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Background The new noninvasive Vitalstream (VS) continuous physiological monitor (Caretaker Medical LLC, Charlottesville, Virginia), allows continuous cardiac output by a low pump-inflated, finger cuff that pneumatically couples arterial pulsations via a pressure line to a pressure sensor for detection and analysis. Physiological data are communicated wirelessly to a tablet-based user interface via Bluetooth or Wi-Fi. We evaluated its performance against thermodilution cardiac output in patients undergoing cardiac surgery. Methods We compared the agreement between thermodilution cardiac output to that obtained by the continuous noninvasive system during cardiac surgery pre and post-cardiac bypass. Thermodilution cardiac output was performed routinely when clinically indicated by an iced saline cold injectate system. All comparisons between VS and TD/CCO data were post-processed. In order to match the VS CO readings to the averaged discrete TD bolus data, the averaged CO readings of the ten seconds of VS CO data points prior to a sequence of TD bolus injections was matched. Time alignment was based on the medical record time and the VS time-stamped data points. The accuracy against reference TD measurements was assessed via Bland–Altman analysis of the CO values and standard concordance analysis of the ΔCO values (with a 15% exclusion zone). Results Analysis of the data compared the accuracy of the matched measurement pairs of VS and TD/CCO VS absolute CO values with and without initial calibration to the discrete TD CO values, as well as the trending ability, i.e., ΔCO values of the VS physiological monitor compared to those of the reference. The results were comparable with other non-invasive as well as invasive technologies and Bland-Altman analyses showed high agreement between devices in a diverse patient population. The results are significant regarding the goal of expanding access to effective, wireless and readily implemented fluid management monitoring tools to hospital sections previously not covered because of the limitations of traditional technologies. Conclusion This study demonstrated that the agreement between the VS CO and TD CO was clinically acceptable with a percent error (PE) of 34.5 to 38% with and without external calibration. The threshold for an acceptable agreement between the VS and TD was considered to be below 40% which is below the threshold recommended by others.

Background Despite increased interest in non-invasive arterial pressure monitoring, the majority of commercially available technologies have failed to satisfy the limits established for the validation of automatic arterial pressure monitoring by the Association for the Advancement of Medical Instrumentation (AAMI). According to the ANSI/AAMI/ISO 81060–2:2013 standards, the group-average accuracy and precision are defined as acceptable if bias is not greater than 5 mmHg and standard deviation is not greater than 8 mmHg. In this study, these standards are used to evaluate the CareTaker® (CT) device, a device measuring continuous non-invasive blood pressure via a pulse contour algorithm called Pulse Decomposition Analysis. Methods A convenience sample of 24 patients scheduled for major abdominal surgery were consented to participate in this IRB approved pilot study. Each patient was monitored with a radial arterial catheter and CT using a finger cuff applied to the contralateral thumb. Hemodynamic variables were measured and analyzed from both devices for the first thirty minutes of the surgical procedure including the induction of anesthesia. The mean arterial pressure (MAP), systolic and diastolic blood pressures continuously collected from the arterial catheter and CT were compared. Pearson correlation coefficients were calculated between arterial catheter and CT blood pressure measurements, a Bland-Altman analysis, and polar and 4Q plots were created. Results The correlation of systolic, diastolic, and mean arterial pressures were 0.92, 0.86, 0.91, respectively ( p <  0.0001 for all the comparisons). The Bland-Altman comparison yielded a bias (as measured by overall mean difference) of −0.57, −2.52, 1.01 mmHg for systolic, diastolic, and mean arterial pressures, respectively with a standard deviation of 7.34, 6.47, 5.33 mmHg for systolic, diastolic, and mean arterial pressures, respectively ( p <  0.001 for all comparisons). The polar plot indicates little bias between the two methods (90%/95% CI at 31.5°/52°, respectively, overall bias = 1.5°) with only a small percentage of points outside these lines. The 4Q plot indicates good concordance and no bias between the methods. Conclusions In this study, blood pressure measured using the non-invasive CT device was shown to correlate well with the arterial catheter measurements. Larger studies are needed to confirm these results in more varied settings. Most patients exhibited very good agreement between methods. Results were well within the limits established for the validation of automatic arterial pressure monitoring by the AAMI.

