It is crucial to precisely monitor ventilation and correctly diagnose ventilation-related pathological states for averting lung collapse and lung failure in Intensive Care Unit (ICU) patients. Although Electrical Impedance Tomography (EIT) may deliver this information continuously and non-invasively at bedside, to date there are no studies that systematically compare EIT and Dual Energy CT (DECT) during inspiration and expiration (ΔDECT) regarding varying physiological and ICU-typical pathological conditions such as atelectasis. This study aims to prove the accuracy of EIT through quantitative identification and monitoring of pathological ventilation conditions on a four-quadrant basis using ΔDECT. In a cohort of 13 pigs, this study investigated systematic changes in tidal volume (TV) and positive end-expiratory pressure (PEEP) under physiological ventilation conditions. Pathological ventilation conditions were established experimentally by single-lung ventilation and pulmonary saline lavage. Spirometric data were compared to voxel-based entire lung ΔDECT, and EIT intensities were compared to ΔDECT of a 12-cm slab of the lung around the EIT belt, the so called ΔDECT Belt . To validate ΔDECT data with spirometry, a Pearson’s correlation coefficient of 0.92 was found for 234 ventilation conditions. Comparing EIT intensity with ΔDECT (Belt) , the correlation r = 0.84 was found. Normalized cross-correlation function (NCCF) between scaled global impedance (EIT) waveforms and global volume ventilator curves was r = 0.99 ± 0.003. The EIT technique correctly identified the ventilated lung in all cases of single-lung ventilation. In the four-quadrant based evaluation, which assesses the difference between end-expiratory lung volume (ΔEELV) and the corresponding parameter in EIT, i.e. the end-expiratory lung impedance (ΔEELI), the Pearson’s correlation coefficient of 0.94 was found. The respective Pearson’s correlation coefficients implies good to excellent concurrence between global and regional EIT ventilation data validated by ventilator spirometry and DECT imaging. By providing real-time images of the lung, EIT is a promising, EIT is a promising, clinically robust tool for bedside assessment of regional ventilation distribution and changes of end-expiratory lung volume.

Die Begriffe E‑Health und Digitalisierung sind Kernelemente eines Wandels unserer Zeit. Wesentliche Treiber dieses Wandels sind – neben einem dynamischen Markt – die gravierenden Vorteile für das Gesundheitswesen in der Bearbeitung von Aufgaben und Anforderungen. Das Aufkommen großer Datenmengen, das rapide wachsende medizinische Wissen, die rasch fortschreitenden technologischen Entwicklungen und das Ziel einer personalisierten individuell angepassten Therapie für den Patienten machen den Einsatz zwingend notwendig. Während E‑Health den Einsatz von Informations- und Kommunikationstechnologien im Gesundheitswesen beschreibt, sind dem Begriff der Digitalisierung die zugrundeliegenden Prozesse der Veränderungen und Innovationen zugeordnet. Digitale Technologien umfassen Software- und Hardware-basierte Entwicklungen. Unter dem Begriff „klinische Datenintelligenz“ werden Eigenschaften hinsichtlich der Leistungsfähigkeit und der Zusammenarbeit klinisch relevanter Systeme charakterisiert. Die Hierarchie in der digitalen Bearbeitung bildet Ebenen von der reinen Datenverwaltung über klinische Entscheidungsunterstützung bis zu automatisierten Prozessabläufen und autonom agierenden Einheiten ab. Die Kombination aus Patientendatenmanagement und klinischer Entscheidungsunterstützung beweist hierbei ihren Stellenwert in Bezug auf Fehlervermeidung, Prävention, Qualität und Sicherheit, insbesondere bei der Arzneimitteltherapie. Ziel dieser Übersicht ist die Darstellung der bereits bestehenden Realität in der Klinik mit den daraus abzuleitenden Perspektiven aus der Sicht des medizinischen Anwenders.

