Monitoring Of Parameters Research Articles

Effects of intraoperative different fluid therapy protocols on postoperative renal functions

PurposePlanning intraoperative fluid therapy in patients undergoing major abdominal surgery is important. It was aimed to define the difference between fluid therapy protocols for renal function, bleeding and postoperative service follow-ups.Materials and methodsThis is an observational case-controlled prospective study. Sixty patients aged 18–65 years who had undergone pancreatic surgery between December 2023– February 2023 were included in the study. Liberal (Group 1; n = 30) and targeted fluid therapies (Group 2; n = 30) were administered to the patients. Liberal fluid therapy was planned with 8–10 ml/kg/h crystalloid infusion. The targeted fluid therapy (TFT) group (Group 2; n = 30) began with a 2 ml/kg/h crystalloid infusion at the baseline. Additional fluid boluses were given in 250 ml of colloid infused over 10 min if PVI was > 13% for at least five minutes. The patients were staged using the KDIGO (Kidney Disease: Improving Global Outcomes) criteria. The amount of bleeding during surgery was recorded for both groups.ResultsNo significant difference was observed in postoperative renal function. A significant difference was observed in the amount of intraoperative bleeding. The amount of bleeding was greater in patients managed with liberal fluid therapy. No significant difference was observed between the groups in the oral intake (hour), drain withdrawal (hour) mobilization (hour) and discharge (day) times and there isn’t any statistically significant differance between groups in cost effectivity (p>0.05).ConclusionKidney function was preserved during individualized targeted fluid therapy using non-invasive haemodynamic monitoring parameters.

Assessing the degradability of biodegradable-packaging base material through the insertion of organic solid waste deriving from composting process

The intensification of the use of plastic materials in recent decades has caused several environmental impacts, becoming direct incentives for research and development of alternatives that minimize the massive amount of plastics used by societies. In this context, so-called biodegradable materials emerge, with emphasis on starch-based compounds, which, although they have limited mechanical properties and low water resistance, allow the mixture with various reinforcing agents, in order to overcome the deficiencies for their application in larger scales without detracting from its focus on biodegradability. In this sense, the present study aimed to evaluate the biodegradability of a starch-based biopolymer, with the addition of different proportions of malt bagasse, this residue from the production process of beer; evaluating and monitoring parameters of the composting process of this mixture with organic solid waste. Biodegradation was determined from the visual assessment of the material, monitoring parameters such as pH, temperature, humidity and organic matter, being recorded in an electronic spreadsheet for descriptive analysis. The results obtained, when compared to the control composting unit, indicate a lower biological activity on the compost, consequently, a greater resistance to biodegradation. After three weeks of composting, it was difficult to identify the material and after four weeks, it was not possible to identify the biopolymer, indicating its biodegradation and incorporation into the substrate. It was observed that the material showed changes in its mechanical properties during composting. It is concluded that the material is totally biodegradable in all malt bagasse compositions, under composting conditions.

Eosinophilia as Monitoring Parameter for Chronic Graft-versus-Host Disease and Vitamin D Metabolism as Monitoring Parameter for Increased Infection Rates in Very Long-Term Survivors of Allogeneic Stem Cell Transplantation—A Prospective Clinical Study

Background: Our aim is to investigate cardiovascular risk factors, chronic graft-versus-host disease (CGvHD), and vitamin D metabolism in very long-term survivors of adult allogeneic stem cell transplantation (alloSCT). Methods: This study is a prospective unicentric, non-interventional trial. The detailed study protocol is available via the WHO Clinical Trial Registry. Results: We were able to include 33 patients with a mean age of 60.5 years (SD 11.1). Acute myeloid leukemia (AML) was the most frequent underlying disease (n = 12; 36.4%). The median survival time was 9.0 years (IQR 8.5–13.0). Relevant cardiovascular risk factors in the study population are the body mass index, cholesterol, LDL cholesterol, and lipoprotein(a). Cardiovascular risk factors have no significant impact on HRQoL. CGvHD of the skin as a limited disease was present in six patients (18.2%), and it has no impact on HRQoL. CGvHD was significantly associated with eosinophilia in peripheral blood (p = 0.003). Three patients (9.1%) had a shortage of calcitriol, and one patient (3.0%) took calcium substitution. The shortage is significantly associated with increased infection rates (p = 0.038). Conclusions: Cardiovascular risk factors and CGvHD need to be closely monitored. Eosinophilia might be a good and convenient monitoring parameter for CGvHD.

