Hanady Mohammed Elfeky, Janna Omaran, Noha S Shaban, Ahmed Elmohamady, Nagwa Doha, Noha Afify
{"title":"Effectiveness of diaphragmatic ultrasound as a predictor of successful weaning from mechanical ventilation.","authors":"Hanady Mohammed Elfeky, Janna Omaran, Noha S Shaban, Ahmed Elmohamady, Nagwa Doha, Noha Afify","doi":"10.1007/s10877-025-01317-8","DOIUrl":"10.1007/s10877-025-01317-8","url":null,"abstract":"","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"1015-1026"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144626431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Vojnar, Patrick Achenbach, Moritz Flick, Daniel Reuter, Michael Sander, Bernd Saugel, Ann-Kristin Schubert, Christine Gaik
{"title":"Haemodynamic monitoring and management during non-cardiac surgery: a survey among German anaesthesiologists.","authors":"Benjamin Vojnar, Patrick Achenbach, Moritz Flick, Daniel Reuter, Michael Sander, Bernd Saugel, Ann-Kristin Schubert, Christine Gaik","doi":"10.1007/s10877-025-01284-0","DOIUrl":"10.1007/s10877-025-01284-0","url":null,"abstract":"<p><p>In 2023, the first German guideline on intraoperative haemodynamic monitoring and management for adults having non-cardiac surgery was published. The aim of this survey was to identify how anaesthetists in Germany managed intraoperative haemodynamics and blood pressure before its publication. In September to October 2023, members of the German Society of Anaesthesiology and Intensive Care Medicine (DGAI) were invited via email to participate in this anonymous online survey. Thirty-one questions covered demographics, clinical experience, approaches to perioperative blood pressure measurement and common thresholds, as well as the use of advanced haemodynamic monitoring and its potential therapeutic implications. 1,079 fully completed questionnaires were included in the analysis. When intermittent oscillometry was used to measure blood pressure, a 3-minute interval was usually applied during induction of anaesthesia (42%; 451/1,079). For invasive blood pressure monitoring, more than half (53%; 574/1,079) inserted an arterial line after induction of anaesthesia. Nearly all (94%; 1,012/1,079) focused on the mean arterial pressure for blood pressure monitoring, with a large majority (77%; 779/1012) considering values below 60-65 mmHg to be critically low. Intraoperative hypotension was managed based on an internal protocol by only 21% (223/1,079). Regarding advanced haemodynamic monitoring, 43% (459/1,079) frequently used pulse contour analysis, while 67% (721/1,079) reported that monitors with finger-cuff technology were not available in their department. 47% (504/1,079) cited a lack of experience as one of the main reasons for the infrequent use of cardiac output monitoring. This survey among DGAI members provides important insights into current practices of haemodynamic monitoring and management prior to the publication of the recent German guideline on 'Intraoperative haemodynamic monitoring and management of adults having non-cardiac surgery'.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"853-861"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474607/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143692349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Philipp Helmer, Sebastian Hottenrott, Kathrin Wienböker, Jürgen Brugger, Christian Stoppe, Benedikt Schmid, Peter Kranke, Patrick Meybohm, Michael Sammeth
{"title":"Postoperative use of fitness trackers for continuous monitoring of vital signs: a survey of hospitalized patients.","authors":"Philipp Helmer, Sebastian Hottenrott, Kathrin Wienböker, Jürgen Brugger, Christian Stoppe, Benedikt Schmid, Peter Kranke, Patrick Meybohm, Michael Sammeth","doi":"10.1007/s10877-025-01273-3","DOIUrl":"10.1007/s10877-025-01273-3","url":null,"abstract":"<p><p>Wearables and Internet of Things (IoT) technologies are increasingly incorporated into healthcare, including perioperative settings. These devices offer continuous non-invasive monitoring of vital signs, patient position, and mobilization. Nonetheless, there is currently little information about tolerance and acceptance of wearables in postoperative patients. We therefore assessed opinions and user experience in postoperative patients who used three popular fitness trackers during their entire hospital stay. Specifically, we evaluate the Apple Watch 7, Garmin Fenix 6 Pro, and Withings ScanWatch. We used an investigator-designed patient questionnaire with 11 questions to quantify patient experience and opinions regarding inpatient and home monitoring. Secondarily, we evaluated compliance and the incidence of associated adverse events during daily patient visits. Data were analyzed using descriptive statistics and non-parametric tests. The majority of the answers to the questions (82.1%) were rated positively defined as Likert-Scale Scores 4 or 5 by the 33 analyzed patients, ranging between 72.7 and 97.0% agreement rate. Specific questions related to data sharing for research and overall user experience received high agreement rates (97.0 and 84.8%, respectively). Women reported slightly higher satisfaction with device comfort, as compared to men (LS-Score 4.8 vs. 4.0). No significant differences were found based on the device model or length of hospitalization. The use of wearable devices in healthcare is rated positively by postoperative inpatients, paving the way for future implementation of these devices in healthcare. However, besides validating the measurement accuracy and demonstrating clinical benefits, several regulatory hurdles must be overcome before implementing wearables in routine clinical care.