Understanding the Interactions Between Driving Behavior and Well-being in Daily Driving: Causal Analysis of a Field Study.

BACKGROUND: Investigating ways to improve well-being in everyday situations as a means of fostering mental health has gained substantial interest in recent years. For many people, the daily commute by car is a particularly straining situation of the day, and thus researchers have already designed various in-vehicle well-being interventions for a better commuting experience. Current research has validated such interventions but is limited to isolating effects in controlled experiments that are generally not representative of real-world driving conditions. OBJECTIVE: The aim of the study is to identify cause-effect relationships between driving behavior and well-being in a real-world setting. This knowledge should contribute to a better understanding of when to trigger interventions. METHODS: We conducted a field study in which we provided a demographically diverse sample of 10 commuters with a car for daily driving over a period of 4 months. Before and after each trip, the drivers had to fill out a questionnaire about their state of well-being, which was operationalized as arousal and valence. We equipped the cars with sensors that recorded driving behavior, such as sudden braking. We also captured trip-dependent factors, such as the length of the drive, and predetermined factors, such as the weather. We conducted a causal analysis based on a causal directed acyclic graph (DAG) to examine cause-effect relationships from the observational data and to isolate the causal chains between the examined variables. We did so by applying the backdoor criterion to the data-based graphical model. The hereby compiled adjustment set was used in a multiple regression to estimate the causal effects between the variables. RESULTS: The causal analysis showed that a higher level of arousal before driving influences driving behavior. Higher arousal reduced the frequency of sudden events (P=.04) as well as the average speed (P=.001), while fostering active steering (P<.001). In turn, more frequent braking (P<.001) increased arousal after the drive, while a longer trip (P<.001) with a higher average speed (P<.001) reduced arousal. The prevalence of sunshine (P<.001) increased arousal and of occupants (P<.001) increased valence (P<.001) before and after driving. CONCLUSIONS: The examination of cause-effect relationships unveiled significant interactions between well-being and driving. A low level of predriving arousal impairs driving behavior, which manifests itself in more frequent sudden events and less anticipatory driving. Driving has a stronger effect on arousal than on valence. In particular, monotonous driving situations at high speeds with low cognitive demand increase the risk of the driver becoming tired (low arousal), thus impairing driving behavior. By combining the identified causal chains, states of vulnerability can be inferred that may form the basis for timely delivered interventions to improve well-being while driving.

Clinical decision support recommending ventilator settings during noninvasive ventilation.

NIV therapy is used to provide positive pressure ventilation for patients. There are protocols describing what ventilator settings to use to initialize NIV; however, the guidelines for titrating ventilator settings are less specific. We developed an advisory system to recommend NIV ventilator setting titration and recorded respiratory therapist agreement rates at the bedside. We developed an algorithm (NIV advisor) to recommend when to change the non-invasive ventilator settings of IPAP, EPAP, and FiO2 based on patient respiratory parameters. The algorithm utilized a multi-target approach; oxygenation, ventilation, and patient effort. The NIV advisor recommended ventilator settings to move the patient's respiratory parameters in a preferred target range. We implemented a pilot study evaluating the usability of the NIV advisor on 10 patients receiving critical care with non-invasive ventilation (NIV). Respiratory therapists were asked their agreement on recommendations from the NIV advisor at the patient's bedside. Bedside respiratory therapists agreed with 91% of the ventilator setting recommendations from the NIV advisor. The POB and VT values were the respiratory parameters that were most often out of the preferred target range. The IPAP ventilator setting was the setting most often considered in need of changing by the NIV advisor. The respiratory therapists agreed with the majority of the recommendations from the NIV advisor. We consider the IPAP recommendations informative in providing the respiratory therapist assistance in targeting preferred POB and Vt values, as these values were frequently out of the target ranges. This pilot implementation was unable to produce the results required to determine the value of the EPAP recommendations. The FiO2 recommendations from the NIV advisor were treated as ancillary information behind the IPAP recommendations.

Breathing variability predicts the suggested need for corrective intervention due to the perceived severity of patient-ventilator asynchrony during NIV.