Radiologic usual interstitial pneumonia (UIP) patterns and concordant clinical characteristics define a diagnosis of idiopathic pulmonary fibrosis (IPF). However, limited expert access and high inter-clinician variability challenge early and pre-invasive diagnostic sensitivity and differentiation of IPF from other interstitial lung diseases (ILDs). We investigated a machine learning-driven software system, Fibresolve, to indicate IPF diagnosis in a heterogeneous group of 300 patients with interstitial lung disease work-up in a retrospective analysis of previously and prospectively collected registry data from two US clinical sites. Fibresolve analyzed cases at the initial pre-invasive assessment. An Expert Clinical Panel (ECP) and three panels of clinicians with varying experience analyzed the cases for comparison. Ground Truth was defined by separate multi-disciplinary discussion (MDD) with the benefit of surgical pathology results and follow-up. Fibresolve met both pre-specified co-primary endpoints of sensitivity superior to ECP and significantly greater specificity (p = 0.0007) than the non-inferior boundary of 80.0%. In the key subgroup of cases with thin-slice CT and atypical UIP patterns (n = 124), Fibresolve’s diagnostic yield was 53.1% [CI: 41.3–64.9] (versus 0% pre-invasive clinician diagnostic yield in this group), and its specificity was 85.9% [CI: 76.7–92.6%]. Overall, Fibresolve was found to increase the sensitivity and diagnostic yield for IPF among cases of patients undergoing ILD work-up. These results demonstrate that in combination with standard clinical assessment, Fibresolve may serve as an adjunct in the diagnosis of IPF in a pre-invasive setting.

Background Neural networks are increasingly used to assess physiological processes or pathologies, as well as to predict the increased likelihood of an impending medical crisis, such as hypotension. Method We compared the capabilities of a single hidden layer neural network of 12 nodes to those of a discrete-feature discrimination approach with the goal being to predict the likelihood of a given patient developing significant hypotension under spinal anesthesia when undergoing a Cesarean section (C/S). Physiological input information was derived from a non-invasive blood pressure device (Caretaker [CT]) that utilizes a finger cuff to measure blood pressure and other hemodynamic parameters via pulse contour analysis. Receiver-operator-curve/area-under-curve analyses were used to compare performance. Results The results presented here suggest that a neural network approach (Area Under Curve [AUC] = 0.89 [ p  < 0.001]), at least at the implementation level of a clinically relevant prediction algorithm, may be superior to a discrete feature quantification approach (AUC = 0.87 [ p  < 0.001]), providing implicit access to a plurality of features and combinations thereof. In addition, the expansion of the approach to include the submission of other physiological data signals, such as heart rate variability, to the network can be readily envisioned. Conclusion This pilot study has demonstrated that increased coherence in Arterial Stiffness (AS) variability obtained from the pulse wave analysis of a continuous non-invasive blood pressure device appears to be an effective predictor of hypotension after spinal anesthesia in the obstetrics population undergoing C/S. This allowed us to predict specific dosing thresholds of phenylephrine required to maintain systolic blood pressure above 90 mmHg.