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"1077-1086"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474713/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143572915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kristen K Thomsen, Jovana Stekovic, Felix Köster, Alina Bergholz, Karim Kouz, Moritz Flick, Daniel I Sessler, Christian Zöllner, Bernd Saugel, Leonie Schulte-Uentrop
{"title":"Wire-in-needle versus conventional syringe-on-needle technique for ultrasound-guided central venous catheter insertion in the internal jugular vein: the WIN randomized trial.","authors":"Kristen K Thomsen, Jovana Stekovic, Felix Köster, Alina Bergholz, Karim Kouz, Moritz Flick, Daniel I Sessler, Christian Zöllner, Bernd Saugel, Leonie Schulte-Uentrop","doi":"10.1007/s10877-024-01232-4","DOIUrl":"10.1007/s10877-024-01232-4","url":null,"abstract":"<p><strong>Purpose: </strong>There are different techniques for ultrasound-guided central venous catheter (CVC) insertion. When using the conventional syringe-on-needle technique, the syringe needs to be removed from the needle after venous puncture to pass the guidewire through the needle into the vein. When, alternatively, using the wire-in-needle technique, the needle is preloaded with the guidewire, and the guidewire-after venous puncture-is advanced into the vein under real-time ultrasound guidance. We tested the hypothesis that the wire-in-needle technique reduces the time to successful guidewire insertion in the internal jugular vein compared with the syringe-on-needle technique in adults.</p><p><strong>Methods: </strong>We randomized 250 patients to the wire-in-needle or syringe-on-needle technique. Our primary endpoint was the time to successful guidewire insertion in the internal jugular vein.</p><p><strong>Results: </strong>Two hundred and thirty eight patients were analyzed. The median (25th percentile, 75th percentile) time to successful guidewire insertion was 22 (16, 38) s in patients assigned to the wire-in-needle technique and 25 (19, 34) s in patients assigned to the syringe-on-needle technique (estimated location shift: 2 s; 95%-confidence-interval: - 1 to 5 s, p = 0.165). CVC insertion was successful on the first attempt in 103/116 patients (89%) assigned to the wire-in-needle technique and in 113/122 patients (93%) assigned to the syringe-on-needle technique. CVC insertion-related complications occurred in 8/116 patients (7%) assigned to the wire-in-needle technique and 19/122 patients (16%) assigned to the syringe-on-needle technique.</p><p><strong>Conclusion: </strong>The wire-in-needle technique-compared with the syringe-on-needle technique-did not reduce the time to successful guidewire insertion in the internal jugular vein. Clinicians can consider either technique for ultrasound-guided CVC insertion in adults.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"805-811"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142466620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Henrik Lynge Hovgaard, Simon Tilma Vistisen, Johannes Enevoldsen, Frank Vincenzo de Paoli, Peter Juhl-Olsen
{"title":"The haemodynamic effects of pneumoperitoneum on pulse pressure variation - a prospective, observational study.","authors":"Henrik Lynge Hovgaard, Simon Tilma Vistisen, Johannes Enevoldsen, Frank Vincenzo de Paoli, Peter Juhl-Olsen","doi":"10.1007/s10877-025-01300-3","DOIUrl":"10.1007/s10877-025-01300-3","url":null,"abstract":"<p><p>The effects of pneumoperitoneum on dynamic predictors of fluid responsiveness such as pulse pressure variation (PPV) remain uncertain. This uncertainty arises from potentially opposing physiological mechanisms that affect cardiovascular dynamics during conditions with increased intra-abdominal pressure (IAP). Deriving PPV with high precision during induction of pneumoperitoneum may provide new insights into the complex relationship between intra-abdominal pressure changes and PPV. The hypothesis was that PPV derived from a generalised additive model (PPV<sub>GAM</sub>) would increase with the induction of pneumoperitoneum and the associacted increase in IAP. This was a prospective, observational study in patients undergoing oesophagectomy. Before and after induction of pneumoperitoneum, haemodynamic variables including PPV and stroke volume variation (SVV) were recorded with the Hemosphere monitor. PPV<sub>GAM</sub> was estimated offline from the arterial blood pressure curve. A total of 34 patients were included in the final analysis. PPV<sub>GAM</sub> increased by a factor of 1.49 (95% CI: 1.25-1.77) as intra-abdominal pressure increased from baseline to 12 mmHg. SVV and PPV from the HemoSphere monitor increased with a factor of 1.25 (95% CI: 1.13-1.39, p < 0.001) and 1.14 (95% CI: 1.00-1.29, p = 0.048), respectively. PPV derived from a generalised additive model increased approximately 50% from the induction of pneumoperitoneum to an IAP of 12 mmHg. PPV and SVV derived from the Hemosphere monitor also increased signicantly.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"863-873"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143970660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sanna Holmskär, Malin Öhrn, Moa Furudahl, Johannes Kesti, Jakob Pansell