Patient-ventilator asynchrony is associated with intolerance to noninvasive ventilation (NIV) and worsened outcomes. Our goal was to develop a tool to determine a patient needs for  intervention by a practitioner due to the presence of patient-ventilator asynchrony. We postulated that a clinician can determine when a patient needs corrective intervention due to the perceived severity of patient-ventilator asynchrony. We hypothesized a new measure, patient breathing variability, would indicate when corrective intervention is suggested by a bedside practitioner due to the perceived severity of patient-ventilator asynchrony. With IRB approval data was collected on 78 NIV patients. A panel of experts reviewed retrospective data from a development set of 10 NIV patients to categorize them into one of the three categories. The three categories were; "No to mild asynchrony-no intervention needed", "moderate asynchrony-non-emergent corrective intervention required", and "severe asynchrony-immediate intervention required". A stepwise regression with a F-test forward selection criterion was used to develop a positive linear logic model predicting the expert panel's categorizations of the need for corrective intervention. The model was incorporated into a software tool for clinical implementation. The tool was implemented prospectively on 68 NIV patients simultaneous to a bedside practitioner scoring the need for corrective intervention due to the perceived severity of patient-ventilator asynchrony. The categories from the tool and the practitioner were compared with the rate of agreement, sensitivity, specificity, and receiver operator characteristic analyses. The rate of agreement in categorizing the suggested need for clinical intervention due to the perceived presence of patient-ventilator asynchrony between the tool and experienced bedside practitioners was 95% with a Kappa score of 0.85 (p < 0.001). Further analysis found a specificity of 84% and sensitivity of 99%. The tool appears to accurately match the suggested need for corrective intervention by a bedside practitioner. Application of the tool allows for continuous, real time, and non-invasive monitoring of patients receiving NIV, and may enable early corrective interventions to ameliorate potential patient-ventilator asynchrony.

Statistical interpretation of the Amerithrax "morph" assay results.

In the Amerithrax investigation PCR-based "morph assays" were used to link the anthrax letters with the RMR-1029 flask at USAMRIID. Quantitative data reported for several of these assays are not consistent with Poisson sampling statistics, but instead exhibit "Taylor's Law" behavior where the variance greatly exceeds the mean. A plausible statistical model for this behavior can explain the large number of observed negative and "inconclusive" findings, and implies a high likelihood that a repository sample could contain a "morph" mutant at concentrations well above the nominal detection limit but nonetheless give a negative or inconclusive test result. A Bayesian framework relates the assay results to the probability that a sample actually contains all four morph mutants, even though it tested negative for at least one. The analysis implies that the observed false negative rate actually does not significantly weaken the conclusion that the morph assays correctly excluded all but the stocks derived from RMR-1029 as possible sources of the letter powders, at least when the test results were unambiguous. These findings expand upon and resolve some of the issues cited in recent reviews, and indicate the importance of developing a rigorous statistical framework for interpreting "morph" assay data.

Real time noninvasive estimation of work of breathing using facemask leak-corrected tidal volume during noninvasive pressure support: validation study.

We describe a real time, noninvasive method of estimating work of breathing (esophageal balloon not required) during noninvasive pressure support (PS) that uses an artificial neural network (ANN) combined with a leak correction (LC) algorithm, programmed to ignore asynchronous breaths, that corrects for differences in inhaled and exhaled tidal volume (VT) from facemask leaks (WOBANN,LC/min). Validation studies of WOBANN,LC/min were performed. Using a dedicated and popular noninvasive ventilation ventilator (V60, Philips), in vitro studies using PS (5 and 10 cm H2O) at various inspiratory flow rate demands were simulated with a lung model. WOBANN,LC/min was compared with the actual work of breathing, determined under conditions of no facemask leaks and estimated using an ANN (WOBANN/min). Using the same ventilator, an in vivo study of healthy adults (n = 8) receiving combinations of PS (3-10 cm H2O) and expiratory positive airway pressure was done. WOBANN,LC/min was compared with physiologic work of breathing/min (WOBPHYS/min), determined from changes in esophageal pressure and VT applied to a Campbell diagram. For the in vitro studies, WOBANN,LC/min and WOBANN/min ranged from 2.4 to 11.9 J/min and there was an excellent relationship between WOBANN,LC/breath and WOBANN/breath, r = 0.99, r(2) = 0.98 (p < 0.01). There were essentially no differences between WOBANN,LC/min and WOBANN/min. For the in vivo study, WOBANN,LC/min and WOBPHYS/min ranged from 3 to 12 J/min and there was an excellent relationship between WOBANN,LC/breath and WOBPHYS/breath, r = 0.93, r(2) = 0.86 (p < 0.01). An ANN combined with a facemask LC algorithm provides noninvasive and valid estimates of work of breathing during noninvasive PS. WOBANN,LC/min, automatically and continuously estimated, may be useful for assessing inspiratory muscle loads and guiding noninvasive PS settings as in a decision support system to appropriately unload inspiratory muscles.

Tirzepatide Therapy in a Patient with Type 2 Diabetes Mellitus, Chylomicronemia, and Heterozygosity for Lipoprotein Lipase Deficiency.

