A New Digital Preoperative Planning Method for Total Hip Arthroplasties

Preoperative templating is an important part of a THA. The ability to accurately determine magnification of the hip on the radiograph and apply identical magnification to the radiograph and template will improve accuracy of preoperative templating of THA. We designed a templating method using a new way of determining the hip magnification with a linear relationship between magnification of the hip and the reference object on top of the pubis symphysis; the relationship was determined on 50 radiographs. We then compared our method with two other templating methods: an analog method assuming an average hip magnification of 15% and a digital method determining the hip magnification with a one-to-one relationship between the reference object and the hip. All methods were reproducible. Uniform undersizing occurred when templating with the digital method based on the one-to-one relationship; the analog method best predicted the implanted prosthesis size, closely followed by our new digital templating method; the new method will be particularly applicable for preoperative THA when analog methods are replaced by digital method

FlexEvent:going beyond Case-Centric Exploration and Analysis of Multivariate Event Sequences

In many domains, multivariate event sequence data is collected focused around an entity (the case). Typically, each event has multiple attributes, for example, in healthcare a patient has events such as hospitalization, medication, and surgery. In addition to the multivariate events, also the case (a specific attribute, e.g., patient) has associated multivariate data (e.g., age, gender, weight). Current work typically only visualizes one attribute per event (label) in the event sequences. As a consequence, events can only be explored from a predefined case-centric perspective. However, to find complex relations from multiple perspectives (e.g., from different case definitions, such as doctor), users also need an event- and attribute-centric perspective. In addition, support is needed to effortlessly switch between and within perspectives. To support such a rich exploration, we present FlexEvent: an exploration and analysis method that enables investigation beyond a fixed case-centric perspective. Based on an adaptation of existing visualization techniques, such as scatterplots and juxtaposed small multiples, we enable flexible switching between different perspectives to explore the multivariate event sequence data needed to answer multi-perspective hypotheses. We evaluated FlexEvent with three domain experts in two use cases with sleep disorder and neonatal ICU data that show our method facilitates experts in exploring and analyzing real-world multivariate sequence data from different perspectives

Continuous sensing and quantification of body motion in infants:A systematic review

Abnormal body motion in infants may be associated with neurodevelopmental delay or critical illness. In contrast to continuous patient monitoring of the basic vitals, the body motion of infants is only determined by discrete periodic clinical observations of caregivers, leaving the infants unattended for observation for a longer time. One step to fill this gap is to introduce and compare different sensing technologies that are suitable for continuous infant body motion quantification. Therefore, we conducted this systematic review for infant body motion quantification based on the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). In this systematic review, we introduce and compare several sensing technologies with motion quantification in different clinical applications. We discuss the pros and cons of each sensing technology for motion quantification. Additionally, we highlight the clinical value and prospects of infant motion monitoring. Finally, we provide suggestions with specific needs in clinical practice, which can be referred by clinical users for their implementation. Our findings suggest that motion quantification can improve the performance of vital sign monitoring, and can provide clinical value to the diagnosis of complications in infants.</p

Fractional anisotropy in white matter tracts of very-low-birth-weight infants

Background: Advances in neonatal intensive care have not yet reduced the high incidence of neurodevelopmental disability among very-low-birth-weight (VLBW) infants. As neurological deficits are related to white-matter injury, early detection is important. Diffusion tensor imaging (DTI) could be an excellent tool for assessment of white-matter injury. Objective: To provide DTI fractional anisotropy (FA) reference values for white-matter tracts of VLBW infants for clinical use. Materials and methods: We retrospectively analysed DTI images of 28 VLBW infants (26-32 weeks gestational age) without evidence of white-matter abnormalities on conventional MRI sequences, and normal developmental outcome (assessed at age 1-3 years). For DTI an echoplanar sequence with diffusion gradient (b = 1,000 s/mm2) applied in 25 non-collinear directions was used. We measured FA and apparent diffusion coefficient (ADC) of different white-matter tracts in the first 4 days of life. Results: A statistically significant correlation was found between gestational age and FA of the posterior limb of the internal capsule in VLBW infants (r = 0.495, P<0.01). Conclusion: Values of FA and ADC were measured in white-matter tracts of VLBW infants. FA of the pyramidal tracts measured in the first few days after birth is related to gestational age

Monitoring the respiratory rate of preterm infants using an ultrathin film sensor embedded in the bedding: a comparative feasibility study

Objective: To determine the feasibility of unobtrusively monitoring the respiratory rate (RR) in preterm infants by using a film-like pressure sensor placed between the mattress and the bedding. Approach: The RR was simultaneously measured by processing the chest impedance (CI) and the ballistographic (BSG) signal acquired from the pressure sensor in 10 preterm infants of varying body weight. Nearly 27 h of data were analyzed from these infants while in different body positions including both spontaneously breathing infants and those receiving non-invasive respiratory support. Main results: The RR acquired from the BSG signal (RR-BSG) was significantly correlated (r = 0.74) to the RR derived from the CI (RR-CI) with narrow 95% limits of agreement (10 breaths min -1). A subanalysis of epochs most and least affected by infant movement yielded comparable results. Significance: Irrespective of body weight or infant position, unobtrusively monitoring the RR of preterm infants is feasible using film-like pressure sensors

CheckMates, Helping Nurses Plan Ahead in the Neonatal Intensive Care Unit

Workflow in a neonatal intensive care unit (NICU) is relatively unpredictable, which makes it difficult to plan activities. Simple tasks, such as checking device statuses may be forgotten, resulting in disturbing alarms. In this paper, we will present CheckMates, ambient lighting displays, which visualize device statuses to provide nurses with more overview. We performed expert reviews to obtain insights into the different potentials of CheckMates. Additionally, we performed a simulation study to gather user experiences regarding the functioning of CheckMates and their capacity to improve planning in an NICU environment. The results showed a variety of potential benefits for increasing nurses&rsquo; overview of device statuses and their opportunities for workflow planning. Furthermore, CheckMates did not appear to be distracting

Predictive monitoring of critical cardiorespiratory alarms in neonates under intensive care

We aimed at reducing alarm fatigue in neonatal intensive care units by developing a model using machine learning for the early prediction of critical cardiorespiratory alarms. During this study in over 34,000 patient monitoring hours in 55 infants 278,000 advisory (yellow) and 70,000 critical (red) alarms occurred. Vital signs including the heart rate, breathing rate, and oxygen saturation were obtained at a sampling frequency of 1 Hz while heart rate variability was calculated by processing the ECG – both were used for feature development and for predicting alarms. Yellow alarms that were followed by at least one red alarm within a short post-alarm window constituted the case-cohort while the remaining yellow alarms constituted the control cohort. For analysis, the case and control cohorts, stratified by proportion, were split into training (80%) and test sets (20%). Classifiers based on decision trees were used to predict, at the moment the yellow alarm occurred, whether a red alarm(s) would shortly follow. The best performing classifier used data from the 2-min window before the occurrence of the yellow alarm and could predict 26% of the red alarms in advance (18.4s, median), at the expense of 7% additional red alarms. These results indicate that based on predictive monitoring of critical alarms, nurses can be provided a longer window of opportunity for preemptive clinical action. Further, such as algorithm can be safely implemented as alarms that are not algorithmically predicted can still be generated upon the usual breach of the threshold, as in current clinical practice