Semi-automatic line-system provisioning with an integrated physical-parameter-aware methodology: field verification and operational feasibility

We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time to our knowledge, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in real-time to extract physical link parameters for fast optical fiber line systems provisioning. Our methodology has the following advantages over traditional design: a minimized footprint at user sites, accurate estimation of the necessary optical network characteristics via complementary telemetry technologies, and the capability to conduct all operation work remotely. The last feature is crucial, as it enables remote operation to implement network design settings for immediate response to quality of transmission (QoT) degradation and reversion in the case of unforeseen problems. We successfully performed semi-automatic line system provisioning over field fiber network facilities at Duke University, Durham, North Carolina. The tasks of parameter retrieval, equipment setting optimization, and system setup/provisioning were completed within 1 h. The field operation was supervised by on-duty personnel who could access the system remotely from different time zones. By comparing Q-factor estimates calculated from the extracted link parameters with measured results from 400G transceivers, we confirmed that our methodology has a reduction in the QoT prediction errors ( ±0.3dB ) over existing designs ( ±0.6dB ).

Active Diagnostic Experimentation on Wind Turbine Blades with Vibration Measurements and Analysis

Abstract This paper deals with the key operational problems of wind turbosets, especially offshore, where vibrations are generated by rotor blades, as a consequence of erosive wear or icing. The primary causes of the imbalance of wind turbine rotors have been characterised, the observable symptoms of which include various forms of vibrations, transmitted from the turbine wheel to the bearing nodes of the power train components. Their identification was the result of an active diagnostic experiment, which actually entered the aerodynamic-mass imbalance of a turbine rotor into a wind power train, built as a small scale model. The recording of the observed monitoring parameters (vibration, aerodynamic, mechanical and electrical) made it possible to determine a set of symptoms (syndrome) of the deteriorated (entered) dynamic state of the entire wind turboset. This provides the basis for positive verification of the assumed concept and methodology of diagnostic testing, the constructed laboratory station and the measuring equipment used. For this reason, testing continued, taking into account the known and recognisable faults that most often occur during the operation of offshore wind turbosets. Transferring the results of this type of model research to full-size, real objects makes it possible to detect secondary (fatigue) damage to the elements transmitting torque from the wind turbine rotor to the generator early, especially the thrust bearings or gear wheel teeth.

Enhancing boundary detection of radiofrequency ablation lesions through photoacoustic mapping

Atrial fibrillation (A-fib) is the most common type of heart arrhythmia, typically treated with radiofrequency catheter ablation to isolate the heart from abnormal electrical signals. Monitoring the formation of ablation-induced lesions is crucial for preventing recurrences and complications arising from excessive or insufficient ablation. Existing imaging modalities lack real-time feedback, and their intraoperative usage is in its early stages. A critical need exists for an imaging-based lesion indexing (LSI) method that directly reflects tissue necrosis formation. Previous studies have indicated that spectroscopic photoacoustic (sPA) imaging can differentiate ablated tissues from their non-ablated counterparts based on PA spectrum variation. In this paper, we introduce a method for detecting ablation lesion boundaries using sPA imaging. This approach utilizes ablation LSI, which quantifies the ratio between the signal from ablated tissue and the total tissue signal. We enhance boundary detection accuracy by adapting a regression model-based compensation. Additionally, the method was cross-validated with clinically used intraoperative monitoring parameters. The proposed method was validated with ex vivo porcine cardiac tissues with necrotic lesions created by different ablation durations. The PA-measured lesion size was compared with gross pathology. Statistical analysis demonstrates a strong correlation (R > 0.90) between the PA-detected lesion size and gross pathology. The PA-detected lesion size also exhibits a moderate to strong correlation (R > 0.75) with local impedance changes recorded during procedures. These results suggest that the introduced PA imaging-based LSI has great potential to be incorporated into the clinical workflow, guiding ablation procedures intraoperatively.

