Short-term variation of the fetal heart rate as a marker of intraamniotic infection in pregnancies with preterm prelabor rupture of membranes: a historical cohort study

INTRODUCTION

Intraamniotic infection (IAI) and subsequent early-onset neonatal sepsis (EONS) are among the main complications associated with preterm prelabor rupture of membranes (PPROM). Currently used diagnostic tools have been shown to have poor diagnostic performance for IAI. This study aimed to investigate whether the exposure to IAI before delivery is associated with short-term variation of the fetal heart rate in pregnancies with PPROM.

METHODS

Observational cohort study of 678 pregnancies with PPROM, delivering between 24 + 0 and 33 + 6 gestational weeks from 2012 to 2019 in five labor units in Stockholm County, Sweden. Electronic medical records were examined to obtain background and exposure data. For the exposure IAI, we used the later diagnosis of EONS in the offspring as a proxy. EONS is strongly associated to IAI and was considered a better proxy for IAI than the histological diagnosis of acute chorioamnionitis, since acute chorioamnionitis can be observed in the absence of both positive microbiology and biochemical markers for inflammation. Cardiotocography traces were analyzed by a computerized algorithm for short-term variation of the fetal heart rate, which was the main outcome measure.

RESULTS

Twenty-seven pregnancies were categorized as having an IAI, based on the proxy diagnosis of EONS after birth. Fetuses exposed to IAI had significantly lower short-term variation values in the last cardiotocography trace before birth than fetuses who were not exposed (5.25 vs 6.62 ms; unadjusted difference: -1.37, p = 0.009). After adjustment for smoking and diabetes, this difference remained significant. IAI with a later positive blood culture in the neonate (n = 12) showed an even larger absolute difference in STV (-1.65; p = 0.034), with a relative decrease of 23.5%.

CONCLUSION

In pregnancies with PPROM, fetuses exposed to IAI with EONS as a proxy have lower short-term variation of the fetal heart rate than fetuses who are not exposed. Short-term variation might be useful as adjunct surveillance in pregnancies with PPROM.

Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities

The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications.

Process mining and data mining applications in the domain of chronic diseases: A systematic review

The widespread use of information technology in healthcare leads to extensive data collection, which can be utilised to enhance patient care and manage chronic illnesses. Our objective is to summarise previous studies that have used data mining or process mining methods in the context of chronic diseases in order to identify research trends and future opportunities. The review covers articles that pertain to the application of data mining or process mining methods on chronic diseases that were published between 2000 and 2022. Articles were sourced from PubMed, Web of Science, EMBASE, and Google Scholar based on predetermined inclusion and exclusion criteria. A total of 71 articles met the inclusion criteria and were included in the review. Based on the literature review results, we detected a growing trend in the application of data mining methods in diabetes research. Additionally, a distinct increase in the use of process mining methods to model clinical pathways in cancer research was observed. Frequently, this takes the form of a collaborative integration of process mining, data mining, and traditional statistical methods. In light of this collaborative approach, the meticulous selection of statistical methods based on their underlying assumptions is essential when integrating these traditional methods with process mining and data mining methods. Another notable challenge is the lack of standardised guidelines for reporting process mining studies in the medical field. Furthermore, there is a pressing need to enhance the clinical interpretation of data mining and process mining results.

The role of compression in large scale data transfer and storage of typical biomedical signals at hospitals

In modern hospitals, monitoring patients' vital signs and other biomedical signals is standard practice. With the advent of data-driven healthcare, Internet of medical things, wearable technologies, and machine learning, we expect this to accelerate and to be used in new and promising ways, including early warning systems and precision diagnostics. Hence, we see an ever-increasing need for retrieving, storing, and managing the large amount of biomedical signal data generated. The popularity of standards, such as HL7 FHIR for interoperability and data transfer, have also resulted in their use as a data storage model, which is inefficient. This article raises concern about the inefficiency of using FHIR for storage of biomedical signals and instead highlights the possibility of a sustainable storage based on data compression. Most reported efforts have focused on ECG signals; however, many other typical biomedical signals are understudied. In this article, we are considering arterial blood pressure, photoplethysmography, and respiration. We focus on simple lossless compression with low implementation complexity, low compression delay, and good compression ratios suitable for wide adoption. Our results show that it is easy to obtain a compression ratio of 2.7:1 for arterial blood pressure, 2.9:1 for photoplethysmography, and 4.1:1 for respiration.

Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics-An Overview of Current Applications, Challenges, and Future Opportunities

Work-related musculoskeletal disorders (WMSDs) are a major contributor to disability worldwide and substantial societal costs. The use of wearable motion capture instruments has a role in preventing WMSDs by contributing to improvements in exposure and risk assessment and potentially improved effectiveness in work technique training. Given the versatile potential for wearables, this article aims to provide an overview of their application related to the prevention of WMSDs of the trunk and upper limbs and discusses challenges for the technology to support prevention measures and future opportunities, including future research needs. The relevant literature was identified from a screening of recent systematic literature reviews and overviews, and more recent studies were identified by a literature search using the Web of Science platform. Wearable technology enables continuous measurements of multiple body segments of superior accuracy and precision compared to observational tools. The technology also enables real-time visualization of exposures, automatic analyses, and real-time feedback to the user. While miniaturization and improved usability and wearability can expand the use also to more occupational settings and increase use among occupational safety and health practitioners, several fundamental challenges remain to be resolved. The future opportunities of increased usage of wearable motion capture devices for the prevention of work-related musculoskeletal disorders may require more international collaborations for creating common standards for measurements, analyses, and exposure metrics, which can be related to epidemiologically based risk categories for work-related musculoskeletal disorders.

Evaluation of In-Cloth versus On-Skin Sensors for Measuring Trunk and Upper Arm Postures and Movements

Smart workwear systems with embedded inertial measurement unit sensors are developed for convenient ergonomic risk assessment of occupational activities. However, its measurement accuracy can be affected by potential cloth artifacts, which have not been previously assessed. Therefore, it is crucial to evaluate the accuracy of sensors placed in the workwear systems for research and practice purposes. This study aimed to compare in-cloth and on-skin sensors for assessing upper arms and trunk postures and movements, with the on-skin sensors as the reference. Five simulated work tasks were performed by twelve subjects (seven women and five men). Results showed that the mean (±SD) absolute cloth-skin sensor differences of the median dominant arm elevation angle ranged between 1.2° (±1.4) and 4.1° (±3.5). For the median trunk flexion angle, the mean absolute cloth-skin sensor differences ranged between 2.7° (±1.7) and 3.7° (±3.9). Larger errors were observed for the 90th and 95th percentiles of inclination angles and inclination velocities. The performance depended on the tasks and was affected by individual factors, such as the fit of the clothes. Potential error compensation algorithms need to be investigated in future work. In conclusion, in-cloth sensors showed acceptable accuracy for measuring upper arm and trunk postures and movements on a group level. Considering the balance of accuracy, comfort, and usability, such a system can potentially be a practical tool for ergonomic assessment for researchers and practitioners.

Measurements and observations of movements at work for warehouse forklift truck operators

Inclinometry and video analyses can provide objective measures of physical workloads. The study aim was to measure and observe arm, back and head postures and movements among forklift truck operators (FLTOs) during a working day, analyzing differences between types of forklift trucks and to assess reported workload and health. Twenty-five male FLTOs in a high-level warehouse were randomly included. The data collected comprised technical measurements, video analyses of postures and movements, and a questionnaire measuring health, pain and workload. On average, the FLTOs rotated their head more than 45°, in total, 232 times/h. Video analysis revealed that FLTOs periodically drive the forklift truck sideways with the head rotated in the direction of travel, and in periods look upwards, in which the head is highly rotated and extended. Inclinometry and observations during the working day has the potential to be a valuable part of risk assessment promoting occupational safety and health.

Reducing postural load in order picking through a smart workwear system using real-time vibrotactile feedback

Vibrotactile feedback training may be one possible method for interventions that target at learning better work techniques and improving postures in manual handling. This study aimed to evaluate the short term effect of real-time vibrotactile feedback on postural exposure using a smart workwear system for work postures intervention in simulated industrial order picking. Fifteen workers at an industrial manufacturing plant performed order-picking tasks, in which the vibrotactile feedback was used for postural training at work. The system recorded the trunk and upper arm postures. Questionnaires and semi-structured interviews were conducted about the users' experience of the system. The results showed reduced time in trunk inclination ≥20°, ≥30° and ≥45° and dominant upper arm elevation ≥30° and ≥45° when the workers received feedback, and for trunk inclination ≥20°, ≥30° and ≥45° and dominant upper arm elevation ≥30°, after feedback withdrawal. The workers perceived the system as useable, comfortable, and supportive for learning. The system has the potential of contributing to improved postures in order picking through an automated short-term training program.