Complex, often high-dimensional time series are observed in medical applications such as intensive care. We review statistical tools for intelligent alarm systems, which are helpful for guiding medical decision-making in time-critical situations. The procedures described can also be applied for decision support or in closed-loop controllers. Robust time series filters allow one to extract a signal in the form of a time-varying trend with little or no delay. Additional rules-based, for instance, on suitably designed statistical tests-can be incorporated to preserve or detect interesting patterns such as level shifts or trend changes. Statistical pattern detection is a useful preprocessing step for decision-support systems. Dimension reduction techniques allow the compression of the often high-dimensional time series into a few variables containing most of the information inherent in the observed data. Combining such techniques with tools for analyzing the relationships among the variables in the form of large partial correlations or similar trend behavior improves the interpretability of the extracted variables and provides information that is thus meaningful to physicians.

Metrology is the science of measurements. Although of critical importance in medicine and especially in critical care, frequent confusion in terms and definitions impact either interphysician communications or understanding of manufacturers’ and engineers’ instructions and limitations when using devices. In this review, we first list the terms defined by the International Bureau of Weights and Measures regarding quantities and units, measurements, devices for measurement, properties of measuring devices, and measurement standards. The traditional tools for assessing the most important measurement quality criteria are also reviewed with clinical examples for diagnosis, alarm, and titration purposes, as well as for assessing the uncertainty of reference methods.

To the Editor,In response to the publication of the article by Kawaji et al. in this journal, describing a study comparing Premier Heart's Multifunction Cardiogram (MCG) with coronary angiography (CAG) including quantitative coronary angiography (QCA), and fractional flow reserve (FFR) in the assessment of coronary artery disease (CAD), 1 we have significant concerns about the conduct, results and interpretation of the study.The authors enrolled 100 stable patients over a time span of 6 months but only 89 were actually included.Given the wide inclusion criteria for a study at one of the leading cardiology centers in Japan it must be assumed that those 89 patients represented a fraction of the eligible patients.Moreover, nearly 50% of the patients were 75 years or older which even by Japanese population standards seems to be a distribution skewed toward elderly patients.Therefore, a relevant selection bias cannot be ruled out.A second concern is that hemodynamically relevant collateral circulation was apparently not considered in the analysis of the CAG findings.As the goal of this study was to identify

Metrology is the science of measurements. Although of critical importance in medicine and especially in critical care, frequent confusion in terms and definitions impact either interphysician communications or understanding of manufacturers’ and engineers’ instructions and limitations when using devices. In this review, we first list the terms defined by the International Bureau of Weights and Measures regarding quantities and units, measurements, devices for measurement, properties of measuring devices, and measurement standards. The traditional tools for assessing the most important measurement quality criteria are also reviewed with clinical examples for diagnosis, alarm, and titration purposes, as well as for assessing the uncertainty of reference methods.

In day to day medical care, patients, nursing staff and doctors currently face a bewildering and rapidly growing number of health-related apps running on various "smart" devices and there are also uncountable possibilities for the use of such technology. Concerning regulation, a risk-based approach is applied for development and use (including safety and security considerations) of medical and health-related apps. Considering safety-related issues as well as organizational matters, this is a sensible approach but requires honest self-assessment as well as a high degree of responsibility, networking and good quality management by all those involved. This cannot be taken for granted. Apart from regulatory aspects it is important to not only consider what is reasonable, helpful or profitable. Quality aspects, safety matters, data protection and privacy as well as liability issues must also be considered but are often not adequately respected. If software quality is compromised, this endangers patient safety as well as data protection, privacy and data integrity. This can for example result in unwanted advertising or unauthorized access to the stored data by third parties; therefore, local, regional and international regulatory measures need to be applied in order to ensure safe use of medical apps in all possible areas, including the operating room (OR) with its highly specialized demands. Lawmakers need to include impulses from all stakeholders in their considerations and this should include input from existing private initiatives that already deal with the use and evaluation of apps in a medical context. Of course, this process needs to respect pre-existing national, European as well as international (harmonized) standards.