{"title":"Is quantitative pupillometry affected by ambient light? A prospective crossover study.","authors":"Sanna Holmskär, Malin Öhrn, Moa Furudahl, Johannes Kesti, Jakob Pansell","doi":"10.1007/s10877-025-01293-z","DOIUrl":"10.1007/s10877-025-01293-z","url":null,"abstract":"<p><strong>Purpose: </strong>Pupillary examination is a central part of the neurological assessment. While quantitative pupillometry (QP) improves reliability, the impact of ambient light, particularly on the Neurological Pupil index (NPi), remains unclear. This study aimed to clarify the effects of ambient light on QP parameters in a critical care setting.</p><p><strong>Methods: </strong>We performed a prospective crossover study, including 20 adult patients requiring invasive ventilation. Pupillometry was performed during bright condition (BC1), then dark condition (DC), then bright condition again (BC2). In our primary analysis we compared NPi values across conditions (DC1 vs. BC, BC vs. DC2, DC1 vs. DC2). In the secondary analysis, we compared all other QP parameters.</p><p><strong>Results: </strong>All QP values except constriction velocity and dilation velocity were non-normal. The median NPi was significantly lower in BC compared to dark conditions DC1 in both eyes. In 25% of participants the NPi decreased by 0.6 or more. Conversely, a significant increase in median NPi of both eyes was observed when switching from bright conditions back to dark (BC vs. DC2). No significant difference was found between the two dark condition measurements (DC1 and DC2). The secondary analysis showed that the differences in NPi were driven by differences in most, but not all, QP parameters included in NPi.</p><p><strong>Conclusions: </strong>We corroborate previous findings that the level of ambient light affects QP parameters in critically ill patients. This needs to be considered for accurate interpretation of QP parameters. Future studies may explore potential automated light correction methods for wider clinical applicability.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"975-986"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144027129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maksim Katsin, Maxim Glebov, Haim Berkenstadt, Dina Orkin, Yotam Portnoy, Adi Shuchami, Amit Yaniv-Rosenfeld, Teddy Lazebnik
{"title":"Developing a machine learning-based prediction model for postinduction hypotension.","authors":"Maksim Katsin, Maxim Glebov, Haim Berkenstadt, Dina Orkin, Yotam Portnoy, Adi Shuchami, Amit Yaniv-Rosenfeld, Teddy Lazebnik","doi":"10.1007/s10877-025-01295-x","DOIUrl":"10.1007/s10877-025-01295-x","url":null,"abstract":"<p><p>Arterial hypotension is a common and often unintended event during surgery under general anesthesia, associated with increased postoperative complications, such as kidney injury, myocardial injury, and stroke. Postinduction hypotension (PIH) is influenced by patient-specific factors, chronic medication use, and anesthetic induction regimens. Traditional predictive models struggle with this complexity, making machine learning (ML) a promising alternative due to its ability to handle complex datasets and identify hidden patterns. This study aimed to develop and validate an ML-based model for predicting PIH and identifying key clinical predictors. A retrospective cohort study of 20,309 adult patients undergoing non-obstetric surgery under general anesthesia with intravenous induction was conducted. The primary outcome was the occurrence of PIH, defined as mean arterial pressure (MAP) < 55 mmHg within 10 min post-induction. Data were split into training and validation sets using k-fold cross-validation. The model's predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC), and feature importance was assessed using SHapley Additive exPlanations (SHAP) values. PIH occurred in 4,948 patients (24.4%). Key predictors included preinduction systolic and mean arterial pressures, propofol dose, and beta-blocker use. The ML model achieved an AUC of 0.732 in predicting PIH. The ML-based model demonstrated significant predictive capability for PIH, identifying key clinical predictors. This model holds the potential for improving preoperative planning and patient risk stratification. However, further validation through prospective studies is necessary to confirm these findings.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"889-899"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474600/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143995222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stefan Schwerin, Srdjan Z Dragovic, Julian Ostertag, Duy-Minh Nguyen, Gerhard Schneider, Matthias Kreuzer
