):311-316. doi:10.1097/SHK.0000000000000977\u003c/li\u003e\n\u003cli\u003eParhar KKS, Zjadewicz K, Soo A, et al. Epidemiology, Mechanical Power, and 3-Year Outcomes in Acute Respiratory Distress Syndrome Patients Using Standardized Screening. An Observational Cohort Study. \u003cem\u003eAnn Am Thorac Soc\u003c/em\u003e. 2019;16(10):1263-1272. doi:10.1513/ANNALSATS.201812-910OC\u003c/li\u003e\n\u003cli\u003eChi Y, Zhang Q, Yuan S, Zhao Z, Long Y, He H. Twenty-four-hour mechanical power variation rate is associated with mortality among critically ill patients with acute respiratory failure: a retrospective cohort study. \u003cem\u003eBMC Pulm Med\u003c/em\u003e. 2021;21(1). doi:10.1186/S12890-021-01691-4\u003c/li\u003e\n\u003cli\u003eYoon S, Nam JS, Blank RS, et al. Association of Mechanical Energy and Power with Postoperative Pulmonary Complications in Lung Resection Surgery: A Post Hoc Analysis of Randomized Clinical Trial Data. \u003cem\u003eAnesthesiology\u003c/em\u003e. 2024;140(5):920-934. doi:10.1097/ALN.0000000000004879,\u003c/li\u003e\n\u003cli\u003eGama De Abreu M, Costa ELV. Mechanical Energy and Power: Time to Incorporate Them into Routine Monitoring of Mechanical Ventilation? \u003cem\u003eAnesthesiology\u003c/em\u003e. 2024;140(5):877-880. doi:10.1097/ALN.0000000000004927,\u003c/li\u003e\n\u003cli\u003eVan Der Meijden S, Molenaar M, Somhorst P, Schoe A. Calculating mechanical power for pressure-controlled ventilation. \u003cem\u003eIntensive Care Med\u003c/em\u003e. 2019;45:1495-1497. doi:10.1007/s00134-019-05698-8\u003c/li\u003e\n\u003c/ol\u003e "},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\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":"journal-of-clinical-monitoring-and-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Clinical Monitoring and Computing](https://www.springer.com/journal/10877)","snPcode":"10877","submissionUrl":"https://submission.nature.com/new-submission/10877/3","title":"Journal of Clinical Monitoring and Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"mechanical energy, protective ventilation, ARDS","lastPublishedDoi":"10.21203/rs.3.rs-7022366/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7022366/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDespite the substantial advancements in mechanical ventilation (MV), mortality remains high. Mechanical energy (ME), MV forces are associated with outcomes. Real-time monitoring of ME and the adjustment of MV according to ME may result in ventilation with lower ME.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eRandomized controled trial conducted at the ECMO Centre Ostrava, Czech Republic, from March 2023 to March 2024 enrolled adult patients on MV (with or without extracorporeal membrane oxygenation, ECMO) with acute respiratory failure. A system for real-time ME monitoring (geometric method and simplified Becher\u0026acute;s formula) has been developed. In the intervention arm, the physician was able to observe the ME in real time and adjust the MV parameters accordingly. In the control group, the ME was concealed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 494 subjects were screened and 33 patients were randomized (further 7 ECMO patients). There was no significant difference between the control and intervention groups. Median ME\u003csub\u003eGeom\u003c/sub\u003e was 3.22 J/min (maximum 15.2 J/min) and ME\u003csub\u003eBecher\u003c/sub\u003e of 5.94 J/min (maximum 18.4 J/min). Only a weak (but significant, p\u0026thinsp;=\u0026thinsp;0.0001) correlation between ME\u003csub\u003eGeom\u003c/sub\u003e and ME\u003csub\u003eBecher\u003c/sub\u003e was observed. A highly significant difference was observed in ME between day and night (6 a.m. \u0026minus;\u0026thinsp;6 p.m.).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eAlthough real-time ME measurement is feasible, there was no significant difference in ME between the control and intervention groups with low ME in both groups. Experience physicians was capable of safe MV, even if they do not know the exact ME value. The night shift was a high-risk period for developing lung damage due to elevated ME.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e\u003cp\u003eClinicalTrials NCT06035146\u003c/p\u003e","manuscriptTitle":"Protective mechanical ventilation controlled by the real-time mechanical energy measurement","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 12:49:08","doi":"10.21203/rs.3.rs-7022366/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-14T18:29:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-14T06:41:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T13:38:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88228725580539227659555440320035481878","date":"2025-08-12T04:45:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89338963406963610658120863450993481325","date":"2025-08-06T18:32:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-06T18:15:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-02T02:52:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-02T02:51:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Clinical Monitoring and Computing","date":"2025-07-01T16:24:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-clinical-monitoring-and-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Clinical Monitoring and Computing](https://www.springer.com/journal/10877)","snPcode":"10877","submissionUrl":"https://submission.nature.com/new-submission/10877/3","title":"Journal of Clinical Monitoring and Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"260e62b0-2a5c-42af-a6e2-ff30a0a42d85","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-03T09:23:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 12:49:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7022366","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7022366","identity":"rs-7022366","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}