Patienten, Pflegekräfte, Ärztinnen und Ärzte sehen sich im medizinischen Alltag einer rasch wachsenden und unüberschaubaren Zahl an gesundheitsbezogenen Apps und Einsatzmöglichkeiten von „smarten“ Geräten gegenüber. Die Schnittstelle zwischen Herstellung, Anwendung und Sicherheit von Apps im Bereich Medizin und Gesundheit basiert im Rahmen der Regulation auf einem risikoadaptierten Ansatz. Dieser scheint aus sicherheitstechnischen und praktisch organisatorischen Erwägungen sinnvoll, erfordert allerdings von allen Beteiligten ein hohes Maß an Selbsteinschätzung, Verantwortungsbewusstsein, Vernetzung und Qualitätsmanagement. Es kann nicht zwingend davon ausgegangen werden, dass all dies gegeben ist. Abseits der Regulation stellt sich nicht nur die Frage, was sinnvoll, hilfreich und nutzbringend ist, sondern es sind auch Qualitätsaspekte, Sicherheit, Datenschutz und Haftung zu beachten. Diese Aspekte werden in der täglichen Anwendungspraxis häufig ausgeblendet. Qualitätseingeschränkte Software gefährdet die Patientensicherheit sowie den Datenschutz und die Datenspeicherung. Unerwünschte Nebenwirkungen sind beispielsweise irreguläre Werbungen und unerlaubtes Eindringen von außen. Daher sind lokale, regionale und internationale regulatorische Netzwerke nachzuschalten – mit dem Ziel, eine sichere Anwendung von Medical Apps bis hinein in den Hochsicherheitsbereich des OP zu gewährleisten. Der Gesetzgeber ist aufgefordert, Impulse aller Beteiligten aufzugreifen (einschließlich existierender privatwirtschaftlicher Initiativen), die sich mit der Bewertung von Apps im medizinischen Kontext auseinandersetzen. Dies ist natürlich unter Berücksichtigung bereits existierender nationaler, europäischer sowie internationaler (harmonisierter) Vorgaben umzusetzen.

The measurement of body (core) temperature is well established in clinical care. However, there are still numerous challenges especially in mature and premature infants including the lack of a reliable, non-invasive and fast measurement method for body core temperature. The current standard of care, technological challenges and limitations, as well as current and future research needs will be discussed in this contribution.