Background/Objective: A patient with well-controlled type 2 diabetes mellitus (T2DM) and a heterozygote for lipoprotein lipase deficiency (HeLPL) presented with chronic chylomicrons (CMs). Some patients with T2DM can develop CMs due to poor glycemic control or genetic defects that result in a decrease in the lipoprotein lipase (LPL) activity. This study aimed to describe a patient with HeLPL with T2DM and persistent CM on maximal standard lipid-lowering therapy who then used tirzepatide as a novel way to treat CM. Case Report: A patient with well-controlled T2DM with persistent CM and HeLPL was treated with tirzepatide and titrated to 15 mg/week, resulting in resolution of his CM (triglyceride [TG] level, <850 mg/dL) with a 58% reduction in the serum TG level after 2 months and then an 86% reduction after 5 months of therapy. His A1C level and body weight decreased from 6.9% to 6.3% and by 12 lbs in 2 months and then to 5.6% and by 20 lbs after 5 months, respectively. Discussion: The resolution of CM and reduction in the TG level by tirzepatide cannot be solely explained by an improvement in glycemic control or a decrease in body weight but may also be related to other effects of tirzepatide. Conclusion: Tirzepatide caused a significant decrease in the TG level in a patient with CM, T2DM, and HeLPL. The mechanism(s) underlying this effect is not completely understood but warrants further study.

Use of a Portable Electronic Interface Improves Clinical Handoffs and Adherence to Lung Protective Ventilation.

Background: Mechanical ventilation (MV) is used to support patients with respiratory impairment. Evidence supports the use of lung-protective ventilation (LPV) during MV to improve outcomes. However, studies have demonstrated poor adherence to LPV guidelines. We hypothesized that an electronic platform adapted to a hand-held tablet receiving real-time ventilatory parameters could increase clinician awareness of key LPV parameters. Furthermore, we speculated that an electronic shift-change tool could improve the quality of clinician handoffs. Methods: Using a specially designed Wi-Fi dongle to transmit data from three ventilators and a respiratory monitor, we implemented a system that displays data from all ventilators under the care of a Respiratory Care Practitioner (RCP) on an electronic tablet. In addition, the tablet created a handoff checklist to improve shift-change communication. In a simulated ICU environment, we monitored the performance of eight RCPs at baseline and while using the system. Results: Using the system, the time above guideline Pplat decreased by 74% from control, and the time outside the VT range decreased by 60% from control, p = 0.007 and 0.015, respectively. The handoff scores improved quality significantly from 2.8 to 1.6 on a scale of 1 to 5 (1 being best), p = 0.03. Conclusion: In a simulated environment, an electronic RT tool can significantly improve shift-change communication and increase the RCP's level of LPV adherence.

Patients alter power of breathing as the primary response to changes in pressure support ventilation.

INTRODUCTION: The patient-ventilator relationship is dynamic as the patient's health fluctuates and the ventilator settings are modified. Spontaneously breathing patients respond to mechanical ventilation by changing their patterns of breathing. This study measured the physiologic response when pressure support (PS) settings were modified during mechanical ventilation. METHODS: Subjects were instrumented with a non-invasive pressure, flow, and carbon dioxide airway sensor to estimate tidal volume, respiratory rate, minute ventilation, and end-tidal CO2. Additionally, a catheter was used to measure esophageal pressure and estimate effort exerted during breathing. Respiratory function measurements were obtained while PS settings were adjusted 569 times between 5 and 25 cmH2O. RESULTS: Data was collected on 248 patients. The primary patient response to changes in PS was to adjusting effort (power of breathing) followed by adjusting tidal volume. Changes in respiratory rate were less definite while changes in minute ventilation and end-tidal CO2 appeared unrelated to the change in PS. CONCLUSION: The data indicates that patients maintain a set minute ventilation by adjusting their breathing rate, volume, and power. The data indicates that the subjects regulate their Ve and PetCO2 by adjusting power of breathing and breathing pattern.

Decision support system facilitates rapid decreases in pressure support and appropriate inspiratory muscle workloads in adults with respiratory failure.

PURPOSE: A commercially available decision support system (DSS) provides guidance for setting inspiratory pressure support (PS) to maintain work of breathing (WOB/min), breathing frequency (f), and tidal volume (VT) in proper clinical ranges (VentAssist™). If these values are outside the proper clinical range patients may suffer fatigue, atrophy, hypoventilation, hyperventilation, volutrauma, or VT deficiency. The purpose of our study was to evaluate the increase of the percentage of breaths in the targeted clinical ranges when the DSS guidance for setting the PS was followed. MATERIALS AND METHODS: The study included 43 intubated adults with respiratory failure in an academic medical intensive care unit. Each of the patients had received ventilatory support for >24h with no weaning trials attempted. Clinicians switched the ventilator to PS then proceeded to utilize the guidance recommended by the DSS for setting PS for 21 patients (intervention group); while the clinicians caring for the remaining 23 patients did not have access to the DSS (control group). RESULTS: The use of a DSS to set PS level increased the percentage of breaths in the targeted clinical range [28% to 48%, p value<0.0001]. An unexpected result was that while following the DSS 18 of the 21 patients were rapidly weaned to minimal ventilator settings within 46±38min; however, when the DSS was not available weaning to minimal ventilator settings lasted 21±12h [p value<0.0001]. CONCLUSIONS: The DSS is successful at assisting clinicians on how to set PS specific to a patient's individual demands (VT and f) while accounting for their breathing effort (WOB/min). The DSS appears to promote rapid weaning of PS to minimal ventilator settings when appropriate.