Captive cetacean attractions are growing in number globally, their operators citing entertainment, education, and conservation as benefits. Those for and against developing such attractions claim public support. Previous public opinion research, however, shows little consensus, partly due to the introduction of biases in study design that influence participants' responses. Those involved in, or concerned with, developing and licensing these attractions need to better understand what drives the lack of consensus to take socially-acceptable decisions. We reviewed previous research on public opinion of cetacean captivity, noting possible sources of bias. Survey question wording can be a major source of introduced bias, so we used an open-ended photo elicitation approach. We showed tourists in the Turks Caicos Islands (  = 292) images of a marine mammal park (MMP) killer whale show and a swim-with-the-dolphins (SWTD) attraction and asked for their qualitative comments on the potential development of each. They also indicated how likely they would be to visit each on a Likert scale. Respondents were generally against visiting MMP killer whale shows, with 60.9% not likely to visit. SWTD attractions were more popular; 60.3% were likely to visit. For SWTD, USA residents were more likely to visit; older respondents and those staying in all-inclusive resorts were less likely. Those staying in all-inclusive resorts were also less likely to visit MMP killer whale shows. The great majority of qualitative comments centred on either entertainment value or animal welfare concerns. There were very few, if any, comments on the education or conservation value of these attractions. Our findings contradict several previous studies on public opinion of captive cetaceans that did not use photo elicitation. The support shown for MMP killer whale shows in this survey was well below that claimed by studies conducted on behalf of captive cetacean attraction operators. Opposition to SWTD was also noticeably lower than that found in surveys conducted with wild cetacean tourism participants. This difference can likely be attributed to the different survey populations and settings, but this variation is also very likely attributable to researcher-introduced bias. While photo selection can introduce bias, photo elicitation reduces reliance on pre-scripted questions and responses, and seems to effectively reduce other forms of bias. Allowing open-ended responses, where participants responded to an image, seems to have given a more representative understanding of what is at the forefront of the public's mind than closed questioning. These conclusions, among others made in this study, suggest that development decisions for captive cetacean attractions are being made on imprecise data. Going forward, data collected via responder-led, open-ended, bias-minimising approaches should at least be considered when informing such decisions.

Apoptosis, a type of programmed cell death, is a universal and essential cellular function. There are numerous homeostatic biological roles of apoptosis and many diseases have or cause mys- or dis- regulated apoptosis, most notably cancer’s escape from apoptotic signals. Apoptosis has many distinctive characteristics including membrane blebbing, chromatin condensation, and most importantly for these studies, the activation of a class of protease proteins called caspases. Caspases are cysteine aspartic proteases with a unique preference to cleave hundred of substrates after acidic residues, especially aspartate. These cleavage events can activate, modify, or inhibit the substrate’s function, which leads to the dismantling of the cell during apoptosis. This process is well conserved throughout metazoan evolution, with parallel pathways in coral, fish, flies, worms and mice. To study apoptotic protease activity, the Wells Lab has developed a proteomic-based technique. This technique is an unbiased positive enrichment labeling mass spectrometry protocol. While the protocol was developed for studying caspase substrates during apoptosis in human cell culture, it is very versatile, allowing for use in almost any protein sample like perturbed cellular lysates, different species and primary samples. Chapter 1 covers the protocol specifics and uses, summarizing a decade’s worth of optimization and application. The DegraBase is the compilation of 44 different experiments using the N-terminal labeling method to examine apoptotic proteolytic activity described in Chapter 2. While much of the experimentation work was completed before I started the project, I completed compilation and standardization of raw data, and worked with Emily Crawford on the analysis. This global analysis reveals there is a large increase in proteolytic activity after apoptotic induction, and caspases account for 25% of the newly created fragments. Within caspase substrates, there is no single biological process or sub-cellular location that is targeted, as caspases appear to cleave substrates throughout all the different pathways of the cell. Additionally, this database is also a good resource for endogenous proteolysis, including free methionines, and signal and transis peptide processing. Analysis of the DegraBase also reveals evolutionary and biological discoveries. As the apoptotic pathway to activate caspases is highly conserved throughout metazoans, we wanted to investigate the conservation of caspase substrates. In Chapter 3, the comparison of caspase substrates in worm, fly, mouse and human reveals a hierarchal structure. My contribution includes the murine dataset and comparison analysis in collaboration with Emily Crawford. We found caspase cleavage is highly conserved at the pathway level, while individual targets and sites are not as well conserved the more distant the animals. The unbiased and large size of the DegraBase also reveals broader caspase activity than previously described. Caspases had been assumed to have absolute specificity for aspartate and no activity for glutamate. However, with the large dataset, in Chapter 4, I reveal significant activity after glutamate and even potential activity after phosphoserine. This activity is verified through biochemical assays and x-ray crystallography, and expands the number of apoptotic caspase substrates by 15%. As many chemotherapeutics induce apoptosis, apoptotic, especially caspase, proteolytic substrates may be good biomarkers of treatment efficacy. The development of mouse models and a positive control are discussed in Chapter 5. These models utilize the DegraBase and labeling technology to identify peptides enriched in the blood and tumor specific to treatment responding mice as potential biomarkers.