Patterns of glycaemic control and associated factors among adult patients with diabetes attending medical referral clinics in two public hospitals in North-West Ethiopia: a cross-sectional study

BackgroundPoor glycaemic control is the most challenging issue in diabetes care globally. The glycated haemoglobin (HbA1c) value is the most standard monitoring parameter for appropriate glycaemic control status.ObjectiveTo assess the...

THE USE OF NERVE MONITORIZATION IN PAROTID, SUBMANDIBULAR GLAND AND FACIAL SURGERY AND ITS EFFECT ON PROGNOSIS

Objective: The facial nerve and its branches are at risk during facial surgery. The surgery with the highest risk is parotid and submandibular gland surgery. An attempt was made to determine threshold values in terms of paralysis in nerve monitoring parameters. These determined values could not be used to predict facial nerve function after surgery. The aim of this study is to investigate the relationship between the parameters detected by nerve stimulation during surgery and postoperative facial nerve dysfunction in patients who underwent parotid and submandibular gland surgery. Material and Methods: A total of 29 facial nerve branches of 13 patients who underwent superficial parotidectomy or submandibular gland resection were examined. Patients were examined in two groups: those who did not develop paralysis after surgery and those who developed paralysis or sequelae. The relationship between the patient's pre- and postoperative House-Brackmann staging and potential changes detected during surgery was investigated. Results: Paralysis was detected in 8 of 29 nerves that were stimulated, and the affected branches were the cervicofacial branch and the marginal mandibular branch. No difference was observed in the mean threshold stimulation values and responses determined before, during and at the end of dissection between patients who developed paralysis and those who did not. Conclusion: Unlike the literature, it is determined that no electrophysiological measurement result can predict the postoperative phase as a result of ROC-curve analysis and logistic regression analysis. It is thought that these results are caused by the fact that the developing paralysis is at low stages and heal within one month.

A bridge dynamic response analysis and load recognition method using traffic imaging

As the primary variable load of bridges, vehicle load is an important parameter for bridge health monitoring. However, traditional Weigh-in-Motion (WIM) systems and the commonly used method of placing sensors on the bridge are challenging to apply in load monitoring for many small and medium-sized bridges. Therefore, this paper proposes a bridge vehicle load identification method based on traffic surveillance video data. Leveraging the surveillance video data on the bridge, without introducing additional hardware devices, the displacement of target points is detected through sub-pixel level image detection algorithms, enabling non-contact measurement of bridge structural response through imaging. A spatiotemporal relationship model of structural displacement, vehicle load, and load distribution is established to solve for vehicle load. Finally, model bridge tests under various loading conditions and engineering practice experiments are conducted to validate the feasibility of the method. The results of the model bridge tests show that the structural displacement measured using traffic video measurement has a deviation of less than 10% compared to the measurements obtained using contact displacement sensors (LVDT), and it can accurately reflect the displacement characteristics of the structure. The results of the field tests demonstrate that the average estimation deviation for heavy vehicle loads ranging from 12 to 18 tons is approximately 18%, meeting the engineering requirements. The proposed method can provide load statistical information for the extensive health monitoring of small and medium-sized bridges and offer a new technical pathway for obtaining bridge load information.

Fourteen-year slow moving landslide monitoring and benchmark velocity parameters of natural slopes at ‘Serra do Mar’, Brazil

Fourteen-year slow moving landslide monitoring and benchmark velocity parameters of natural slopes at ‘Serra do Mar’, Brazil

Location method of ill-conditioned microseismic source and its engineering application