The cholinergic anti-inflammatory pathway in resistant hypertension treated with renal denervation

Background

Renal denervation (RDN) reduces sympathetic tone and may alter the sympathetic-parasympathetic balance. The autonomic nervous system is partly a regulator of innate immunity via the cholinergic anti-inflammatory pathway (CAP) which inhibits inflammation via the vagus nerve. Placental Growth Factor (PlGF) influences a neuro-immunological pathway in the spleen which may contribute to hypertension. The aim of this study was to investigate if modulation of renal sympathetic nerve activity affects CAP in terms of cytokine release as well as levels of PlGF.

Methods

Ten patients treated with RDN (Medtronic Inc), were analyzed for TNF, IL-1b and IL-10 and Lipopolysaccharide (LPS)-stimulated cytokine release before RDN, 1 day after and at 3- and 6-months follow-up. Four patients who underwent elective coronary angiography served as disease controls (DC).

Results

Baseline TNF was significantly lower 1 day after RDN (p = 0.03). LPS-stimulated (0, 10 and 100 ng/mL) TNF and IL-1b were significantly lower 1 day after RDN (TNF p = 0.0009, p = 0.0009 and p = 0.001, IL-1b; p = 0.0001, p = 0.002 and p = 0.005). IL-10 was significantly higher one day after RDN (p = ns, p = 0.02 and p = 0.01). These differences however declined during follow up. A more marked TNF reduction was achieved with a cholinergic analogue, GTS-21, in LPS-stimulated whole blood as compared with samples without GTS-21. Cytokine levels in controls did not differ before and 1 day after coronary angiography. PlGF was significantly higher in RDN patients and DC compared with healthy controls but did not change during follow-up.

Conclusion

RDN has an immediate effect on TNF in vivo and cytokine release ex vivo but seems to wane over time suggesting that current RDN techniques may not have long-lasting immunomodulatory effect. Repeated and extended stimulation of CAP in resistant hypertension by targeting neural circuits may be a potential therapeutic strategy for treatment of both hypertension and inflammation.

Electronic supplementary material

The online version of this article (10.1186/s10020-019-0097-y) contains supplementary material, which is available to authorized users.

P-Ergonomics Platform: Toward Precise, Pervasive, and Personalized Ergonomics using Wearable Sensors and Edge Computing

Preventive healthcare has attracted much attention recently. Improving people’s lifestyles and promoting a healthy diet and wellbeing are important, but the importance of work-related diseases should not be undermined. Musculoskeletal disorders (MSDs) are among the most common work-related health problems. Ergonomists already assess MSD risk factors and suggest changes in workplaces. However, existing methods are mainly based on visual observations, which have a relatively low reliability and cover only part of the workday. These suggestions concern the overall workplace and the organization of work, but rarely includes individuals’ work techniques. In this work, we propose a precise and pervasive ergonomic platform for continuous risk assessment. The system collects data from wearable sensors, which are synchronized and processed by a mobile computing layer, from which exposure statistics and risk assessments may be drawn, and finally, are stored at the server layer for further analyses at both individual and group levels. The platform also enables continuous feedback to the worker to support behavioral changes. The deployed cloud platform in Amazon Web Services instances showed sufficient system flexibility to affordably fulfill requirements of small to medium enterprises, while it is expandable for larger corporations. The system usability scale of 76.6 indicates an acceptable grade of usability.

Fusion of Heart Rate, Respiration and Motion Measurements from a Wearable Sensor System to Enhance Energy Expenditure Estimation

This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21⁻65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R² = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R² = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R² = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications.

Validation of a computerized algorithm to quantify fetal heart rate deceleration area

INTRODUCTION

Reliability in visual cardiotocography interpretation is unsatisfying, which has led to the development of computerized cardiotocography. Computerized analysis is well established for antenatal fetal surveillance but has yet not performed sufficiently during labor. We aimed to investigate the capacity of a new computerized algorithm compared with visual assessment in identifying intrapartum fetal heart rate baseline and decelerations.

MATERIAL AND METHODS

In all, 312 intrapartum cardiotocography tracings with variable decelerations were analyzed by the computerized algorithm and visually examined by two observers, blinded to each other and the computer analysis. The width, depth and area of each deceleration was measured. Four cases (>100 variable decelerations) were subjected to in-depth detailed analysis. The outcome measures were bias in seconds (width), beats per minute (depth), and beats (area) between computer and observers using Bland-Altman analysis. Interobserver reliability was determined by calculating intraclass correlation and Spearman rank analysis.