[...]detailed information on diet might be a confounder in the model predicting weight because it can be a predictor of age and weight. The sample included 571 monolingual and bilingual (Chinese-American) patients at the University of California San Francisco. Add to that the model's overall fit by R··2 or a reduction in the standard error of the estimate, and the prediction power improves.

DATA The deal with decoding categorical data by Christopher Seaman, I. Elaine Allen and Julia E. Seaman In everyday analysis, often we come across categorical data such as color, region or any other method of grouping observations together. Because there are only two machines, we can track whether machine B was used and, if it wasn't, we know machine A was active instead. Creating a linear regression model to predict cost of production with two machines gives us the solution that the information on the cost of machine A, as the reference category, is completely captured in the constant term ß0. Think of it as giving a shortcut to the model to make quick decisions, allowing the model to quickly check the reference category rather than having to check membership in every other category.

A nonsignificant odds ratio (1.08, 0.99-1.26 confidence interval, or CI) in the largest study3 concluded that the study may have been underpowered to show a statistically significant effect. In 2016, the U.S. Department of Health and Human Services dropped its recommendations about regular teeth flossing because no adequately controlled studies proving a benefit existed.6 Here, the absence of confirmatory evidence (studies were only three months) may have been too short to show an effect. The \"file drawer problem\"8 assumes that less convincing or perhaps negative studies are less likely to be published and, if true, ' may result in publication bias in the outcome of a systematic review.

[...]it is not guaranteed that respondents will be truthful in surveys, especially about personal or stigmatized behavior that a respondent is unlikely to admit. QP ADDITIONAL RESOURCES The following resources expand on the design of surveys and types of surveys: + Andrews, Dorine, Blair Nonnecke and Jennifer Preece, \"Electronic Survey Methodology: A Case Study in Reaching Hard-to-Involve Internet Users,\" International Journal of Human Computer Interaction, Vol. 16, No. 2, 2003, pp. 185-210. + Guidolin, Keegan, Steven D. Wexner, Flora Jung, Shawn Khan, Shirley Xiaoxuan Deng, Abirami Kirubarajan, Fayez Quereshy and Sami Chadi, \"Strengths and Weaknesses in the Methodology of Survey-based Research in Surgery: A Call for Standardization,\" Surgery, 2021, www.sciencedirect.com/science/ article/pii/S0039606021000234. + Pew Research Center, \"Questionnaire Design,\" www.pewresearch. org/methods/u-s-survey-research/ questionnaire-design. + Louisiana State University GROK Knowledge Base, \"Survey Design and Administration Best Practices,\" https:// grok.lsu.edu/article.aspx?articleid=17958. The following online calculators can be used for sample size and confidence intervals: + Creative Research Systems, \"Sample Size Calculator,\" www.surveysystem.com/sscalc.htm. + Conjoint.ly, \"Sample Size Calculator,\" https://conjointly.com/blog/ sample-size-calculator. + University of California San Francisco Clinical & Translational Science Institute, \"Sample Size Calculators for Designing Clinical Research,\" https://sample-size.net. + READ MORE Learn how one organization with limited resources used survey tools to collect process data for quality management purposes.