Microseismic event location is one of the core parameters in microseismic monitoring, and the accuracy of localization will directly affect the effectiveness of engineering applications. However, limited by spatial factors, the geometry of the sensor installation will be close to linear, which makes the localization equation suffer from the pathological problem, and the localization accuracy is greatly reduced. To address this problem, the reasons for the pathological problem are analyzed from the perspective of the objective function residuals and coefficient matrix. The pathological problem is caused by the combined effect of the poorer sensor array and data errors, and its residual isosurface shows a conical distribution, and as the residual value decreases, the apex of the isosurface gradually extends to the far side, and the localization results do not converge. For this reason, an improved regularized Newton downhill localization algorithm is proposed. In this method, firstly, the Newtonian downhill method is improved so that the magnitudes of the seismic source parameters are the same, and the condition number of the coefficient matrix is reduced; then, the L-curve method is used to calculate the regularization factor for the pathological equations, and the coefficient matrix is improved; finally, the pathological equations are regularized, and the seismic source coordinates are obtained by the improved Newtonian downhill method. The results of engineering applications show that compared with the traditional algorithm based on automatic of P-arrival picking, the number of effective microseismic events calculated by the proposed localization algorithm is increased by 194.7 %, and the localization accuracy is substantially improved. The proposed algorithm reduces the problem of low accuracy of S-arrival picking and allows localization using only P-wave arrival. The method reduces the quality requirements of the data and significantly improves the utilization of microseismic events and positioning accuracy.

Safer operating areas (SOA) of cylindrical lithium-ion battery – A probabilistic approach

This study introduces a real-time probabilistic safety assessment of a 18650 cylindrical battery. The physics-based failure scenarios from battery abuse are mapped onto Bayesian Network framework, enabling a quantitative estimation of monitoring parameters, health indicators and loss of control events. The model (encompassing multiple states, weightage factors, interdependencies, and uncertainties) is validated with 70 experimental data points of the same geometry, comprising 4 categories of abuses (surface heating, fast overcharging, external short circuit, and internal deformation). Through testing, probabilistic safety thresholds are established for 3 observed events: gas formation, venting, and fire and explosion.Sensitivity analysis reveals state of charge (at SOC > 50 %) and surface temperature (at Tsurf > 90°C) as the most influential parameters while inadequate cooling system and current interrupt device (CID) as influential safeguards for thermal runaway and fire to occur. Moreover, the identified safety thresholds are subjected to validation and testing against multiple health indicators to draw important insights. Probability, P(fire)deformation>P(fire)surface heat as internal deformation lowers onset to thermal runaway. In culmination, a safer operating area (SOA) is proposed, leveraging the identified thresholds and most sensitive parameters. The proposed SOA with 4 distinct boundaries is not only consistent with the temporal variations in cell temperature during thermal abuse test, but also provides a robust approach to monitor the safety of a battery.

Esophageal oxyhemoglobin saturation as a resuscitative metric in hemorrhagic shock

BackgroundMixed venous saturation (SvO2) is considered the gold standard to assess the adequacy of tissue oxygen delivery (DO2) in shock states. However, SvO2 monitoring is challenging as it requires an...

Evaluation of non-invasive biomarkers of kidney allograft rejection in a prospective multicenter unselected cohort study (EU-TRAIN)

Non-invasive biomarkers are promising tools for improving kidney allograft rejection monitoring, but their clinical adoption requires more evidence in specifically designed studies. To address this unmet need, we designed the EU-TRAIN study, a large prospective multicentric unselected cohort funded by the European Commission. Here, we included consecutive adult patients who received a kidney allograft in nine European transplant centers between November 2018 and June 2020. We prospectively assessed gene expression levels of 19 blood messenger RNAs, four antibodies targeting non-human leukocyte antigen (HLA) endothelial antigens, together with circulating anti-HLA donor-specific antibodies (DSA). The primary outcome was allograft rejection (antibody-mediated, T cell-mediated, or mixed) in the first year post-transplantation. Overall, 412 patients were included, with 812 biopsies paired with a blood sample. CD4 gene expression was significantly associated with rejection, while circulating anti-HLA DSA had a significant association with allograft rejection and a strong association with antibody-mediated rejection. All other tested biomarkers, including AKR1C3, CD3E, CD40, CD8A, CD9, CTLA4, ENTPD1, FOXP3, GZMB, ID3, IL7R, MS4A1, MZB1, POU2AF1, POU2F1, TCL1A, TLR4, and TRIB1, as well as antibodies against angiotensin II type 1 receptor, endothelin 1 type A receptor, C3a and C5a receptors, did not show significant associations with allograft rejection. The blood messenger RNAs and non-HLA antibodies did not show an additional value beyond standard of care monitoring parameters and circulating anti-HLA DSA to predict allograft rejection in the first year post-transplantation. Thus, our results open avenues for specifically designed studies to demonstrate the clinical relevance and implementation of other candidate non-invasive biomarkers in kidney transplantation practice.