{"title":"Correction: EEG features associated with Alzheimer's disease and Frontotemporal dementia are not reflected by processed indices used in anesthesia monitoring.","authors":"Stefan Schwerin, Srdjan Z Dragovic, Julian Ostertag, Duy-Minh Nguyen, Gerhard Schneider, Matthias Kreuzer","doi":"10.1007/s10877-025-01354-3","DOIUrl":"10.1007/s10877-025-01354-3","url":null,"abstract":"","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"1111"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145000634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Petar Milovanovic, Julia Braun, Cynthia Alexandra Hunn, Justyna Lunkiewicz, David Werner Tscholl, Greta Gasciauskaite
{"title":"Avatar-based versus conventional patient monitoring with distant vision: a computer-based simulation study.","authors":"Petar Milovanovic, Julia Braun, Cynthia Alexandra Hunn, Justyna Lunkiewicz, David Werner Tscholl, Greta Gasciauskaite","doi":"10.1007/s10877-024-01239-x","DOIUrl":"10.1007/s10877-024-01239-x","url":null,"abstract":"<p><p>Patient monitoring in the perioperative setting can be challenging, especially when monitoring multiple patients simultaneously or managing dynamic situations that require movement around the operating room. We aimed to evaluate whether avatar-based patient monitoring, which presents vital signs in the form of changing colors, shapes and motion, improves remote vital sign recognition compared to conventional monitoring. We conducted a prospective, single-center, computer-based simulation study to evaluate how anesthesia providers recognize vital signs when using the Philips Visual Patient Avatar at different viewing distances (8 and 16 m) compared to conventional monitoring. The primary outcome was the total number of correctly identified vital signs which were compared for the two distances and the two devices using mixed Poisson regression. We analyzed data from 28 anesthesia providers who participated in 112 simulations. The correct recognition rate using the Visual Patient Avatar compared to conventional monitoring at 8 m was increased by 74% (rate ratio 1.74, 95% CI, 1.42 to 2.14, p < 0.001) and by 51% at 16-meter viewing distance (rate ratio 1.51, 95% CI, 1.23 to 1.87, p < 0.001). We observed scenario-specific superior performance for six vital signs at 8 m. The results provide empirical evidence that avatar-based monitoring can significantly improve the perception of vital signs when using distant vision.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"1065-1075"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474633/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142638981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C J de Wijs, J R Behr, L W J M Streng, M E van der Graaf, F A Harms, E G Mik
{"title":"Automated mitochondrial oxygen consumption (mitoVO<sub>2</sub>) analysis via a bi-directional long short-term memory neural network.","authors":"C J de Wijs, J R Behr, L W J M Streng, M E van der Graaf, F A Harms, E G Mik","doi":"10.1007/s10877-025-01291-1","DOIUrl":"10.1007/s10877-025-01291-1","url":null,"abstract":"<p><p>Monitoring in vivo mitochondrial oxygen tension (mitoPO<sub>2</sub>) enables the measurement of mitochondrial oxygen consumption (mitoVO<sub>2</sub>), providing deeper insights into the skin's mitochondrial environment. However, current mitoVO<sub>2</sub> analysis often relies on manual identification of start and end points, which introduces substantial inter-user variability. Addressing this limitation is crucial for broader adoption, comparability, and reproducibility across research groups. Therefore, the aim of this study was to develop a neural network-based software that automatically analyzes mitoVO<sub>2</sub>. A Bi-directional Long Short-Term Memory neural network was trained on 125 mitoPO<sub>2</sub> measurement sequences and optimized through Bayesian optimization. It identifies start points and measurement periods, then applies a modified Michaelis-Menten fit to calculate mitoVO<sub>2</sub>. This framework, embedded in automated software, was validated against the consensus of 3 raters. Bayesian optimization yielded an overall network performance of 94.2% on the test set. The neural network identified 91% of mitoVO<sub>2</sub> start points within a ± 5-sample range of the manual consensus. Mean mitoVO<sub>2</sub> values for the consensus and software were 6.56 and 6.63 mmHg s<sup>- 1</sup>, respectively, corresponding to a bias of -0.057 mmHg s<sup>- 1</sup>. Multiple runs of the network on the same dataset produced identical results, confirming consistency and eliminating inter-user variability. The developed neural network-based software automatically and consistently analyzes mitoVO<sub>2</sub> measurements, substantially reducing reliance on subjective judgments. By enabling a standardized approach to mitoVO<sub>2</sub> analysis, this tool improves data comparability and reproducibility across research settings. Future work will focus on further refining precision and extending functionality through multi-center collaborations.</p>","PeriodicalId":15513,"journal":{"name":"Journal of Clinical Monitoring and Computing","volume":" ","pages":"947-956"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12474646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143752972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}