Cardiac output (CO) is one of the more elusive hemodynamic variables when it comes to clinical assessment. In contrast to heart rate and blood pressure which can be felt and counted, clinicians are very poor when it comes to estimating CO by clinical assessment only.1–3 Moreover, other more easily accessible hemodynamic variables (heart rate, blood pressure, central venous pressure) alone or in combination cannot serve as surrogates for CO. This means that CO has to be measured, if clinical decision making shall be based on this variable. But why should we bother about CO? Because knowledge of CO can help us make therapeutic decisions that may improve patient outcomes. CO, stroke volume, or parameters derived from CO are the main target parameters in most goal-directed therapy protocols that have been shown to improve relevant patient outcomes.4–6 In these protocols, CO is used to guide therapy with the aim to optimize hemodynamics in perioperative settings, in septic patients, in severe trauma, and other disease entities. The majority of these protocols that have improved patient outcomes in prospective clinical trials require absolute measurements of CO or stroke volume as input for the respective decision support algorithms.5,6 Therefore, CO must be measured and it must be measured in a way that measurement errors do not lead to inadvertent therapeutic decision errors. For many years, thermodilution with the pulmonary artery catheter (PAC) was the accepted clinical standard for measurement of CO.7 Starting with the results from the SUPPORT study in 1996,8 the medical community became more critical of the ubiquitous use of PACs and began looking for alternative technologies for CO measurement in clinical practice. A multitude of methods ranging from invasive, but “less” invasive than the PAC, to completely noninvasive was investigated in preclinical and clinical trials, and numerous devices have been introduced to the market and are used in clinical practice.9 If a good fairy would grant us at least 1 wish for a CO monitor, our wish would be quite simple and straightforward: The device should measure absolute CO accurately, precisely, and noninvasively in any given patient. It should be easy to use, comfortable for the patient, risk-free, mobile, robust, and inexpensive. With this simple wish in mind the study by Bubenek-Turconi et al.10 could not be more relevant and timely. In their well-designed and well-conducted clinical study, the authors compare a noninvasive continuous CO monitor, the Nexfin, against bolus thermodilution CO via the PAC. The authors studied 28 cardiac surgery patients shortly after coming off cardiopulmonary bypass during their first hours in the intensive care unit. In comparing Nexfin readings with thermodilution, the investigators took great care to minimize measurement errors both for Nexfin and for the reference thermodilution. While they found good agreement between both methods in tracking CO changes induced by therapeutic interventions and overall bias was small both for relative and absolute measurements, limits of agreement for absolute measurements were close to 40%. The Bland-Altman plots show that a reference CO value of 6 L/min may be displayed as anything from 3.9 to 8.1 L/min on the noninvasive device. In their discussion, the authors correctly point to the well-publicized fact that thermodilution in itself can be erroneous and contribute significantly to the observed limits of agreement. This may imply that at least some of the observed measurement error of Nexfin may be caused by the imperfection of thermodilution. On the contrary, the process of measuring thermodilution CO in this study was meticulous, representing the clinical state of the art which is also documented by an intrinsic precision of <3%. Therefore, one may assume that observed differences between thermodilution CO and noninvasive CO may have been caused primarily by the latter. In their discussion, Bubenek-Turconi et al.10 diligently put their results into perspective with the pertinent literature and clinical practice. But one of the authors’ conclusions leaves one puzzled, namely that the Nexfin despite limited accuracy compared against a PAC could be “a suitable monitor for the perioperative continuous measurement of CO.” The study shows that this device can track relative changes of CO quite satisfactorily in stable patients. This is important when checking whether a patient responds to, for instance, a fluid bolus with an adequate increase in CO. But, in clinical practice, it is at least as important to know whether the patient is hypodynamic or hyperdynamic or just right. Most hemodynamic protocols target absolute values for CO.5,6 Let us assume our protocol targets a cardiac index of 4.0 L/min/m2. Let us further assume we measure CO with a device that, similar to the study results by Bubenek-Turconi et al.,10 has limits of agreement of close to 40%. A true value for cardiac index of 4.0 could then result in a measured value between 2.4 and 5.6, the former probably resulting in aggressive resuscitation of the patient, the latter in an immediate reduction of hemodynamic support; although nothing should have been changed, if the true value had been known. This hypothetical example leads to a more general question: how wide are the limits of agreement that we can accept without potentially harming our patients? As long as most hemodynamic protocols are directly or indirectly based on absolute CO values, absolute CO measurements should be so precise and accurate that the measurement errors do not lead to unwanted and potentially dangerous treatment decisions. Keeping that in mind, I am truly concerned about the ongoing debate about which limits of agreement are clinically acceptable. When I started my residency in surgical critical care many years ago, the maybe not fully justified assumption was that CO could be measured with an error of ±15%. Ten years ago, Critchley and Critchley11 suggested accepting limits of agreement of 30% and now we are apparently discussing whether limits of agreement of 40% or more may be clinically acceptable.12,13 It is obvious that limits of agreement of 30% and more may directly impact clinical decision making in an unforeseeable manner. This would not be acceptable to me. My take home message from the excellent study by Bubenek-Turconi et al.10 and from the ensuing discussion is that measurement errors of up to 40% are not acceptable, if one wants to do protocol-driven hemodynamic therapy, and that we need to intensify our quest for less harmful but reliable methods to measure CO. We may need to be more cautious about the results of validation studies with such technologies. Otherwise, we may even want to introduce a totally noninvasive and absolutely inexpensive method—casting a dice. Alea iacta esta—your CO is measured. DISCLOSURES Name: Michael Imhoff, MD, PhD. Contribution: This author wrote the manuscript. Conflicts of Interest: Michael Imhoff reported a Senior Advisor to Boston MedTech Advisors, Inc. (Dedham, MA), consulted for Draeger Medical GmbH (Lübeck, Germany), consulted for CNSystems AG (Graz, Austria), and has equity interest in CNSystems AG. Attestation: Michael Imhoff approved the final manuscript. This manuscript was handled by: Dwayne R. Westenskow, PhD.