Physicochemical behavior and impact of CO2 and CH4 plumes during gas-rich water leakage in a shallow carbonate freshwater aquifer

Carbon capture and storage (CCS) is a promising technology for reducing CO2 emissions. Significant concerns have emerged about the potential leakage of CO2 into shallow aquifers, highlighting the risk to water quality and environmental safety. This underscores the importance of finding monitoring tools suitable for different geological scenarios. If leakage occurs in the context of depleted reservoirs being used for CO2 storage, residual CH4 from the storage complex will likely be entrained together with CO2. However, few studies have addressed the implications of CH4 presence and its potential as a monitoring parameter during CO2 leakage.To address this gap, we simulated a leakage event by injecting water enriched with CO2 and CH4 into a shallow limestone aquifer. The impact of the injection was monitored using a combination of laboratory measurements on water samples and in-situ sensors located downstream from the injection well.All parameters were affected by the simulated leakage. Some monitoring tools allowed us to differentiate the leakage event from natural variations. A key finding of this study was that at 7 m from the injection well, the CH4 breakthrough occurred roughly one day before the CO2 breakthrough, highlighting the potential of CH4 as an early indicator of CO2 leakage and suggesting interesting prospectives for industrial-scale sites. However, further research is needed to confirm the potential of CH4 as a CO2 leakage indicator at industrial scales, due to potential methane oxidation and loss of the signal with longer times and distances.This study contributes to a better understanding of the potential risks and effective monitoring strategies associated with CO2-CH4 leakage in carbonate aquifers.

Joint diagnosis and validation of lightning risk for transmission lines by using multisource data

This study proposes an improved method for assessing lightning risk for typical 750-kV transmission lines in Northwest China. The method involves enhanced preprocessing of multisource parameters and a joint diagnosis of lightning risk; on the basis of the diagnosis results, a cause analysis is conducted to identify towers at high lightning risk. In this study, raw data on the following parameters were obtained and processed: line lightning withstand capability calculation parameters, lightning localization parameters, microtopography parameters, and distributed monitoring parameters. These data were then integrated into a comprehensive multisource database. Furthermore, this study established a model for calculating lightning withstand capability; the study considered the influence of altitude and optimized the classic electrogeometric model. The joint diagnosis method was validated using distributed monitoring data. Through this method, this study identified the characteristics of typical high-risk towers and the underlying factors contributing to the high lightning risk on transmission lines.

Real-time monitoring of middle cerebral artery blood flow using intraoperative transcranial doppler during trans-carotid artery revascularization

ObjectiveTranscarotid artery revascularization (TCAR) has emerged as a safe and effective method for carotid revascularization, offering several key advantages over carotid endarterectomy (CEA) and carotid artery stenting (CAS). Intraoperative transcranial Doppler (TCD) monitoring plays a pivotal role in assessing cerebral hemodynamics and detecting embolic signals during TCAR at our institution. MethodsThis review synthesizes the current literature and provides guidance for TCD monitoring throughout the various phases of TCAR, from preoperative assessment to postoperative management. Key considerations include probe placement, waveform evaluation, interpreting monitoring parameters such as mean flow velocity (MFV), pulsatility index (PI), and percentage change in the MFV (Δ%). Techniques for maintaining the insonation of the middle cerebral artery (MCA) M1 segment and optimal parameter settings for intraoperative TCD monitoring are detailed. ResultsTCAR phases are highlighted, including transcarotid access and vessel control, sheath insertion, the establishment of flow reversal, pre-dilation, stent placement, post-dilation, and closure, while emphasizing the importance of real-time feedback provided by TCD monitoring in identifying embolic signals and assessing changes in cerebral perfusion. The review discusses limitations of TCD monitoring, such as inadequate temporal windows, incorrect vessel identification and reliability issues with automatic emboli detection counters. Furthermore, practical advice is provided on how to navigate common pitfalls encountered during intraoperative TCD monitoring. ConclusionBy understanding the nuances of TCD monitoring and its application in TCAR, intraoperative TCD monitoring may aid to minimize the low but potential risk of intraprocedural embolic events, periprocedural hypoperfusion and postoperative hyperperfusion. Finally, we suggest opportunities for further research in embolization quantification and additional strategies to optimize quality control in TCAR.