RESULTS

The analysis (312 cases) showed excellent intraclass correlation (0.89-0.95) and very strong Spearman correlation (0.82-0.91). The detailed analysis of >100 decelerations in four cases revealed low bias between the computer and the two observers; width 1.4 and 1.4 seconds, depth 5.1 and 0.7 beats per minute, and area 0.1 and -1.7 beats. This was comparable to the bias between the two observers: 0.3 seconds (width), 4.4 beats per minute (depth) and 1.7 beats (area). The intraclass correlation was excellent (0.90-.98).

CONCLUSION

A novel computerized algorithm for intrapartum cardiotocography analysis is as accurate as gold standard visual assessment, with high correlation and low bias.

Elliptical broken line method for calculating capillary density in nailfold capillaroscopy: Proposal and evaluation

Nailfold capillaroscopy is a practical method for identifying and obtaining morphological changes in capillaries which might reveal relevant information about diseases and health. Capillaroscopy is harmless, and seems simple and repeatable. However, there is lack of established guidelines and instructions for acquisition as well as the interpretation of the obtained images; which might lead to various ambiguities. In addition, assessment and interpretation of the acquired images are very subjective. In an attempt to overcome some of these problems, in this study a new modified technique for assessment of nailfold capillary density is introduced. The new method is named elliptic broken line (EBL) which is an extension of the two previously known methods by defining clear criteria for finding the apex of capillaries in different scenarios by using a fitted elliptic. A graphical user interface (GUI) is developed for pre-processing, manual assessment of capillary apexes and automatic correction of selected apexes based on 90° rule. Intra- and inter-observer reliability of EBL and corrected EBL is evaluated in this study. Four independent observers familiar with capillaroscopy performed the assessment for 200 nailfold videocapillaroscopy images, form healthy subject and systemic lupus erythematosus patients, in two different sessions. The results show elevation from moderate (ICC=0.691) and good (ICC=0.753) agreements to good (ICC=0.750) and good (ICC=0.801) for intra- and inter-observer reliability after automatic correction of EBL. This clearly shows the potential of this method to improve the reliability and repeatability of assessment which motivates us for further development of automatic tool for EBL method.

Slightly superior performance of bioimpedance spectroscopy over single frequency regression equations for assessment of total body water

Electrical bioimpedance has been used for several decades to assess body fluid distribution and body composition by using single frequency and bioimpedance spectroscopic (BIS) techniques. It remains uncertain whether BIS methods have better performance compare to single frequency regression equations. In this work the performance of two BIS methods and four different 50 kHz single frequency prediction equations was studied in a data set of wrist-to-ankle tetrapolar BIS measurements (5-1000 kHz) together with reference values of total body water obtained by tritium dilution in 92 patients. Data were compared using regression techniques and Bland-Altman plots. The results of this study showed that all methods produced similarly high correlation and concordance coefficients, indicating good accuracy as a method. Limits of agreement analysis indicated that the population level performance of Sun's prediction equations was very similar to the performance of both BIS methods. However, BIS methods in practice have slightly better predictive performance than the single-frequency equations as judged by higher correlation and the limits of agreement from the Bland-Altman analysis. In any case, the authors believe that an accurate evaluation of performance of the methods cannot be done as long as the evaluation is done using Bland-Altman analysis, the commonly accepted technique for this kind of performance comparisons.

A knitted garment using intarsia technique for Heart Rate Variability biofeedback: Evaluation of initial prototype

Heart rate variability (HRV) biofeedback is a method based on paced breathing at specific rate called resonance frequency by giving online feedbacks from user respiration and its effect on HRV. Since the HRV is also influence by different factors like stress and emotions, stress related to an unfamiliar measurement device, cables and skin electrodes may cover the underling effect of such kind of intervention. Wearable systems are usually considered as intuitive solutions which are more familiar to the end-user and can help to improve usability and hence reducing the stress. In this work, a prototype of a knitted garment using intarsia technique is developed and evaluated. Results show the satisfactory level of quality for Electrocardiogram and thoracic electrical bioimpedance i.e. for respiration monitoring as a part of HRV biofeedback system. Using intarsia technique and conductive yarn for making the connection instead of cables will reduce the complexity of fabrication in textile production and hence reduce the final costs in a final commercial product. Further development of garment and Android application is ongoing and usability and efficiency of final prototype will be evaluated in detail.

