Strategies to mitigate bias from time recording errors in pharmacokinetic studies

Opportunistic pharmacokinetic (PK) studies have sparse and imbalanced clinical measurement data, and the impact of sample time errors is an important concern when seeking accurate estimates of treatment response. We evaluated an approximate Bayesian model for individualized pharmacokinetics in the presence of time recording errors (TREs), considering both a short and long infusion dosing pattern. We found that the long infusion schedule generally had lower bias in estimates of the pharmacodynamic (PD) endpoint relative to the short infusion schedule. We investigated three different design strategies for their ability to mitigate the impact of TREs: (i) shifting blood draws taken during an active infusion to the post-infusion period, (ii) identifying the best next sample time by minimizing bias in the presence of TREs, and (iii) collecting additional information on a subset of patients based on estimate uncertainty or quadrature-estimated variance in the presence of TREs. Generally, the proposed strategies led to a decrease in bias of the PD estimate for the short infusion schedule, but had a negligible impact for the long infusion schedule. Dosing regimens with periods of high non-linearity may benefit from design modifications, while more stable concentration-time profiles are generally more robust to TREs with no design modifications

Evaluation of Noninvasive Respiratory Volume Monitoring in the PACU of a Low Resource Kenyan Hospital

This research aims to evaluate the use of the noninvasive respiratory volume monitor (RVM) compared to the standard of care (SOC) in the Post-Anesthesia Care Unit (PACU) of Kijabe Hospital, Kenya. The RVM provides real-time measurements for quantitative monitoring of non-intubated patients. Our evaluation was focused on the incidence of postoperative opioid-induced respiratory depression (OIRD). The RVM cohort (N = 50) received quantitative OIRD assessment via the RVM, which included respiratory rate, minute ventilation, and tidal volume. The SOC cohort (N = 46) received qualitative OIRD assessment via patient monitoring with oxygenation measurements (SpO2) and physical examination. All diagnosed cases of OIRD were in the RVM cohort (9/50). In the RVM cohort, participants stayed longer in the PACU and required more frequent airway maneuvers and supplemental oxygen, compared to SOC (all p \u3c 0.05). The SOC cohort may have had fewer diagnoses of OIRD due to the challenging task of distinguishing hypoventilation versus OIRD in the absence of quantitative data. To account for the higher OIRD risk with general anesthesia (GA), a subgroup analysis was performed for only participants who underwent GA, which showed similar results. The use of RVM for respiratory monitoring of OIRD may allow for more proactive care

Revealing a signaling role of phytosphingosine-1-phosphate in yeast

Perturbing metabolic systems of bioactive sphingolipids with genetic approachMultiple types of “omics” data collected from the systemSystems approach for integrating multiple “omics” informationPredicting signal transduction information flow: lipid; TF activation; gene expressio

A Smartphone-based Decision Support Tool Improves Test Performance Concerning Application of the Guidelines for Managing Regional Anesthesia in the Patient Receiving Antithrombotic or Thrombolytic Therapy

BACKGROUND: The American Society of Regional Anesthesia and Pain Medicine (ASRA) consensus statement on regional anesthesia in the patient receiving antithrombotic or thrombolytic therapy is the standard for evaluation and management of these patients. The authors hypothesized that an electronic decision support tool (eDST) would improve test performance compared with native physician behavior concerning the application of this guideline. METHODS: Anesthesiology trainees and faculty at 8 institutions participated in a prospective, randomized trial in which they completed a 20-question test involving clinical scenarios related to the ASRA guidelines. The eDST group completed the test using an iOS app programmed to contain decision logic and content of the ASRA guidelines. The control group completed the test by using any resource in addition to the app. A generalized linear mixed-effects model was used to examine the effect of the intervention. RESULTS: After obtaining institutional review board's approval and informed consent, 259 participants were enrolled and randomized (eDST = 122; control = 137). The mean score was 92.4 ± 6.6% in the eDST group and 68.0 ± 15.8% in the control group (P < 0.001). eDST use increased the odds of selecting correct answers (7.8; 95% CI, 5.7 to 10.7). Most control group participants (63%) used some cognitive aid during the test, and they scored higher than those who tested from memory alone (76 ± 15% vs. 57 ± 18%, P < 0.001). There was no difference in time to completion of the test (P = 0.15) and no effect of training level (P = 0.56). CONCLUSIONS: eDST use improved application of the ASRA guidelines compared with the native clinician behavior in a testing environment

Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised)

Most current clustering based anomaly detection methods use scoring schema and thresholds to classify anomalies. These methods are often tailored to target specific data sets with "known" number of clusters. The paper provides a streaming clustering and anomaly detection algorithm that does not require strict arbitrary thresholds on the anomaly scores or knowledge of the number of clusters while performing probabilistic anomaly detection and clustering simultaneously. This ensures that the cluster formation is not impacted by the presence of anomalous data, thereby leading to more reliable definition of "normal vs abnormal" behavior. The motivations behind developing the INCAD model and the path that leads to the streaming model is discussed.Comment: 13 pages; fixes typos in equations 5,6,9,10 on inference using Gibbs samplin

Passerine Exposure to Primarily PCDFs and PCDDs in the River Floodplains Near Midland, Michigan, USA

House wren (Troglodytes aedon), tree swallow (Tachycineta bicolor), and eastern bluebird (Sialia sialis) tissues collected in study areas (SAs) downstream of Midland, Michigan (USA) contained concentrations of polychlorinated dibenzofurans (PCDFs) and polychlorinated dibenzo-p-dioxins (PCDDs) greater than in upstream reference areas (RAs) in the region. The sum of concentrations of PCDD/DFs (ΣPCDD/DFs) in eggs of house wrens and eastern bluebirds from SAs were 4- to 22-fold greater compared to those from RAs, whereas concentrations in tree swallow eggs were similar among areas. Mean concentrations of ΣPCDD/DFs and sum 2,3,7,8-tetrachlorodibenzo-p-dioxin equivalents (ΣTEQsWHO-Avian), based on 1998 WHO avian toxic equivalency factors, in house wren and eastern bluebird eggs ranged from 860 (430) to 1500 (910) ng/kg wet weight (ww) and 470 (150) to 1100 (510) ng/kg ww, respectively, at the most contaminated study areas along the Tittabawassee River, whereas mean concentrations in tree swallow eggs ranged from 280 (100) to 760 (280) ng/kg ww among all locations. Concentrations of ΣPCDD/DFs in nestlings of all studied species at SAs were 3- to 50-fold greater compared to RAs. Mean house wren, tree swallow, and eastern bluebird nestling concentrations of ΣPCDD/DFs and ΣTEQsWHO-Avian ranged from 350 (140) to 610 (300) ng/kg ww, 360 (240) to 1100 (860) ng/kg ww, and 330 (100) to 1200 (690) ng/kg ww, respectively, at SAs along the Tittabawassee River. Concentrations of ΣTEQsWHO-Avian were positively correlated with ΣPCDD/DF concentrations in both eggs and nestlings of all species studied. Profiles of relative concentrations of individual congeners were dominated by furan congeners (69–84%), primarily 2,3,7,8-tetrachlorodibenzofuran and 2,3,4,7,8-pentachlorodibenzofuran, for all species at SAs on the Tittabawassee and Saginaw rivers but were dominated by dioxin congeners at upstream RAs

profdpm: An R Package for MAP Estimation in a Class of Conjugate Product Partition Models

The profdpm package facilitates inference at the posterior mode for a class of product partition models. Dirichlet process mixtures are currently the only available class members. Several methods are implemented to search for the maximum posterior estimate of the data partition. This article discusses the relevant theory, the R and underlying C implementation, and examples of high level functionality. Keywords:˜product partition model, MAP estimate, clustering, R, C. 1

profdpm: An R Package for MAP Estimation in a Class of Conjugate Product Partition Models

Abstract The profdpm package facilitates inference at the posterior mode for a class of product partition models (PPM). Dirichlet process mixtures are currently the only available class members. Several methods are implemented to search for the maximum posterior estimate of the data partition. This article discusses the relevant theory, the R and underlying C implementation, and examples of high level functionality