Automated Insulin Delivery System: A Solution for Moderate to High-Risk Ramadan Fasting in People Living with Type 1 Diabetes.

Objectives: Background investigated whether Ramadan, a yearly religious fasting lasting for 1 month, could challenge the metabolic control obtained under a hybrid closed-loop (HCL) therapy in patients living with type 1 diabetes (T1D). Material and Method: This real-life prospective study involved 20 patients with T1D and moderate to high-risk score of adverse events at baseline. We compared continuous glucose monitoring (CGM) parameters under HCL therapy 1 month before and during the Ramadan fasting month. The main outcome was the evolution of the percentage of time-in-range (TIR, 70-180 mg/dL) between the two time points, and secondary outcomes were the evolution of other CGM parameters and frequency of acute metabolic events. Results: We observed no statistical difference regarding TIR (mean±SD) (63 ± 11% during fasting vs. 62 ± 12% before) as well as for other parameters including time spent under 70 mg/dL (1.1 ± 1.0% vs. 1.5 ± 1.3%) and percentage of HCL use (93 ± 5% vs. 94 ± 5%). No acute metabolic event was observed during fasting under HCL. Results were homogenous across baseline risk score groups.

Variability in sleep architecture and alterations in circadian rhythms in patients with acute cerebral infarction accompanied by sleep-disordered breathing.

To continuously and dynamically monitor the sleep status of patients in the acute phase of cerebral infarction, and to investigate the characteristics of acute cerebral infarction(ACI)associated with sleep-disordered breathing (SDB), variations in sleep structure, and changes in sleep circadian rhythms. Patients with ACI within 48h of onset who were admitted to the Department of Neurology at Kailuan General Hospital from November 2020 to December 2022 were selected. Detailed baseline information such as age, gender, smoking history, drinking history, were recorded for the selected participants. From the beginning of their hospitalization, the selected participants were monitored for their sleep status continuously for 5 days using the Intelligent Mattress-based Sleep Monitoring Platform System(IMSMPS). Based on the heart rate data obtained from the monitoring, the interdaily stability (IS) and intradaily variability (IV) of the sleep circadian rhythm were calculated. 1,367 patients with ACI were selected. Monitoring results over 5 days indicated 147 cases (10.75%) without SDB, and 1,220 cases (89.25%) with SDB. Among the group with SDB, there were 248 cases (18.14%) with continuous mild SDB, 395 cases (28.90%) with moderate SDB, 295 cases (21.58%) with severe SDB, and 282 cases (20.63%) that fluctuated between different severity levels. Within this fluctuating group, 152 cases (53.90%) fluctuated between two severity levels, 120 cases (42.55%) between three levels, and 10 cases (3.55%) among all four levels. There were statistically significant differences (P < 0.05) in the sleep latency, sleep efficiency, non-rapid eye movement stages 1-2, rapid eye movement, proportion of non-rapid eye movement, proportion of rapid eye movement, wake after sleep onset, time out of bed, number of awakenings, respiratory variability index, and heart rate variability index among patients with ACI monitored from day 1 to 5. However, other monitored sleep structure parameters did not show statistically significant differences (P > 0.05). The coefficient of variation for all sleep monitoring parameters ranged between 14.54 and 36.57%. The IV in the SDB group was higher than in the group without SDB (P < 0.05), and the IS was lower than in the group without SDB (P < 0.05). Patients in the acute phase of cerebral infarction have a high probability of accompanying SDB. The sleep structure of these patients shows significant variability based on the onset time of the stroke, and some patients experience fluctuations among different severity levels of SDB. ACI accompanied by SDB can further reduce the IS of a patient's sleep circadian rhythm and increase its IV.

Digital outcome measures are associated with brain atrophy in patients with multiple sclerosis

BackgroundDigital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression.ObjectiveTo study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS.MethodsIn this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates.ResultsIn PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12.ConclusionOur results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.