Cholinergic anti-inflammatory pathway activity in dialysis patients: a role for neuroimmunomodulation?

Background

The cholinergic anti-inflammatory pathway (CAP) modulates inflammatory responses through the vagus nerve and the α-7-nicotinic acetylcholine receptor (α7nAChR) on macrophages and immune cells. Sympathetic/parasympathetic imbalance and chronic inflammation are both linked to poor outcome in dialysis patients. The aim of this study was to investigate CAP activity in these patients.

Methods

Twenty dialysis patients, 12 hemodialysis (HD) and 8 peritoneal dialysis (PD) patients (12 male, 8 female; age range 47–83 years) and 8 controls (5 male, 3 female; age range 31–52 years) were analyzed for C-reactive protein (CRP), tumor necrosis factor (TNF), interleukin-1b (IL-1b), IL-6 and IL-10 at baseline. The cytokines were then assessed after whole blood stimulation ex vivo with lipopolysaccharide (LPS) (10 and 100 ng/mL) and again in the presence of 45 and 90 μmol/L GTS-21, a cholinergic α7nAChR agonist.

Results

CRP, TNF, IL-1 and IL-6 were significantly higher, whereas IL-10 was significantly lower at baseline in patients compared with controls. After LPS stimulation, TNF increased significantly more in patients than in controls but decreased to similar levels in both groups after addition of GTS-21. IL-6 attenuation was comparable with TNF and the IL-1b pattern was similar but remained significantly higher in patients. Interestingly, IL-10 increased after GTS-21 in a dose-dependent manner, but only in patients. Results in HD and PD patients did not differ.

Conclusions

The response of immune cells after LPS exposure and cholinergic stimulation suggests a functional CAP in dialysis patients. It may thus be possible to target the α7nAChR control of cytokine release as an anti-inflammatory strategy and thereby improve outcome in these patients.

Development and preliminary evaluation of an Android based heart rate variability biofeedback system

The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic electrical bioimpedance (respiration) measurement device has been developed. The system performance and usability have been evaluated in a brief study with eight healthy volunteers. The result demonstrates real-time performance of system and positive effects of biofeedback training session by increased HRV and reduced heart rate. Further development of the application and training protocol is ongoing to investigate duration of training session to find an optimum length and interval of biofeedback sessions to use in potential interventions.

Automated NREM sleep staging using the electro-oculogram: a pilot study

Automatic sleep staging from convenient and unobtrusive sensors has received considerable attention lately because this can enable a large range of potential applications in the clinical and consumer fields. In this paper the focus is on achieving non-REM (NREM) sleep staging from ocular electrodes. From these signals, specific patterns related to sleep such as slow eye movements, K-complexes, eye blinks, and spectral features are estimated. Although such patterns are characteristic of the Electroencephalogram, they can also be visible to a lesser extent on signals from ocular electrodes. Automatic sleep staging was implemented using two approaches: i) based on a state-machine and ii) using a neural network. The first one relied on the recommendations of the American Academy of Sleep Medicine, and the second one used a multilayer perceptron which was trained on manually sleep-staged data. Results were obtained on the data of five volunteers who participated in a nap experiment. Manual sleep staging of this data, performed by an expert, was used as reference. Five stages were considered, namely wake with eyes open, wake with eyes closed, and sleep stages N1, N2, and N3. The results were characterized in terms of confusion matrices from which the Cohen's κ coefficients were estimated. The values of κ for both the state-machine and neural-network based automatic sleep staging approaches were 0.79 and 0.59 respectively. Thus, the state-machine based approach shows a very good agreement with manual staging of sleep-data.

Synthesis and pharmacological activity of 5-substituted 2-(N,N-dialkylaminoethyl)amino- and 2-N-methylpiperazinyl-1,3,4-thiadiazoles

5-Substituted 2-amino-1,3,4-thiadiazoles were transformed to their corresponding 2-bromo derivatives. The reaction of the 5-substituted 2-bromo-1,3,4-thiadiazoles with N,N-dialkylaminoethylamines or N-methylpiperazine afforded the corresponding amino-1,3,4-thiadiazole derivatives. All prepared compounds displayed antihistaminic, anticholinergic, and norepinephrine-potentiating activities.