Keeping Bystanders Active:Resuscitating Resuscitation Skills

Introduction: Sufficient CPR skills in the general population are essential to make them active bystanders and contribute to an effective chain of survival in cardiac arrest emergencies. However, having a large proportion of the population regularly retrained is practically infeasible. Objective: The aim of this study was to assess and retrain cardiopulmonary resuscitation (CPR) skills of individuals who received (limited) CPR training several months to years prior. Method: Ninety-nine German adults in a possession of a driver's license were asked to perform CPR on a Laerdal Resusci Anne (R) QCPR manikin (Laerdal, Stavanger, Norway). After initial assessment, participants watched an instructional video and completed short, isolated compression, and ventilation practice with live feedback. CPR competency was assessed again after retraining and after a retention interval of 45 min. Results: Our results indicate that only 2% of participants managed to reach the performance criteria set by the European Resuscitation Council Guidelines, with most failing to reach even the lowest levels of performance. This corroborates earlier observations that CPR skills have deteriorated almost completely after a long retention interval, calling into question "one-and-done" certification of this basic life-saving. However, we also demonstrated that performance strikingly increased after watching a 6-min instructional video and a short opportunity for isolated practice. This increase in performance was stable over 45 min with 96% of participants meeting performance levels specified in the Guidelines. Closer inspection of the isolated compression practice data suggests that performance was very high at the start of the practice already, indicating that short refresher videos might suffice to change bystanders that would not have initiated CPR due to lack of knowledge into active first responders. Conclusion: We suggest that short refresher trainings could be an effective and affordable means of improving basic lifesaving skills to increase the effective contribution of bystanders during emergencies

Within-Subject Performance on a Real-Life, Complex Task and Traditional Lab Experiments:Measures of Word Learning, Raven Matrices, Tapping, and CPR

In this data report, we describe a three-session experiment spanning six months. Several well-controlled laboratory tasks (Word Learning, Raven Matrices, and Tapping) and Cardiopulmonary Resuscitation (CPR), a complex but well-defined real-world task, were administered. Data are reported from 50 participants for the first session, 40 for the second, and 34 for the third. CPR is a useful domain for studying real-world performance inside the laboratory because clear performance standards can be applied to quantifying learners’ proficiency covering both the first steps that need to be taken prior to the initiation of CPR (declarative knowledge) as well as the compressions and ventilations themselves (procedural skill). This research resulted in a rich dataset with a range of different measures for all participants. For all tasks, the complete set of raw data are made available along with relevant aggregate performance scores (see https://osf.io/m8bxe/). The raw data in particular will enable other researchers to explore potential analyses and modeling beyond the scope of our own. The details of the data collection protocol and available data are documented here to facilitate this process

The khmer software package: enabling efficient nucleotide sequence analysis

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/

The khmer software package: enabling efficient nucleotide sequence analysis [version 1; referees: 2 approved, 1 approved with reservations]

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/

Colorectal cancer incidences in Lynch syndrome: a comparison of results from the prospective lynch syndrome database and the international mismatch repair consortium

Objective To compare colorectal cancer (CRC) incidences in carriers of pathogenic variants of the MMR genes in the PLSD and IMRC cohorts, of which only the former included mandatory colonoscopy surveillance for all participants. Methods CRC incidences were calculated in an intervention group comprising a cohort of confirmed carriers of pathogenic or likely pathogenic variants in mismatch repair genes (path_MMR) followed prospectively by the Prospective Lynch Syndrome Database (PLSD). All had colonoscopy surveillance, with polypectomy when polyps were identified. Comparison was made with a retrospective cohort reported by the International Mismatch Repair Consortium (IMRC). This comprised confirmed and inferred path_MMR carriers who were first- or second-degree relatives of Lynch syndrome probands. Results In the PLSD, 8,153 subjects had follow-up colonoscopy surveillance for a total of 67,604 years and 578 carriers had CRC diagnosed. Average cumulative incidences of CRC in path_MLH1 carriers at 70 years of age were 52% in males and 41% in females; for path_MSH2 50% and 39%; for path_MSH6 13% and 17% and for path_PMS2 11% and 8%. In contrast, in the IMRC cohort, corresponding cumulative incidences were 40% and 27%; 34% and 23%; 16% and 8% and 7% and 6%. Comparing just the European carriers in the two series gave similar findings. Numbers in the PLSD series did not allow comparisons of carriers from other continents separately. Cumulative incidences at 25 years were < 1% in all retrospective groups. Conclusions Prospectively observed CRC incidences (PLSD) in path_MLH1 and path_MSH2 carriers undergoing colonoscopy surveillance and polypectomy were higher than in the retrospective (IMRC) series, and were not reduced in path_MSH6 carriers. These findings were the opposite to those expected. CRC point incidence before 50 years of age was reduced in path_PMS2 carriers subjected to colonoscopy, but not significantly so

SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort

Identifying the potential for Severe Acute Respiratory Syndrome : Coronavirus 2 (SARS-CoV-2) reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders, and the choice of baseline time point and show how to account for both in reinfection analysis

Model Predictions for Game-specific and Player-Specific Knowledge Drive Transfer of Learning Between Games of Strategic Interaction

In this document, we present all of the model predictions for an upcoming study to be to run in the Spring of 216. During this experiment, participants will sequentially play two games of strategic interaction for 50 rounds in one of four possible game orders, playing either iterated Prisoner’s Dilemma (PD) or iterated Chicken Game (CG) twice (PDPD or CGCG order) or playing each game once (PDCG or CGPD order). During each game, participants will play with a computerized confederate agent which uses a particular strategy, playing the first game of a condition using the T4T strategy and using the PT4T strategy during the second game (T4T_PT4T order) or vice versa (PT4T_T4T order). The trustworthiness of the confederate agent will remain constant over the course of both games, manipulated to be either high (HT) or low (LT) trustworthiness. Finally, the information that participants receive about confederate agents will be manipulated. Participants will be told that they will play both games with either the same participant (one-agent condition) or that they would be randomly paired with another participant to play with during the second game after the first game (two-agent condition). This document is organized into 32 sections, one for each of the experimental conditions, each with six different figures. The first graph of a section shows the smoothed round-by-round predicted proportion of each of the five game outcomes during a condition. The proportion of each outcome was smoothed to remove the round-by-round variability in the game’s outcomes and to allow the reader observe the general behavioral trends predicted by the model. Following the first figure of a section, five additional figures are presented, showing the actual round-by-round predicted proportion of a single outcome over the course both games during condition, with 95% CI intervals

Integrating Methods to Improve Model-based Performance Prediction

The initial performance of individuals is often difficult for models of learning and retention to predict. One such modelis the predictive performance equation (PPE) a mathematical model of learning and retention that uses regularities seenin human learning to predict future performance.To generate predictions, PPEs free parameters must be calibrated to aminimum amount of historical performance data, preventing valid predictions for initial learning events.Prior research(Collins, Gluck, Walsh, Krusmark &amp; Gunzelmann, 2016; Collins, Gluck, &amp; Walsh, 2017), has shown that the generaliza-tion of best fitting parameters from prior data can improve initial performance predictions.Here we build on that research,using Bayesian hierarchical modeling to estimate free parameters from various sources of prior data. Bayesian hierarchalmodeling allows an opportunity to improve and add structure to the parameters used by PPE, improving its application tocognitive technology in education and training